Genetically Driven Hyperglycemia Increases Risk of Coronary Artery Disease Separately From Type 2 Diabetes

Mendelian randomization studies on coronary artery disease: a systematic review and meta-analysis

BACKGROUND

Coronary artery disease (CAD) remains one of the leading causes of mortality worldwide. We aimed to summarize what is currently known with regard to causal modifiable risk factors associated with CAD in populations of diverse ancestries through conducting a systematic review and meta-analysis of Mendelian randomization (MR) studies on CAD.

METHODS

The databases Embase, Medline, Cochrane Library and Web of Science were searched on the 19th and 20th of December 2022 for MR studies with CAD as a primary outcome; keywords of the search strategy included "coronary artery disease" and "mendelian randomization". Studies were included if they were published in the English language, included only human participants, employed Mendelian randomization as the primary methodology and studied CAD as the outcome of interest. The exclusion criteria resulted in the removal of studies that did not align with the predefined inclusion criteria, as well as studies which were systematic reviews themselves, and used the same exposure and outcome source as another study. An ancestry-specific meta-analysis was subsequently conducted on studies which investigated either body mass index, lipid traits, blood pressure or type 2 diabetes as an exposure variable. Assessment of publication bias and sensitivity analyses was conducted for risk of bias assessment in the included studies.

RESULTS

A total of 1781 studies were identified through the database searches after de-duplication was performed, with 47 studies included in the quantitative synthesis after eligibility screening. Approximately 80% of all included study participants for MR studies on CAD were of European descent irrespective of the exposure of interest, while no study included individuals of African ancestry. We found no evidence of differences in terms of direction of causation between ancestry groups; however, the strength of the respective relationships between each exposure and CAD were different, with this finding most evident when blood pressure was the exposure of interest.

CONCLUSIONS

Findings from this review suggest that patterns regarding the causational relationship between modifiable risk factors and CAD do not differ in terms of direction when compared across diverse ancestry populations. Differences in the observed strengths of the respective relationships however are indicative of the value of increasing representation in non-European populations, as novel genetic pathways or functional SNPs relating to CAD may be uncovered through a more global analysis.

SYSTEMATIC REVIEW REGISTRATION

The protocol for this systematic review was registered to the International Prospective Register of Systematic Reviews (PROSPERO) and is publicly available online (CRD42021272726).

Incretins and cardiovascular disease: to the heart of type 2 diabetes?

Major cardiovascular outcome trials and real-life observations have proven that glucagon-like peptide-1 (GLP-1) receptor agonists (GLP-1RAs), regardless of structural GLP-1 homology, exert clinically relevant cardiovascular protection. GLP-1RAs provide cardioprotective benefits through glycaemic and non-glycaemic effects, including improved insulin secretion and action, body-weight loss, blood-pressure lowering and improved lipid profile, as well as via direct effects on the heart and vasculature. These actions are likely combined with anti-inflammatory and antioxidant properties that translate into robust and consistent reductions in atherothrombotic events, particularly in people with type 2 diabetes and established atherosclerotic CVD. GLP-1RAs may also have an impact on obesity and chronic kidney disease, conditions for which cardiovascular risk-reducing options are limited. The available evidence has prompted professional and medical societies to recommend GLP-1RAs for mitigation of the cardiovascular risk in people with type 2 diabetes. This review summarises the clinical evidence for cardiovascular protection with use of GLP-1RAs and the main mechanisms underlying this effect. Moreover, it looks into how the availability of upcoming dual and triple incretin receptor agonists might expand the possibility for cardiovascular protection in people with type 2 diabetes.

Decoding the genetic relationship between Alzheimer's disease and type 2 diabetes: potential risk variants and future direction for North Africa

Introduction

Alzheimer's disease (AD) and Type 2 diabetes (T2D) are both age-associated diseases. Identification of shared genes could help develop early diagnosis and preventive strategies. Although genetic background plays a crucial role in these diseases, we noticed an underrepresentation tendency of North African populations in omics studies.

Materials and methods

First, we conducted a comprehensive review of genes and pathways shared between T2D and AD through PubMed. Then, the function of the identified genes and variants was investigated using annotation tools including PolyPhen2, RegulomeDB, and miRdSNP. Pathways enrichment analyses were performed with g:Profiler and EnrichmentMap. Next, we analyzed variant distributions in 16 worldwide populations using PLINK2, R, and STRUCTURE software. Finally, we performed an inter-ethnic comparison based on the minor allele frequency of T2D-AD common variants.

Results

A total of 59 eligible papers were included in our study. We found 231 variants and 363 genes shared between T2D and AD. Variant annotation revealed six single nucleotide polymorphisms (SNP) with a high pathogenic score, three SNPs with regulatory effects on the brain, and six SNPs with potential effects on miRNA-binding sites. The miRNAs affected were implicated in T2D, insulin signaling pathways, and AD. Moreover, replicated genes were significantly enriched in pathways related to plasma protein binding, positive regulation of amyloid fibril deposition, microglia activation, and cholesterol metabolism. Multidimensional screening performed based on the 363 shared genes showed that main North African populations are clustered together and are divergent from other worldwide populations. Interestingly, our results showed that 49 SNP associated with T2D and AD were present in North African populations. Among them, 11 variants located in DNM3, CFH, PPARG, ROHA, AGER, CLU, BDNF1, CST9, and PLCG1 genes display significant differences in risk allele frequencies between North African and other populations.

Conclusion

Our study highlighted the complexity and the unique molecular architecture of North African populations regarding T2D-AD shared genes. In conclusion, we emphasize the importance of T2D-AD shared genes and ethnicity-specific investigation studies for a better understanding of the link behind these diseases and to develop accurate diagnoses using personalized genetic biomarkers.

