A genomic approach to therapeutic target validation identifies a glucose-lowering GLP1R variant protective for coronary heart disease

Exploring the shared genetic landscape of diabetes and cardiovascular disease: findings and future implications

Diabetes is a rapidly growing global health concern projected to affect one in eight adults by 2045, which translates to roughly 783 million people. The profound metabolic alterations often present in dysglycaemia significantly increase the risk of cardiovascular complications. While genetic susceptibility plays a crucial role in diabetes and its vascular complications, identifying genes and molecular mechanisms that influence both diseases simultaneously has proven challenging. A key reason for this challenge is the pathophysiological heterogeneity underlying these diseases, with multiple processes contributing to different forms of diabetes and specific cardiovascular complications. This molecular heterogeneity has limited the effectiveness of large-scale genome-wide association studies (GWAS) in identifying shared underlying mechanisms. Additionally, our limited knowledge of the causal genes, cell types and disease-relevant states through which GWAS signals operate has hindered the discovery of common molecular pathways. This review highlights recent advances in genetic epidemiology, including studies of causal associations that have uncovered genetic and molecular factors influencing both dysglycaemia and cardiovascular complications. We explore how disease subtyping approaches can be critical in pinpointing the unique molecular signatures underlying both diabetes and cardiovascular complications. Finally, we address critical research gaps and future opportunities to advance our understanding of both diseases and translate these discoveries into tangible benefits for patient care and population health.

In vivo functional profiling and structural characterisation of the human Glp1r A316T variant

Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are effective therapies for type 2 diabetes (T2D) and obesity, yet patient responses are variable. Variation in the human Glp1r gene might be directly linked to therapeutic responses. A naturally occurring missense variant, A316T, protects against T2D and cardiovascular disease. Here, we have generated and characterised a human Glp1r A316T mouse model. Human Glp1r A316T/A316T mice displayed lower fasting blood glucose versus wildtype littermates, even under metabolic stress, and exhibited alterations in islet cytoarchitecture and α/β identity under a high-fat, high-sucrose diet. This was however associated with blunted responses to GLP-1RAs in vivo. Further investigations in rodent and human β-cell models demonstrated that human Glp1r A316T exhibits characteristics of constitutive activation but dampened GLP-1RA responses. Results are further supported by cryo-EM analyses and molecular dynamics simulations of GLP-1R A316T structure, collectively demonstrating that the A316T variant governs basal GLP-1R activity and pharmacological responses to GLP-1R-targeting therapies.

Adequate sleep duration accentuates the effect of glucagon-like peptide-1 receptor variant on HbA1c: A gene-environment interaction study

BACKGROUND

Both glucagon-like peptide-1 receptor (GLP1R) agonists and lifestyle modifications are widely adopted in managing glycemia. However, the joint effects of GLP1R agonists with lifestyle on glycemic traits have not been evaluated.

METHODS

This gene-environment study tested the interaction between GLP1R-rs10305492 variant, consistent with the effect of GLP1R agonist therapies, and four lifestyle factors (diet, physical activity, sleep duration, and chronotype) for glucose and glycated hemoglobin (HbA1c) levels among 263,846 UK Biobank participants. Linear regression models were conducted to evaluate the effects of the rs10305492 and lifestyle factors on glucose and HbA1c levels.

RESULTS

GLP1R-rs10305492-AA/AG genotype combined a healthy diet, regular physical activity, adequate sleep duration, or morning chronotype were associated with lower glucose and HbA1c levels (all P for trend < 0.001). A synergistic effect was found between rs10305492 and sleep duration on HbA1c, suggesting a recommended adequate sleep duration (7-8 h/day) may amplify the HbA1c lowering effect of GLP1R agonists. Joint effects of the rs10305492 and adequate sleep were associated with a 26 % reduced risk of hyperglycemia (>7.8 mmol/L) risk and a 22 % lower of high HbA1c (>39 mmol/mol or 5.7 %).

CONCLUSIONS

Combining GLP1R agonists with adequate sleep may provide additional benefits for glycemic control in clinical practice.

GLP-1 receptor agonist-based therapies and cardiovascular risk: a review of mechanisms

Cardiovascular outcome trials (CVOTs) in people living with type 2 diabetes mellitus and obesity have confirmed the cardiovascular benefits of glucagon-like peptide 1 receptor agonists (GLP-1RAs), including reduced cardiovascular mortality, lower rates of myocardial infarction, and lower rates of stroke. The cardiovascular benefits observed following GLP-1RA treatment could be secondary to improvements in glycemia, blood pressure, postprandial lipidemia, and inflammation. Yet, the GLP-1R is also expressed in the heart and vasculature, suggesting that GLP-1R agonism may impact the cardiovascular system. The emergence of GLP-1RAs combined with glucose-dependent insulinotropic polypeptide and glucagon receptor agonists has shown promising results as new weight loss medications. Dual-agonist and tri-agonist therapies have demonstrated superior outcomes in weight loss, lowered blood sugar and lipid levels, restoration of tissue function, and enhancement of overall substrate metabolism compared to using GLP-1R agonists alone. However, the precise mechanisms underlying their cardiovascular benefits remain to be fully elucidated. This review aims to summarize the findings from CVOTs of GLP-1RAs, explore the latest data on dual and tri-agonist therapies, and delve into potential mechanisms contributing to their cardioprotective effects. It also addresses current gaps in understanding and areas for further research.

Association of Novel Antihyperglycemic Drugs Versus Metformin With a Decrease in Asthma Exacerbations

BACKGROUND

Similar to metformin, dipeptidyl peptidase-4 inhibitors (DPP-4 Is), glucagon-like peptidase 1 receptor agonists (GLP-1 RAs), and sodium glucose co-transporter-2 inhibitors (SGLT-2 Is) may improve control of asthma owing to their multiple potential mechanisms, including differential improvements in glycemic control, direct anti-inflammatory effects, and systemic changes in metabolism.

OBJECTIVE

To investigate whether these novel antihyperglycemic drugs were associated with fewer asthma exacerbations compared with metformin in patients with asthma comorbid with type 2 diabetes.

METHODS

Using a Japanese national administrative database, we constructed 3 active comparators-new user cohorts of 137,173 patients with a history of asthma starting the novel antihyperglycemic drugs and metformin between 2014 and 2022. Patient characteristics were balanced using overlap propensity score weighting. The primary outcome was the first exacerbation requiring systemic corticosteroids, and the secondary outcomes included the number of exacerbations requiring systemic corticosteroids.

RESULTS

DPP-4 Is and GLP-1 RAs were associated with a higher incidence of exacerbations requiring systemic corticosteroids compared with metformin (DPP-4 Is: 18.2 vs 17.4 per 100 person-years, hazard ratio: 1.09, 95% confidence interval [CI]: 1.05-1.14; GLP-1 RAs: 24.9 vs 19.0 per 100 person-years, hazard ratio: 1.14, 95% CI: 1.01-1.28). In contrast, the incidence of exacerbations requiring systemic corticosteroids was similar between the SGLT-2 Is and metformin groups (17.3 vs 18.1 per 100 person-years, hazard ratio: 1.00, 95% CI: 0.97-1.03). While DPP-4 Is and GLP-1 RAs were associated with more exacerbations requiring systemic corticosteroids, SGLT-2 Is were associated with slightly fewer exacerbations requiring systemic corticosteroids (53.7 vs 56.6 per 100 person-years, rate ratio: 0.95, 95% CI: 0.91-0.99).

