new research on statins and diabetes

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Researchers solve mystery of how statins improve blood vessel health

Statins designed to lower cholesterol have long been noted to work in mysterious ways to improve other aspects of cardiovascular health. A Stanford Medicine-led study uncovers how they do it.

May 8, 2023 - By Nina Bai

Researchers at Stanford Medicine and their colleagues have discovered how statins improve cardiovascular health beyond lowering cholesterol.  roger ashford/Shutterstock.com

Using new genetic tools to study statins in human cells and mice, Stanford Medicine researchers and collaborators have uncovered how the cholesterol-lowering drugs protect the cells that line blood vessels. 

The findings provide new insight into statins’ curiously wide-ranging benefits, for conditions ranging from arteriosclerosis to diabetes, that have long been observed in the clinic.

“The study gives us an understanding, at a very deep mechanistic level, of why statins have such a positive effect outside of reducing LDL,” said professor of medicine Joseph Wu , MD, PhD, referring to low-density lipoprotein, or “bad” cholesterol. “Given how many people take statins, I think the implications are pretty profound.”

Statins are the most prescribed medications in the country, with more than 40 million Americans taking them. Developed in the 1980s from compounds found in mold and fungi, statins target an enzyme that regulates cholesterol production in the liver. But clinical trials have shown that they also seem to safeguard against cardiovascular disease beyond their ability to lower cholesterol.

Heart failure patients who take statins, for example, are less likely to suffer a second heart attack. They have also been shown to prevent the clogging of arteries, reduce inflammation and even lower cancer risk. Yet these underlying mechanisms are poorly understood.

“Statins were invented to lower cholesterol by targeting the liver. But we didn’t know the targets or the pathways in the cardiovascular system,” said  Chun Liu , PhD, an instructor at the  Stanford Cardiovascular Institute  and co-lead author of the  study  published May 8 in  Nature Cardiovascular Research .  Mengcheng Shen , PhD, and Wilson Tan, PhD, postdoctoral scholars at the Stanford Cardiovascular Institute, are the other co-lead authors, and Wu is the senior author.

Hints from a dish

To take a closer look at statins’ effect on blood vessels, Liu and colleagues tested a common statin, simvastatin, on lab-grown human endothelial cells derived from induced pluripotent stem cells. Endothelial cells make up the lining of blood vessels, but in many diseases they transform into a different cell type, known as mesenchymal cells, which are poor substitutes.

“Mesenchymal cells are less functional and make tissues stiffer so they cannot relax or contract correctly,” Liu said.

The researchers suspected that statins could reduce this harmful transition. Indeed, endothelial cells treated with simvastatin in a dish formed more capillary-like tubes, a sign of their enhanced ability to grow into new blood vessels.

RNA sequencing of the treated cells offered few clues. The researchers saw some changes in gene expression, but they “didn’t find anything interesting,” Liu said.

It was not until they employed a newer technique called ATAC-seq that the role of statins became apparent. ATAC-seq reveals what happens at the epigenetic level, meaning the changes to gene expression that do not involve changes to the genetic sequence.

They found that the changes in gene expression stemmed from the way strings of DNA are packaged inside the cell nucleus. DNA exists in our cells not as loose strands but as a series of tight spools around proteins, together known as chromatin. Whether particular DNA sequences are exposed or hidden in these spools determines how much they are expressed.

“When we adopted the ATAC-seq technology, we were quite surprised to find a really robust epigenetic change of the chromatin,” Liu said.

ATAC-seq revealed that simvastatin-treated cells had closed chromatin structures that reduced the expression of genes that cause the endothelial-to-mesenchymal transition. Working backward, the researchers found that simvastatin prevents a protein known as YAP from entering the nucleus and opening chromatin.

The YAP protein is known to play important roles in development, such as regulating the size of our organs, but also has been implicated in the abnormal cell growth seen in cancer.

A look at diabetes

To see the drug in context, the researchers tested simvastatin on diabetic mice. Diabetes causes subtle changes to blood vessels that mimic the damage commonly seen in people who are prescribed statins — older patients who do not have a cardiovascular condition, Liu said. 

They found that after eight weeks on simvastatin, the diabetic mice had significantly improved vascular function, with arteries that more easily relaxed and contracted.

“If we can understand the mechanism, we can fine-tune this drug to be more specific to rescuing vascular function,” Liu said.

The findings also provide a more detailed picture of the vascular disease process, which could help doctors identify and treat early signs of vascular damage.

“I’ve been taking statins for the past 10 years to keep my cholesterol down. I also knew it has good vascular effects. I just didn’t know how it does it,” said Wu, the Simon H. Stertzer, MD, Professor who is also the director of the Stanford Cardiovascular Institute. “This study explains how.”

Researchers from the University of North Texas and the Ohio State University College of Medicine contributed to this study.

The study was supported by funding from the National Institutes of Health (grants R01 HL130020, R01 HL150693, R01 HL163680, R01 HL145676, P01 HL141084, R01 HL141371, R01 HL126527, R01 HL15864, R01 HL161002, R01 HL155282 and 18CDA34110293), an American Heart Association SFRN grant, an AHA Career Development Award and the Tobacco-Related Disease Research Program.

About Stanford Medicine

Stanford Medicine is an integrated academic health system comprising the Stanford School of Medicine and adult and pediatric health care delivery systems. Together, they harness the full potential of biomedicine through collaborative research, education and clinical care for patients. For more information, please visit med.stanford.edu .

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Risk of diabetes with statins

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• Peer review
• Ishak A Mansi , professor of medicine 1 ,
• Priya Sumithran , principal research fellow 2 ,
• Mustafa Kinaan , assistant professor of medicine 3
• 1 Department of Education, Orlando VA Health Care System, Orlando, Florida
• 2 Department of Medicine (St Vincent’s), University of Melbourne, Melbourne, Australia
• 3 Department of Internal Medicine, University of Central Florida, Orlando
• Correspondence to I Mansi ishak.mansi{at}UTSouthwestern.edu

What you need to know

Statins are associated with a small increased risk of new-onset diabetes, which is higher in people with other risk factors for diabetes, and in association with high intensity statins and older age

When starting a patient on statins, emphasise the importance of lifestyle modifications, including healthy diet and physical activity

Consider monitoring blood glucose levels when starting or intensifying statin therapy (although no evidence based guidance is available for how often this monitoring should occur)

A 65 year old white man is presenting for his routine check-up. He has no history of smoking, hypertension, diabetes, or cardiovascular disease, and takes no regular medications. His total cholesterol is 5.25 mmol/L, low density lipoprotein (LDL) cholesterol is 3.34 mmol/L, and high density lipoprotein (HDL) cholesterol is 1.5 mmol/dL. His blood pressure is 125/70 mm Hg. He is attempting to adhere to a heart-healthy lifestyle. You discuss whether to start a statin for primary prevention of cardiovascular disease.

The patient is aware of the benefit of statins in lowering the risk of cardiovascular disease, but has read media reports that statins cause diabetes. He asks about the magnitude of the risk of developing diabetes, and how to minimise it, to help him decide whether to take a statin. How would you advise him?

How do statins affect blood glucose?

Statins are medications that lower blood cholesterol. They act by inhibiting the 3-hydroxy-3-methylglutaryl-CoA (HMG-CoA) reductase enzyme, which catalyses the principal rate-limiting step in cholesterol synthesis by the liver. 1

Statins are generally well tolerated and have shown benefits in lowering cardiovascular morbidity and mortality. 2 However, their association with an increased risk of new onset diabetes led the US Food and Drug Administration to approve a label revision in 2012 to add that increases in glycated haemoglobin (HbA 1c ) and fasting glucose levels have been reported with statins. 3 The European Medicines Agency also noted the increased risk of incident diabetes among statin users at risk of developing the disease and recommended monitoring, but stipulated that the risk-benefit balance remains clearly positive. 4

The precise mechanisms by which statins increase the risk of diabetes are not fully understood. Nonetheless, evidence suggests that statins may contribute to both key pathophysiological drivers of type 2 diabetes: multi-organ insulin resistance and dysfunction of insulin secreting pancreatic beta cells. 5 6 7 Proposed mechanisms of beta cell dysfunction are described elsewhere. 8 9

How common is this adverse effect?

Estimates of how often diabetes occurs in people taking statins vary widely depending on population characteristics, study type, and statin intensity. Table 1 summarises some estimates of risk of diabetes, as well as estimates of cardiovascular benefits, from randomised controlled trials (RCTs). 10 11 12 13 14 Based on estimates from these RCTs, for every 100 to 250 people who take statins for two to five years, one additional person will develop diabetes attributable to taking statins. Estimates from observational studies are similar 15 or slightly greater, but some observational studies have reported multi-fold increases in risk of incident diabetes in some populations or in cohorts with medical conditions that were not well represented in RCTs. 5 16 17

Summary of selected estimates of risk (from randomised controlled trials and their meta-analyses) of diabetes and cardiovascular benefits attributable to statin use

• View inline

Consensus exists that the increased rates of diabetes in people who take statins are due to statins, rather than methodological weakness in studies that examined the risk of diabetes and statins. These studies included RCTs, 10 meta-analyses of RCTs (some of which are summarised in table 1 ), 11 12 observational studies, 16 17 18 19 20 and consensus statements. 12 21 A causal link is supported by mendelian randomisation studies, which showed that gene variants associated with less activity of HMG-CoA reductase enzyme (analogous to inhibiting the enzyme by statins) are associated with a higher risk of diabetes. 22 23

A meta-analysis of 13 RCTs reported a 9% increased odds of developing diabetes among statin users over four years (odds ratio 1.09; 95% confidence interval 1.02 to 1.17). 11 Not all meta-analyses of RCTs have found this association, since different meta-analyses included different RCTs based on their inclusion and exclusion criteria. 2 13 RCTs were commonly not designed to detect diabetes, used different criteria for reporting diabetes, were occasionally terminated prematurely, and often had contamination between study arms, and high attrition or low treatment adherence rates. 24 The use of intention-to-treat analysis in the presence of high contamination, high attrition, and low adherence can underestimate adverse events.

Evidence suggests an association between the risk of developing diabetes and the use of higher potency statins. A nested case-control analysis from a multinational cohort (136 966 patients) compared diabetes incidence in users of higher potency statins with that of users of lower potency statins for secondary prevention after admission to hospital for a cardiovascular event. 15 The study found that, over a two year period, the rate of diabetes in patients prescribed higher potency statins was 15% higher than in those taking lower potency statins (fixed effect rate ratio 1.15, 95% CI 1.05 to 1.26).

The timeline of new diabetes after statin initiation is not well delineated, but evidence suggests that the risk increases one to four months after statin initiation. 6 15 25 The study mentioned above indicated that the excess risk was greatest in the first four months after initiation of high potency statins. 15

In people with pre-existing diabetes, evidence from small RCTs and a large cohort study indicates an association between statins and progression of diabetes. 25 26 27

What factors increase the risk of diabetes with statin use?

High intensity statins (atorvastatin 40 and 80 mg, and rosuvastatin 20 and 40 mg) 14 27 28 —higher cumulative statin dose is also associated with higher risk. 15 29

Pre-existing risk factors for type 2 diabetes—such as impaired fasting glucose, metabolic syndrome, and obesity. 5 28

Fatty liver 29 or increased thickness of epicardial fat 30 —presence of fatty liver has been associated with a threefold increased risk of diabetes compared with those with low liver fat. 29 31

Older age—a meta-analysis found a stronger association between statins and risk of incident diabetes in trials with older participants (aged over 65) compared with younger participants. 11

Evidence is uncertain on whether diabetes risk may vary by statin type (eg, lipophilic versus hydrophilic, or specific statins) 5 11 15 32 —but mendelian randomisation studies suggest that diabetes risk with statins is likely to be a class effect. 22 23 Large scale head-to-head studies are required to resolve this question.

How can we minimise the risk of harm?

If a patient develops diabetes after statin use, clinicians should follow standard guidelines for managing diabetes. Currently no data are available to guide an evidence based approach for those whose diabetes specifically follows statin use.

As summarised in table 1 , the number need to treat to prevent a cardiovascular event is typically lower for statins than the number needed to harm (ie, number needed to cause a new case of diabetes). However, each individual’s risk, and their values and preferences, need to be taken into account. Whereas there is agreement on statin use for secondary prevention of cardiovascular diseases, guidelines vary in their recommendations for prescribing statins for primary prevention, as well as in the tool that they use to predict cardiovascular risk ( table 2 ). 2 33 34 35 36 37 Cardiovascular risk calculation tools facilitate applying knowledge from RCTs to the general population, but no RCTs have examined the benefits of prescribing statins solely using risk calculators.

Selected guideline recommendations for statin use for primary prevention of cardiovascular diseases, and application of guidelines to the patient in the case scenario

Given the uncertainties and lack of high quality evidence to guide clinicians and patients on managing the risk of developing diabetes with statins, practical advice is largely based on expert opinion. Our approach to these discussions with patients is summarised in box 1 . 39 40 41 42 43 44 45 46

Tips for prescribers—a suggested approach to reduce risk of diabetes with statin use

Check blood glucose after initiation of statins or escalation of doses. We suggest checking baseline fasting blood glucose and/or HbA 1c before starting statins to establish a baseline, at 3-6 months after starting statin, and yearly thereafter.

Ask patients with pre-existing diabetes to more closely monitor their blood glucose levels.

Determining the risk of type 2 diabetes for your patient at baseline can assist with risk stratification. Diabetes risk score calculators include the American Diabetes Association risk tool, the QDiabetes score, 38 and the Finnish Diabetes Risk Score. 39

Emphasise the importance of healthy dietary choices and physical activity. 40 41 42 In people at high risk of type 2 diabetes, lifestyle modification and weight loss can reduce the incidence of diabetes. 43

Assess the need for high intensity statins carefully, since guidelines may differ on their indications and evidence shows a higher risk of diabetes. Some guideline recommendations are presented in table 2

Assess for presence of secondary causes of hypercholesterolaemia such as hypothyroidism. Treating the underlying cause may obviate the need for pharmacotherapy. 43

If possible, change medications that increase the risk of diabetes, such as thiazide diuretics and beta-blockers, if the patient has no strong indications for these drugs. 44 45

Minimise drug-drug interactions that may increase the level of statins within the body, especially if using high intensity statins. Two main classes of drug interactions are important:

Drugs that affect CYP3A4/5 † (CYP3A4/5 inhibitors, eg, amiodarone, clarithromycin, diltiazem, grapefruit juice, itraconazole, ketoconazole, protease inhibitors), which mainly increase plasma concentrations of simvastatin, atorvastatin, and lovastatin

Drugs that affect transport proteins (eg, cyclosporin). 46

If these agents are unavoidable, consider a lower dose of statins.

†Pravastatin and rosuvastatin are minor substrates for CYP3A4, hence their levels are minimally affected

Areas of uncertainty

Insulin sensitising medications (such as metformin or pioglitazone) have been proposed for some patients with prediabetes who are starting statins, 47 or using lower intensity statins combined with other cholesterol lowering treatments that are not known to be associated with diabetes. 47 Currently, no data are available on the efficacy of these approaches.

Further research is needed to define the timeline of statin-associated diabetes and delineating its genetic predisposition. Other pressing questions include: Is statin-associated diabetes reversible upon statin discontinuation? Would intermittent use minimise this risk while maintaining cardiovascular benefits? Answers to these questions would help in optimising statin use in different populations along the spectrum of cardiovascular risk.

This potential adverse effect of diabetes with statin use should not be a barrier to starting statin treatment when indicated. Discussing this potential adverse event with patients is an important step towards shared decision making for initiating stains.

Tips for patients

What are statins.

Statins are medications that lower blood cholesterol.

Statins decrease the risk of heart attacks and strokes, particularly in those who have already had such events.

However, a risk may be associated with statins.

If 250 people (not taking statins) were followed for two years, 10 of them would develop diabetes. If these 250 people were taking statins for two years, 11 of them would be expected to develop diabetes (instead of 10). This additional one person is an approximate estimate that can be higher according to other factors, such as having obesity or impaired fasting glucose (when blood glucose is higher than normal but lower than level required to diagnose diabetes).

Balancing risks and benefits probabilities

In people without pre-existing cardiovascular diseases (heart attacks or strokes) or other high risk factors for these, the benefit of taking a statin is small but still greater than the risk of developing diabetes from taking it.

Tell your doctor if you, or someone in your family, has diabetes or cardiovascular diseases. This may be important in weighing the risks and the benefits of statins.

Diet and exercise

Maintain a healthy lifestyle to lower your risks of cardiovascular disease and diabetes (including following a healthy diet such as Mediterranean diet, and exercise) in conjunction with statin use. Do not depend only on taking medication (statin) to lower your risk.

Monitoring and adjusting statins

Discuss with your doctor if monitoring of blood glucose is needed while on statin therapy.

Discuss with your doctor whether adjusting your statin therapy to a lower potency formulation or lower dose should be considered.