The role of metabolic syndrome in sudden cardiac death risk: Recent evidence and future directions

Metabolic syndrome (MetS) is a frequent condition whose deleterious effects on the cardiovascular system are often underestimated. MetS is nowadays considered a real pandemic with an estimated prevalence of 25% in general population. Individuals with MetS are at high risk of sudden cardiac death (SCD) as this condition accounts for 50% of all cardiac deaths in such a population. Of interest, recent studies demonstrated that individuals with MetS show 70% increased risk of SCD even without previous history of coronary heart disease (CHD). However, little is known about the interplay between the two conditions. MetS is a complex disease determined by genetic predisposition, unhealthy lifestyle and ageing with deleterious effects on different organs. MetS components trigger a systemic chronic low-grade pro-inflammatory state, associated with excess of sympathetic activity, cardiac hypertrophy, arrhythmias and atherosclerosis. Thus, MetS has an important burden on the cardiovascular system as demonstrated by both preclinical and clinical evidence. The aim of this review is to summarize recent evidence concerning the association between MetS and SCD, showing possible common aetiological processes, and to indicate prospective for future studies and therapeutic targets.

Robust estimates of heritable coronary disease risk in individuals with type 2 diabetes

Type 2 diabetes (T2D) is an important heritable risk factor for coronary artery disease (CAD), the risk of both diseases being increased by metabolic syndrome (MS). With the availability of large-scale genome-wide association data, we aimed to elucidate the genetic burden of CAD risk in T2D predisposed individuals within the context of MS and their shared genetic architecture. Mendelian randomization (MR) analyses supported a causal relationship between T2D and CAD [odds ratio (OR) = 1.13 per log-odds unit 95% confidence interval (CI): 1.10-1.16; p = 1.59 × 10-17 ]. Simultaneously adjusting MR analyses for the effects of the T2D instrument including blood pressure, dyslipidaemia, and obesity attenuated the association between T2D and CAD (OR = 1.07, 95% CI: 1.04-1.11). Bayesian locus-overlap analysis identified 44 regions with the same causal variant underlying T2D and CAD genetic signals (FDR < 1%) at a posterior probability >0.7; five (MHC, LPL, ABO, RAI1 and MC4R) of these regions contain genome-wide significant (p < 5 × 10-8 ) associations for both traits. Given the small effect sizes observed in genome-wide association studies for complex diseases, even with 44 potential target regions, this has implications for the likely magnitude of CAD risk reduction that might be achievable by pure T2D therapies.

Random plasma glucose levels and cause-specific mortality among Chinese adults without known diabetes: an 11-year prospective study of 450,000 people

INTRODUCTION

We examined the associations between long-term usual random plasma glucose (RPG) levels and cause-specific mortality risks among adults without known diabetes in China.

RESEARCH DESIGN AND METHODS

The China Kadoorie Biobank recruited 512,891 adults (59% women) aged 30-79 from 10 regions of China during 2004-2008. At baseline survey, and subsequent resurveys of a random subset of survivors, participants were interviewed and measurements collected, including on-site RPG testing. Cause of death was ascertained via linkage to local mortality registries. Cox regression yielded adjusted HR for all-cause and cause-specific mortality associated with usual levels of RPG.

RESULTS

During median 11 years' follow-up, 37,214 deaths occurred among 452,993 participants without prior diagnosed diabetes or other chronic diseases. There were positive log-linear relationships between RPG and all-cause, cardiovascular disease (CVD) (n=14,209) and chronic kidney disease (CKD) (n=432) mortality down to usual RPG levels of at least 5.1 mmol/L. At RPG <11.1 mmol/L, each 1.0 mmol/L higher usual RPG was associated with adjusted HRs of 1.14 (95% CI 1.12 to 1.16), 1.16 (1.12 to 1.19) and 1.44 (1.22 to 1.70) for all-cause, CVD and CKD mortality, respectively. Usual RPG was positively associated with chronic liver disease (n=547; 1.45 (1.26 to 1.66)) and cancer (n=12,680; 1.12 (1.09 to 1.16)) mortality, but with comparably lower risks at baseline RPG ≥11.1 mmol/L. These associations persisted after excluding participants who developed diabetes during follow-up.

CONCLUSIONS

Among Chinese adults without diabetes, higher RPG levels were associated with higher mortality risks from several major diseases, with no evidence of apparent thresholds below the cut-points for diabetes diagnosis.

Current trends in epidemiology of cardiovascular disease and cardiovascular risk management in type 2 diabetes

With the advances in diabetes care, the trend of incident cardiovascular disease (CVD) in patients with type 2 diabetes mellitus (T2DM) has been decreasing over past decades. However, given that CVD is still a major cause of death in patients with diabetes and that the risk of CVD in patients with T2DM is more than twice that in those without DM, there are still considerable challenges to the prevention of CVD in diabetes. Accordingly, there have been several research efforts to decrease cardiovascular (CV) risk in T2DM. Large-scale genome-wide association studies (GWAS) and clinical cohort studies have investigated the effects of factors, such as genetic determinants, hypoglycaemia, and insulin resistance, on CVD and can account for the unexplained CV risk in T2DM. Lifestyle modification is a widely accepted cornerstone method to prevent CVD as the first-line strategy in T2DM. Recent reports from large CV outcome trials have proven the positive CV effects of sodium-glucose cotransporter-2 (SGLT-2) inhibitors and glucagon-like peptide-1 receptor agonists (GLP-1RAs) in patients with high CVD risk. Overall, current practice guidelines for the management of CVD in T2DM are moving from a glucocentric strategy to a more individualised patient-centred approach. This review will discuss the current epidemiologic trends of CVD in T2DM and the risk factors linking T2DM to CVD, including genetic contribution, hypoglycaemia, and insulin resistance, and proper care strategies, including lifestyle and therapeutic approaches.