CONCLUSIONS

While DPP-4 Is and GLP-1 RAs were associated with poorer control of asthma compared with metformin, SGLT-2 Is offered asthma control comparable to that of metformin.

Diabetes mellitus-Progress and opportunities in the evolving epidemic

Diabetes, a complex multisystem metabolic disorder characterized by hyperglycemia, leads to complications that reduce quality of life and increase mortality. Diabetes pathophysiology includes dysfunction of beta cells, adipose tissue, skeletal muscle, and liver. Type 1 diabetes (T1D) results from immune-mediated beta cell destruction. The more prevalent type 2 diabetes (T2D) is a heterogeneous disorder characterized by varying degrees of beta cell dysfunction in concert with insulin resistance. The strong association between obesity and T2D involves pathways regulated by the central nervous system governing food intake and energy expenditure, integrating inputs from peripheral organs and the environment. The risk of developing diabetes or its complications represents interactions between genetic susceptibility and environmental factors, including the availability of nutritious food and other social determinants of health. This perspective reviews recent advances in understanding the pathophysiology and treatment of diabetes and its complications, which could alter the course of this prevalent disorder.

Exome sequencing identifies novel genetic variants associated with varicose veins

BACKGROUND

Varicose veins (VV) are one of the common human diseases, but the role of genetics in its development is not fully understood.

METHODS

We conducted an exome-wide association study of VV using whole-exome sequencing data from the UK Biobank, and focused on common and rare variants using single-variant association analysis and gene-level collapsing analysis.

FINDINGS

A total of 13,823,269 autosomal genetic variants were obtained after quality control. We identified 36 VV-related independent common variants mapping to 34 genes by single-variant analysis and three rare variant genes (PIEZO1, ECE1, FBLN7) by collapsing analysis, and most associations between genes and VV were replicated in FinnGen. PIEZO1 was the closest gene associated with VV (P = 5.05 × 10-31), and it was found to reach exome-wide significance in both single-variant and collapsing analyses. Two novel rare variant genes (ECE1 and METTL21A) associated with VV were identified, of which METTL21A was associated only with females. The pleiotropic effects of VV-related genes suggested that body size, inflammation, and pulmonary function are strongly associated with the development of VV.

CONCLUSIONS

Our findings highlight the importance of causal genes for VV and provide new directions for treatment.

Association of RASGRP1 polymorphism with vascular complications in Chinese diabetic patients with glycemic control and antihypertensive treatment

BACKGROUND

Studies have shown that RASGRP1 was potently associated with the onset of type 2 diabetes mellitus (T2DM), and RASGRP1 rs7403531 was significantly correlated with islet function in T2DM patients. However, the effect of RASGRP1 polymorphism on blood glucose and blood pressure in T2DM patients after continuous treatment has yet to be fully elucidated.

OBJECTIVE

This study aimed to explore the association between RASGRP1 genetic polymorphism and cardiovascular complications in T2DM patients, so as to provide more evidence for the individualized treatment of T2DM patients.

METHODS

We retrospectively analyzed a large-scale multicenter drug clinical study cohort that based on a 2 × 2 factorial (glucose control axis and blood pressure lowering axis) randomized controlled design, with follow-up for 5 years. The major vascular endpoint events included cardiovascular death, non-fatal stroke, coronary heart disease, new-onset or worsening renal disease, and diabetic retinopathy. RASGRP1 rs12593201, rs56254815 and rs7403531 were finally selected as candidate single nucleotide polymorphisms. Mixed linear model and Cox hazard ratio (HR) model were used for data analysis with IBM SPSS (version 20.0 for windows; Chicago, IL).

RESULTS

Our study enrolled 1357 patients with high-risk diabetes, with a mean follow-up duration of 4.8 years. RASGRP1 rs7403531 was associated with vascular events in hypoglycemic and antihypertensive therapy. Specifically, compared with CC carriers, patients with CT/TT genotype had fewer major microvascular events (HR = 0.41, 95% confidence interval (CI) 0.21-0.80, P = 0.009), and reduced the risk of major eye disease events (HR = 0.44, 95% CI 0.20-0.94, P = 0.03). For glucose lowering axis, CT/TT carriers had a lower risk of secondary nephropathy (HR = 0.48, 95% CI 0.25-0.92, P = 0.03) in patients with standard glycemic control. For blood pressure lowering axis, all cerebrovascular events (HR = 2.24, 95% CI 1.11-4.51, P = 0.025) and stroke events (HR = 2.07, 95% CI 1.03-4.15, P = 0.04) were increased in patients with CC genotype compared to those with CT/TT genotype in the placebo group, respectively. Furthermore, patients with CC genotype showed a reduced risk of major cerebrovascular events in antihypertensive group (HR = 0.36, 95% CI 0.15-0.86, P = 0.021). For RASGRP1 rs56254815, compared with the AA genotype carriers, the systolic blood pressure of AG/GG carriers in the antihypertensive group decreased by 1.5mmhg on average (P = 0.04). In the placebo group, the blood pressure of AG/GG carriers was 1.7mmHg higher than that of AA carriers (P = 0.02).

CONCLUSION

We found that patients with G allele of RASGRP1 (rs56254815) showed a better antihypertensive therapy efficacy in T2DM patients. The rs7403531 T allele could reduce the risk of major microvascular events and major eye diseases in T2DM patients receiving either hypoglycemic or antihypertensive therapy. Our findings suggest that RASGRP1 genetic polymorphism might predict the cardiovascular complications in T2DM patients.

The landscape of the methodology in drug repurposing using human genomic data: a systematic review

The process of drug development is expensive and time-consuming. In contrast, drug repurposing can be introduced to clinical practice more quickly and at a reduced cost. Over the last decade, there has been a significant expansion of large biobanks that link genomic data to electronic health record data, public availability of various databases containing biological and clinical information and rapid development of novel methodologies and algorithms in integrating different sources of data. This review aims to provide a thorough summary of different strategies that utilize genomic data to seek drug-repositioning opportunities. We searched MEDLINE and EMBASE databases to identify eligible studies up until 1 May 2023, with a total of 102 studies finally included after two-step parallel screening. We summarized commonly used strategies for drug repurposing, including Mendelian randomization, multi-omic-based and network-based studies and illustrated each strategy with examples, as well as the data sources implemented. By leveraging existing knowledge and infrastructure to expedite the drug discovery process and reduce costs, drug repurposing potentially identifies new therapeutic uses for approved drugs in a more efficient and targeted manner. However, technical challenges when integrating different types of data and biased or incomplete understanding of drug interactions are important hindrances that cannot be disregarded in the pursuit of identifying novel therapeutic applications. This review offers an overview of drug repurposing methodologies, providing valuable insights and guiding future directions for advancing drug repurposing studies.

Abolishing β-arrestin recruitment is necessary for the full metabolic benefits of G protein-biased glucagon-like peptide-1 receptor agonists

AIM

Earlier studies have shown that peptide glucagon-like peptide-1 receptor (GLP-1R) agonists with reduced β-arrestin recruitment show enhanced anti-hyperglycaemic efficacy through avoidance of GLP-1R desensitization. However, the ligand modifications needed to decrease β-arrestin recruitment usually also reduces GLP-1R affinity, therefore higher doses are needed. Here we aimed to develop new, long-acting, G protein-biased GLP-1R agonists with acute signalling potency comparable with semaglutide, to provide insights into specific experimental and therapeutic scenarios.

MATERIALS AND METHODS

New GLP-1R agonist peptides were assessed using a variety of in vitro and in vivo assays.