Education into practice

What would you discuss with a patient when you review the results of their blood lipid profile?

Think about the last time you talked to a patient about starting a statin for primary prevention of cardiovascular disease. To what extent did you emphasise the importance of healthy diet and exercise despite using a statin? How might you alter your discussion next time?

How patients were involved in the creation of this article

We emailed or handed the box entitled “Tips for patients” to several of our patients in the USA, Australia, and the Middle East. Our patients found the information helpful and modified the format and contents of the box, which guided us to the current format.

One of our patients asked to add headings to our tips to make them more memorable. Another requested to add that statins are cholesterol lowering medication.

How this article was created

We searched “Hydroxymethylglutaryl-CoA Reductase Inhibitors/adverse effects”[ MeSH Terms] AND diabetes[MeSH Terms]; sorting by the most recent entries, and limiting the search to English language and human species. The search resulted in 510 articles. Limiting the search to the past five years further limited the results to 159 publications. After reviewing abstracts or studies of the latter group, only 63 publications were found relevant (four were categorised as clinical trials, one as protocol for a clinical trial, four as meta-analysis, 23 as narrative reviews or editorials, and 31 as observational studies).

Competing interests: The BMJ has judged that there are no disqualifying financial ties to commercial companies. The authors declare the following other interests: none.

Further details of The BMJ policy on financial interests are here: https://www.bmj.com/about-bmj/resources-authors/forms-policies-and-checklists/declaration-competing-interests

Funding source: No specific funding was provided for this work. PS is supported by an Investigator Grant from the National Health and Medical Research Council (1178482).

Contributorship and guarantor: All authors contributed to planning of the manuscript, wrote sections of the first draft, made substantial revisions to the content, and approved the final work. IM is the guarantor.

Disclaimer: The views expressed herein are those of the authors and do not reflect the official policy or position of the Department of Defense, VA Administration, or the US Government. One of the authors is an employee of the US government. This work was prepared as part of his official duties and, as such, there is no copyright to be transferred.

Provenance and peer review: commissioned; externally peer reviewed.

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• Published: 10 December 2021

Statins and diabetes mellitus progression: a fly in the ointment?

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• Dimitri P. Mikhailidis 2  

Nature Reviews Endocrinology volume  18 ,  pages 137–138 ( 2022 ) Cite this article

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Statins might exert diabetogenic effects, potentially increasing insulin resistance and worsening glucose control. However, patients with diabetes mellitus are at high or very high cardiovascular risk and, thus, statin use is strongly recommended. Adding ezetimibe to statins might be helpful in achieving lipid targets and reducing cardiovascular risk without adversely affecting glucose metabolism.

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REVIEW article

Statins and risk of type 2 diabetes: mechanism and clinical implications.

• 1 Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
• 2 Kuopio University Hospital, Kuopio, Finland

Statins are widely used to prevent cardiovascular disease events. Cardiovascular diseases and type 2 diabetes are tightly connected since type 2 diabetes is a major risk factor for cardiovascular diseases. Additionally, cardiovascular diseases often precede the development of type 2 diabetes. These two diseases have common genetic and environmental antecedents. Statins are effective in the lowering of cardiovascular disease events. However, they have also important side effects, including an increased risk of type 2 diabetes. The first study reporting an association of statin treatment with the risk of type 2 diabetes was the WOSCOPS trial (West of Scotland Coronary Prevention Study) in 2001. Other primary and secondary cardiovascular disease prevention studies as well as population-based studies have confirmed original findings. The purpose of our review is to examine and summarize the most important findings of these studies as well as to describe the mechanisms how statins increase the risk of type 2 diabetes.

1 Introduction

Several risk factors are shared between type 2 diabetes (T2D) and cardiovascular disease (CVD), obesity, dyslipidaemia, insulin resistance, and hyperglycaemia. T2D is a major risk factor for CVD, and CVD often precedes the development of T2D. Thus, these diseases have common genetic and environmental antecedents ( 1 ).

Mendelian randomization (MR) approach uses a genetic instrument to infer causal associations between an exposure and an outcome ( 2 ). These studies have demonstrated that body mass index (BMI), waist-to-hip ratio ( 3 ), elevated blood pressure ( 4 ), smoking ( 5 ), and total triglycerides ( 6 ) are causally associated with the risk of both T2D and CVD. MR studies also indicate that T2D is causally associated with coronary artery disease independent of other risk factors ( 7 , 8 ). However, a major difference is in low-density cholesterol concentrations (LDL-C) since high concentrations of LDL-C are causally associated with CVD ( 9 ) but not with the risk of T2D ( Figure 1 ).

Figure 1 Mendelian Randomization studies have shown that body mass index, waist-to- hip ratio, insulin resistance, total triglycerides, blood pressure and smoking are causally associated with the risk of type 2 diabetes and cardiovascular diseases. High LDL cholesterol concentration is causally associated with cardiovascular diseases but not with type 2 diabetes.

Statins were introduced for the first time in 1987 when lovastatin was approved in the United States. Simvastatin and pravastatin were approved in 1991, fluvastatin in 1994, atorvastatin in 1997, rosuvastatin in 2003 and pitavastatin in 2009. Several trials reported that statins are effective in the lowering of LDL-C ( 10 , 11 ), and therefore statins are currently the most widely prescribed drugs in the primary and secondary prevention of CVD events ( 12 ). The maximum dose of rosuvastatin, atorvastatin and simvastatin lower LCL-C by 50-60%, lovastatin by 50%, and pravastatin and lovastatin by 30-40%. Statins inhibit 3-hydroxymethyl glutaryl coenzyme A (HMG-CoA) reductase, an intracellular enzyme catalysing the conversion of HMG-CoA to mevalonate during the rate-determined step of cholesterol metabolism ( 13 , 14 ). However, statins have side effects, especially hyperglycaemia and the risk of T2D. Therefore, the United States Safety and Drug Administration released changes in statin safety label in 2012 that statins increase glycosylated haemoglobin A1c (HbA1c) and fasting glucose concentrations ( 15 ).

The first studies suggesting that statins increase the risk of T2D came from statin trials ( 16 ). The benefit of trials is that they include large number of participants. However, trial data have important limitations. The hypothesis in statin trials was that statins reduce the risk of CVD by lowering LDL-C concentrations. The primary endpoints in these trials were incident CVD events, and not conversion to T2D according to the criteria of the American Diabetes Association ( 17 ). Therefore, it is impossible to make reliable conclusions from these trials with respect to incident T2D. Participants needed to have elevated LDL-C concentrations and a high risk of CVD, and therefore they differed from the general population. Furthermore, most meta-analyses combined primary and secondary prevention populations which is problematic because secondary prevention populations include survivors of CVD. Additionally, the diagnosis of T2D was often evaluated post hoc and based on self-reported T2D or physician diagnosed T2D without internationally accepted criteria for diabetes. In none of these trials the diagnosis of T2D was based on the measurements of fasting and 2-hour glucose concentrations and HbA1c according to the American Diabetes Association criteria ( 17 ) resulting in underestimation of cases of T2D ( 18 ).

2 The first evidence that statins increase the risk of T2D

The first study showing that statins were associated with the risk of T2D was the WOSCOPS trial (West of Scotland Coronary Prevention Study) ( 19 ). A total of 5 974 participants did not have diabetes at baseline and 139 of them developed T2D during the study. Pravastatin therapy resulted in a 30% reduction of the cases of T2D in a post hoc analysis of this study. The diagnosis of T2D was based only on fasting glucose measurements. The PROSPER trial (pravastatin in elderly individuals at risk of vascular disease) included 5 804 participants and reported a 19% decrease in the risk of coronary artery disease, but no significant increases or decreases in incident T2D ( 20 ). The PROVE-IT TIMI 22 sub-study reported for the first time increases in glucose and HbA1c concentrations and incident T2D for atorvastatin ( 21 ), and the Phase Z of the A to Z trial for simvastatin ( 22 ).

The JUPITER trial (Justification for the Use of Statins in Prevention: Intervention Trial Evaluating Rosuvastatin) randomly assigned 17 802 men and women to rosuvastatin 20 mg/daily. The participants had LDL-C < 3.4 mmol/l and high-sensitivity C-reactive protein levels of 2.0 mg/l or higher ( 23 ). Myocardial infarction, stroke, arterial revascularization, hospitalization for unstable angina, or death from CVD formed the primary endpoint of this trial. Rosuvastatin significantly lowered CVD events by 44%, and increased incident physician-reported T2D by 26% compared to the placebo group.

Sattar et al. ( 24 ) published the first large meta-analysis of statin-induced incident T2D. This meta-analysis included 91140 participants from13 trials. Statin therapy increased the risk of incident T2D by a 9%. Preiss et al. ( 25 ) reported in another meta-analysis including 32 752 participants from five statin trials that there was a significant increase in fasting glucose levels and that the risk of T2D increased by 12%. In this study high intensity statin trials (atorvastatin, rosuvastatin, simvastatin) were more often associated with incident T2D than moderately intensity statins (pravastatin, pitavastatin). Carter et al. published similar results in a population-based study ( 26 ). Thakker et al. ( 27 ) reported the results of a meta-analysis including 141 863 participants without diabetes from 29 trials and found that 12% of the participants developed T2D.

Early findings from statin trials showed that that pre-existing risk factors for T2D, including age, obesity, total triglycerides, and blood pressure, increased the development of statin-mediated hyperglycaemia. Data from the Treating to New Targets (n=7 595) and IDEAL (n=7 461) trials reported that increased fasting glucose (≥5.6 mmol/l) and the components of the metabolic syndrome increased the risk of T2D ( 28 – 30 ). Of the patients having high statin dose (atorvastatin, simvastatin) and 2-4 risk factors for T2D, 14,3% developed T2D whereas from the patients on a lower-dose statin dose 11,9% developed T2D. Thus, the dose-related effects of statins may depend also on the general risk factors for T2D ( 28 ). Additionally, in meta-analyses of large clinical trials other drugs used for the prevention of CVD events, niacin, thiazide diuretics and beta-blockers increased the risk of T2D from 9% to 43% ( 31 ).

In summary, the first statin trials and meta-analyses showed a decrease in the risk of T2D for pravastatin by 0-30%, and an increase in the risk of T2D by 12% for rosuvastatin, atorvastatin and simvastatin. The risk of T2D was somewhat greater for high-intensity statins (rosuvastatin, atorvastatin, simvastatin) compared to low- and medium-intensity statins. Importantly, an increased risk of incident T2D by statins was comparable with the risk of T2D of other drugs (beta-blockers and thiazide diuretics) used for the prevention of CVD.

3 Effects of statin therapy on glucose control in patients with previously diagnosed T2D

Zhou et al. ( 32 ) investigated the effects of statin treatment on glucose control in a meta-analysis including 3 232 participants having previously diagnosed T2D from 26 eligible studies. The investigators found that statin therapy did not have significant effects on glycaemic control (HbA1c, fasting glucose) in these patients. The results of Cui et al. ( 33 ) were different. They investigated HbA1c changes in 23 trials including 2 707 patients with previously diagnosed T2D and found a small but significant increase in HbA1c when statins were compared with placebo. High-intensity atorvastatin worsened glycaemic control whereas moderate-intensity pitavastatin improved it ( 33 ).

Erqou et al. ( 34 ) analysed the results from 9 696 participants (4 980 on statin, 4 716 controls) included in nine trials. The mean HbA1c of the participants randomized to statin treatment was modestly but significantly increased by 0.12% compared to the control group after an average follow-up of 3.6 years. Alvarez-Jimenez et al. ( 35 ) performed a meta-analysis of HbA1c concentrations based on 67 studies including over 25 000 patients with T2D. Statin increased HbA1c by 0.21%.

Mansi et al. ( 36 ) investigated the association of statin treatment initiation and diabetes progression in 83 022 statin users and non-users. The investigators found that statin users had a higher likelihood to start insulin treatment, develop significant hyperglycaemia, and a need to increase additional glucose-lowering medication. High-intensity LDL-C lowering medication was associated with an increased likelihood of diabetes progression among statin users compared to non-users. This study gave important information about the effects of statin therapy on glycaemic control among patients with diabetes.

In summary, statins worsened hyperglycaemia in patients with previously diagnosed T2D but increases in HbA1c were moderate. Statin users had an increased risk for T2D progression and insulin treatment initiation.

4 Statins and incident T2D in population-based studies

The limitation of previous statin trials is that the participants were selected among the individuals having a high risk of CVD. Therefore, the participants included in these studies do not represent the general population. Additionally, the diagnosis of T2D in previous studies was based often on self-reported diabetes or fasting glucose measurement that underestimate the incidence of T2D. The current diagnostic criteria for diabetes are the measurements of fasting and 2h glucose and HbA1c.

The first population studies indicated that the risk of statin-induced T2D was considerably higher than in statin trials. Carter et al. ( 26 ) conducted a population-based retrospective study including 471 250 patients treated with statin, aged 66 or older and without diabetes at baseline. A total of 38 470 patients were treated with pravastatin, 268 254 with atorvastatin, 11 923 with fluvastatin or lovastatin, 76 774 with rosuvastatin, and 75 829 with simvastatin. Compared with pravastatin, atorvastatin increased the risk of incident T2D by 22%, rosuvastatin by 18%, and simvastatin by 10%. Fluvastatin and lovastatin did not increase the risk of T2D compared to pravastatin. The strengths of this study were a large sample size, and a population-based design. The limitations were that this study did not have a control group of participants without statin treatment, and measurements of glucose or HbA1c. These findings are comparable to those of a study by Zaharan et al. ( 37 ) reporting that atorvastatin increased the risk of incident T2D by 25%, rosuvastatin by 42%, and simvastatin by 14%. In the Women’s Health Initiative study including 161 808 postmenopausal women without diabetes at baseline reported that statin therapy was associated with a 48% increase in the risk of self-reported diabetes ( 38 ).

Djousse L et al. ( 39 ) investigated the association of the effects of statin potency (low, medium, high) with incident T2D in 3 390 799 US Veterans. The authors reported that compared to no statin use low statin potency increased the risk of incident T2D by 21%, medium potency by 22%, and high statin potency by 34% (daily doses for simvastatin ≥80 mg, atorvastatin ≥40 mg, rosuvastatin ≥10 mg). This study shows that high doses of the most potent statins, simvastatin, atorvastatin, and rosuvastatin, increase further the risk of incident T2D.

We investigated the mechanisms associated with statin-induced T2D in the population-based Metabolic Syndrome in Men (METSIM) cohort ( 40 , 41 ) including 8,749 non-diabetic participants, aged 45-73 years at baseline. During a 6-year follow-up we diagnosed incident T2D in 625 men. The criteria for diabetes were a need of glucose-lowering medication during the follow-up, elevated glucose concentrations in fasting or in an oral glucose tolerance test, or HbA1c ≥6.5% (48 mmol/mol). We found a 46% increased risk of T2D in the participants on statin treatment (n=2 142). Simvastatin and atorvastatin increased the risk of T2D in a dose-dependent manner. Statin treatment was additionally associated with decreased insulin sensitivity by 24% and deceased insulin secretion by 12% compared with the participants without statin treatment.

The prospective population-based Rotterdam Study included 8 567 participants without diabetes at baseline and a follow-up for 15 years ( 42 ). Statin treatment increased the risk of incident T2D by 38% after the adjustment for confounding factors. Diabetes was diagnosed by fasting glucose or a non-fasting glucose concentration ‗ 11.1 mmol/l. Subjects with impaired glucose homeostasis at baseline and obesity had the highest risk of T2D.

Crandall et al. ( 43 ) investigated incident T2D in the Diabetes Prevention Program Outcomes Study (n=3 234). This randomized clinical trial investigated the effects of different interventions to prevent T2D. The diagnosis of incident diabetes was based on an annual oral glucose tolerance test. At 10 years, the cumulative incidence of diabetes in the participants on statin treatment was 36% (20% in the placebo group, 33% in participants on metformin therapy, and 43% in the lifestyle group). This study was the first to investigate the statin-diabetes association within randomized clinical trial in the participants with high risk of diabetes. Statin use was associated with greater risk of T2D irrespective of the treatment group, with pooled 36% risk for incident T2D.

Engeda et al. ( 44 ) performed a meta-analysis of eight randomized controlled trials and 15 observational studies. The incidence of T2D in both randomized controlled trials and observational studies. Incident T2D was substantially larger in observational studies (55%) than in trials (11%).

In summary, several population-based studies have reported substantially higher number of incident cases of T2D among the individuals on statin treatment compared to previous CVD trials. This indicates that previous statin trials have largely underestimated the true incidence of T2D in patients on statin treatment.

5 Effects of genetic variants on statin function and the risk of T2D

Genetic variants in the three genes have effects on statin function, the solute carrier organic anion transporter family member 1B1 gene ( SLCO1B1 ), 3-Hydroxy-3-Methylglutaryl-CoA Reductase ( HMGCR ), and Low-Density Lipoprotein Receptor ( LDLR ).