Multiethnic Genome-Wide Association Study of Subclinical Atherosclerosis in Individuals With Type 2 Diabetes

BACKGROUND

Coronary artery calcification (CAC) and carotid artery intima-media thickness (cIMT) are measures of subclinical atherosclerosis in asymptomatic individuals and strong risk factors for cardiovascular disease. Type 2 diabetes (T2D) is an independent cardiovascular disease risk factor that accelerates atherosclerosis.

METHODS

We performed meta-analyses of genome-wide association studies in up to 2500 T2D individuals of European ancestry (EA) and 1590 T2D individuals of African ancestry with or without exclusion of prevalent cardiovascular disease, for CAC measured by cardiac computed tomography, and 3608 individuals of EA and 838 individuals of African ancestry with T2D for cIMT measured by ultrasonography within the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium.

RESULTS

We replicated 2 loci (rs9369640 and rs9349379 near PHACTR1 and rs10757278 near CDKN2B) for CAC and one locus for cIMT (rs7412 and rs445925 near APOE-APOC1) that were previously reported in the general EA populations. We identified one novel CAC locus (rs8000449 near CSNK1A1L/LINC00547/POSTN at 13q13.3) at P=2.0×10-8 in EA. No additional loci were identified with the meta-analyses of EA and African ancestry. The expression quantitative trait loci analysis with nearby expressed genes derived from arterial wall and metabolic tissues from the Genotype-Tissue Expression project pinpoints POSTN, encoding a matricellular protein involved in bone formation and bone matrix organization, as the potential candidate gene at this locus. In addition, we found significant associations (P<3.1×10-4) for 3 previously reported coronary artery disease loci for these subclinical atherosclerotic phenotypes (rs2891168 near CDKN2B-AS1 and rs11170820 near FLJ12825 for CAC, and rs7412 near APOE for cIMT).

CONCLUSIONS

Our results provide potential biological mechanisms that could link CAC and cIMT to increased cardiovascular disease risk in individuals with T2D.

Acute and Chronic Effects of Low-Volume High-Intensity Interval Training Compared to Moderate-Intensity Continuous Training on Glycemic Control and Body Composition in Older Women with Type 2 Diabetes

Objective: To compare the acute and chronic effects of low-volume high-intensity interval training (HIIT) to moderate-intensity continuous training (MICT) on glycemic control, body composition and continuous glucose monitoring (CGM) in older women with type 2 diabetes (T2D). Methods: Thirty older women (68 ± 5 years) with T2D were randomized in two groups—HIIT (75 min/week) or MICT (150 min/week). Glucose homeostasis (A1c, glucose, insulin, HOMA-IR2) and body composition (iDXA) were measured before and after the 12-week exercise intervention. During the first and last week of training (24-h before and 48-h after exercise), the following CGM-derived data were measured: 24-h and peak glucose levels, glucose variability and time spent in hypoglycemia as well as severe and mild hyperglycemia. Results: While lean body mass increased (p = 0.035), total and trunk fat mass decreased (p ≤ 0.007), without any difference between groups (p ≥ 0.81). Fasting glucose levels (p = 0.001) and A1c (p = 0.014) significantly improved in MICT only, with a significant difference between groups for fasting glucose (p = 0.02). Neither HIIT nor MICT impacted CGM-derived data at week 1 (p ≥ 0.25). However, 24-h and peak glucose levels, as well as time spent in mild hyperglycemia, decreased in HIIT at week 12 (p ≤ 0.03). Conclusion: These results suggest that 12 weeks of low-volume HIIT is enough to provide similar benefit to MICT for body composition and improve the acute effect of exercise when measured with CGM.

Genetically determined elevated C-reactive protein associated with primary colorectal cancer risk: Mendelian randomization with lifestyle interactions

Systemic inflammation-related etiologic pathways via inflammatory cytokines in the development of colorectal cancer (CRC) have not been convincingly determined and may be confounded by lifestyle factors or reverse causality. We investigated the genetically predicted C-reactive protein (CRP) phenotype in the potential causal pathway of primary CRC risk in postmenopausal women in a Mendelian randomization (MR) framework. We employed individual-level data of the Women's Health Initiative Database for Genotypes and Phenotypes Study, which consists of 5 genome-wide association (GWA) studies, including 10,142 women, 737 of whom developed primary CRC. We examined 61 GWA single-nucleotide polymorphisms (SNPs) associated with CRP by using weighted/penalized MR weighted-medians and MR gene-environment interactions that allow some relaxation of the strict variable requirements and attenuate the heterogeneous estimates of outlying SNPs. In lifestyle-stratification analyses, genetically determined CRP exhibited its effects on the decreased CRC risk in non-viscerally obese and high-fat diet subgroups. In contrast, genetically driven CRP was associated with an increased risk for CRC in women who smoked ≥ 15 cigarettes/day, with significant interaction of the gene-smoking relationship. Further, a substantially increased risk of CRC induced by CRP was observed in relatively short-term users (< 5 years) of estrogen (E)-only and also longer-term users (5 to > 10 years) of E plus progestin. Our findings may provide novel evidence on immune-related etiologic pathways connected to CRC risk and suggest the possible use of CRP as a CRC-predictive biomarker in women with particular behaviors and CRP marker-informed interventions to reduce CRC risk.

The Relationship Between Type 2 Diabetes, NAFLD, and Cardiovascular Risk

PURPOSE OF REVIEW

Nonalcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (T2DM) are strongly associated. Both also associate with an increased risk of cardiovascular disease (CVD).