RESULTS

First, we show that very substantial reductions in β-arrestin recruitment efficacy are required to realize fully the benefits of GLP-1R agonism on blood glucose lowering in mice, with more moderate reductions being less effective. Secondly, our lead compound (SRB107) performs substantially better than semaglutide for effects on blood glucose and weight loss, which may be jointly attributable to its biased agonist action and protracted pharmacokinetics. Thirdly, we show that biased agonist-specific GLP-1R internalization profiles occur at clinically relevant pharmacological concentrations. Finally, we show that SRB107 cAMP signalling is differentially modulated by single and double GLP1R coding variants seen in human populations, with implications for GLP-1R agonist pharmacogenomics.

CONCLUSIONS

Completely abolishing β-arrestin recruitment improves the anti-hyperglycaemic effects of GLP-1R agonists in mice.

GLP1 Receptor Agonists-Effects beyond Obesity and Diabetes

Glucagon-like peptide-1 receptor agonists (GLP1RA) have been transformative for patients and clinicians in treating type-2 diabetes and obesity. Drugs of this class, the bioavailability of which is continuously improving, enable weight loss and control blood glucose with minimal unwanted side effects. Since adopting GLP1RA for treating metabolic diseases, animal and clinical studies have revealed their beneficial effects on several other pathologies, including cardiovascular diseases, neurodegeneration, kidney disease, and cancer. A notable commonality between these diseases is their association with older age. Clinical trials and preclinical data suggest that GLP1RA may improve outcomes in these aging-related diseases. Some of the benefits of GLP1RA may be indirect due to their effects on obesity and glucose metabolism. However, there is building evidence that GLP1RA may also act directly on multiple organs implicated in aging-related pathology. This review aims to compile the studies reporting the effects of GLP1RA on aging-related diseases and discuss potential underlying mechanisms.

Rare Heterozygous Loss-of-Function Variants in the Human GLP-1 Receptor Are Not Associated With Cardiometabolic Phenotypes

CONTEXT

Lost glucagon-like peptide 1 receptor (GLP-1R) function affects human physiology.

OBJECTIVE

This work aimed to identify coding nonsynonymous GLP1R variants in Danish individuals to link their in vitro phenotypes and clinical phenotypic associations.

METHODS

We sequenced GLP1R in 8642 Danish individuals with type 2 diabetes or normal glucose tolerance and examined the ability of nonsynonymous variants to bind GLP-1 and to signal in transfected cells via cyclic adenosine monophosphate (cAMP) formation and β-arrestin recruitment. We performed a cross-sectional study between the burden of loss-of-signaling (LoS) variants and cardiometabolic phenotypes in 2930 patients with type 2 diabetes and 5712 participants in a population-based cohort. Furthermore, we studied the association between cardiometabolic phenotypes and the burden of the LoS variants and 60 partly overlapping predicted loss-of-function (pLoF) GLP1R variants found in 330 566 unrelated White exome-sequenced participants in the UK Biobank cohort.

RESULTS

We identified 36 nonsynonymous variants in GLP1R, of which 10 had a statistically significant loss in GLP-1-induced cAMP signaling compared to wild-type. However, no association was observed between the LoS variants and type 2 diabetes, although LoS variant carriers had a minor increased fasting plasma glucose level. Moreover, pLoF variants from the UK Biobank also did not reveal substantial cardiometabolic associations, despite a small effect on glycated hemoglobin A1c.

CONCLUSION

Since no homozygous LoS nor pLoF variants were identified and heterozygous carriers had similar cardiometabolic phenotype as noncarriers, we conclude that GLP-1R may be of particular importance in human physiology, due to a potential evolutionary intolerance of harmful homozygous GLP1R variants.

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.

Association between GLP-1R gene polymorphism and dyslipidemia in Chinese patients with type 2 diabetes mellitus: a case-control study

OBJECTIVE

To evaluate the relationship between GLP-1R gene polymorphisms and type 2 diabetes mellitus with dyslipidemia and without dyslipidemia in China.

METHODS

A total of 200 patients with Type 2 Diabetes Mellitus (T2DM) were included in this study, including 115 with dyslipidemia and 85 without dyslipidemia. We used Sanger double deoxygenation terminal assay and PCR-RFLP to detect genotype of the GLP-1R rs10305420 and rs3765467 loci. T-test was used to analyze the association between gene polymorphisms and lipid indicators. SHEsis online analysis software was used to analyze the linkage balance effect of loci, and SPSS 26 was used to calculate the gene interaction by dominant model.

RESULTS

The genotype distribution of the two loci in the sample of this study was in accordance with Hardy-weinberg equilibrium. There were significant differences in the genotype distribution and allele frequency of rs3765467 between T2DM patients with and without dyslipidemia (GG 52.9%, GA+AA 47.1% vs. GG 69.6%, GA+AA 30.4%; P = 0.017). Under the dominant model, the effects of rs3765467 A allele and rs10305420 T allele on dyslipidemia had multiplicative interactions (P = 0.016) and additive interactions (RERI = 0.403, 95% CI [-2.708 to 3.514]; AP = 0.376, 95% CI [-2.041, 2.793]). Meanwhile, HbA_1c levels in rs3765467 A allele carriers (GA+AA) were found to be significantly lower than those in patients with GG genotype (P = 0.006).

CONCLUSION

The rs3765467 (G/A) variant is associated with the incidence of dyslipidemia, and G allele may be a risk factor for dyslipidemia.

Pharmacogenetics of Glucagon-like-peptide-1 receptor in diabetes management

Type 2 diabetes mellitus (T2DM) is a complex metabolic disorder, primarily characterized by a decrease in insulin secretion and typically accompanied by insulin resistance. When untreated, T2DM is leading to an inevitable long-term complication. However, the novel treatment of T2DM like for example Glucagon-like Peptide-1 receptor agonists (GLP-1 RAs) give new perspectives for the patients to achieve a better glycemic control and additional metabolic improvements. Pharmacogenetics is a field in pharmacotherapy, which investigates the individual response to the medical treatment, according to polymorphic variations in the receptors of the drugs. This review aims to summarize current scientific evidence on the pharmacogenetics of the GLP-1 RA /liraglutide/ and the possible implementation in the treatment of T2D.

Transcriptomics for Clinical and Experimental Biology Research: Hang on a Seq

Sequencing the human genome empowers translational medicine, facilitating transcriptome-wide molecular diagnosis, pathway biology, and drug repositioning. Initially, microarrays are used to study the bulk transcriptome; but now short-read RNA sequencing (RNA-seq) predominates. Positioned as a superior technology, that makes the discovery of novel transcripts routine, most RNA-seq analyses are in fact modeled on the known transcriptome. Limitations of the RNA-seq methodology have emerged, while the design of, and the analysis strategies applied to, arrays have matured. An equitable comparison between these technologies is provided, highlighting advantages that modern arrays hold over RNA-seq. Array protocols more accurately quantify constitutively expressed protein coding genes across tissue replicates, and are more reliable for studying lower expressed genes. Arrays reveal long noncoding RNAs (lncRNA) are neither sparsely nor lower expressed than protein coding genes. Heterogeneous coverage of constitutively expressed genes observed with RNA-seq, undermines the validity and reproducibility of pathway analyses. The factors driving these observations, many of which are relevant to long-read or single-cell sequencing are discussed. As proposed herein, a reappreciation of bulk transcriptomic methods is required, including wider use of the modern high-density array data-to urgently revise existing anatomical RNA reference atlases and assist with more accurate study of lncRNAs.