5.1 SLCO1B1

SLCO1B1 gene encodes a liver-specific member of the organic anion transported family. The encoded protein organic-anion-transporting polypeptide 1B1 (OATP1B1) is highly expressed in the liver. The function of OATP1B1i s to transport statins and several other endogenous metabolites into the liver ( 45 ). Genetic variants in the SLCO1B1 gene are associated with impaired transporter function ( 46 ). SLCO1B1 rs4363657 variant is strongly associated with an increased risk of statin-induced myopathy ( 47 ).

We investigated the association of the effective C allele of SLCO1B1 rs4149056 with the risk of T2D in the METSIM study ( 48 ). S LCO1B1 rs4149056-C did not have significant association with the risk of T2D, glucose concentrations, insulin sensitivity, or insulin secretion. These findings suggest that OATP1B1-dependent transport of statins in the liver does not play a significant role in glucose metabolism. However, the participants on simvastatin treatment had higher fasting glucose, insulin, and proinsulin concentrations, lower LDL cholesterol concentration, and increased insulin resistance than the participants without statin treatment when we compared clinical and laboratory measurements between the carriers of the CC + CT genotype of SLCO1B1 rs4149056.

We also investigated the effects of SLCO1B1 rs4149056-C on metabolite concentrations in the participants on simvastatin treatment (n=1 373) and in age- and BMI-matched controls (n=1 368) without any statin medication. We found that concentrations of dicarboxylic acids were decreased in the participants with simvastatin. This may result in an increase of beta- and peroxisomal oxidation and increased turnover of cholesterol into bile acids. Consequently, steroidogenesis decreases attributable of limited availability of cholesterol for steroid synthesis ( 48 ).

In summary, SLCO1B1 rs4149056-C did not have a significant association with the risk of T2D, elevated glucose concentration, insulin resistance, or impaired insulin secretion.

5.2 HMGCR gene

HMG-CoA reductase is the rate-limiting enzyme for cholesterol synthesis. It is regulated by a negative feedback mechanism mediated by sterols and non-sterol metabolites derived from mevalonate.

Statins inhibits the HMG-CoA reductase enzyme that suppresses the synthesis of mevalonate, cholesterol, and its downstream metabolites ( 48 , 49 ). Several studies have clarified the significance of the HMG-CoA gene as a risk factor for T2D.

Swerdlow et al. ( 50 ) included in their analyses 223 463 individuals from 43 genetic studies. Each additional HMGCR rs17238484-G allele was associated with a mean 0.06 mmol/l lower LDL-C concentration and a 2% higher risk of T2D. Additionally, this variant was associated with higher body weight (0·30 kg), waist circumference (0·32 cm), plasma insulin concentration (1.62%), and plasma glucose concentration (0.23%). HMGCR rs12916-T allele was also associated with 6% higher risk of T2D, and quite similar effects on LDL-C concentration, weight, and waist circumference as HMGCR rs17238484-G allele. The authors concluded that the increased risk of T2D in individuals having statins treatment was at least partially explained by HMGCR inhibition, and weight gain.

Another recent GWAS meta-analysis included > 2 million participants of European and East Asian ancestry ( 51 ). Genetically mimicked effects of statins and ezetimibe were associated with higher risk of T2D, and BMI which was claimed to explain more than half of the effects of statins on the risk of T2D, in contrast to previously published results where the effects of BMI as a modified were modest ( 50 ). We did not observe increased weight gain in the participants on statin treatment who developed new T2D in our 6-year follow-up study of the METSIM cohort including 8 749 non-diabetic participants ( 40 ). Therefore, the role of weight gain and the effects of HMGCR variants as a causal factor for conversion to T2D is controversial ( 52 , 53 ). It is important to remember that weight gain increases insulin resistance but does not have a direct effect on insulin secretion. Insulin secretion decreases when insulin secretion from pancreatic β-cells is not able to compensate for decreased insulin sensitivity. Therefore, in a previous study where insulin resistance increased insulin secretion increased correspondingly which is expected in studies having short follow-up ( 54 ).

In summary, HMGCR rs17238484-G allele increased the risk of T2D by 2%, body weight by 0·30 kg, waist circumference by 0·32 cm, plasma insulin concentration by 1.6%, and glucose concentration by 0.2%. These changes were small and therefore more studies are needed to confirm original results.

5.3 LDLR gene

Familial hypercholesterolemia is caused by homozygous or heterozygous pathogenic mutations in the LDLR gene ( 55 , 56 ). Such mutations result in the expression of LDL receptors or transport of LDL-C into the cells ( 57 ). The association of familial hypercholesterolemia with a low risk of diabetes was first reported in 1997 ( 58 ). Fall et al. ( 59 ) reported a significant association between genetically increased circulating LDL-C concentrations and a decreased risk of T2D. However, the authors concluded that these associations could be caused by survival bias, pleiotropy, or unknown confounding factors and should be interpreted with caution. Lotta et al. ( 60 ) found an association between LDL-lowering genetic variants and T2D in a meta-analysis including 50 775 individuals with T2D and 60 801 individuals with coronary artery disease. However, the association of LDLR with the risk of T2D was not causal. Two other studies reported that patients with familial hypercholesterolemia have a decreased risk of diabetes ( 61 , 62 ).

LDL-C is causally associated with coronary artery disease ( 63 , 64 ). White et al. constructed a genetic instrument composed of 130 genetic variants for LDL-C ( 65 ). This genetic instrument was significantly associated with increased LDL-C concentrations as well as with an increased risk of coronary artery disease, odds ratio and its 95% confidence intervals for LDL-C were 1.68 (1.51-1.87). LDL-C was also associated with a decreased risk for diabetes, odds ratio and its 95% confidence limits were 0.79 (0.71-0.88). Therefore, clinical trials of lipid lowering agents should carefully monitor for glycemia and conversion to T2D ( 66 ).

In summary, accumulating evidence shows that elevated LDL-C concentration is inversely associated with decreased risk of T2D, but there is no firm evidence that this association is causal.

6 Mechanisms leading to incident diabetes with statin medication: human studies

We investigated the mechanisms underlying the risk of T2D associated with statin treatment in the METSIM cohort ( 40 , 41 ) including 8 749 non-diabetic participants. New T2D was diagnosed in 625 men during a 6-year follow-up. We first validated our measurements of insulin sensitivity and insulin secretion in a separate sample of 287 non-diabetic individuals not belonging to the METSIM cohort. These individuals participated in an intravenous glucose tolerance test to evaluate insulin secretion and euglycemic-hyperinsulinemic clamp study to evaluate insulin sensitivity ( 67 ). We calculated 11 different indices for insulin secretion and 6 indices for insulin sensitivity. The ratio of insulin and glucose areas (from 0 to 30 min) under the curve (InsAUC 0-30 /GluAUC 0-30 ) had the highest correlation (0.66) with the first phase insulin secretion and Matsuda index had the highest correlation (0.77) with the M value of the euglycemic hyperinsulinemic clamp. We found that the participants on statin treatment (n=2 142) had a 46% increased risk of T2D. Insulin sensitivity was decreased by 24% and insulin secretion by 12% in individuals on statin treatment. Our study shows that both insulin resistance and decreased insulin secretion were the mechanisms leading to the conversion to T2D ( 19 ).

Abbasi et al. ( 54 ) performed a clinical trial of atorvastatin 40 mg daily in 71 participants without CVD or T2D at baseline. The length of this study was 10 weeks. Atorvastatin increased insulin resistance by 8% and insulin secretion by 9% compared to the baseline measurements. In their study insulin secretion increased to compensate insulin resistance caused by atorvastatin during their trial. Our study lasted 6 years and therefore the pancreas was unable to compensate for increasing insulin resistance over a long time resulting in a decrease of insulin secretion ( 19 ).

In a meta-analysis of Baker et al. ( 68 ) pravastatin increased insulin sensitivity, atorvastatin and rosuvastatin did not affect insulin sensitivity and simvastatin decreased insulin sensitivity in participants without T2D. Alvarez-Jimenez et al. ( 35 ) investigated the effects of statin therapy on glycaemic control and insulin resistance based on a meta-analysis of 67 separate studies including > 25 000 participants. In participants with normal HbA1c (<6.5% or 48 mmol/l) rosuvastatin and atorvastatin induced significant increases in HbA1c in most of the studies. In participants having HbA1c > 6.5% only atorvastatin induced a significant increase in HbA1c. The same investigators analysed also changes in HOMA insulin resistance index. Rosuvastatin, simvastatin, and atorvastatin significantly increased insulin resistance in a subgroup having relatively low insulin resistance. The strength of this study is a large sample size, but HOMA-IR is not a reliable index for insulin resistance.

7 In vitro and in vivo studies on mechanisms leading to impaired insulin secretion and insulin resistance by statins

Both insulin resistance and impaired insulin secretion are hallmarks of T2D. Most of the genetic variants increasing the risk of T2D are regulating insulin secretion, and only few of insulin sensitivity ( 69 ). Decreased insulin secretion is the major contributor to statin-induced diabetes. Insulin production in the β-cells is controlled by several transcription factors playing crucial roles in the regulation of both the differentiation of β-cells into insulin-producing cells and β-cell function ( 70 , 71 ). Therefore, understanding of the mechanisms resulting in disturbances in insulin secretion is important.

HMGCR increases modestly the risk of T2D ( 50 ). Takei et al. ( 72 ) deleted Hmgcr in a β-cell specific manner by using the Cre-loxP technique in mice. Mice lacking Hmgcr in β-cells exhibited low insulin concentrations and hyperglycemia attributable to decreases in both β-cell mass and insulin secretion. The β-cell mass reduction was mainly caused by impaired proliferation of β-cells. The investigators concluded that HMGCR plays critical roles not only in insulin secretion but also in the development of β-cells. These findings demonstrate the importance of the mevalonate pathway in the maintenance of β-cells and glucose homeostasis.

LDLR plays an important role in β-cell dysfunction. Statins reduce cholesterol synthesis via the HMG-CoA reductase pathway ( 70 ) resulting in increased cholesterol entry and accumulation in pancreatic β-cells, and impairment in β-cell function via glucose-induced Ca 2+ signalling pathways ( 70 , 73 – 76 ). In our study simvastatin decreased glucose-stimulated insulin secretion in MIN6 β-cells at normal glucose concentration by multiple mechanisms, including inhibitory effects on the acetylcholine and GPR40 pathways, whereas simvastatin-induced impairment in insulin secretion was substantially less in the GLP-1 receptor and GPR119 pathways ( 76 ). Interestingly, exenatide prevented statin related LDLR increase and improved insulin secretion in pancreatic β-cells ( 77 ). However, detailed mechanisms how statins inhibit cholesterol synthesis and lead to impaired L-type Ca 2+ signalling function remains unclear ( 74 ).

The isoprenoids, products of mevalonate pathways are likely to be important for insulin secretion. Lovastatin decreased glucose-induced insulin secretion by 50% in rat islets, but co-incubation with mevalonate abolished this effect ( 78 ). Wang et al. ( 79 ) investigated the effects of simvastatin on glucose homeostasis in streptozotocin induced diabetic rats. They reported that statin therapy increased glucose concentrations over a period of 12 weeks. In another study the effects of simvastatin on insulin secretion were studied in mouse MIN6 cells and showed that high concentrations of simvastatin significantly reduced the synthesis and secretion of insulin compared to the control group ( 80 ). Similar results were also obtained in another simvastatin study in intact single-islet cultures ( 81 ).

Figure 2 illustrates possible mechanisms how statins impair insulin secretion. Statins are taken into the liver by transporter protein OATP1B1. In the liver statins inhibit HGM-CoA resulting in downregulation of the mevalonate pathway and increases in LDLR expression and LDL-C concentrations. High concentrations of LDL-C are toxic in the pancreatic beta-cells and lead to impaired insulin secretion in the pancreas, and finally hyperglycaemia and T2D. This mechanism is supported by a mouse model lacking LDLR. In this model pancreatic β-cells were protected from accumulation of cholesterol and consequently β-cell function was not impaired ( 82 ).

Figure 2 Proposed mechanisms by which statins increase the risk of type 2 diabetes. Statins are transported into the liver by OATP1 resulting in an increase in the LDLR expression and consequently higher absorption of LDL-C into the liver. Expression of LDLR in pancreas is increased upon statin intake, leading to higher concentration of LDL-C. High concentrations of LDL-C in the pancreas results in lipotoxycity in β-cells, decreasing insulin secretion and contributing to the development of T2D. LDLR, low density cholesterol receptor; T2D, type 2 diabetes.

8 In vitro and in vivo studies on mechanisms leading to impaired insulin resistance

Statins increase insulin resistance, but molecular mechanisms are largely unknown. Insulin resistance is found in several tissues, especially in skeletal muscle, liver, and adipose tissue. Insulin resistance itself does not result in the conversion to T2D because impaired insulin secretion is always needed to generate hyperglycaemia. However, long-lasting insulin resistance can contribute to the conversion to T2D if insulin secretion does not compensate insulin resistance.

Skeletal muscle is the main site for insulin-stimulated glucose uptake. Glucose uptake into skeletal muscle is mediated by glucose transporter GLUT4. Grundwald et al. ( 83 ) investigated expression of proteins related to GLUT4 mediated glucose uptake in human skeletal muscle tissue from patients on statin treatment. They demonstrated that a short-term statin treatment with statins affected AMPKα and AKT activity in human skeletal-muscle primary myotubes. The conclusion of this study was that AMPKα activation by statins and the blocking of AKT may lead to insulin resistance.

Our metabolomics study showed that genetic inhibition of HMG-CoA reductase was negatively correlated with sphingomyelins and phosphatidylcholines, which increase insulin resistance ( 15 ). Sarsenbayeva et al. ( 84 ) investigated the association of genetic or pharmacological HMG-CoA reductase inhibition in adipose tissue and concluded that high concentrations of simvastatin decreased adipocyte glucose uptake. They also found a positive association of HMGCR with the insulin signalling pathway, suggesting that reduced activity of HMGCR may contribute to insulin resistance.

Hye Jin Wang et al. ( 85 ) found that statin treatment contributed to the development of T2D in mice. Statin treatment (rosuvastatin, atorvastatin, fluvastatin, pravastatin) upregulated the gene expression of key enzymes involved in hepatic gluconeogenesis ( G6PC and PCK1 ) resulting in increasing glucose production in the liver, and hepatic insulin resistance. Interestingly, these effects were mediated through autophagy induction in the liver.

Statins upregulate mitochondrial acylcarnitine carrier gene expression ( 86 ). However, detailed metabolite profile of individual acylcarnitines remains unknown. Previous studies have shown that branched-chain amino acids are associated with insulin resistance and the risk of T2D ( 86 – 89 ). We found in the participants of the METSIM study that simvastatin increased concentrations of fife short-chain mitochondrial acylcarnitines, two valine derived metabolites (isobutyrylcarnitine C4, isovalerylcarnitine C5), two isoleucine derived metabolites (2-methylbutyrylcarnitine C5, succinylcarnitine C4-DC), and one lysine derived metabolite (glutarylcarnitine, C4-DC) ( 15 ) ( Figure 3 ). Additionally, these participants also had increased fasting and 2h glucose concentrations, decreased insulin sensitivity and insulin secretion compared to participants who were not on statin treatment.

Figure 3 Effects of simvastatin on metabolism of branched chain amino acids. Simvastatin affects the metabolism of branched chain amino acids resulting in the generation of short-chain acyl carnitines (C4 and C5). Short-chain acyl carnitines are associated with insulin resistance. CoA, coenzyme A.

In summary, several studies have been published on the association of statins with insulin resistance in skeletal muscle, adipose tissue, and liver but exact mechanisms how insulin resistance is increased are still largely unknown.

9 Clinical implications of statin treatment

Several randomised trials have shown that statins lower effectively LDL-C concentrations and the risk of CVD events (coronary deaths, coronary revascularisations, myocardial infarctions, and strokes). It has been estimated that an effective statin treatment for about 5 years in 10 000 patients typically prevents major CVD events in about 1 000 (10%) patients at high risk of heart attacks and strokes (secondary prevention) and 500 (5%) patients at lower risk (primary prevention) ( 13 ). There are no significant differences with respect to cardiovascular outcomes between hydrophilic statins (simvastatin, fluvastatin, lovastatin, atorvastin) and hydrophilic statins (rosuvastatin, pravastatin) ( 90 ). Adverse effects of statin treatment are myopathy (muscle pain or weakness), incident T2D, and haemorrhagic strokes. It has been evaluated that the treatment of 10 000 patients for 5 years with a standard statin treatment, causes about 5 cases of myopathy, 50–100 new cases of T2D, and 5–10 haemorrhagic strokes ( 13 ).