RECENT FINDINGS

Several studies have provided evidence that NAFLD could be an independent CVD risk factor. Given the strong association between NAFLD and T2DM, assessing the independent CV effect of these two conditions remains challenging. However, patients with T2DM and NAFLD exhibit higher risk of CVD compared with T2DM without NAFLD suggesting a potential synergistic increase of CV risk in patients with both T2DM and NAFLD supported by several shared pathophysiological pathways. Several anti-diabetic therapies have shown beneficial effect on both NAFLD and CVD. Patients with T2DM and NAFLD should be considered at high risk of CVD and could benefit from more intensive CV prevention. Additional long-term follow-up is needed to demonstrate that the treatment of NAFLD effectively reduces the risk of CVD.

Clinical and metabolomic predictors of regression to normoglycemia in a population at intermediate cardiometabolic risk

Background

Impaired fasting glucose (IFG) is a prevalent and potentially reversible intermediate stage leading to type 2 diabetes that increases risk for cardiometabolic complications. The identification of clinical and molecular factors associated with the reversal, or regression, from IFG to a normoglycemia state would enable more efficient cardiovascular risk reduction strategies. The aim of this study was to identify clinical and biological predictors of regression to normoglycemia in a non-European population characterized by high rates of type 2 diabetes.

Methods

We conducted a prospective, population-based study among 9637 Mexican individuals using clinical features and plasma metabolites. Among them, 491 subjects were classified as IFG, defined as fasting glucose between 100 and 125 mg/dL at baseline. Regression to normoglycemia was defined by fasting glucose less than 100 mg/dL in the follow-up visit. Plasma metabolites were profiled by Nuclear Magnetic Resonance. Multivariable cox regression models were used to examine the associations of clinical and metabolomic factors with regression to normoglycemia. We assessed the predictive capability of models that included clinical factors alone and models that included clinical factors and prioritized metabolites.

Results

During a median follow-up period of 2.5 years, 22.6% of participants (n = 111) regressed to normoglycemia, and 29.5% progressed to type 2 diabetes (n = 145). The multivariate adjusted relative risk of regression to normoglycemia was 1.10 (95% confidence interval [CI] 1.25 to 1.32) per 10 years of age increase, 0.94 (95% CI 0.91–0.98) per 1 SD increase in BMI, and 0.91 (95% CI 0.88–0.95) per 1 SD increase in fasting glucose. A model including information from age, fasting glucose, and BMI showed a good prediction of regression to normoglycemia (AUC = 0.73 (95% CI 0.66–0.78). The improvement after adding information from prioritized metabolites (TG in large HDL, albumin, and citrate) was non-significant (AUC = 0.74 (95% CI 0.68–0.80), p value = 0.485).

Conclusion

In individuals with IFG, information from three clinical variables easily obtained in the clinical setting showed a good prediction of regression to normoglycemia beyond metabolomic features. Our findings can serve to inform and design future cardiovascular prevention strategies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01246-1.

Genetically Predicted C-Reactive Protein Associated With Postmenopausal Breast Cancer Risk: Interrelation With Estrogen and Cancer Molecular Subtypes Using Mendelian Randomization

Background

Immune-related etiologic pathways that influence breast cancer risk are incompletely understood and may be confounded by lifestyles or reverse causality. Using a Mendelian randomization (MR) approach, we investigated the potential causal relationship between genetically elevated C-reactive protein (CRP) concentrations and primary invasive breast cancer risk in postmenopausal women.

Methods

We used individual-level data obtained from 10,179 women, including 537 who developed breast cancer, from the Women’s Health Initiative Database for Genotypes and Phenotypes Study, which consists of five genome-wide association (GWA) studies. We examined 61 GWA single-nucleotide polymorphisms (SNPs) previously associated with CRP. We employed weighted/penalized weighted–medians and MR gene–environment interactions that allow instruments’ invalidity to some extent and attenuate the heterogeneous estimates of outlying SNPs.

Results

In lifestyle-stratification analyses, genetically elevated CRP decreased risk for breast cancer in exogenous estrogen-only, estrogen + progestin, and past oral contraceptive (OC) users, but only among relatively short-term users (<5 years). Estrogen-only users for ≥5 years had more profound CRP-decreased breast cancer risk in dose–response fashion, whereas past OC users for ≥5 years had CRP-increased cancer risk. Also, genetically predicted CRP was strongly associated with increased risk for hormone-receptor positive or human epidermal growth factor receptor-2 negative breast cancer.

Conclusions

Our findings may provide novel evidence on the immune-related molecular pathways linking to breast cancer risk and suggest potential clinical use of CRP to predict the specific cancer subtypes. Our findings suggest potential interventions targeting CRP–inflammatory markers to reduce breast cancer risk.

The Role of Genetically Determined Glycemic Traits in Breast Cancer: A Mendelian Randomization Study

Background

Circulating glycemic traits (GTs) have been considered a risk factor for breast cancer, but studies using GT-associated genetic variants as an instrumental variable are limited and inconclusive.

Methods

Our Mendelian Randomization analysis used the most recent genome-wide datasets focusing on European women.

Results

Of 44 single-nucleotide polymorphisms (SNPs) with GTs, 38 fasting-glucose and 6 fasting-insulin SNPs showed heterogeneous associations with breast cancer, without significant directional pleiotropy observed.

Conclusion

Our findings indicate a null association between genetically determined GTs and breast cancer risk among European women. Our findings may contribute to more complete characterizing of metabolic pathways in GTs and breast cancer.