FALCON systematically interrogates free fatty acid biology and identifies a novel mediator of lipotoxicity

Cellular exposure to free fatty acids (FFAs) is implicated in the pathogenesis of obesity-associated diseases. However, there are no scalable approaches to comprehensively assess the diverse FFAs circulating in human plasma. Furthermore, assessing how FFA-mediated processes interact with genetic risk for disease remains elusive. Here, we report the design and implementation of fatty acid library for comprehensive ontologies (FALCON), an unbiased, scalable, and multimodal interrogation of 61 structurally diverse FFAs. We identified a subset of lipotoxic monounsaturated fatty acids associated with decreased membrane fluidity. Furthermore, we prioritized genes that reflect the combined effects of harmful FFA exposure and genetic risk for type 2 diabetes (T2D). We found that c-MAF-inducing protein (CMIP) protects cells from FFA exposure by modulating Akt signaling. In sum, FALCON empowers the study of fundamental FFA biology and offers an integrative approach to identify much needed targets for diverse diseases associated with disordered FFA metabolism.

Precision Medicine and the future of Cardiovascular Diseases: A Clinically Oriented Comprehensive Review

Cardiac diseases form the lion's share of the global disease burden, owing to the paradigm shift to non-infectious diseases from infectious ones. The prevalence of CVDs has nearly doubled, increasing from 271 million in 1990 to 523 million in 2019. Additionally, the global trend for the years lived with disability has doubled, increasing from 17.7 million to 34.4 million over the same period. The advent of precision medicine in cardiology has ignited new possibilities for individually personalized, integrative, and patient-centric approaches to disease prevention and treatment, incorporating the standard clinical data with advanced "omics". These data help with the phenotypically adjudicated individualization of treatment. The major objective of this review was to compile the evolving clinically relevant tools of precision medicine that can help with the evidence-based precise individualized management of cardiac diseases with the highest DALY. The field of cardiology is evolving to provide targeted therapy, which is crafted as per the "omics", involving genomics, transcriptomics, epigenomics, proteomics, metabolomics, and microbiomics, for deep phenotyping. Research for individualizing therapy in heart diseases with the highest DALY has helped identify novel genes, biomarkers, proteins, and technologies to aid early diagnosis and treatment. Precision medicine has helped in targeted management, allowing early diagnosis, timely precise intervention, and exposure to minimal side effects. Despite these great impacts, overcoming the barriers to implementing precision medicine requires addressing the economic, cultural, technical, and socio-political issues. Precision medicine is proposed to be the future of cardiovascular medicine and holds the potential for a more efficient and personalized approach to the management of cardiovascular diseases, contrary to the standardized blanket approach.

Genetically proxied therapeutic prolyl-hydroxylase inhibition and cardiovascular risk

Prolyl hydroxylase (PHD) inhibitors are in clinical development for anaemia in chronic kidney disease. Epidemiological studies have reported conflicting results regarding safety of long-term therapeutic haemoglobin (Hgb) rises through PHD inhibition on risk of cardiovascular disease. Genetic variation in genes encoding PHDs can be used as partial proxies to investigate the potential effects of long-term Hgb rises. We used Mendelian randomization to investigate the effect of long-term Hgb level rises through genetically proxied PHD inhibition on coronary artery disease (CAD: 60 801 cases; 123 504 controls), myocardial infarction (MI: 42 561 cases; 123 504 controls) or stroke (40 585 cases; 406 111 controls). To further characterize long-term effects of Hgb level rises, we performed a phenome-wide association study (PheWAS) in up to 451 099 UK Biobank individuals. Genetically proxied therapeutic PHD inhibition, equivalent to a 1.00 g/dl increase in Hgb levels, was not associated (at P < 0.05) with increased odds of CAD; odd ratio (OR) [95% confidence intervals (CI)] = 1.06 (0.84, 1.35), MI [OR (95% CI) = 1.02 (0.79, 1.33)] or stroke [OR (95% CI) = 0.91 (0.66, 1.24)]. PheWAS revealed associations with blood related phenotypes consistent with EGLN's role, relevant kidney- and liver-related biomarkers like estimated glomerular filtration rate and microalbuminuria, and non-alcoholic fatty liver disease (Bonferroni-adjusted P < 5.42E-05) but these were not clinically meaningful. These findings suggest that long-term alterations in Hgb through PHD inhibition are unlikely to substantially increase cardiovascular disease risk; using large disease genome-wide association study data, we could exclude ORs of 1.35 for cardiovascular risk with a 1.00 g/dl increase in Hgb.

Genetic variants of the GLP-1R gene affect the susceptibility and glucose metabolism of gestational diabetes mellitus: a two-center nested case‒control study

BACKGROUND

Gestational diabetes mellitus (GDM) is the most common complication during pregnancy, occurring under the combined action of environmental and genetic factors. Genetic variants of glucagon-like peptide-1 receptor (GLP-1R) have been reported to affect insulin secretion and susceptibility to type 2 diabetes. This study aimed to explore the role of GLP-1R polymorphisms in GDM and glucose metabolism.

METHODS

A two-center nested case‒control study was designed, including 200 pregnant women with GDM and 200 pregnant women without GDM genotyped for five tag SNPs of GLP-1R using Sanger sequencing. Logistic regression was used to evaluate the relationship between GLP-1R polymorphisms and GDM risk. Glucose and insulin concentrations were measured based upon the 75 g oral glucose tolerance test (OGTT). Beta cell function of different genotypes was estimated with the 60 min insulinogenic index (IGI₆₀) and OGTT-derived disposition index (DI).

RESULTS

Mutant genotype AG + GG of tag SNP rs6458093 nominally increased GDM risk (p = 0.049), especially among subjects younger than 35 years (p = 0.024) and with BMI no less than 24 (p = 0.041), after adjusting for confounders. Meanwhile, compared with subjects with wild genotype AA, subjects with genotype AG + GG of rs6458093 also showed nominally significantly lower IGI₆₀ (p = 0.032) and DI (p = 0.029), as well as significantly higher 75 g OGTT-based 1 h glucose load plasma glucose levels (p = 0.045). Moreover, the mutant heterozygous genotype GA of tag SNP rs3765467 nominally decreased GDM risk among subjects older than 35 years (p = 0.037) but showed no association with insulin secretion and glucose homeostasis.

CONCLUSIONS

Tag SNP rs6458093 of GLP-1R was nominally associated with increased GDM risk and affected beta cell function and postprandial glucose metabolism, while tag SNP rs3765467 of GLP-1R was nominally associated with decreased GDM risk, providing evidence for molecular markers and etiological study of GDM.

On the Verge of Precision Medicine in Diabetes

The epidemic of type 2 diabetes (T2D) is a significant global public health challenge and a major cause of morbidity and mortality. Despite the recent proliferation of pharmacological agents for the treatment of T2D, current therapies simply treat the symptom, i.e. hyperglycemia, and do not directly address the underlying disease process or modify the disease course. This article summarizes how genomic discovery has contributed to unraveling the heterogeneity in T2D, reviews relevant discoveries in the pharmacogenetics of five commonly prescribed glucose-lowering agents, presents evidence supporting how pharmacogenetics can be leveraged to advance precision medicine, and calls attention to important research gaps to its implementation to guide treatment choices.