Statins are effective in the lowering not only the risk of CVD, but also microvascular complications. Nielsen et al. ( 91 ) demonstrated that microvascular complications decreased during the statin treatment among 213 974 individuals with diabetes from Denmark aged 40 years or older. The follow-up of their study was 215 725 person-years. Compared with individuals without statin treatment, individuals on statin treatment had a 40% lower risk of diabetic retinopathy, 34% lower risk of diabetic neuropathy, and 12% lower risk of gangrene of the foot. However, statin treatment did not lower the risk of diabetic nephropathy.

Several studies available show compelling evidence that statin treatment has more benefit in the prevention of CVD than potential harm related to increased risk of T2D. Diabetes risk is therefore not a reason to withhold statin treatment. Several risk factors for T2D, obesity, blood pressure, total triglycerides, and smoking increase the risk for the conversion to diabetes, and therefore beneficial lifestyle also helps to prevent T2D.

10 Concluding remarks

Meta-analyses of clinical statin trials to lower cardiovascular events reported an increase in the risk of diabetes by 9-12% ( 24 , 25 , 27 ) whereas in large population studies the risk was substantially higher. In a meta-analysis of 15 observational studies the risk of incident T2D was 55% ( 44 ). In four individual studies the risk of incident T2D was from 36-48% ( 38 , 40 , 42 , 43 ), and in the US Veterans study ( 39 ) 21-22% for low and median potency statins (pravastatin, fluvastatin), and 34% for high potency statins (simvastatin, atorvastatin, rosuvastatin). Clinical statin treatment trials have significantly underestimated the effects of statins on the risk of T2D. Additionally, the diagnosis of T2D has not performed according to internationally accepted criteria leading to underestimation of incident T2D. In the clinical trials the risk of T2D has been quite similar between different statins but in the population studies statin potency has been a significant factor increasing the risk of T2D.

Recent studies have clarified the significance of the genetic variants as regulators of statin function. A recent study showed for the first time that a variant of the SLCO1B1 gene encoding OATP1B1-dependent transport of statins in the liver did not have significant association with the risk of T2D ( 48 ) whereas variants of the HMGCR gene was associated with a 2-6% elevated risk of T2D ( 50 ). Interestingly, the pathogenic mutations of the LDLR gene increase LDL-C concentration causing familial hypercholesterolemia and are associated with a low risk of T2D, although this association has not be proven to be causal.

Cellular mechanisms how statins increase the conversion to T2D are largely unknown. Impaired insulin secretion is needed to generate hyperglycaemia and the conversion to T2D. The role of insulin resistance can contribute to the conversion to T2D if insulin secretion does not compensate insulin resistance. Statins inhibit HGM-CoA resulting in downregulation of the mevalonate pathway and increases in LDL-C concentrations which are toxic in the pancreatic beta-cells and lead to impaired insulin secretion, and finally to incident T2D. Understanding cellular mechanisms leading to statin-induced incident T2D is the most important challenge in future studies.

Author contributions

ML and LF wrote the manuscript and performed literature search. This work has not been published or submitted for publication elsewhere. All authors contributed to the article and approved the submitted version.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords: statin, type 2 diabetes, glucose, insulin secretion, insulin resistance

Citation: Laakso M and Fernandes Silva L (2023) Statins and risk of type 2 diabetes: mechanism and clinical implications. Front. Endocrinol. 14:1239335. doi: 10.3389/fendo.2023.1239335

Received: 13 June 2023; Accepted: 29 August 2023; Published: 19 September 2023.

Reviewed by:

Copyright © 2023 Laakso and Fernandes Silva. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Markku Laakso, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Statins and diabetes: What are the connections?

Affiliation.

• 1 School of Cardiovascular and Metabolic Health, University of Glasgow, BHF Glasgow Cardiovascular Research Centre, 126 University Place, Glasgow G12 8TA, UK. Electronic address: [email protected].
• PMID: 36858834
• DOI: 10.1016/j.beem.2023.101749

Randomized trials suggest moderate-intensity statins increase type 2 diabetes risk by around 11% with a potential further 12% moving to high-intensity statins, such that high intensity may increase risk by 20% or more relative to placebo. These data translate into one extra diabetes case per 100-200 statin recipients over 5 years, with ∼10-fold greater benefits on major vascular outcomes. The underlying mechanisms for diabetes harm are not clear but could include modest weight gain (noted in randomized trials), or, speculatively, beta cell harm. Concordant genetic studies link HMG CoA Reductase inhibition to diabetes risk and weight gain. Patients should be warned about a slight diabetes risk when prescribed statin and told that modest lifestyle improvements can i) nullify diabetes risk, and ii) improve cardiovascular risks beyond statins. Doctors should also measure glycemia status post statin commencement, most commonly with HbA1c, and tailor lifestyle advice and care dependent on the results.

Keywords: HbA1c; Mendelian randomization; Randomized trials; cardiovascular outcomes; lifestyle.

Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Publication types

• Research Support, Non-U.S. Gov't
• Cardiovascular Diseases* / etiology
• Cardiovascular Diseases* / prevention & control
• Diabetes Mellitus, Type 2* / drug therapy
• Hydroxymethylglutaryl-CoA Reductase Inhibitors* / adverse effects
• Hydroxymethylglutaryl-CoA Reductase Inhibitors

Grants and funding

• RE/18/6/34217/BHF_/British Heart Foundation/United Kingdom

Statins and Diabetes: What You Should Know

Heart disease is one of the most common complications of diabetes. Taking medicine to lower your cholesterol levels can be key to preventing heart disease and stroke.

Lifestyle changes such as eating healthy and being active are an important part of managing diabetes. But your doctor may also prescribe a combination of medicines to help you manage your diabetes and reduce the risk of complications. Because heart disease is one of the most common complications of diabetes, taking statins to lower your cholesterol levels can be key to preventing heart disease and stroke.

Heart disease is the leading cause of death for people in the United States, especially among White, Black, and Native Hawaiian or Other Pacific Islander people. While heart disease and stroke can affect anyone, people with certain health conditions, like diabetes, are at higher risk. People with diabetes are twice as likely to have heart disease or a stroke compared to people without diabetes. And the longer you have diabetes, the more likely you are to have heart disease. This is because over time, high blood sugar can damage the blood vessels and nerves that control your heart.

A common cause of heart disease for people with diabetes is plaque ( cholesterol deposits) that builds up in the arteries. When plaque continues to build, your arteries narrow, making it harder for blood to flow to your heart. This can cause heart muscles to weaken, which can increase the risk of heart attack and stroke. For this reason, your doctor may prescribe a statin (blood cholesterol-lowering medicine) to reduce your risk of heart disease.

About half of people who are taking medicine to manage their high blood cholesterol are using a statin. While statin use is highly recommended to lower the risk of heart disease, research shows that younger adults, women, and people without insurance are less likely to receive a statin prescription. Compared with non-Hispanic White people, non-Hispanic Black and Hispanic people have lower rates of cholesterol management. Further, women and Black adults are less likely to use statins. It’s important to know your risk for heart disease and stroke and to talk to your health care professional about all possible treatment plans.

What Are Statins?

Statins are a type of cholesterol-lowering medicine that reduces the amount of cholesterol made in the liver. Statins also help remove LDL (“bad”) cholesterol that’s already in the blood and raise your HDL (“good”) cholesterol . They can also:

• Reduce the buildup of plaque on the walls of your arteries.
• Stabilize plaque so that it doesn’t break off and block blood flow to the heart or brain.
• Decrease swelling in the walls of your arteries.
• Decrease the chance of blood clots forming.

There are several types of statins, each with different dosage levels and intensity (strength). A statin prescription will be based on your individual factors. These include your blood cholesterol levels, your risk for heart disease, and your tolerance of a specific statin. Your health care team will work with you to determine the best type and dosage to reduce your risk of heart disease and manage your diabetes.

Can Statins Increase Blood Sugar?

Some research has found that using statins increases blood sugar because statin use can stop your body’s insulin from doing its job properly. This can put people who use statins at higher risk of developing type 2 diabetes.

Despite the risk, statin use is still recommended for many people with and without diabetes who have high blood cholesterol. This is because even though there are risks with taking this medicine, there are greater potential risks if you don’t take them, like having a heart attack or stroke. Remember everyone is different. It’s always best to talk to your doctor about your individual risks and benefits of taking statins.

What Else Can I Do to Protect My Heart?

Having healthy cholesterol and blood sugar levels are important to reduce your risk of heart disease.

Although statins help reduce your risk of heart disease, healthy lifestyle habits are an important part of reducing your risk. Lifestyle changes you can make to reduce your risk include:

• Eating healthy. Include more whole grains, fruits and non-starchy vegetables, and lean protein in each meal . Also try to avoid foods high in added sugars, saturated fat, and sodium (salt).
• Maintaining a healthy weight. Too much belly fat can increase your risk for type 2 diabetes, heart disease, and stroke. If your body mass index (BMI) falls within the overweight or obesity range , losing even just a few pounds can lower your cholesterol and blood sugar levels.
• Being active. One of the best ways to manage diabetes is to get regular physical activity . Little changes like taking the stairs instead of the elevator are good ways to get your body moving.
• Managing your blood sugar. High blood sugar damages blood vessels and nerves throughout different parts of your body, including your heart. Keeping your blood sugar in your target range is key for managing diabetes and preventing serious complications.
• Managing your blood pressure. High blood pressure can damage your arteries by making them less elastic. This can decrease the flow of blood and oxygen to your heart and leads to heart disease. A normal blood pressure is below 120/80 mm Hg  (or the target your health care professional sets).
• Limiting or avoiding alcohol. The  Dietary Guidelines for Americans   recommends  that adults of legal drinking age choose not to drink, or drink in moderation. This means two drinks or less a day for men or one drink or less a day for women. Drinking at levels above the moderate drinking guidelines increases the risk of health problems, like high blood pressure and some types of cancer.
• Quitting smoking if you smoke. Smoking greatly increases your risk for heart disease. If you smoke, there are several programs and resources to help you quit. If you don’t smoke, don’t start.

Talk to Your Doctor

Be sure to talk to your doctor if you have any questions or concerns about your diabetes management and treatment plan. And don’t forget, you can work with a diabetes care and education specialist to help avoid health complications such as heart disease. Your care team is there to help you prevent or treat any health problems caused by diabetes.

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Statins and new-onset diabetes in primary prevention setting: an updated meta-analysis stratified by baseline diabetes risk

• Original Article
• Published: 07 November 2023
• Volume 61 , pages 351–360, ( 2024 )

Cite this article

• Walter Masson   ORCID: orcid.org/0000-0002-5620-6468 1 ,
• Martín Lobo 2 ,
• Leandro Barbagelata 1 &
• Juan P. Nogueira 3 , 4  

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The use of statins has been associated with an increased risk of new-onset diabetes. The characteristics of the population could influence this association. The objective of this study was to determine the risk of new-onset diabetes with the use of statins in patients in primary prevention, with an assessment of the results according to the baseline risk of developing diabetes of the included population.

We performed an updated meta-analysis including randomized trials of statin therapy in primary prevention settings that report new-onset diabetes. The rate of new cases of diabetes in the control arms was estimated for each study. The studies were classified into two groups (low rate: < 7.5 events per 1000 patients-year; high rate; ≥ 7.5 events per 1000 patients-year). The fixed-effects model was performed.

Eight studies (70,453 patients) were included. Globally, statin therapy was associated with an increased risk of new-onset diabetes (OR 1.1; 95% CI 1.0–1.2, I 2 35%) . When we analyzed the studies according to the baseline diabetes risk in the control groups, the results showed that there was a greater risk only in the studies with a high baseline rate (OR 1.2; 95% CI 1.1–1.3, I 2 0%; interaction p value = 0.01).

Globally, the use of statins in patients in primary prevention was associated with an increased risk of new-onset diabetes. In the stratified analysis, this association was observed only in the group of studies with a high baseline rate of events.

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WM and LB participated in the conception and design of the research. WM, LB and JPN participated in the data collection. The interpretation of the data and the statistical analysis was done by WM and ML. WM and LB drafted the manuscript. All authors performed a critical review of the final document. All authors have read and agreed to the published version of the manuscript.

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Masson, W., Lobo, M., Barbagelata, L. et al. Statins and new-onset diabetes in primary prevention setting: an updated meta-analysis stratified by baseline diabetes risk. Acta Diabetol 61 , 351–360 (2024). https://doi.org/10.1007/s00592-023-02205-w

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• Published: 22 April 2019

Association between statin treatment and new-onset diabetes mellitus: a population based case–control study

• Dong-Won Kim 1 ,
• Do-Hoon Kim 1   na1 ,
• Joo-Hyun Park   ORCID: orcid.org/0000-0002-4358-4208 1   na1 ,
• Moonyoung Choi 1 ,
• Shinhye Kim 1 ,
• Hyonchong Kim 1 ,
• Da-eun Seul 1 ,
• Soo-Gyeong Park 1 ,
• Jin-Hyung Jung 2 ,
• Kyungdo Han 2 &
• Yong-Gyu Park 2  

Diabetology & Metabolic Syndrome volume  11 , Article number:  30 ( 2019 ) Cite this article

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Metrics details

Several studies suggest that statin may increase the risk of new-onset diabetes mellitus (NODM). This study aimed to evaluate the association between the duration and recent use of statin, and the risk of NODM, based on population-based data sets.

We used the South Korean National Health Insurance Service National Sample Cohort database for this nationwide case–control study. Of the 1 million participants, 6417 participants with NODM in 2012–2013 and 32,085 controls without diabetes (1:5 propensity score matched with age, sex, index year, and year of diabetes diagnosis) were included. In these patients, we examined the statin prescription record for 3 years preceding the outcome. We used conditional logistic regression to calculate the odds ratios (ORs) and 95% confidence intervals (CIs).

After adjustment of covariates, there were no significant differences in the risk of NODM when analyzed according to cumulative use days. The risk of NODM was increased only in the short-term and recent user group (OR 1.48, 95% CI 1.21 to 1.82) whose cumulative prescription days are less than 6 months and whose last prescription is within 6 months of diagnosis.

Conclusions

The risk of NODM was not associated with an increase in the cumulative duration of statin use or with non-recent use. Only recent short-term use of statin was associated with an increased risk of NODM. Diabetes screening are warranted during initial statin therapy.

Statins, also known as HMG-CoA reductase inhibitors, are among the most commonly used drugs for the prevention of cardiovascular disease (CVD). Clinical evidence for the benefit of statin therapy has already been demonstrated in several studies [ 1 , 2 , 3 ], and the drug is generally considered to be relatively safe [ 4 ]. Furthermore, in the recent recommendation for the treatment of hyperlipidemia, the 2013 American College of Cardiology/American Heart Association (ACC/AHA) guideline [ 5 ] extended the range of statin therapy in comparison to the previous 2002 National Cholesterol Education Program—Adult Treatment Panel III (NCEP-ATP III) guideline [ 6 ]. Because of this change, statins are expected to be used more widely.

However, as statin use increases, the risks associated with statin use are important. Questions on the relationship between statin use and new-onset diabetes mellitus (NODM) have been consistently raised, and recently conducted studies have reported several results on the increased risk of NODM [ 7 , 8 , 9 , 10 , 11 , 12 ]. Recently, the US Food and Drug Administration issued a warning on the possible increase in glucose and HbA1c levels, through changes in the labeling requirement for statin. In addition, the European Medicines Agency mentioned that statins could increase the risk of type 2 diabetes [ 13 ].

However, current available evidence is mainly based on post hoc analyses of randomized controlled trials or meta-analytic results derived from predominantly Western populations. Several studies suggest that Asians are more sensitive to statin therapy and adverse effects could be greater [ 14 , 15 ], but only a small number of Asians were included in previous studies. Namely, the debate on the side effects of statin-induced diabetes mellitus (DM) is on-going and clear assessment of the increased risk of NODM due to statin use is very important.

Therefore, this study attempted to analyze the risk of NODM according to the duration and recent use of statin therapy using data from the database of the Korean National Health Insurance Service-National Sample Cohort (NHIS-NSC).

Data source

This study used data from the NHIS-NSC database, which consists of approximately one million medical insurance subscribers, who were selected using the stratified random sampling method with 1476 strata by sex (2 strata), age (18 strata), and level of income (41 strata) [ 16 ]. NHIS-NSC database is a randomized sample of 2% of the national population of the Republic of Korea and the subscribers were followed from January 2012 to December 2013.

The NHIS-NSC contains information about participants’ insurance eligibility, medical treatment history, healthcare provider’s institution and general health examination. The insurance eligibility database also includes information on the participant’s identity and socioeconomic situation. The medical treatment database includes details of medical treatment, disease diagnoses codes, and prescriptions. The institutional review board (IRB) of Korea University approved the progress of this study (IRB-AS15103). The ethics committee waived the need for participant consent, because the study involved routinely collected medical data that were anonymized at all stages, including during the data cleaning and statistical analysis. This study was carried out according to the ethical principles of the Declaration of Helsinki of the World Medical Association.