An investigation of causal relationships between prediabetes and vascular complications

Prediabetes is a state of glycaemic dysregulation below the diagnostic threshold of type 2 diabetes (T2D). Globally, ~352 million people have prediabetes, of which 35-50% develop full-blown diabetes within five years. T2D and its complications are costly to treat, causing considerable morbidity and early mortality. Whether prediabetes is causally related to diabetes complications is unclear. Here we report a causal inference analysis investigating the effects of prediabetes in coronary artery disease, stroke and chronic kidney disease, complemented by a systematic review of relevant observational studies. Although the observational studies suggest that prediabetes is broadly associated with diabetes complications, the causal inference analysis revealed that prediabetes is only causally related with coronary artery disease, with no evidence of causal effects on other diabetes complications. In conclusion, prediabetes likely causes coronary artery disease and its prevention is likely to be most effective if initiated prior to the onset of diabetes.

Mendelian Randomization Study: The Association Between Metabolic Pathways and Colorectal Cancer Risk

Background: The roles of obesity-related biomarkers and their molecular pathways in the development of postmenopausal colorectal cancer (CRC) have been inconclusive. We examined insulin resistance (IR) as a major hormonal pathway mediating the association between obesity and CRC risk in a Mendelian randomization (MR) framework.

Methods: We performed MR analysis using individual-level data of 11,078 non-Hispanic white postmenopausal women from our earlier genome-wide association study. We identified four independent single-nucleotide polymorphisms associated with fasting glucose (FG), three with fasting insulin (FI), and six with homeostatic model assessment–IR (HOMA-IR), which were not associated with obesity. We estimated hazard ratios (HRs) for CRC by adjusting for potential confounding factors plus genetic principal components.

Results: Overall, we observed no direct association between combined 13 IR genetic instruments and CRC risk (HR = 0.96, 95% confidence interval [CI]: 0.78–1.17). In phenotypic analysis, genetically raised HOMA-IR exhibited its effects on the increased risk and FG and FI on the reduced risk for CRC, but with a lack of statistical power. Subgroup analyses by physical activity level and dietary fat intake with combined phenotypes showed that genetically determined IR was associated with reduced CRC risk in both physical activity-stratified (single contributor: MTRR rs722025; HR = 0.12, 95% CI: 0.02–0.62) and high-fat diet subgroups (main contributor: G6PC2 rs560887; HR = 0.59, 95% CI: 0.37–0.94).

Conclusions: Complex evidence was observed for a potential causal association between IR and CRC risk. Our findings may provide an additional value of intervention trials to lower IR and reduce CRC risk.

Genetics Insights in the Relationship Between Type 2 Diabetes and Coronary Heart Disease

Diabetes mellitus is a major risk factor for coronary heart disease (CHD). The major form of diabetes mellitus is type 2 diabetes mellitus (T2D), which is thus largely responsible for the CHD association in the general population. Recent years have seen major advances in the genetics of T2D, principally through ever-increasing large-scale genome-wide association studies. This article addresses the question of whether this expanding knowledge of the genomics of T2D provides insight into the etiologic relationship between T2D and CHD. We will investigate this relationship by reviewing the evidence for shared genetic loci between T2D and CHD; by examining the formal testing of this interaction (Mendelian randomization studies assessing whether T2D is causal for CHD); and then turn to the implications of this genetic relationship for therapies for CHD, for therapies for T2D, and for therapies that affect both. In conclusion, the growing knowledge of the genetic relationship between T2D and CHD is beginning to provide the promise for improved prevention and treatment of both disorders.

Genetics of diabetes mellitus and diabetes complications

Diabetes is one of the fastest growing diseases worldwide, projected to affect 693 million adults by 2045. Devastating macrovascular complications (cardiovascular disease) and microvascular complications (such as diabetic kidney disease, diabetic retinopathy and neuropathy) lead to increased mortality, blindness, kidney failure and an overall decreased quality of life in individuals with diabetes. Clinical risk factors and glycaemic control alone cannot predict the development of vascular complications; numerous genetic studies have demonstrated a clear genetic component to both diabetes and its complications. Early research aimed at identifying genetic determinants of diabetes complications relied on familial linkage analysis suited to strong-effect loci, candidate gene studies prone to false positives, and underpowered genome-wide association studies limited by sample size. The explosion of new genomic datasets, both in terms of biobanks and aggregation of worldwide cohorts, has more than doubled the number of genetic discoveries for both diabetes and diabetes complications. We focus herein on genetic discoveries for diabetes and diabetes complications, empowered primarily through genome-wide association studies, and emphasize the gaps in research for taking genomic discovery to the next level.

Non-alcoholic fatty liver disease and cardiovascular disease: assessing the evidence for causality

Non-alcoholic fatty liver disease (NAFLD) is highly prevalent among individuals with type 2 diabetes. Although epidemiological studies have shown that NAFLD is associated with cardiovascular disease (CVD), it remains unknown whether NAFLD is an active contributor or an innocent bystander. Plasma lipids, low-grade inflammation, impaired fibrinolysis and hepatokines are potential mediators of the relationship between NAFLD and CVD. The Mendelian randomisation approach can help to make causal inferences. Studies that used common variants in PNPLA3, TM6SF2 and GCKR as instruments to investigate the relationship between NAFLD and coronary artery disease (CAD) have reported contrasting results. Variants in PNPLA3 and TM6SF2 were found to protect against CAD, whereas variants in GCKR were positively associated with CAD. Since all three genes have been associated with non-alcoholic steatohepatitis, the second stage of NAFLD, the question of whether low-grade inflammation is an important mediator of the relationship between NAFLD and CAD arises. In contrast, the differential effects of these genes on plasma lipids (i.e. lipid-lowering for PNPLA3 and TM6SF2, and lipid-raising for GCKR) strongly suggest that plasma lipids account for their differential effects on CAD risk. This concept has recently been confirmed in an extended set of 12 NAFLD susceptibility genes. From these studies it appears that plasma lipids are an important mediator between NAFLD and CVD risk. These findings have important clinical implications, particularly for the design of anti-NAFLD drugs that also affect lipid metabolism.