Identification and single-base gene-editing functional validation of a cis-EPO variant as a genetic predictor for EPO-increasing therapies

Hypoxia-inducible factor prolyl hydroxylase inhibitors (HIF-PHIs) are currently under clinical development for treating anemia in chronic kidney disease (CKD), but it is important to monitor their cardiovascular safety. Genetic variants can be used as predictors to help inform the potential risk of adverse effects associated with drug treatments. We therefore aimed to use human genetics to help assess the risk of adverse cardiovascular events associated with therapeutically altered EPO levels to help inform clinical trials studying the safety of HIF-PHIs. By performing a genome-wide association meta-analysis of EPO (n = 6,127), we identified a cis-EPO variant (rs1617640) lying in the EPO promoter region. We validated this variant as most likely causal in controlling EPO levels by using genetic and functional approaches, including single-base gene editing. Using this variant as a partial predictor for therapeutic modulation of EPO and large genome-wide association data in Mendelian randomization tests, we found no evidence (at p < 0.05) that genetically predicted long-term rises in endogenous EPO, equivalent to a 2.2-unit increase, increased risk of coronary artery disease (CAD, OR [95% CI] = 1.01 [0.93, 1.07]), myocardial infarction (MI, OR [95% CI] = 0.99 [0.87, 1.15]), or stroke (OR [95% CI] = 0.97 [0.87, 1.07]). We could exclude increased odds of 1.15 for cardiovascular disease for a 2.2-unit EPO increase. A combination of genetic and functional studies provides a powerful approach to investigate the potential therapeutic profile of EPO-increasing therapies for treating anemia in CKD.

Application of Artificial Intelligence in Discovery and Development of Anticancer and Antidiabetic Therapeutic Agents

Spectacular developments in molecular and cellular biology have led to important discoveries in cancer research. Despite cancer is one of the major causes of morbidity and mortality globally, diabetes is one of the most leading sources of group of disorders. Artificial intelligence (AI) has been considered the fourth industrial revolution machine. The most major hurdles in drug discovery and development are the time and expenditures required to sustain the drug research pipeline. Large amounts of data can be explored and generated by AI, which can then be converted into useful knowledge. Because of this, the world's largest drug companies have already begun to use AI in their drug development research. In the present era, AI has a huge amount of potential for the rapid discovery and development of new anticancer drugs. Clinical studies, electronic medical records, high-resolution medical imaging, and genomic assessments are just a few of the tools that could aid drug development. Large data sets are available to researchers in the pharmaceutical and medical fields, which can be analyzed by advanced AI systems. This review looked at how computational biology and AI technologies may be utilized in cancer precision drug development by combining knowledge of cancer medicines, drug resistance, and structural biology. This review also highlighted a realistic assessment of the potential for AI in understanding and managing diabetes.

Glucagon-like Peptide-1 Receptor Agonists in the Management of Type 2 Diabetes Mellitus and Obesity: The Impact of Pharmacological Properties and Genetic Factors

Glucagon-like peptide-1 (GLP-1) receptor agonists are a new class of antihyperglycemic drugs that enhance appropriate pancreatic β-cell secretion, pancreatic α-cell (glucagon) suppression, decrease liver glucose production, increase satiety through their action on the central nervous system, slow gastric emptying time, and increase insulin action on peripheral tissue. They are effective in the management of type 2 diabetes mellitus and have a favorable effect on weight loss. Their cardiovascular and renal safety has been extensively investigated and confirmed in many clinical trials. Recently, evidence has shown that in addition to the existing approaches for the treatment of obesity, semaglutide in higher doses promotes weight loss and can be used as a drug to treat obesity. However, some T2DM and obese patients do not achieve a desired therapeutic effect of GLP-1 receptor agonists. This could be due to the multifactorial etiologies of T2DM and obesity, but genetic variability in the GLP-1 receptor or signaling pathways also needs to be considered in non-responders to GLP-1 receptor agonists. This review focuses on the pharmacological, clinical, and genetic factors that may influence the response to GLP-1 receptor agonists in the treatment of type 2 diabetes mellitus and obesity.

Human Genomics and Drug Development

Insights into the genetic basis of human disease are helping to address some of the key challenges in new drug development including the very high rates of failure. Here we review the recent history of an emerging, genomics-assisted approach to pharmaceutical research and development, and its relationship to Mendelian randomization (MR), a well-established analytical approach to causal inference. We demonstrate how human genomic data linked to pharmaceutically relevant phenotypes can be used for (1) drug target identification (mapping relevant drug targets to diseases), (2) drug target validation (inferring the likely effects of drug target perturbation), (3) evaluation of the effectiveness and specificity of compound-target engagement (inferring the extent to which the effects of a compound are exclusive to the target and distinguishing between on-target and off-target compound effects), and (4) the selection of end points in clinical trials (the diseases or conditions to be evaluated as trial outcomes). We show how genomics can help identify indication expansion opportunities for licensed drugs and repurposing of compounds developed to clinical phase that proved safe but ineffective for the original intended indication. We outline statistical and biological considerations in using MR for drug target validation (drug target MR) and discuss the obstacles and challenges for scaled applications of these genomics-based approaches.

The dual glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1 receptor agonist tirzepatide improves cardiovascular risk biomarkers in patients with type 2 diabetes: A post hoc analysis

In a phase 2 trial of once-weekly tirzepatide (1, 5, 10, or 15 mg), dulaglutide (1.5 mg), or placebo, the dual glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1 receptor agonist tirzepatide dose-dependently reduced HbA1c and body weight in patients with type 2 diabetes. In this post hoc analysis, inflammation, endothelial dysfunction, and cellular stress biomarkers were measured at baseline, 4, 12, and 26 weeks to evaluate the additional effects of tirzepatide on cardiovascular risk factors. At 26 weeks, tirzepatide 10 and 15 mg decreased YKL-40 (also known as chitinase-3 like-protein-1), intercellular adhesion molecule 1 (ICAM-1), leptin, and growth differentiation factor 15 levels versus baseline, and YKL-40 and leptin levels versus placebo and dulaglutide. Tirzepatide 15 mg also decreased ICAM-1 levels versus placebo and dulaglutide, and high-sensitivity C-reactive protein (hsCRP) levels versus baseline and placebo, but not dulaglutide. GlycA, interleukin 6, vascular cell adhesion molecule 1, and N-terminal-pro hormone B-type natriuretic peptide levels were not significantly changed in any group. YKL-40, hsCRP, and ICAM-1 levels rapidly decreased within 4 weeks of treatment with tirzepatide 10 and 15 mg, whereas the decrease in leptin levels was more gradual and did not plateau by 26 weeks. In this hypothesis-generating exploratory analysis, tirzepatide decreased several biomarkers that have been associated with cardiovascular risk.

Dorothy Hodgkin Lecture 2021: Drugs, genes and diabetes

Glycaemic response to metformin and sulphonylureas is heritable - with ~34%-37% of variation explainable by common genetic variation. The premise of this review is that by understanding how genetic variation contributes to drug response we can gain insights into the mechanisms of action of diabetes drugs. Here, I focus on two old drugs, metformin and sulphonylureas, where I would suggest we still have a lot to learn about their mechanism of action or their optimal use in clinical care. The fact that reduced function variants of the key transporter that takes metformin into the liver (OCT1) do not alter glycaemic response to metformin suggests that metformin does not need to get into the liver to work. A subsequent GWAS of metformin response identifies a robust variant that alters GLUT2 expression - which may support increasing evidence that metformin works primarily in the gut. For sulphonylureas, observation from patients with neonatal diabetes due to activating K_ATP channel mutations treated with sulphonylureas identified a novel role for sulphonylureas to enable β-cell incretin response. This work led to recent studies of low-dose sulphonylurea (20 mg gliclazide) in T2DM, which identified that at this dose sulphonylureas augment the incretin effect and increase β-cell glucose sensitivity, without increasing hypoglycaemia risk. This work, prompted by studies in monogenic diabetes, suggests that we have historically been using sulphonylureas at too high a dose. With increasing availability of genetic data pharmacogenomic studies in patients with diabetes should reveal mechanistic insights into old and new diabetes drugs, with the potential for optimized use and novel therapies.