Case–control patient selection from the cohort data

Figure  1 provides information on the participants’ selection. Of the 1 million individuals included in the NHIS-NSC, 387,683, who received screening within the period from January 1, 2012 to December 31, 2013, were selected. A total of 8025 patients who were newly diagnosed with diabetes mellitus (DM), were selected for the study, except for those who were under 20 years of age and those who were prescribed statin only once. In these patients, we observed a record of statin prescriptions for 3 years prior to diagnosis of NODM. Therefore, the study period was defined as 2009–2013, and the wash-out period was 3 years before the study period (2006–2009). We restricted statin users to new statin-users by excluding patients with statin use records for the wash-out period. Patients were also excluded from the study if they were diagnosed with T2DM or they had a history of antidiabetic medication use before the study period. NODM was defined as a fasting glucose level of 126 mg/dl or more, or as a record of a T2DM diagnosis (E11.0–E11.9 based on the ICD-9) and prescription of one or more antidiabetic agents. Finally 6417 patients were selected and assigned to the NODM (case) group. The controls who were not diagnosed for diabetes from 2012 to 2013, were also obtained from the NHIS-NSC database. Of them, 32,085 were assigned to the control group through 1:5 propensity score (PS) matching with age and sex. A PS analysis was carried out on sampled cohorts with logistic regression by age and sex to address selection bias and the presence of potential confounding variables.

Flow diagram of participants included or excluded

Statin exposure, duration, and recent use

Information on statins was extracted from the NHIS-NSC prescription data. We examined prescription records of statins for the previous 3 years from the date of diagnosis of NODM. Patients with statin prescription record for 3 years before diabetes diagnosis were defined as statin users and patients without prescription records for the same period were defined as statin non-users. The total number of days of administration was obtained in the statin user group. The ICD-9 code confirmed the diabetes diagnosis. In addition, we defined the recent use as the presence of statin prescription within 6 months of outcome, and performed a subgroup analysis, depending on whether the recent use.

Determinants of disease and demographic factors

The characteristics of the subjects were defined as information from 2012 to 2013 when they were screened. Smoking, drinking, and exercise status were measured by a self-questionnaire and defined as follows; smoking (current smoker, more than 100 cigarettes and current smoker; non-smoker and ex-smoker, less than 100 cigarettes in a lifetime; ex-smoker, more than 100 cigarettes but former smoker), physical activity (regular exercise, 3 or more days of intense 20 min daily workouts, or 5 or more days of moderate 30 min daily workouts, weekly; no regular exercise), Current drinker (current drinker; non-drinker, those who answered “I do not drink” to the question “How many drinks do you drink?”) Socioeconomic status was divided into 2 groups: 70% including upper and middle levels, and 30% including lower levels. Body mass index (BMI) was defined as body weight divided by height squared, and is expressed in units of kg/m 2 The medical records and diagnoses of the participants were examined for ICD-9 diagnostic codes, drug codes, prescription drugs, and past medical history.

Potential confounders

We performed variable adjustments to select potential confounders. We adjusted for sex, alcohol consumption, smoking and exercise status, BMI, total cholesterol, waist circumference, and hypertension, which are potential confounders that may affect the relationship between statin use and the generation of diabetes.

Statistical analysis

Continuous variables are compared using paired t-tests, and categorical variables are compared using Chi-square tests. A conditional logistic regression model was used to estimate the relative importance of statin therapy. Five groups were identified according to the duration of statin administration: (1) non-users, (2) less than 6 months, (3) 6 months to less than 1 year, (4) 1 year to less than 2 years, (5) 2 year to less than 3 years. For the subgroup analysis of recent use, we divided participants into two groups: recent users (with a prescription record within 6 months) and others (no prescription record within 6 months). Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using unexposed patients as a reference. All statistical analyses were performed using the SAS statistical package (version 9.3, SAS Institute INC). P < 0.05 was considered statistically significant in all the tests.

Table  1 shows the baseline characteristics of those with NODM (case group) and with the non-diabetes control group. We compared each characteristic between the groups, and the 2 groups were balanced in age and sex. The NODM group had the higher BMI, waist circumference (WC), systolic BP (SBP), diastolic BP (DBP), low-density lipoprotein-cholesterol (LDL-C) and triglyceride (TG) level and lower high-density lipoprotein-cholesterol (HDL-C) level than those of non-NODM group. NODM group is more likely to smoke cigarettes and exercise, and less drink alcohol. Socio-Economic levels were lower in the NODM group.

Table  2 shows the association of NODM risk with the duration of statin therapy. After PS matching and adjusting for age and sex, the risk of NODM was significant in statin users compared with non-statin users. However after additional adjustment for drinking, smoking, exercise, BMI, HDL-C, LDL-C, TG, WC, hypertension, no significant increase in NODM risk was observed in the statin user during the 3-year observation period. When analyzed on a per-term basis, significant results were obtained between statin treatment and risk of NODM after the adjustment for age and sex, but were not showed after the adjustment for multiple covariates regardless of the duration of the therapy.

Namely, no statistically significant difference was found in the simple comparison of statin and NODM (OR 1.03, 95% CI 0.93 to 1.14). Analysis of the treatment duration also did not show an increase in NODM risk in all the groups. This implies that the duration of statin therapy is not associated with an increased risk of NODM.

This study further analyzed the effect of recent statin use on NODM risk. Table  3 shows an analysis of the increased risk of NODM with statin therapy duration and recent use. After adjustment for covariates, NODM risk was statistically significantly increased in patients who were prescribed statins for a short period of less than 6 months and within the last 6 months compared to non-statin users (OR 1.48, 95% CI 1.21 to 1.82).

In the present study, the risk of NODM did not increase as the cumulative number of days of statin use increased. Also, the risk of NODM did not increase in non-recent statin users. We observed that the risk of NODM increased only in those in the recent users group who received statin within the last 6 months and short-term user group in the duration of less than 6 months. Namely, the risk of NODM increased in the early stages of statin treatment in Korean general population. This study was conducted to obtain clinically valuable results by analyzing how NODM risk differs according to the time and interval of taking medicine.

The results of the previous studies on the associations between statin use and NODM were as follows. In the Justification for the Use of Statins in Primary Prevention: An Intervention Trial Evaluating Rosuvastatin (JUPITER) trial [ 17 ], which demonstrated the efficacy of rosuvastatin in preventing CVD, a 25% increase in diabetes risk was reported. In the Anglo-Scandinavian Cardiac Outcomes Trial–Lipid Lowering Arm (ASCOT–LLA) [ 18 ], atorvastatin reduced incidences of non-fatal myocardial infarction and fatal coronary artery disease by 36%, and increased the risk of diabetes by 14%. Most other studies and several meta-analyses have also reported that statin use increases the risk of NODM [ 8 , 11 , 19 , 20 , 21 , 22 , 23 ]. These studies have reported that statin increases NODM regardless of the type, although there is a difference in degree.

One WOSCOPS study reported that men with hypercholesterolemia, aged 45–64 years, had a 30% reduction in the risk of developing NODM after 5 years of pravastatin treatment [ 24 ]. However, in the PROSTPER study where pravastatin was given to elderly subjects aged 70 years or older, the risk of diabetes increased by 32% by statin treatment [ 22 ].

Since statin has been implicated in the development of NODM, several studies have reported the biologic mechanisms behind the diabetes-inducing effects of statin. One study suggests that the inhibition of the statin target 3-hydroxy-methylglutaryl-CoA reductase (HMGCR) is an important mechanism [ 25 ]. HMGCR genetic variants and statin treatment were associated with higher body weight and higher risk of type 2 diabetes, suggesting that these effects are a consequence of HMGCR inhibition [ 25 ]. In addition, several independent studies reported that low LDL-C levels have been associated with an increased risk of NODM [ 26 ]. The genetic predisposition of dyslipidemia, FBG, HbA1c, and HOMA-IR, was associated with a lower level of diabetes-related indicators [ 27 ]. High blood LDL-C levels were also associated with a lower risk of diabetes, which was demonstrated by an SNP analysis of the lipid metabolism-related genes [ 28 ]. Another study also reported that the prevalence of type 2 DM was low in patients with familial hypercholesterolemia [ 29 ]. As another mechanism, several studies have shown that statin therapy can be detrimental to pancreatic beta cell function [ 30 ]. Statin dose-dependently induces ß cell damage and insulin resistance in the smooth muscle cells [ 31 ], reduces glucose transporter 4 (GLUT4) expression which is involved in glucose uptake in the peripheral cells [ 31 , 32 , 33 ], and decreases insulin signaling [ 34 , 35 ]. It also inhibits adipocyte differentiation and leads to cell accumulation, so the insulin-sensitive and insulin-resistance hormones cannot be secreted [ 32 ]. Further studies are underway, focusing on the additional mechanisms such as the link between statin therapy and specific microRNAs associated with reduced insulin secretion [ 30 ].

As such, many studies have shown that the use of statin increases the NODM risk [ 8 , 9 , 10 , 11 , 12 , 36 , 37 , 38 ]. However, very few studies have been made on the effects of recent statin uses on the incidence of diabetes, particularly in general Asian populations. Several reports have suggested that recent statin dosing may increase the risk of NODM. There are reports that the short-term risk of diabetes due to statin therapy is higher in patients with diabetes risk factors [ 37 , 39 , 40 ]. In prediabetes patients, who are susceptible to the development of type 2 diabetes, the effects of statin use, such as insulin resistance induction, decreased GLUT4 expression and pancreatic β cell function, may contribute to an increased risk of diabetes [ 30 , 31 , 32 , 33 , 34 , 35 ]. In addition, recent guidance suggests that checking FBG and HbA1c levels before starting statin treatment may be helpful in pre-diabetic patients with high diabetes risk [ 41 ]. This suggests that the results of the present study support the clinical significance of diabetes screening in patients treated with statins.

This study has several strengths. In the present study, we used NHIS-NSC data to include various factors such as age, sex, alcohol consumption, smoking and exercise status, BMI, HDL-C, LDL-C and TG level, WC and hypertension. Calibration improved the quality of the analysis. We also analyzed the association between statin and NODM risk based on a large-scale database of 1 million people. This study is based on the cohort data of 2% of the population of the Republic of Korea that is representative of the nationwide population. Unlike previously conducted retrospective studies, in this study, each patient was analyzed for NODM risk according to statin use for the same 3-year period. PS matching is a statistically meaningful analytical technique that can effectively control disturbance factors. In this research, we strived to minimize statistical bias through PS matching. We also presented a new perspective on the relationship between statin and NODM risk, by analyzing the duration and recent use of statin therapy, which were previously untried.

Nonetheless there are some limitations to this study. First, the NHIS-NSC database does not contain HbA1c results, so it is hard to tell if the definitive diagnostic criteria for diabetes are applied. Second, we could not consider the type of statin and dosage. A meta-analysis has shown that intensive-dose statin therapy was associated with an increased risk of NODM compared with moderate-dose statin therapy [ 42 ]. Further research is therefore needed.

There is a possibility of an indication bias between the recent use of statin and increased risk of NODM, as with other observational studies. Prediabetes, an important risk factor for type 2 diabetes, is often associated with hyperlipidemia [ 43 ]; therefore, it is highly likely that participants with prediabetes had been treated with statin. There is also the possibility of detection bias. It is possible to speculate that patients who have been prescribed statins are clinically evaluated because of the high frequency of visits to the hospital, and are likelier to be diagnosed with diabetes. Unlike randomized studies, observational studies are based on long-term follow-up data from large numbers of participants, which may increase the chance of developing or diagnosing diseases such as diabetes, which can take many years. In this study, we tried to adjust the parameters to eliminate the above bias through PS matching.

This nationwide survey using medical claim data from the NHIS-NSC has shown that the risk of NODM did not increase as the cumulative number of days of statin use increased. Also, the risk of NODM did not increase in non-recent statin users. The risk of NODM increased only in the early stages of statin treatment in Korean general population.

This study is valuable in terms of supporting the clinical value of performing diabetes screening, clinically, when starting statin therapy. When starting statin therapy, life style modification needs to be emphasized and the potential benefits and side effects of statin need to be discussed. Also, periodic screening and monitor-ing for DM may be required. In addition, these findings warrant further studies to determine how long and at what intervals diabetes screening should be initiated after starting statin therapy.

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Authors’ contributions

D-HK conceived this project, and J-HP designed the study. D-WK analyzed the data, wrote the manuscript, and had primary responsibility for final content. SK and MC discussed the results, and HK, D-ES and S-GP commented on the manuscript. K-DH, J-HJ and Y-GP was responsible for statistical work and analysis. All authors read and approved the final manuscript.

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This study was supported by a grant from Korea University in South Korea (K1422241) and Abbott Laboratories.

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Do-Hoon Kim and Joo-Hyun Park contributed equally to this study

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Department of Family Medicine, Korea University Ansan Hospital, Korea University College of Medicine, 123, Jeokgeum-ro, Danwon-gu, Ansan-si, Gyeonggi-do, 15355, Republic of Korea

Dong-Won Kim, Do-Hoon Kim, Joo-Hyun Park, Moonyoung Choi, Shinhye Kim, Hyonchong Kim, Da-eun Seul & Soo-Gyeong Park

Department of Biostatistics, Catholic University College of Medicine, Seoul, Republic of Korea

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Kim, DW., Kim, DH., Park, JH. et al. Association between statin treatment and new-onset diabetes mellitus: a population based case–control study. Diabetol Metab Syndr 11 , 30 (2019). https://doi.org/10.1186/s13098-019-0427-9

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JEAN Y. PARK , ADLINE GHAZI , ANASTASSIOS G. PITTAS , ELLEN VICKERY , JASON P. NELSON , VANITA R. ARODA , D2D RESEARCH GROUP; 854-P: Statin Use and New-Onset Diabetes in People with Prediabetes. Diabetes 1 June 2022; 71 (Supplement_1): 854–P. https://doi.org/10.2337/db22-854-P

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Statins lower the risk of cardiovascular disease, yet may adversely affect glucose metabolism. In the D2d study, which evaluated the effect of vitamin D versus placebo in a contemporary cohort of people with high-risk prediabetes (n=2,423) , we evaluated the association between statin use at baseline and progression to diabetes.

In the D2d study, 1396 participants (58%) were on statin at baseline. Kaplan Meier curves of incident diabetes over 2.5 years by baseline status of statin use and adjusted hazard ratio (95%CI) of the difference in incident diabetes between statin and no statin use were estimated. We tested for a statin use * D2d assignment (vitamin D or placebo) interaction on incident diabetes.

Mean age (SD) was 57±years and 64±8 for those not on vs. on statin; baseline HbA1c was 5.9 ± 0.2% in both groups. 27% of statin users developed diabetes vs. 24% of non-statin users (adjusted HR [95%CI] 1.23 [1.04-1.46]) (Figure) . There was no significant interaction (p=0.67) with vitamin D treatment assignment; therefore, subgroup analyses by D2d treatment assignment are not presented.

Conclusions: In this observational analysis among people at high risk for diabetes, baseline statin use was associated with a 23% higher risk of progression to diabetes after 2.5 years compared to no use. Increased risk of diabetes progression should be considered along with the cardiovascular benefits of statin therapy and diabetes prevention measures re-enforced.

J.Y.Park: None. A.Ghazi: None. A.G.Pittas: None. E.Vickery: None. J.P.Nelson: None. V.R.Aroda: Consultant; Applied Therapeutics, Fractyl Health, Inc., Novo Nordisk, Pfizer Inc., Sanofi, Other Relationship; Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Research Support; Applied Therapeutics, Fractyl Health, Inc., Novo Nordisk, Sanofi. D2d research group: n/a.

American Diabetes Association (1-14-D2d-01) ; National Institutes of Health National Institute of Diabetes and Digestive and Kidney Diseases and Office of Dietary Supplements (U01DK098245)

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• v.95(46); 2016 Nov

Statins and risk for new-onset diabetes mellitus

Dukyong yoon.

a Department of Biomedical Informatics

Seung Soo Sheen

b Department of Pulmonary and Critical Care Medicine, Ajou University School of Medicine

Sukhyang Lee

c College of Pharmacy, Ajou University

Yong Jun Choi

d Department of Endocrinology and Metabolism

Rae Woong Park

Hong-seok lim.

e Department of Cardiology, Ajou University School of Medicine, Suwon, Republic of Korea.