Diabetes and Cardiovascular Disease: an Update

PURPOSE OF REVIEW

Cardiovascular disease (CVD) is the leading cause of mortality in people with diabetes. Our aim was to review the pathophysiology of CVD in diabetes, review related landmark trials, and discuss the cardiovascular benefit of glucose-lowering agents. We have also discussed the role of controversial anti-platelet therapy.

RECENT FINDINGS

Recent studies have shown the impact of glucose-lowering agents on CVD in people with diabetes. Statins are now recommended for all patients with diabetes over the age of 40 regardless of the LDL level given the cardiovascular benefit of these drugs. Current recommendations suggest a blood pressure < 130/80 for individuals with high cardiovascular risk. Cardiovascular risk reduction should be an important part of the management of diabetes. Focusing solely on glycemic control may not be the best therapeutic strategy. Multifactorial risk reduction should be taken into account. Lipid-lowering agents and anti-hypertensives should be a corner stone of treatment of diabetes. With currently available data, glucose-lowering agents with cardiovascular benefit should be started early in the disease process.

Translating GWAS findings into therapies for depression and anxiety disorders: gene-set analyses reveal enrichment of psychiatric drug classes and implications for drug repositioning

BACKGROUND

Depression and anxiety disorders (AD) are the first and sixth leading causes of disability worldwide. Despite their high prevalence and significant disability resulted, there are limited advances in new drug development. Recently, genome-wide association studies (GWAS) have greatly advanced our understanding of the genetic basis underlying psychiatric disorders.

METHODS

Here we employed gene-set analyses of GWAS summary statistics for drug repositioning. We explored five related GWAS datasets, including two on major depressive disorder (MDD2018 and MDD-CONVERGE, with the latter focusing on severe melancholic depression), one on AD, and two on depressive symptoms and neuroticism in the population. We extracted gene-sets associated with each drug from DSigDB and examined their association with each GWAS phenotype. We also performed repositioning analyses on meta-analyzed GWAS data, integrating evidence from all related phenotypes.

RESULTS

Importantly, we showed that the repositioning hits are generally enriched for known psychiatric medications or those considered in clinical trials. Enrichment was seen for antidepressants and anxiolytics but also for antipsychotics. We also revealed new candidates or drug classes for repositioning, some of which were supported by experimental or clinical studies. For example, the top repositioning hit using meta-analyzed p values was fendiline, which was shown to produce antidepressant-like effects in mouse models by inhibition of acid sphingomyelinase.

CONCLUSION

Taken together, our findings suggest that human genomic data such as GWAS are useful in guiding drug discoveries for depression and AD.

Management of Diabetes in Patients Undergoing Bariatric Surgery

PURPOSE OF REVIEW

The number of bariatric surgeries for patients with type 1 or type 2 diabetes continues to grow. Clinicians are challenged to choose therapies that reach glycemic targets without inducing adverse effects in post-bariatric patients without published guidelines. This review evaluates data supporting the best strategies for diabetes management in patients undergoing bariatric surgery.

RECENT FINDINGS

Though few clinical trials have evaluated the safety and effectiveness of different glucose-lowering therapies following bariatric surgery, remission of diabetes or reduced medications is an established benefit of bariatric surgery. Adverse events including diabetic ketoacidosis in post-bariatric patients on sodium-glucose co-transporter 2 (SGLT2) inhibitors or inadequate insulin have been reported in patient's with both type 1 and type 2 diabetes. Metformin, glucagon-like peptide-1 (GLP-1) agonists, dipeptidyl peptidase-4 (DPP-4) inhibitors, SGLT2 inhibitors, insulin, and sulfonylureas have been used successfully in the perioperative period for other surgeries and guidelines recommend adjusting the doses of these medications especially in the perioperative period. Clinicians should favor weight-neutral or weight-loss promoting therapies in post-bariatric surgery patients such as medical nutrition therapy, metformin, GLP-1 agonists, SGLT2 inhibitors, and DPP-4 inhibitors.

The Genetic Epidemiology of Type 2 Diabetes: Opportunities for Health Translation

PURPOSE OF REVIEW

Genome-wide association studies have delineated the genetic architecture of type 2 diabetes. While functional studies to identify target transcripts are ongoing, new genetic knowledge can be translated directly to health applications. The review covers several translation directions but focuses on genomic polygenic scores for screening and prevention.

RECENT FINDINGS

Over 400 genomic variants associated with T2D and its related quantitative traits are now known. Genetic scores comprising dozens to millions of associated variants can predict incident T2D. However, measurement of body mass index is more efficient than genetic scores to detect T2D risk groups, and knowledge of T2D genetic risk alone seems insufficient to improve health. Genetically determined metabolic sub-phenotypes can be identified by clustering variants associated with physiological axes like insulin resistance. Genetic sub-phenotyping may be a way forward to identify specific individual phenotypes for prevention and treatment. Genomic polygenic scores for T2D can predict incident diabetes but may not be useful to improve health overall. Genetic detection of T2D sub-phenotypes could be useful to personalize screening and care.

Post genome-wide gene-environment interaction study: The effect of genetically driven insulin resistance on breast cancer risk using Mendelian randomization

PURPOSE

The role of insulin resistance (IR) in developing postmenopausal breast cancer has not been thoroughly resolved and may be confounded by lifestyle factors such as obesity. We examined whether genetically determined IR is causally associated with breast cancer risk.