Genetically Predicted Glucose-Dependent Insulinotropic Polypeptide (GIP) Levels and Cardiovascular Disease Risk Are Driven by Distinct Causal Variants in the GIPR Region

There is considerable interest in GIPR agonism to enhance the insulinotropic and extrapancreatic effects of GIP, thereby improving glycemic and weight control in type 2 diabetes (T2D) and obesity. Recent genetic epidemiological evidence has implicated higher GIPR-mediated GIP levels in raising coronary artery disease (CAD) risk, a potential safety concern for GIPR agonism. We therefore aimed to quantitatively assess whether the association between higher GIPR-mediated fasting GIP levels and CAD risk is mediated via GIPR or is instead the result of linkage disequilibrium (LD) confounding between variants at the GIPR locus. Using Bayesian multitrait colocalization, we identified a GIPR missense variant, rs1800437 (G allele; E354), as the putatively causal variant shared among fasting GIP levels, glycemic traits, and adiposity-related traits (posterior probability for colocalization [PPcoloc] > 0.97; PP explained by the candidate variant [PPexplained] = 1) that was independent from a cluster of CAD and lipid traits driven by a known missense variant in APOE (rs7412; distance to E354 ∼770 Kb; R 2 with E354 = 0.004; PPcoloc > 0.99; PPexplained = 1). Further, conditioning the association between E354 and CAD on the residual LD with rs7412, we observed slight attenuation in association, but it remained significant (odds ratio [OR] per copy of E354 after adjustment 1.03; 95% CI 1.02, 1.04; P = 0.003). Instead, E354's association with CAD was completely attenuated when conditioning on an additional established CAD signal, rs1964272 (R 2 with E354 = 0.27), an intronic variant in SNRPD2 (OR for E354 after adjustment for rs1964272: 1.01; 95% CI 0.99, 1.03; P = 0.06). We demonstrate that associations with GIP and anthropometric and glycemic traits are driven by genetic signals distinct from those driving CAD and lipid traits in the GIPR region and that higher E354-mediated fasting GIP levels are not associated with CAD risk. These findings provide evidence that the inclusion of GIPR agonism in dual GIPR/GLP1R agonists could potentiate the protective effect of GLP-1 agonists on diabetes without undue CAD risk, an aspect that has yet to be assessed in clinical trials.

Understanding the place for GLP-1RA therapy: Translating guidelines for treatment of type 2 diabetes into everyday clinical practice and patient selection

Since the first glucagon-like peptide 1 (GLP-1) receptor agonist (GLP-1RA) was approved in 2005 (exenatide twice daily) for type 2 diabetes (T2D), the class has developed with newer compounds having more pronounced effects on glycaemic control and body weight. Also, administration regimes have become more convenient with once weekly injections, and recently an oral administration has become available. Large-scale randomized controlled cardiovascular (CV) outcome trials (CVOTs) have shown that GLP-1RA therapy can reduce the risk of CV disease (CVD) in high-risk individuals with T2D. In addition, GLP-1RAs may have renal benefits driven by new-onset macroalbuminuria, although no effect on hard renal endpoints has been found. Subsequently, the place for GLP-1RA therapy has changed over recent years, with most societies endorsing GLP-1RA therapy in patients with established or high risk of CVD independently of glycaemia. Initiation of GLP-1RA therapy can be complex due to differences in efficacy, side effects and safety profiles as well as administration forms within the class. Implementing guideline recommendations into ideal patient selection may be challenging both in specialty and non-specialty settings. To ensure adequate and proactive use of modern glucose-lowering medications in the treatment of T2D, it is essential to recognize patients with high risk or documented CVD. The present review provides an overview of the efficacy and benefits of the currently available GLP-1RA compounds. Furthermore, we review the results from recent large-scale CVOTs in a clinical context and suggest improving the implementation of GLP-1RA therapy across specialties to improve overall patient selection.

Cardiovascular disease in diabetes, beyond glucose

Despite the decades-old knowledge that diabetes mellitus is a major risk factor for cardiovascular disease, the reasons for this association are only partially understood. While this association is true for both type 1 and type 2 diabetes, different pathophysiological processes may be responsible. Lipids and other risk factors are indeed important, whereas the role of glucose is less clear. This lack of clarity stems from clinical trials that do not unambiguously show that intensive glycemic control reduces cardiovascular events. Animal models have provided mechanisms that link diabetes to increased atherosclerosis, and evidence consistent with the importance of factors beyond hyperglycemia has emerged. We review clinical, pathological, and animal studies exploring the pathogenesis of atherosclerosis in humans living with diabetes and in mouse models of diabetes. An increased effort to identify risk factors beyond glucose is now needed to prevent the increased cardiovascular disease risk associated with diabetes.

Genetic Evidence for Repurposing of GLP1R (Glucagon-Like Peptide-1 Receptor) Agonists to Prevent Heart Failure

Background

This study was designed to investigate the genetic evidence for repurposing of GLP1R (glucagon‐like peptide‐1 receptor) agonists to prevent heart failure (HF) and whether the potential benefit exceeds the benefit conferred by more general glycemic control.

Methods and Results

We applied 2‐sample Mendelian randomization of genetically proxied GLP1R agonism on HF as the main outcome and left ventricular ejection fraction as the secondary outcome. The associations were compared with those of general glycemic control on the same outcomes. Genetic associations were obtained from genome‐wide association study summary statistics of type 2 diabetes mellitus (228 499 cases and 1 178 783 controls), glycated hemoglobin (n=344 182), HF (47,309 cases and 930 014 controls), and left ventricular ejection fraction (n=16 923). Genetic proxies for GLP1R agonism associated with reduced risk of HF (odds ratio per 1 mmol/mol decrease in glycated hemoglobin 0.75; 95% CI, 0.64–0.87; P=1.69×10⁻⁴), and higher left ventricular ejection fraction (SD change in left ventricular ejection fraction per 1 mmol/mol decrease in glycated hemoglobin 0.22%; 95% CI, 0.03–0.42; P=0.03). The magnitude of these benefits exceeded those expected from improved glycemic control more generally. The results were similar in sensitivity analyses, and we did not find evidence to suggest that these associations were mediated by reduced coronary artery disease risk.

Conclusions

This genetic evidence supports the repurposing of GLP1R agonists for preventing HF.

Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development

Drug development in cardiovascular disease is stagnating, with lack of efficacy and adverse effects being barriers to innovation. Human genetics can provide compelling evidence of causation through approaches such as Mendelian randomization, with genetic support for causation increasing the probability of a clinical trial succeeding. Mendelian randomization applied to quantitative traits can identify risk factors for disease that are both causal and amenable to therapeutic modification. However, important differences exist between genetic investigations of a biomarker (such as HDL cholesterol) and a drug target aimed at modifying the same biomarker of interest (such as cholesteryl ester transfer protein), with implications for the methodology, interpretation and application of Mendelian randomization to drug development. Differences include the comparative nature of the genetic architecture - that is, biomarkers are typically polygenic, whereas protein drug targets are influenced by either cis-acting or trans-acting genetic variants - and the potential for drug targets to show disease associations that might differ from those of the biomarker that they are intended to modify (target-mediated pleiotropy). In this Review, we compare and contrast the use of Mendelian randomization to evaluate potential drug targets versus quantitative traits. We explain how genetic epidemiological studies can be used to assess the aetiological roles of biomarkers in disease and to prioritize drug targets, including designing their evaluation in clinical trials.