Associated Data

Supplemental Digital Content is available in the text

Although concern regarding the increased risk for new-onset diabetes mellitus (NODM) after statin treatment has been raised, there has been a lack of evidence in real-world clinical practice, particularly in East Asians. We investigated whether statin use is associated with risk for NODM in Koreans. We conducted a retrospective cohort study using the clinical research database from electronic health records. The study cohort consisted of 8265 statin-exposed and 33,060 matched nonexposed patients between January 1996 and August 2013. Matching at a 1:4 ratio was performed using a propensity score based on age, gender, baseline glucose levels (mg/dL), and hypertension. The comparative risks for NODM with various statins (atorvastatin, fluvastatin, pitavastatin, pravastatin, rosuvastatin, and simvastatin) were estimated by both statin exposure versus matched nonexposed and within-class comparisons. The incidence of NODM among the statin-exposed group (6.000 per 1000 patient-years [PY]) was higher than that of the nonexposed group (3.244 per 1000 PY). The hazard ratio (HR) of NODM after statin exposure was 1.872 (95% confidence interval [CI], 1.432–2.445). Male gender (HR, 1.944; 95% CI, 1.497–2.523), baseline glucose per mg/dL (HR, 1.014; 95% CI, 1.013–1.016), hypertension (HR, 2.232; 95% CI, 1.515–3.288), and thiazide use (HR, 1.337; 95% CI, 1.081–1.655) showed an increased risk for NODM, while angiotensin-converting enzyme inhibitor or angiotensin II receptor blocker showed a decreased risk (HR, 0.774; 95% CI, 0.668–0.897). Atorvastatin-exposed patients showed a higher risk for NODM than their matched nonexposed counterparts (HR, 1.939; 95% CI, 1.278–2.943). However, the risk for NODM was not significantly different among statins in within-class comparisons. In conclusion, an increased risk for NODM was observed among statin users in a practical healthcare setting in Korea.

1. Introduction

Statins, also known as 3-hydroxy-3-methyl-glutaryl coenzyme-A reductase inhibitors, are key agents for treating dyslipidemia, a major cardiovascular disease risk factor. [ 1 ] In addition to their ability to lower cholesterol levels in serum, several beneficial pleiotropic effects such as improved endothelial function, stabilization of atherosclerotic plaques, and anti-inflammatory actions have been identified, and the effectiveness of statins for the primary and secondary prevention of cardiovascular disease has been confirmed. [ 2 – 4 ]

Although statins are safe and generally well tolerated by most patients, several relevant adverse effects, mostly myopathy and elevated liver enzymes, may occur. [ 5 ] Among them, one recently emerging risk is the increased incidence of new-onset diabetes mellitus (NODM) associated with statin treatment, [ 6 – 8 ] which prompted the United States Food and Drug Administration to add information to statin labels regarding the increased risk for NODM. [ 9 ]

However, current available evidence is mainly based on post hoc analyses of randomized controlled trials or meta-analytic results derived from predominantly Western populations; thus, further investigations on the risk for statin-induced NODM in unrestricted real-world clinical practice are necessary, particularly in East Asians. Moreover, bodies of evidence on the comparative safety and risks of NODM between various statins are conflicting. [ 10 – 13 ]

In contrast to clinical trial data, electronic health record (EHR) data gathered from daily practice can provide real-world evidence for diverse observational studies. Demographic information and medical records including information such as diagnoses, prescribed drugs, laboratory test results, and inpatient or outpatient visits are available in EHR data. Although using data recorded as free text (radiology reports and nursing records) is technically challenging, coded data (diagnoses, prescriptions, and laboratory test results) are precise and objective and have been widely used for observational studies. [ 14 , 15 ] Furthermore, EHRs contain large amount of data that can afford sufficient statistical power in many cases that clinical trials cannot, due to the limitation of sample size.

We investigated the risk for NODM with statin treatment in real-world clinical settings using a large amount of observational data from EHRs in Korea. First, we evaluated the comparative risk of NODM between statin-exposed patients versus matched nonexposed patients as the primary endpoint. Second, to evaluate the risk of NODM with various statins as a secondary endpoint, we compared patients exposed to a statin with their matched nonexposed counterparts and those exposed to other statins (within-class comparison analysis).

2.1. Data source

We used a clinical research database containing basic information on patient demographics, diagnoses, drug prescriptions, and laboratory test results originating from the EHRs of a tertiary teaching hospital in Korea (Ajou University Hospital) between January 1996 and August 2013. The database included 116,621,303 prescriptions and 158,122,528 laboratory test results from 1980,385 patients. This study was approved by the local Institutional Review Board, and informed consent was waived (MED-MDB-14-201).

2.2. Patient selection and cohort definition

The study cohort consisted of statin-exposed patients and nonexposed patients who were 18 years of age or older in the subject hospital (Fig. ​ (Fig.1). 1 ). Statin-exposed patients were patients exposed to statins for more than 90 consecutive days. Continuous exposure was defined as follows: if repeated prescription of the drug was followed within a 30-day window, 2 prescriptions were considered continuous administration. For the selection of nonexposed patients, those followed up for more than 90 days and not exposed to any statins were selected. The exposure patients were divided into 6 subgroups according to the type of statin: atorvastatin, fluvastatin, pitavastatin, pravastatin, rosuvastatin, and simvastatin. Each subgroup included patients who took each statin continuously for more than 90 days. To include only incident users, when a patient had more than 2 continuous administration periods, only the first one was included in the study. Patients with a proportion of days covering <60% were excluded. Patients who had a psychiatric disorder or received organ transplant(s) were excluded due to the established high risk for NODM in these groups.

Overview of the study design. To evaluate the risk for new-onset diabetes mellitus (NODM) after exposure to statins, statin-exposed patients were compared to matched nonexposed patients (comparison 1). To evaluate the risks associated with 6 different statins (atorvastatin, fluvastatin, pitavastatin, pravastatin, rosuvastatin, and simvastatin), comparison 2 (comparison between patients exposed to each statin and the matched nonexposed patients) and comparison 3 (within-class analysis) were conducted.

Observation for statin exposure began at day 91 from the first exposure to evaluate the long-term effects of statins on NODM. At the observation start point, patients who already had diabetes mellitus (DM) were excluded (Fig. ​ (Fig.1). 1 ). To exclude DM patients, we only included patients who visited the subject hospital more than once, regardless of outpatient visits or hospitalization, and patients who had more than 1 fasting glucose measurement before the start of observation. We also excluded patients with abnormal random glucose levels (≥200 mg/dL), abnormal fasting glucose levels (≥126 mg/dL), abnormal hemoglobin A1c (HbA1c) results (≥6.5%), those with International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) diagnosis codes related to diabetes (E10–E14), and those who had received a prescription for diabetes medication(s) (acarbose, gemigliptin, glibenclamide, gliclazide, glimepiride, linagliptin, metformin, mitiglinide, nateglinide, pioglitazone, repaglinide, saxagliptin, sitagliptin, vildagliptin, and voglibose) including insulin before the start of observations.

The statin nonexposed group included patients who were never exposed to a statin in the subject hospital and were followed up for more than 90 days (Fig. ​ (Fig.1). 1 ). Observations for the nonexposed group were started at the earliest point meeting the following conditions: the patient visited the subject hospital more than twice, regardless of outpatient visits or hospitalization, and had more than 1 fasting and random glucose measurement, but before having abnormal random glucose levels (≥200 mg/dL), abnormal fasting glucose levels (≥126 mg/dL), abnormal HbA1c results, ICD-10 codes related to diabetes (E10–E14), or prescriptions for diabetes medication(s) as described above. Patients who had no observation period defined in this study were excluded.

Observation was ended when the endpoint, NODM, occurred at the subject hospital. NODM was detected using an existing NODM-detection algorithm. [ 16 ] The original version used ICD-9-CM codes, but we modified it to use ICD-10 codes to apply to our data (Supplementary figure S1). First, the algorithm excludes patients who have type 1 DM diagnosis codes (ICD-10 E10). If patients have type 2 DM (T2DM) diagnosis codes (ICD-10 E11), the algorithm checks whether their medication history met the T2DM treatment standard. In cases without T2DM diagnosis codes, patients who received medication(s) for T2DM and had abnormal glucose or HbA1c results were identified as T2DM patients. The earliest time at which patients met the algorithm was considered the time the event occurred.

2.3. Observational variables

We obtained information on age, gender, baseline glucose, the Charlson comorbidity index (CCI), and all concomitant drugs, including thiazide-type diuretics, beta-blockers, angiotensin-converting enzyme inhibitor (ACEi), and angiotensin II receptor blocker (ARB). The age-adjusted CCI is an index of comorbidity. It is calculated using age and the presence of diverse medical conditions. Many studies have used the CCI to select subject groups, minimize group variability, and relay the risk of morbidity. Patients exposed to a fixed-dose combination of ACEi or ARB and thiazide were considered exposed to both ACEi/ARB and thiazide-type diuretics. For each observed drug, the level of exposure was categorized into 3 levels: 0 for nonexposed, 1 for exposure to the drug but the prescribed drug count was less than the median value among the patients exposed to the drug, and 2 for the prescribed drug count equal to or greater than the median value.

2.4. Risk evaluation of NODM after statin exposure

Three models of comparison were used to evaluate the risk for NODM after statin exposure and exposure to individual statins (Fig. ​ (Fig.1). 1 ). In the first model, we compared the risk for NODM between statin-exposed patients and their matched nonexposed counterparts using propensity score matching (1:4 ratio), including the observation period, age, gender, baseline glucose levels, CCI, and hypertension.

In comparisons 2 and 3, we evaluated the risk for NODM after exposure to atorvastatin, fluvastatin, pitavastatin, pravastatin, rosuvastatin, and simvastatin. In comparison 2, the risk for NODM was compared between patients exposed to a statin and matched nonexposed counterparts. The matching method and variables used for matching were the same as in comparison 1. In comparison 3, a within-class comparison was performed to compare the risk for NODM in patients exposed to 1 of the 6 statins with patients exposed to other statins.

2.5. Statistical analysis

For descriptive analyses, we report means with standard deviations for continuous variables and numbers with percentages for categorical variables. Differences in the characteristics between the exposure and comparison groups were compared using chi-square tests and t tests. To determine the incidence of NODM, we used events per 1000 patient-years (PY) during the observation period. The risk for NODM was compared using Kaplan–Meier analysis with the log-rank test. The adjusted hazard ratios (HRs) of statin exposure were estimated using Cox proportional hazards regression analysis after adjusting for age, gender, baseline glucose levels (per mg/dL); CCI at the start of observation; whether hypertension was present at the start of observation; and level of exposure to ACEi, ARB, beta-blockers, and thiazide-type diuretics during the observation period. Based on the results of the JUPITER trial, [ 6 ] we adopted the predicted diabetes incidence rate as 3.0% among statin-exposed patients and 2.4% among controls for the statistical power analysis. The estimated numbers of statin-exposed patients and 1:4 matched controls to be included in the study were 6967 and 27,868, respectively, with 80% power and a 5% 2-sided significance level. The numbers consider the planned sampling process used in our study. We used MS-SQL 2012 (Microsoft, Redmond, WA) as the database-management system. The R package (R Development Core Team, Vienna, Austria) was used for statistical analyses. A P value <0.05 was considered to indicate statistical significance.

3.1. Study group

We identified 14,607 patients as the statin-exposed group and 70,474 patients as their matched nonexposed counterparts (Fig. ​ (Fig.1). 1 ). During the observation period, 4328 patients were exposed to atorvastatin, 359 to fluvastatin, 403 to pitavastatin, 1357 to pravastatin, 1429 to rosuvastatin, 1148 to simvastatin, and 5583 to 2 or more types of statins. Based on propensity score matching, 8265 and 33,060 patients were assigned to the exposed and nonexposed groups, respectively. The matched baseline characteristics are presented in Table ​ Table1. 1 . Major risk factors for the occurrence of DM were well balanced between the exposed and nonexposed groups. In the exposed group, beta-blockers, ACEi/ARB, and thiazide-type diuretics were more frequently used and total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglyceride levels were higher compared to the nonexposed group.

Baseline characteristics of the statin-exposed and matched nonexposed groups.

3.2. Incidence of NODM

The incidence of NODM in the exposed group was 6.000 per 1000 PY and 3.244 in the matched nonexposed group (Table ​ (Table2). 2 ). The incidence rates according to the type of statin were as follows: 4.196 for atorvastatin, 4.176 for fluvastatin, 1.321 for pitavastatin, 4.716 for pravastatin, 4.770 for rosuvastatin, and 6.131 for simvastatin per 1000 PY.

Incidence of NODM according to statin exposure.

3.3. Risk for NODM due to statins

NODM-free survival curves of each group are shown in Fig. ​ Fig.2. 2 . Kaplan–Meier survival curves showed a significantly higher occurrence rate of the primary endpoint NODM in the exposed group ( P  <   0.001, log-rank test). A significant relationship between statin exposure and NODM was consistently shown even after adjusting for age, gender, baseline glucose levels, CCI, hypertension, ACEi/ARB, beta-blockers, and thiazide when using Cox proportional hazard regression analysis (Table ​ (Table3). 3 ). The HR of statin exposure was 1.872 (1.432–2.445). Older age, being male, having higher levels of baseline glucose, hypertension, and exposure to thiazide were the factors that significantly increased the risk for NODM, whereas having taken ACEi or ARB significantly decreased the risk.

Kaplan–Meier plot for new-onset diabetes mellitus (NODM)-free survival in the statin-exposed group and matched nonexposed group. Kaplan–Meier survival curves showed a significantly higher occurrence rate of the primary endpoint NODM in the statin-exposed group compared with that in the matched nonexposed group ( P  < 0.001, log-rank test).

HR of statins and observed variables in NODM.

In comparison 2, among the various statins, only the atorvastatin-exposed group had a significantly higher risk for NODM than their matched nonexposed counterparts. In comparisons 2 and 3, pitavastatin tended to have the lowest HR among the 6 statins but without statistical significance.

In addition, the body mass index (BMI), which was suggested to be a risk factor for statin-induced NODM, was available in 3392 statin-exposed patients with their 13,568 matched nonexposed counterparts. In this subgroup of patients, a significant association between statin exposure and NODM was observed after adjusting for age, gender, baseline glucose levels, hypertension, and BMI when using Cox proportional hazards regression analysis (Supplementary table S1). The HR of statin exposure was 1.641 (1.095–2.458). Higher levels of baseline glucose, hypertension, and BMI ≥ 25 were the factors that significantly increased the risk for NODM. Among the various statins, atorvastatin and simvastatin had a significantly higher risk for NODM than their matched nonexposed counterparts, while pitavastatin tended to have the lowest HR among the 6 individual statins but without statistical significance in comparisons 2 and 3 (refer to Supplementary table S1, Supplemental Content, which illustrates HR of statins and observed variables including BMI for NODM).

4. Discussion

We observed that statin treatment increases the risk for NODM in Korean patients. By providing evidence from real-world practice using a large-scale clinical database through an EHR processing algorithm, the results of the present study support and extend previous reports on the increased risk for incidental diabetes with statin treatment. [ 6 – 8 , 10 ]

Statins are an important medication for the primary and secondary prevention of atherosclerotic cardiovascular diseases and are the most widely used drug prescription due to their well proven benefits and level of safety. [ 1 , 2 , 4 , 17 ] However, after a concern was raised in 2009 that statins increase the risk for NODM, various follow-up studies have been performed, urging treatment guidelines to include labeling on the risk for NODM associated with statins. [ 6 – 9 , 18 ]

Statins not only have therapeutic value for hyperlipidemia but also various pleiotropic effects and are considered essential medications for the prevention and treatment of cardiovascular diseases. [ 2 , 4 , 17 ] However, because the risk for NODM is a serious adverse effect, reassessing the risks and benefits of statins is important to have balanced insight for treatment.

Most results from previous studies, however, have been based on post hoc analyses from large clinical studies or meta-analyses, [ 6 , 7 , 10 , 19 , 20 ] and additional evidence based on real-world clinical settings is needed, particularly in East Asians, due to the lack of studies in those populations. Although a prospective, large-scale clinical trial would be warranted to resolve these remaining issues, due to the amount of time, cost, and workforce that it would require, such a study will probably not be conducted in the near future. Given this context, the usefulness of the present study is enhanced. We identified occurrences of NODM using an EHR-based algorithm (Supplementary figure S1), and this was deemed a reliable method for the surveillance of NODM. [ 16 ] This algorithm provided stricter and more accurate criteria for detecting occurrences of DM than those used in previous studies that defined NODM mainly based on blood glucose, HbA1c levels, and the use of antidiabetic medications. In addition, by using EHR data, including a large number of patients, we were able to minimize selection bias and reflect real-world clinical settings properly despite the retrospective nature of our research.

The HR of 1.87 obtained in this study is a slightly higher value than the results from previous studies. However, this result parallels recent research conducted on Korean patients, in which the relative risk for NODM after statin treatment was high at 1.99, compared to a control group, even though the study included patients who used low-dose atorvastatin. [ 21 ] Accordingly, our results suggest that the risk for NODM related to statins might be higher in East Asians, including Koreans, than in Westerners and that, under real-world conditions, the risk for NODM occurrence might be higher than that in a well controlled prospective clinical trial.

One plausible explanation about the relatively higher HR for statin-induced NODM is the possibility that not only patients with simple dyslipidemia but patients with comorbid cardiovascular diseases might be included relatively more in the present study because it was conducted with patients treated at a tertiary hospital. However, although our results may not be generalizable to every patient in need of statin treatment, considering that patients with comorbid cardiovascular diseases (in whom strict secondary prevention is essential [ 22 ] ) need more active statin treatment, our results may hold important clinical implications.