METHODS

We conducted Mendelian randomization (MR) analyses using individual-level data from our previous meta-analysis of a genome-wide association study (GWAS) (n = 11,109 non-Hispanic white postmenopausal women). Four single-nucleotide polymorphisms were associated with fasting glucose (FG), 2 with fasting insulin (FI), and 6 with homeostatic model assessment-IR (HOMA-IR) but were not associated with obesity. We used this GWAS to employ hazard ratios (HRs) for breast cancer risk by adjusting for potential confounding factors.

RESULTS

No direct association was observed between comprising 12 IR genetic instruments and breast cancer risk (HR = 0.93, 95% CI: 0.76-1.14). In phenotype-specific analysis, genetically elevated FG was associated with reduced risk for breast cancer (main contributor of this MR-effect estimate: G6PC2 rs13431652; HR = 0.59, 95% CI: 0.35-0.99). Genetically driven FI and HOMA-IR were not significantly associated. Stratification analyses by body mass index, exercise, and dietary fat intake with combined phenotypes showed that genetically elevated IR was associated with greater breast cancer risk in overall obesity and inactive subgroups (single contributor: MTRR/LOC729506 rs13188458; HR = 2.21, 95% CI: 1.03-4.75).

CONCLUSIONS

We found complex evidence for causal association between IR and risk of breast cancer, which may support the potential value of intervention trials to lower IR and reduce breast cancer risk.

Leveraging Genetics to Improve Cardiovascular Health in Diabetes: The 2018 Edwin Bierman Award Lecture

The past decade has witnessed an exponential increase in our ability to search the genome for genetic factors predisposing to cardiovascular disease (CVD) and in particular coronary heart disease (CHD). Identifying these genes could lead to the development of innovative strategies to prevent the cardiovascular complications of diabetes by allowing us to 1) create predictive algorithms for the identification of patients at especially high risk of CVD so that these individuals can undergo preventive interventions early in the natural history of the disease; 2) discover as yet unknown disease pathways linking diabetes to atherosclerosis, which can be used as targets for the development of new CVD-preventing drugs specifically directed at subjects with diabetes; and 3) devise personalized programs increasing the cost-effectiveness of preventive interventions by tailoring them to the genetic background of each patient. Substantial progress has been made in each of these three areas as exemplified by the recent development of a CHD genetic risk score improving CHD prediction among subjects with type 2 diabetes, the discovery of a diabetes-specific CHD locus on 1q25 pointing to glutamine synthase (GLUL) and the γ-glutamyl cycle as key regulators of CHD risk in diabetes, and the identification of two genetic loci allowing the selection of patients with type 2 diabetes who may especially benefit from intensive glycemic control. Translating these discoveries into clinical practice will not be without challenges, but the potential rewards, from the perspective of public health as well as that of persons with diabetes, make this goal worth pursuing.

Genetic Determinants of Glycemic Traits and the Risk of Gestational Diabetes Mellitus

Many common genetic polymorphisms are associated with glycemic traits and type 2 diabetes (T2D), but knowledge about genetic determinants of glycemic traits in pregnancy is limited. We tested genetic variants known to be associated with glycemic traits and T2D in the general population for associations with glycemic traits in pregnancy and gestational diabetes mellitus (GDM). Participants in two cohorts (Genetics of Glucose regulation in Gestation and Growth [Gen3G] and Hyperglycemia and Adverse Pregnancy Outcome [HAPO]) underwent oral glucose tolerance testing at 24-32 weeks' gestation. We built genetic risk scores (GRSs) for elevated fasting glucose and insulin, reduced insulin secretion and sensitivity, and T2D, using variants discovered in studies of nonpregnant individuals. We tested for associations between these GRSs, glycemic traits in pregnancy, and GDM. In both cohorts, the fasting glucose GRS was strongly associated with fasting glucose. The insulin secretion and sensitivity GRSs were also significantly associated with these traits in Gen3G, where insulin measurements were available. The fasting insulin GRS was weakly associated with fasting insulin (Gen3G) or C-peptide (HAPO). In HAPO (207 GDM case subjects), all five GRSs (T2D, fasting glucose, fasting insulin, insulin secretion, and insulin sensitivity) were significantly associated with GDM. In Gen3G (43 GDM case subjects), both the T2D and insulin secretion GRSs were associated with GDM; effect sizes for the other GRSs were similar to those in HAPO. Thus, despite the profound changes in glycemic physiology during pregnancy, genetic determinants of fasting glucose, fasting insulin, insulin secretion, and insulin sensitivity discovered outside of pregnancy influence GDM risk.

The Impact of Glycated Hemoglobin (HbA1c) on Cardiovascular Disease Risk: A Mendelian Randomization Study Using UK Biobank

OBJECTIVE

Glycated hemoglobin (HbA_1c) is positively associated with cardiovascular disease (CVD), although evidence is primarily observational. Mendelian randomization studies have only examined its relation with subtypes of CVD. We examined the relation of HbA_1c with CVD and its subtypes in the UK Biobank using Mendelian randomization.

RESEARCH DESIGN AND METHODS

We used 38 genetic variants strongly and independently related to HbA_1c (n = 123,665) applied to the UK Biobank (n = 392,038). We used inverse variance weighting (IVW) to obtain the associations of HbA_1c with CVD, coronary artery disease (CAD), and stroke (overall and stroke subtypes). Sensitivity analyses included Mendelian randomization (MR)-Egger, a weighted median, and exclusion of potentially invalid single nucleotide polymorphisms (SNPs). We also applied the same genetic instruments to CARDIoGRAMplusC4D (Coronary ARtery DIsease Genome wide Replication and Meta-analysis [CARDIoGRAM] plus The Coronary Artery Disease [C4D] Genetics) 1000 Genomes-based genome-wide association study (n = 184,305) as a validation for CAD.