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10-8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.

Old Paradoxes and New Opportunities for Appetite Control in Obesity

Human obesity is accompanied by alterations in the blood concentrations of multiple circulating appetite regulators. Paradoxically, most of the appetite-inhibitory hormones are elevated in nonsyndromic obesity, while most of the appetite stimulatory hormones are reduced, perhaps reflecting vain attempts of regulation by inefficient feedback circuitries. In this context, it is important to understand which appetite regulators exhibit a convergent rather than paradoxical behavior and hence are likely to contribute to the maintenance of the obese state. Pharmacological interventions in obesity should preferentially consist of the supplementation of deficient appetite inhibitors or the neutralization of excessive appetite stimulators. Here, we critically analyze the current literature on appetite-regulatory peptide hormones. We propose a short-list of appetite modulators that may constitute the best candidates for therapeutic interventions.

Precision Medicine: A New Paradigm in Therapeutics

A key goal of clinical care is to treat patients as individuals and to approach therapeutics in such a way that it has optimal efficacy and minimal toxicity. With swift technological advances, such as genomic sequencing and molecular targeted drug exploitation, the concept of precision medicine has been robustly promoted in recent years. Precision medicine endeavors to demarcate diseases using multiple data sources from genomics to digital health metrics in order to facilitate an individualized yet "evidence-based" decision regarding diagnostic and therapeutic approaches. In this way, therapeutics can be centered toward patients based on their molecular presentation rather than grouping them into broad categories with a "one size fits all" approach. This review article is aimed to provide a broad overview of the advent and emergence of precision medicine in view of its current implications.

Mendelian randomization for studying the effects of perturbing drug targets

Drugs whose targets have genetic evidence to support efficacy and safety are more likely to be approved after clinical development. In this paper, we provide an overview of how natural sequence variation in the genes that encode drug targets can be used in Mendelian randomization analyses to offer insight into mechanism-based efficacy and adverse effects. Large databases of summary level genetic association data are increasingly available and can be leveraged to identify and validate variants that serve as proxies for drug target perturbation. As with all empirical research, Mendelian randomization has limitations including genetic confounding, its consideration of lifelong effects, and issues related to heterogeneity across different tissues and populations. When appropriately applied, Mendelian randomization provides a useful empirical framework for using population level data to improve the success rates of the drug development pipeline.

Mendelian randomization for studying the effects of perturbing drug targets

Drugs whose targets have genetic evidence to support efficacy and safety are more likely to be approved after clinical development. In this paper, we provide an overview of how natural sequence variation in the genes that encode drug targets can be used in Mendelian randomization analyses to offer insight into mechanism-based efficacy and adverse effects. Large databases of summary level genetic association data are increasingly available and can be leveraged to identify and validate variants that serve as proxies for drug target perturbation. As with all empirical research, Mendelian randomization has limitations including genetic confounding, its consideration of lifelong effects, and issues related to heterogeneity across different tissues and populations. When appropriately applied, Mendelian randomization provides a useful empirical framework for using population level data to improve the success rates of the drug development pipeline.

Incretin Hormones in Obesity and Related Cardiometabolic Disorders: The Clinical Perspective

The prevalence of obesity continues to grow rapidly worldwide, posing many public health challenges of the 21st century. Obese subjects are at major risk for serious diet-related noncommunicable diseases, including type 2 diabetes mellitus, cardiovascular disease, and non-alcoholic fatty liver disease. Understanding the mechanisms underlying obesity pathogenesis is needed for the development of effective treatment strategies. Dysregulation of incretin secretion and actions has been observed in obesity and related metabolic disorders; therefore, incretin-based therapies have been developed to provide new therapeutic options. Incretin mimetics present glucose-lowering properties, together with a reduction of appetite and food intake, resulting in weight loss. In this review, we describe the physiology of two known incretins—glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1), and their role in obesity and related cardiometabolic disorders. We also focus on the available and incoming incretin-based medications that can be used in the treatment of the above-mentioned conditions.

Glucose-Dependent Insulinotropic Peptide in the High-Normal Range Is Associated With Increased Carotid Intima-Media Thickness

OBJECTIVE

While existing evidence supports beneficial cardiovascular effects of glucagon-like peptide 1 (GLP-1), emerging studies suggest that glucose-dependent insulinotropic peptide (GIP) and/or signaling via the GIP receptor may have untoward cardiovascular effects. Indeed, recent studies show that fasting physiological GIP levels are associated with total mortality and cardiovascular mortality, and it was suggested that GIP plays a role in pathogenesis of coronary artery disease. We investigated the associations between fasting and postchallenge GIP and GLP-1 concentrations and subclinical atherosclerosis as measured by mean intima-media thickness in the common carotid artery (IMT_meanCCA) and maximal intima-media thickness in the carotid bifurcation (IMT_maxBulb).

RESEARCH DESIGN AND METHODS

Participants at reexamination within the Malmö Diet and Cancer-Cardiovascular Cohort study (n = 3,734, mean age 72.5 years, 59.3% women, 10.8% subjects with diabetes, fasting GIP available for 3,342 subjects, fasting GLP-1 available for 3,299 subjects) underwent oral glucose tolerance testing and carotid ultrasound.

RESULTS

In linear regression analyses, each 1-SD increment of fasting GIP was associated with increased (per mm) IMT_meanCCA (β = 0.010, P = 0.010) and IMT_maxBulb (β = 0.014; P = 0.040) in models adjusted for known risk factors and glucose metabolism. In contrast, each 1-SD increment of fasting GLP-1 was associated with decreased IMT_maxBulb (per mm, β = -0.016, P = 0.014). These associations remained significant when subjects with diabetes were excluded from analyses.

CONCLUSIONS

In a Swedish elderly population, physiologically elevated levels of fasting GIP are associated with increased IMT_meanCCA, while GLP-1 is associated with decreased IMT_maxBulb, further emphasizing diverging cardiovascular effects of these two incretin hormones.

The association of clinical phenotypes to known AD/FTD genetic risk loci and their inter-relationship

To elucidate how variants in genetic risk loci previously implicated in Alzheimer’s Disease (AD) and/or frontotemporal dementia (FTD) contribute to expression of disease phenotypes, a phenome-wide association study was performed in two waves. In the first wave, we explored clinical traits associated with thirteen genetic variants previously reported to be linked to disease risk using both the 23andMe and UKB cohorts. We tested 30 additional AD variants in UKB cohort only in the second wave. APOE variants defining ε2/ε3/ε4 alleles and rs646776 were identified to be significantly associated with metabolic/cardiovascular and longevity traits. APOE variants were also significantly associated with neurological traits. ABI3 variant rs28394864 was significantly associated with cardiovascular (e.g. (hypertension, ischemic heart disease, coronary atherosclerosis, angina) and immune-related trait asthma. Both APOE variants and CLU variant were significantly associated with nearsightedness. HLA- DRB1 variant was associated with diseases with immune-related traits. Additionally, variants from 10+ AD genes (BZRAP1-AS1, ADAMTS4, ADAM10, APH1B, SCIMP, ABI3, SPPL2A, ZNF232, GRN, CD2AP, and CD33) were associated with hematological measurements such as white blood cell (leukocyte) count, monocyte count, neutrophill count, platelet count, and/or mean platelet (thrombocyte) volume (an autoimmune disease biomarker). Many of these genes are expressed specifically in microglia. The associations of ABI3 variant with cardiovascular and immune-related traits are one of the novel findings from this study. Taken together, it is evidenced that at least some AD and FTD variants are associated with multiple clinical phenotypes and not just dementia. These findings were discussed in the context of causal relationship versus pleiotropy via Mendelian randomization analysis.