The methodology that we used allowed us to evaluate the comparative risk for NODM according to the different types of statins. The results suggested that atorvastatin, one of the most lipophilic statins, significantly increased the risk for NODM. Although the mechanisms associated with an increased risk for DM and exposure to statins have not yet been fully revealed, lipophilic statins might be more diabetogenic via several harmful effects, they may have on glucose intolerance, because they penetrate the cell membrane easier and thus are likely to have more extrahepatic effects than hydrophilic statins. Lipophilic statins such as atorvastatin and simvastatin can reduce insulin secretion by inhibiting L-type Ca 2+ channels and exocytosis in pancreatic beta-cells. [ 23 ] In addition, they decrease the expression of glucose transporter 4 in adipocytes and aggravate insulin sensitivity. [ 24 , 25 ] However, these differences between lipophilic and hydrophilic statins need to be clarified further. [ 26 ]

On the other hand, although not statistically significant, pitavastatin tended to lower the risk for NODM in the present study. Similarly, in recent Japanese studies, it had a positive impact on glucose metabolism. [ 9 , 27 , 28 ] A decrease in coenzyme Q10 due to statins lowers the inflow of Ca 2+ , which is associated with insulin secretion, leading to abnormal glucose metabolism. [ 29 ] However, pitavastatin has been suggested to have minimal effects on coenzyme Q10 via a unique pharmacological mechanism. [ 30 , 31 ] In addition, it has been argued that, by increasing adiponectin and high-density lipoprotein cholesterol, pitavastatin favorably affects glucose metabolism. [ 30 , 32 ]

Meanwhile, when comparing HRs between statins, pitavastatin and pravastatin tended to produce a lower risk for NODM. However, because statistical significance was not observed, caution should be applied when interpreting these results, and further study is needed to verify this finding.

In addition, the use of ACEi or ARB reduced the occurrence of DM, and thiazide-type diuretics increased it. These results are consistent with previous reports [ 20 , 33 ] and should be considered by patients at high risk for abnormal glucose metabolism.

The present study does not discredit the proven benefits of statin treatment or the current guidelines recommending the active use of statins for patients at high risk for cardiovascular diseases, including diabetes. [ 18 , 34 , 35 ] However, our major results suggest that, for low-risk patients (i.e., those with simple dyslipidemia and/or subclinical atherosclerosis) or patients at high risk for developing diabetes, the balance of risks and benefits should be considered more carefully when determining statin treatment, including the type and dose. Particularly in East Asians, there might be a need to be more cautious regarding the intensity of statin use because relatively less-intensive treatments could bring sufficient lipid-lowering and even plaque regression in those populations compared to Western populations. [ 36 , 37 ]

Importantly, the actions that should be taken if diabetes occurs after using a statin remain unanswered. Additional investigations on whether reducing or stopping statin treatment or changing the type of statin being used would restore glucose metabolism and diabetes are needed.

The present study had several limitations. First, the intensity of statin was not considered. Despite a report on a higher risk for NODM after intensive statin treatment, [ 35 ] whether there is a definite correlation between dosage and risk for NODM, as suggested by a recent paper showing an increased risk for NODM even with a low dose of statins in Asian populations, [ 21 ] remains controversial. Previous studies have reported that the mere use of a statin is important for NODM development itself, regardless of the dosage. [ 8 , 19 , 21 ] Second, the comparative risk for NODM between various statins was analyzed as a secondary endpoint; therefore, it was underpowered, and further studies are needed. Third, BMI was not available for all of the patients and was not included in the main analysis, and BMI ≥ 25 was used in propensity matching and Cox regression analysis in the subgroup of patients. However, considering that the association between BMI and statin-induced diabetes remains controversial [ 7 , 21 ] and that BMI may exhibit ethnic differences (only 4.7% of the Korean population has a BMI > 30, the level at which it is considered a risk factor for DM [ 8 , 38 ] ), a different criteria regarding BMI might be appropriate to apply to East Asians, and these findings need to be prospectively verified in further studies.

5. Conclusion

We confirmed an increased risk for incident diabetes after statin treatment based on data from real-world clinical practice in Korea. Among various statins, atorvastatin might be more prone to increase the risk for DM than their matched nonexposed counterparts. We need more careful consideration regarding the balance between the risks and benefits when determining statin treatment.

Supplementary Material

Abbreviations: ACEi = angiotensin-converting enzyme inhibitor, ARB = angiotensin II receptor blocker, BMI = body mass index, CCI = Charlson comorbidity index, CI = confidence interval, DM = diabetes mellitus, EHR = electronic health record, HR = hazard ratio, ICD-10 = the International Classification of Diseases 10th Revision, NODM = new-onset diabetes mellitus.

DY and SSS have contributed equally to the article.

Funding/support: The research was supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI14C3201). We also received support from the Bio and Medical Technology Development Program of the National Research Foundation funded by the Ministry of Science, Information and Communications Technology, and Future Planning, Republic of Korea (no. 2013M3A9B5075838), and the Ajou University School of Medicine (M-2015-C0460-00109).

The authors have no conflicts of interest to disclose.

Supplemental Digital Content is available for this article.

The English in this document has been checked by at least 2 professional editors, both native speakers of English. For a certificate, please see: http://www.textcheck.com/certificate/QfVXGe .

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How can I plan what to eat or drink when I have diabetes?

How can physical activity help manage my diabetes, what can i do to reach or maintain a healthy weight, should i quit smoking, how can i take care of my mental health, clinical trials for healthy living with diabetes.

Healthy living is a way to manage diabetes . To have a healthy lifestyle, take steps now to plan healthy meals and snacks, do physical activities, get enough sleep, and quit smoking or using tobacco products.

Healthy living may help keep your body’s blood pressure , cholesterol , and blood glucose level, also called blood sugar level, in the range your primary health care professional recommends. Your primary health care professional may be a doctor, a physician assistant, or a nurse practitioner. Healthy living may also help prevent or delay health problems  from diabetes that can affect your heart, kidneys, eyes, brain, and other parts of your body.

Making lifestyle changes can be hard, but starting with small changes and building from there may benefit your health. You may want to get help from family, loved ones, friends, and other trusted people in your community. You can also get information from your health care professionals.

What you choose to eat, how much you eat, and when you eat are parts of a meal plan. Having healthy foods and drinks can help keep your blood glucose, blood pressure, and cholesterol levels in the ranges your health care professional recommends. If you have overweight or obesity, a healthy meal plan—along with regular physical activity, getting enough sleep, and other healthy behaviors—may help you reach and maintain a healthy weight. In some cases, health care professionals may also recommend diabetes medicines that may help you lose weight, or weight-loss surgery, also called metabolic and bariatric surgery.

Choose healthy foods and drinks

There is no right or wrong way to choose healthy foods and drinks that may help manage your diabetes. Healthy meal plans for people who have diabetes may include

• dairy or plant-based dairy products
• nonstarchy vegetables
• protein foods
• whole grains

Try to choose foods that include nutrients such as vitamins, calcium , fiber , and healthy fats . Also try to choose drinks with little or no added sugar , such as tap or bottled water, low-fat or non-fat milk, and unsweetened tea, coffee, or sparkling water.

Try to plan meals and snacks that have fewer

• foods high in saturated fat
• foods high in sodium, a mineral found in salt
• sugary foods , such as cookies and cakes, and sweet drinks, such as soda, juice, flavored coffee, and sports drinks

Your body turns carbohydrates , or carbs, from food into glucose, which can raise your blood glucose level. Some fruits, beans, and starchy vegetables—such as potatoes and corn—have more carbs than other foods. Keep carbs in mind when planning your meals.

You should also limit how much alcohol you drink. If you take insulin  or certain diabetes medicines , drinking alcohol can make your blood glucose level drop too low, which is called hypoglycemia . If you do drink alcohol, be sure to eat food when you drink and remember to check your blood glucose level after drinking. Talk with your health care team about your alcohol-drinking habits.

Find the best times to eat or drink

Talk with your health care professional or health care team about when you should eat or drink. The best time to have meals and snacks may depend on

• what medicines you take for diabetes
• what your level of physical activity or your work schedule is
• whether you have other health conditions or diseases

Ask your health care team if you should eat before, during, or after physical activity. Some diabetes medicines, such as sulfonylureas  or insulin, may make your blood glucose level drop too low during exercise or if you skip or delay a meal.

Plan how much to eat or drink

You may worry that having diabetes means giving up foods and drinks you enjoy. The good news is you can still have your favorite foods and drinks, but you might need to have them in smaller portions  or enjoy them less often.

For people who have diabetes, carb counting and the plate method are two common ways to plan how much to eat or drink. Talk with your health care professional or health care team to find a method that works for you.

Carb counting

Carbohydrate counting , or carb counting, means planning and keeping track of the amount of carbs you eat and drink in each meal or snack. Not all people with diabetes need to count carbs. However, if you take insulin, counting carbs can help you know how much insulin to take.

Plate method

The plate method helps you control portion sizes  without counting and measuring. This method divides a 9-inch plate into the following three sections to help you choose the types and amounts of foods to eat for each meal.

• Nonstarchy vegetables—such as leafy greens, peppers, carrots, or green beans—should make up half of your plate.
• Carb foods that are high in fiber—such as brown rice, whole grains, beans, or fruits—should make up one-quarter of your plate.
• Protein foods—such as lean meats, fish, dairy, or tofu or other soy products—should make up one quarter of your plate.

If you are not taking insulin, you may not need to count carbs when using the plate method.

Work with your health care team to create a meal plan that works for you. You may want to have a diabetes educator  or a registered dietitian  on your team. A registered dietitian can provide medical nutrition therapy , which includes counseling to help you create and follow a meal plan. Your health care team may be able to recommend other resources, such as a healthy lifestyle coach, to help you with making changes. Ask your health care team or your insurance company if your benefits include medical nutrition therapy or other diabetes care resources.

Talk with your health care professional before taking dietary supplements

There is no clear proof that specific foods, herbs, spices, or dietary supplements —such as vitamins or minerals—can help manage diabetes. Your health care professional may ask you to take vitamins or minerals if you can’t get enough from foods. Talk with your health care professional before you take any supplements, because some may cause side effects or affect how well your diabetes medicines work.

Research shows that regular physical activity helps people manage their diabetes and stay healthy. Benefits of physical activity may include

• lower blood glucose, blood pressure, and cholesterol levels
• better heart health
• healthier weight
• better mood and sleep
• better balance and memory

Talk with your health care professional before starting a new physical activity or changing how much physical activity you do. They may suggest types of activities based on your ability, schedule, meal plan, interests, and diabetes medicines. Your health care professional may also tell you the best times of day to be active or what to do if your blood glucose level goes out of the range recommended for you.

Do different types of physical activity

People with diabetes can be active, even if they take insulin or use technology such as insulin pumps .

Try to do different kinds of activities . While being more active may have more health benefits, any physical activity is better than none. Start slowly with activities you enjoy. You may be able to change your level of effort and try other activities over time. Having a friend or family member join you may help you stick to your routine.

The physical activities you do may need to be different if you are age 65 or older , are pregnant , or have a disability or health condition . Physical activities may also need to be different for children and teens . Ask your health care professional or health care team about activities that are safe for you.

Aerobic activities

Aerobic activities make you breathe harder and make your heart beat faster. You can try walking, dancing, wheelchair rolling, or swimming. Most adults should try to get at least 150 minutes of moderate-intensity physical activity each week. Aim to do 30 minutes a day on most days of the week. You don’t have to do all 30 minutes at one time. You can break up physical activity into small amounts during your day and still get the benefit. 1

Strength training or resistance training

Strength training or resistance training may make your muscles and bones stronger. You can try lifting weights or doing other exercises such as wall pushups or arm raises. Try to do this kind of training two times a week. 1

Balance and stretching activities

Balance and stretching activities may help you move better and have stronger muscles and bones. You may want to try standing on one leg or stretching your legs when sitting on the floor. Try to do these kinds of activities two or three times a week. 1

Some activities that need balance may be unsafe for people with nerve damage or vision problems caused by diabetes. Ask your health care professional or health care team about activities that are safe for you.

Stay safe during physical activity

Staying safe during physical activity is important. Here are some tips to keep in mind.

Drink liquids

Drinking liquids helps prevent dehydration , or the loss of too much water in your body. Drinking water is a way to stay hydrated. Sports drinks often have a lot of sugar and calories , and you don’t need them for most moderate physical activities.

Avoid low blood glucose

Check your blood glucose level before, during, and right after physical activity. Physical activity often lowers the level of glucose in your blood. Low blood glucose levels may last for hours or days after physical activity. You are most likely to have low blood glucose if you take insulin or some other diabetes medicines, such as sulfonylureas.

Ask your health care professional if you should take less insulin or eat carbs before, during, or after physical activity. Low blood glucose can be a serious medical emergency that must be treated right away. Take steps to protect yourself. You can learn how to treat low blood glucose , let other people know what to do if you need help, and use a medical alert bracelet.

Avoid high blood glucose and ketoacidosis

Taking less insulin before physical activity may help prevent low blood glucose, but it may also make you more likely to have high blood glucose. If your body does not have enough insulin, it can’t use glucose as a source of energy and will use fat instead. When your body uses fat for energy, your body makes chemicals called ketones .

High levels of ketones in your blood can lead to a condition called diabetic ketoacidosis (DKA) . DKA is a medical emergency that should be treated right away. DKA is most common in people with type 1 diabetes . Occasionally, DKA may affect people with type 2 diabetes  who have lost their ability to produce insulin. Ask your health care professional how much insulin you should take before physical activity, whether you need to test your urine for ketones, and what level of ketones is dangerous for you.

Take care of your feet

People with diabetes may have problems with their feet because high blood glucose levels can damage blood vessels and nerves. To help prevent foot problems, wear comfortable and supportive shoes and take care of your feet  before, during, and after physical activity.

If you have diabetes, managing your weight  may bring you several health benefits. Ask your health care professional or health care team if you are at a healthy weight  or if you should try to lose weight.

If you are an adult with overweight or obesity, work with your health care team to create a weight-loss plan. Losing 5% to 7% of your current weight may help you prevent or improve some health problems  and manage your blood glucose, cholesterol, and blood pressure levels. 2 If you are worried about your child’s weight  and they have diabetes, talk with their health care professional before your child starts a new weight-loss plan.

You may be able to reach and maintain a healthy weight by

• following a healthy meal plan
• consuming fewer calories
• being physically active
• getting 7 to 8 hours of sleep each night 3

If you have type 2 diabetes, your health care professional may recommend diabetes medicines that may help you lose weight.

Online tools such as the Body Weight Planner  may help you create eating and physical activity plans. You may want to talk with your health care professional about other options for managing your weight, including joining a weight-loss program  that can provide helpful information, support, and behavioral or lifestyle counseling. These options may have a cost, so make sure to check the details of the programs.

Your health care professional may recommend weight-loss surgery  if you aren’t able to reach a healthy weight with meal planning, physical activity, and taking diabetes medicines that help with weight loss.

If you are pregnant , trying to lose weight may not be healthy. However, you should ask your health care professional whether it makes sense to monitor or limit your weight gain during pregnancy.

Both diabetes and smoking —including using tobacco products and e-cigarettes—cause your blood vessels to narrow. Both diabetes and smoking increase your risk of having a heart attack or stroke , nerve damage , kidney disease , eye disease , or amputation . Secondhand smoke can also affect the health of your family or others who live with you.

If you smoke or use other tobacco products, stop. Ask for help . You don’t have to do it alone.

Feeling stressed, sad, or angry can be common for people with diabetes. Managing diabetes or learning to cope with new information about your health can be hard. People with chronic illnesses such as diabetes may develop anxiety or other mental health conditions .

Learn healthy ways to lower your stress , and ask for help from your health care team or a mental health professional. While it may be uncomfortable to talk about your feelings, finding a health care professional whom you trust and want to talk with may help you

• lower your feelings of stress, depression, or anxiety
• manage problems sleeping or remembering things
• see how diabetes affects your family, school, work, or financial situation

Ask your health care team for mental health resources for people with diabetes.

Sleeping too much or too little may raise your blood glucose levels. Your sleep habits may also affect your mental health and vice versa. People with diabetes and overweight or obesity can also have other health conditions that affect sleep, such as sleep apnea , which can raise your blood pressure and risk of heart disease.

NIDDK conducts and supports clinical trials in many diseases and conditions, including diabetes. The trials look to find new ways to prevent, detect, or treat disease and improve quality of life.

What are clinical trials for healthy living with diabetes?

Clinical trials—and other types of clinical studies —are part of medical research and involve people like you. When you volunteer to take part in a clinical study, you help health care professionals and researchers learn more about disease and improve health care for people in the future.

Researchers are studying many aspects of healthy living for people with diabetes, such as

• how changing when you eat may affect body weight and metabolism
• how less access to healthy foods may affect diabetes management, other health problems, and risk of dying
• whether low-carbohydrate meal plans can help lower blood glucose levels
• which diabetes medicines are more likely to help people lose weight

Find out if clinical trials are right for you .