RESULTS

In the UK Biobank, HbA_1c was not associated with CVD using IVW (odds ratio [OR] 1.11 per %, 95% CI 0.83-1.48). However, HbA_1c was associated with increased CAD risk (OR 1.50 per %, 95% CI 1.08-2.11) with directionally consistent results from MR-Egger and weighted median. The positive association with CAD was more pronounced when we excluded potentially invalid SNPs (OR 2.24 per %, 95% CI 1.55-3.25). The positive association was replicated in CARDIoGRAM (OR 1.52 per %, 95% CI 1.03-2.26). The association of HbA_1c with stroke and its subtypes was less clear given the low number of cases.

CONCLUSIONS

HbA_1c likely causes CAD. The underlying mechanisms remain to be elucidated.

Shared Genetic Contribution of Type 2 Diabetes and Cardiovascular Disease: Implications for Prognosis and Treatment

PURPOSE OF REVIEW

The increased cardiovascular disease (CVD) risk in subjects with type 2 diabetes (T2D) is well established. This review collates the available evidence and assesses the shared genetic background between T2D and CVD: the causal contribution of common risk factors to T2D and CVD and how genetics can be used to improve drug development and clinical outcomes.

RECENT FINDINGS

Large-scale genome-wide association studies (GWAS) of T2D and CVD support a shared genetic background but minimal individual locus overlap. Mendelian randomisation (MR) analyses show that T2D is causal for CVD, but GWAS of CVD, T2D and their common risk factors provided limited evidence for individual locus overlap. Distinct but functionally related pathways were enriched for CVD and T2D genetic associations reflecting the lack of locus overlap and providing some explanation for the variable associations of common risk factors with CVD and T2D from MR analyses.

Mendelian randomisation in type 2 diabetes and coronary artery disease

Type 2 diabetes, coronary artery disease and hypertension are associated with anthropometric and biomarker traits, including waist-to-hip-ratio, body mass index and altered glucose and insulin levels. Clinical trials, for example of weight-loss interventions, show these factors are causal, but lifelong impact of subtle changes in body mass index and body fat distribution are less clear. The use of human genetics can quantify the causal effects of long-term exposure to subtle changes of modifiable risk factors. Mendelian randomisation (MR) uses human genetic variants associated with the risk factor to quantify the relationship between risk factor and disease outcome. The last two years have seen an increase in the number of MR studies investigating the relationship between anthropometric traits and metabolic diseases. This review provides an overview of these recent MR studies in relation to type 2 diabetes, coronary artery disease and hypertension. MR provides evidence for causal associations of waist-to-hip-ratio, body mass index and altered glucose levels with type 2 diabetes, coronary artery disease and hypertension.

A Decade of Genetic and Metabolomic Contributions to Type 2 Diabetes Risk Prediction

PURPOSE OF REVIEW

The purpose of this review was to summarize and reflect on advances over the past decade in human genetic and metabolomic discovery with particular focus on their contributions to type 2 diabetes (T2D) risk prediction.

RECENT FINDINGS

In the past 10 years, a combination of advances in genotyping efficiency, metabolomic profiling, bioinformatics approaches, and international collaboration have moved T2D genetics and metabolomics from a state of frustration to an abundance of new knowledge. Efforts to control and prevent T2D have failed to stop this global epidemic. New approaches are needed, and although neither genetic nor metabolomic profiling yet have a clear clinical role, the rapid pace of accumulating knowledge offers the possibility for "multi-omic" prediction to improve health.

Mining the Genome for Therapeutic Targets

Current pharmacological options for type 2 diabetes do not cure the disease. Despite the availability of multiple drug classes that modulate glycemia effectively and minimize long-term complications, these agents do not reverse pathogenesis, and in practice they are not selected to correct the molecular profile specific to the patient. Pharmaceutical companies find drug development programs increasingly costly and burdensome, and many promising compounds fail before launch to market. Human genetics can help advance the therapeutic enterprise. Genomic discovery that is agnostic to preexisting knowledge has uncovered dozens of loci that influence glycemic dysregulation. Physiological investigation has begun to define disease subtypes, clarifying heterogeneity and suggesting molecular pathways for intervention. Convincing genetic associations have paved the way for the identification of effector transcripts that underlie the phenotype, and genetic or experimental proof of gain or loss of function in select cases has clarified the direction of effect to guide therapeutic development. Genetic studies can also examine off-target effects and furnish causal inference. As this information is curated and made widely available to all stakeholders, it is hoped that it will enhance therapeutic development pipelines by accelerating efficiency, maximizing cost-effectiveness, and raising ultimate success rates.

Mendelian randomization in cardiometabolic disease: challenges in evaluating causality

Mendelian randomization (MR) is a burgeoning field that involves the use of genetic variants to assess causal relationships between exposures and outcomes. MR studies can be straightforward; for example, genetic variants within or near the encoding locus that is associated with protein concentrations can help to assess their causal role in disease. However, a more complex relationship between the genetic variants and an exposure can make findings from MR more difficult to interpret. In this Review, we describe some of these challenges in interpreting MR analyses, including those from studies using genetic variants to assess causality of multiple traits (such as branched-chain amino acids and risk of diabetes mellitus); studies describing pleiotropic variants (for example, C-reactive protein and its contribution to coronary heart disease); and those investigating variants that disrupt normal function of an exposure (for example, HDL cholesterol or IL-6 and coronary heart disease). Furthermore, MR studies on variants that encode enzymes responsible for the metabolism of an exposure (such as alcohol) are discussed, in addition to those assessing the effects of variants on time-dependent exposures (extracellular superoxide dismutase), cumulative exposures (LDL cholesterol), and overlapping exposures (triglycerides and non-HDL cholesterol). We elaborate on the molecular features of each relationship, and provide explanations for the likely causal associations. In doing so, we hope to contribute towards more reliable evaluations of MR findings.