Watch a video of NIDDK Director Dr. Griffin P. Rodgers explaining the importance of participating in clinical trials.

What clinical trials for healthy living with diabetes are looking for participants?

You can view a filtered list of clinical studies on healthy living with diabetes that are federally funded, open, and recruiting at www.ClinicalTrials.gov . You can expand or narrow the list to include clinical studies from industry, universities, and individuals; however, the National Institutes of Health does not review these studies and cannot ensure they are safe for you. Always talk with your primary health care professional before you participate in a clinical study.

This content is provided as a service of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), part of the National Institutes of Health. NIDDK translates and disseminates research findings to increase knowledge and understanding about health and disease among patients, health professionals, and the public. Content produced by NIDDK is carefully reviewed by NIDDK scientists and other experts.

NIDDK would like to thank: Elizabeth M. Venditti, Ph.D., University of Pittsburgh School of Medicine.

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Older adults with diabetes experienced functional decline during the COVID-19 pandemic, research finds

by University of Toronto

Researchers found that approximately one in five older Canadian adults with diabetes and no pre-pandemic functional limitations developed functional limitations for the first time during the COVID-19 pandemic. Functional limitations refer to difficulties with basic mobility-related tasks, such as walking two to three blocks, standing up from a chair, or climbing stairs. In comparison, only one in eight of their peers without diabetes developed functional limitations during the pandemic. The study was published in the Canadian Journal of Diabetes .

"Functional status is an important predictor of longevity and quality of life among older adults, and individuals with diabetes face a higher risk of functional decline than the general population," said first author Andie MacNeil, a research assistant at the Factor-Inwentash Faculty of Social Work (FIFSW) and the Institute for Life Course and Aging at the University of Toronto.

"Because the pandemic exacerbated many risk factors for functional decline, such as social isolation and physical inactivity, we wanted to examine changes in functional status among this population."

The study's sample came from the Canadian Longitudinal Study on Aging, a national longitudinal study of older Canadians. Respondents with diabetes were 53% more likely to develop at least one functional limitation during the pandemic compared to respondents without diabetes. Even after taking into account major risk factors for functional decline, such as such as physical activity, obesity, smoking, and other chronic health conditions, older adults with diabetes still faced a 28% higher risk of developing functional limitations .

"It is important for health professionals to encourage their older patients, particularly those with diabetes, to engage in behaviors that can help maintain their functional status, such as regular physical activity," said co-author Susanna Abraham Cottagiri, doctoral candidate at the School of Medicine at Queens University.

The study also found that socioeconomic factors were associated with functional limitations among older adults with and without diabetes. When compared to those with an annual household income of $100,000 or more, older adults with diabetes with an income of $20,000 or less had a five-fold higher risk of developing at least one functional limitation.

Even among those without diabetes, those with an income of $20,000 or less had double the risk of developing at least one functional limitation compared to those with an annual income of $100,000 or more.

"While socioeconomic status is an important predictor of functional decline among those both with and without diabetes, the magnitude of this relationship is much greater for respondents with diabetes," said co-author Ying Jiang, a senior epidemiologist at the Public Health Agency of Canada.

The authors also examined the probabilities of functional limitations across various patient characteristics such as sex, diabetes status, and household income, and then stratified into several risk factors, such as age, physical activity level, smoking status, multimorbidity, and weight. Across various patient profiles, socioeconomic status was a consistent driver of functional status.

Co-author Professor Paul Villeneuve at the Department of Neuroscience and the CHAIM Research Center, Carleton University, hypothesized the possible reason for this pattern: "People with low socioeconomic status face disproportionate stressors over their lifetime that may adversely impact their physical functioning in older age, such as working more physically demanding jobs, worse nutrition, and living in areas with less greenspace and walkability."

The researchers hope these findings can be used to inform interventions to promote better physical functioning among middle age and older adults.

"Combining lifestyle approaches that integrate physical activity with nutrition interventions have been shown to improve physical function in older adults with diabetes," said co-author Margaret de Groh, scientific manager at the Public Health Agency of Canada.

"Poverty remains a major barrier to nutrition and food security ," said senior author Professor Esme Fuller-Thomson at the University of Toronto's FIFSW and director of the Institute for Life Course & Aging. "It is important to think about broader strategies to decrease poverty and improve food access in Canada in order to promote better physical functioning among older adults ."

The study included 6,045 participants of the Canadian Longitudinal Study on Aging (CLSA) who were free from functional limitations in the 2015–2018 wave of data collection and who provided information on their functional status during the COVID-19 pandemic (September–December 2020).

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New study focuses on the placenta for clues to the development of gestational diabetes

A new study led by the Harvard Pilgrim Health Care Institute has identified that a deficit in the placental expression of the gene insulin-like growth factor 1 (IGFBP1) and low IGFBP1 circulating levels are associated with insulin resistance during pregnancy, highlighting a potential risk factor for the development of gestational diabetes.

The study, "Placental IGFBP1 levels during early pregnancy and the risk of insulin resistance and gestational diabetes," appears in the April 16, 2024 edition of Nature Medicine .

Gestational diabetes, a disease that can lead to multiple pregnancy and delivery complications, is the most common pregnancy metabolic complication, affecting 1 in 7 pregnancies. Existing research has shown that excess insulin resistance in pregnancy contributes to gestational diabetes, but the exact causes of this resistance remain unclear.

"The placenta -- the major driver of changes in insulin physiology in pregnancy -- is likely a key source of hormones involved in the development of gestational diabetes," says Marie-France Hivert, Harvard Medical School associate professor of population medicine at the Harvard Pilgrim Health Care Institute and lead author of the study. "Our goal was to discover novel placental factors that are implicated in gestational diabetes, by studying all proteins expressed in placenta tissues, across the human genome. We identified placental insulin-like growth factor 1 (IGFBP1) as a secreted placental factor that is likely implicated in regulation of glucose in human pregnancy."

The study builds on Dr. Hivert's extensive research into the determinants of gestational diabetes using genetics and other omics approaches, and their interaction with lifestyle and environmental factors. The study team conducted genome-wide RNA sequencing on maternal-facing placental tissue samples, and measured identified proteins in blood collected in multiple pregnancy cohorts with diverse backgrounds.

The team identified 14 genes whose placental RNA expression levels were associated with insulin resistance, finding the strongest association with gene IGFBP1. By measuring the IGFBP1 protein levels in circulation, they found that IGFBP1 levels rise over the course of pregnancy and are 5 times higher in pregnant people compared to outside of pregnancy, arguing for the placenta being one of the major sources of this protein during pregnancy. Results also show that low levels of circulating IGFBP1 in early pregnancy could predict who is likely to develop gestational diabetes in late second trimester of pregnancy. Finally, the team found that the trajectory of IGFBP1 levels across pregnancy differs in people who have a subtype of gestational diabetes characterized by insulin resistance previously shown more likely to develop pregnancy complications.

"Identifying a novel protein that characterizes a subtype of gestational diabetes is one additional step towards developing precision medicine for gestational diabetes," adds Dr. Hivert. "It's possible that measuring IGFBP1 in the first trimester could help identify people at risk of developing gestational diabetes early in pregnancy, potentially offering a window for prevention. We hope to conduct future research to address whether this protein plays a causal role in gestational glycemic regulation."

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Materials provided by Harvard Pilgrim Health Care Institute . Note: Content may be edited for style and length.

Journal Reference :

• Marie-France Hivert, Frédérique White, Catherine Allard, Kaitlyn James, Sana Majid, François Aguet, Kristin G. Ardlie, Jose C. Florez, Andrea G. Edlow, Luigi Bouchard, Pierre-Étienne Jacques, S. Ananth Karumanchi, Camille E. Powe. Placental IGFBP1 levels during early pregnancy and the risk of insulin resistance and gestational diabetes . Nature Medicine , 2024; DOI: 10.1038/s41591-024-02936-5

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The unexpected health benefits of Ozempic and Mounjaro

Research is showing that these new weight-loss drugs can help treat conditions from addiction to kidney disease—and may even be contributing to a boom of “Ozempic babies.”

Casey Arnold, who lives in a suburb of Houston, spent years trying to quit smoking. She’d tried nicotine patches. That failed. She tried quitting cold turkey but that made her short tempered. On other occasions the idea of quitting made her so anxious, she smoked more to ease her fears.

By the time she permanently gave up cigarettes in the winter of 2023, at age 55, she’d been smoking for four decades and was up to two packs a day. But this time it was a new type of weight loss drug that helped her quit.

GLP-1, short for glucagon-like peptide 1, is a natural hormone that stimulates the production and release of insulin, slows digestion, curbs appetite, and blunts the brain’s focus on food. GLP-1 agonist drugs, like exanetide, tirzepatide and semaglutide, mimic this hormone. They were originally developed as diabetes treatments, but as more people began taking them, researchers observed these medications are effective for many more conditions than just diabetes and weight loss.

The FDA recently approved semaglutide, the active ingredient of Wegovy, for the treatment of obesity and for reducing the risk of heart attack and stroke in patients with obesity and heart disease . But as the number of people taking these drugs grows, physicians and researchers are learning about unanticipated health benefits for conditions where treatments have been limited, such as addiction, heart failure, and kidney disease.

( Ozempic is a serious drug with serious risks. Here’s what to know. )

Arnold quit smoking while participating in a clinical trial examining the potential of GLP-1 agonists as a treatment for smoking addiction.

“It was totally opposite of when I tried to quit in my previous years,” Arnold says. “I was shocked at how calm I was, compared to how I used to think about quitting.” Instead of anxiety and rage, she felt at peace, and her cravings faded.

“It’s just been an avalanche across the different patient populations,” says Mark Petrie , a cardiologist at the University of Glasgow, whose research focuses on the use of GLP-1 agonists in patients with heart failure. “It’s just good news all around.”

Heart failure with preserved ejection fraction

More than six million Americans are living with heart failure , a condition where the heart progressively loses the ability to pump enough blood to the rest of the body. Of these patients, approximately half have a type known as heart failure with preserved ejection fraction , in which the heart can pump normally but is too stiff to fill up with blood.

In a study published last year , researchers tested semaglutide as a treatment for heart failure with preserved ejection fraction in patients who were not diabetic. The result: patients who received the drug showed fewer symptoms and reported a better quality of life, compared to those who received the placebo. Patients who received the drug had lower levels of C-reactive protein, which is a marker for inflammation.

“This is a big finding,” says James de Lemos, a cardiologist at UT Southwestern Medical Center, in Dallas, Texas, who was not associated with the study. The study was too small to determine if semaglutide can reduce the risk of hospitalization or death but given the stark improvement in patient quality of life, it’s promising.

Although some of these benefits are likely due to weight loss, that’s just part of what makes this treatment effective.

These medications are also cardioprotective and reduce inflammation, which is known to be a driver of heart failure, says Amanda Vest , a cardiologist at the Cleveland Clinic, who specializes in treating patients with heart failure. “We must continue to think more expansively than just about the number on the scale,” Vest says.

For patients with the other major type of heart failure—heart failure with reduced ejection fraction—there is less evidence, so far, that these drugs are effective. More trials are in the works to determine which types of patients will benefit from the use of these medications.

Kidney disease

An estimated 850 million people worldwide are living with chronic kidney disease ,   but there are few effective treatments. Historically, the main strategy has been to stall kidney failure for as long as possible and then move the patient to dialysis or wait for a kidney transplant. But nine out of 10 patients die of complications before reaching that point.

For patients with severe chronic kidney disease, “you are looking at a mortality rate that’s 10 to 20 percent a year,” says Katherine Tuttle , a nephrologist at the University of Washington Medicine. “This is on par with the worst malignancies.”

As a couple of recent studies have shown , the GLP-1 agonist dulaglutide helps patients who suffer from chronic kidney disease and diabetes. In a recent trial looking at the effect of semaglutide on patients with chronic kidney disease and type 2 diabetes, the treatment was so effective at delaying the progression of chronic kidney disease that the clinical trial was stopped early so that all the trial patients could benefit from the drug.

“It’s the only semaglutide trial that was stopped early for efficacy,” says Tuttle, who is on the executive committee for the trial. “To stop a trial early for efficacy, the bar is set really high,” which includes strong enough evidence for its efficacy that it would be no longer considered ethical to continue giving patients the placebo.

( New obesity drugs are coming. Here's how they could change everything. )

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As Tuttle notes, the effects on the kidneys is only partially due to reductions in risk factors such as blood pressure, blood sugar, and weight. Other benefits are likely to result from reduced inflammation.

“They have a profound anti-inflammatory effect,” Tuttle says. “Our field is really under recognizing the importance of inflammation, particularly in kidney damage caused by diabetes.”

Results from the trial will be published later this year.

Effects on fertility

For a growing number of patients on GLP-1 agonists, such as Ozempic or Mounjaro, one surprising side effect has been unexpected pregnancy, which for some patients, has come after years of struggling with infertility. Although more research is needed to explore the link between GLP-1 agonists and pregnancy, it’s become enough of a phenomenon that ‘Ozempic babies’ has become a trending phrase. Meanwhile, experts think there are several factors responsible.

The first factor is the fact that GLP-1 agonists cause a delayed gastric emptying, which can cause oral contraception pills to be absorbed by the body at a slower rate. “These drugs are altering that particular part of the drug absorption phase,” says Archana Sadhu , an endocrinologist at Houston Methodist Hospital, adding that this effect can be particularly prominent during dosage increases. This means that oral birth control may not be as effective.

The second factor is the link between polycystic ovarian syndrome (PCOS)—the leading cause of infertility in women—and insulin resistance.

“Insulin resistance will dysregulate the ovarian cycle,” Sadhu says. Insulin resistance can lead to infertility by disrupting hormones such as estrogen and testosterone, which are related to fertility; and it can affect the release of eggs from the ovaries. When patients start taking GLP-1 agonists, this reduces their insulin resistance, which boosts fertility.

However, the effects of these drugs on pregnancy are still unknown, which means that it’s important for patients to talk with their doctors about any plans for becoming pregnant, as well as strategies for contraception, which may include adding in a second method to augment oral contraceptive pills, or switching to a different method.

Treating addiction

Since Ozempic and Mounjaro have been become more common, patients have been reporting several unexpected side effects, such as a diminished desire to smoke or drink. Although more research is needed, it’s thought that the part of the brain that is responsible for food cravings overlaps with the part of the brain that is responsible for cravings for substances of abuse, says Luba Yammine, an addiction researcher at UTHealth Houston.

For doctors working in the field, earlier versions of these GLP-1 drugs showed tremendous potential as anti-addiction medications.

“We have far fewer medications available” for treating addiction and many patients report difficulties accessing these, says Christian Hendershot, an addiction researcher at the University of North Carolina School of Medicine. The field also receives less research funding compared with other diseases.

For Yammine, she first became interested in studying the effect of GLP-1 agonists on addiction while working in primary care, where she had several patients who were smokers with diabetes. Yammine would counsel her patients on quitting smoking, prescribing nicotine patches or the medication buproprion, to help them quit. But most of the time these strategies failed.

“It’s hard to quit smoking, period,” Yammine says. “The vast majority of smokers want to quit, but even with the use of these therapies, many of them are not successful.”

To help these smokers with their diabetes she would prescribe GLP-1 agonist medications, only to discover when they returned for a follow-up that they had quit smoking. When she asked them what happened, their answer was that suddenly their cravings vanished. “That was a very interesting finding,” Yammine says.

This happened often enough that Yammine decided to explore the impact of these GLP-1 receptor agonists on addiction through a clinical trial.

Yammine and her collaborators led a pilot study , in which 46 percent of the participants who received exanetide, plus nicotine patches and smoking cessation counseling, were able to quit, compared to 26 percent of participants who received nicotine patches, counseling, and a placebo. Yammine and her collaborators are now following up with a larger trial. They are also planning a separate trial with semaglutide.

For the patients in the study who received exanetide, their post-cessation weight was 5.6 pounds lower than those who received the placebo, a side effect that can help offset the weight gain that is often associated with quitting smoking.  

“This weight gain is very problematic,” Yammine says, adding that many patients are either afraid to quit or relapse due to concerns about weight gain, while it can also put them at heightened risk for developing weight-related conditions, such as type 2 diabetes.

For Arnold, who was enrolled in a follow up trial that Yammine is conducting, the months in which she was participating in the trial was characterized both by a calmness surrounding her efforts to quit, as well as minimal weight gain. Since the trial has ended, she’s been able to maintain her efforts to quit smoking, although she gained a little weight. “I don’t have cravings,” Arnold says. “It’s this weight gain that is bothering me.”

Arnold, who works for an HVAC company, would really like to go back on exanetide, but as is the case with so many other patients who have experienced benefits from GLP-1 receptor agonists, she’s finding that it’s too expensive to do so. Just one month’s supply costs about $1,000, and without FDA approval for its use as an anti-addiction drug, most health insurance companies won’t pay for it.

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