The Need for Precision Medicine to be Applied to Diabetes

Precision medicine refers to the tailoring of medical treatment for an individual based on large amounts of biologic and extrinsic data. The fast advancing fields of molecular biology, gene sequencing, machine learning, and other technologies enable precision medicine to utilize this detailed information to enhance clinical management decision-making for an individual in the real time of the disease course. Traditional clinical decision making is based on reacting to a relatively limited number of phenotypes that are determined by history, physical examination, and conventional lab tests. Precision medicine depends on highly detailed profiling of the patient's genetic, morphologic, and metabolic makeup. The precision medicine approach can be applied to individuals with diabetes to select treatments most likely to offer benefit and least likely to cause side effects, offering prospects of improved clinical outcomes and economic costs savings over current empiric practices. As genetic, metabolomic, immunologic, and other sophisticated testing becomes less expensive and more widespread in the medical record, it is expected that precision medicine will become increasingly applied to diabetes care.

Cardiovascular effects of glucagon-like peptide 1 receptor agonists: from mechanistic studies in humans to clinical outcomes

Type 2 diabetes mellitus (T2DM) is currently one of the most prevalent diseases, with as many as 415 million patients worldwide. T2DM is characterized by elevated blood glucose levels and is often accompanied by several comorbidities, such as cardiovascular disease. Treatment of T2DM is focused on reducing glucose levels by either lifestyle changes or medical treatment. One treatment option for T2DM is based on the gut-derived hormone glucagon-like peptide 1 (GLP-1). GLP-1 reduces blood glucose levels by stimulating insulin secretion, however, it is rapidly degraded, and thereby losing its glycaemic effect. GLP-1 receptor agonists (GLP-1RAs) are immune to degradation, prolonging the glycaemic effect. Lately, GLP-1RAs have spiked the interest of researchers and clinicians due to their beneficial effects on cardiovascular disease. Preclinical and clinical data have demonstrated that GLP-1 receptors are abundantly present in the heart and that stimulation of these receptors by GLP-1 has several effects. In this review, we will discuss the effects of GLP-1RA on heart rate, blood pressure, microvascular function, lipids, and inflammation, as measured in human mechanistic studies, and suggest how these effects may translate into the improved cardiovascular outcomes as demonstrated in several trials.

Nutrient consumption-dependent association of a glucagon-like peptide-1 receptor gene polymorphism with insulin secretion

Since type 2 diabetes (DM) is a life-style related disease, life-style should be considered when association between genetic factors and DM are examined. However, most studies did not examine genetic associations in consideration with lifestyle. Glucagon-like peptide-1 (GLP-1) receptor (GLP1R) mediates the insulinotropic action of GLP-1 in β-cells. We here examined the association while taking into consideration of interactions between the gene polymorphism and various nutrient factors. Participants from the population-based Iwaki study of Japanese subjects held in 2014–2017 with information on nutritional intake evaluated by self-administered dietary history questionnaire, and GLP1R genotype (rs3765467: A/G), were included (n = 1,560). Although not significant, insulin secretion indices assessed by homeostasis model assessment of β-cell function (HOMA-β) in subjects with the GG genotype tended to be lower than in those with the AA+AG genotypes in most groups stratified into tertiles based on daily nutrient consumptions (high, middle, and low). Stratification also showed that the GG genotype was a significant risk for decreased insulin secretion (HOMA-β ≤ 30) even after adjustment for multiple factors (age, body mass index, alcohol consumption), but only in the highest tertiles of energy, protein and carbohydrate consumption in men [odds ratios (95% confidence interval) 3.95 (1.03–15.1), 15.83 (1.58–158.9), and 4.23 (1.10–11.2), respectively]. A polymorphism of the GLP1R gene was associated with decreased insulin secretion in a nutrient consumption-dependent manner in Japanese men, indicating an interaction between GLP1R and nutritional factors in the pathophysiology of DM.

Exome sequencing and characterization of 49,960 individuals in the UK Biobank

The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world1. Here we describe the release of exome-sequence data for the first 49,960 study participants, revealing approximately 4 million coding variants (of which around 98.6% have a frequency of less than 1%). The data include 198,269 autosomal predicted loss-of-function (LOF) variants, a more than 14-fold increase compared to the imputed sequence. Nearly all genes (more than 97%) had at least one carrier with a LOF variant, and most genes (more than 69%) had at least ten carriers with a LOF variant. We illustrate the power of characterizing LOF variants in this population through association analyses across 1,730 phenotypes. In addition to replicating established associations, we found novel LOF variants with large effects on disease traits, including PIEZO1 on varicose veins, COL6A1 on corneal resistance, MEPE on bone density, and IQGAP2 and GMPR on blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical importance, and show that 2% of this population has a medically actionable variant. Furthermore, we characterize the penetrance of cancer in carriers of pathogenic BRCA1 and BRCA2 variants. Exome sequences from the first 49,960 participants highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community.

Glucagon-like peptide-1 receptor and sarcoglycan delta genetic variants can affect cardiovascular risk in chronic kidney disease patients under hemodialysis

BACKGROUND

Chronic kidney disease (CKD) patients under hemodialysis show a higher risk of cardiovascular (CV) mortality and morbidity than the general population. This study aims to identify genetic markers that could explain the increased CV risk in hemodialysis.

METHODS

A total of 245 CKD patients under hemodialysis were recruited and followed up for 5 years to record CV events. Genetic analysis was performed using single-nucleotide polymorphisms (SNPs) genotyping by Infinium Expanded Multi-Ethnic Genotyping Array (Illumina, San Diego, CA, USA) comparing patients with and without a history of CV events [161 cardiovascular diseases (CVDs) and 84 no CVDs]. The fixation index (Fst) measure was used to identify the most differentiated SNPs, and gene ontology analysis [Protein Analysis THrough Evolutionary Relationships (PANTHER) and Ingenuity Pathway Analysis (IPA)] was applied to define the biological/pathological roles of the associated SNPs. Partitioning tree analysis interrogated the genotype-phenotype relationship between discovered genetic variants and CV phenotypes. Cox regression analysis measured the effect of these SNPs on new CV events during the follow-up (FU).

RESULTS

Fst analysis identified 3218 SNPs that were significantly different between CVD and no CVD. Gene ontology analysis identified two of these SNPs as involved in cardiovascular disease pathways (Ingenuity Pathway) and heart development (Panther) and belonging to 2 different genes: Glucagon-like peptide-1 receptor (GLP1R) and Sarcoglycan delta (SGCD). The phenotype-genotype analysis found a higher percentage of CVD patients carrying the GLP1R rs10305445 allele A (P = 0.03) and lower percentages of CVD patients carrying the SGCD rs145292439 allele A (P = 0.038). Moreover, SGCD rs145292439 was associated with higher levels of high-density lipoprotein (P = 0.015). Cox analysis confirmed the increased frequency of CV events during the 5-year FU in patients carrying GLP1R rs1035445 allele A but it did not show any significant association with SGCD rs145292439.

CONCLUSIONS

This study identified GLP1R rs10305445 and SCGD rs145292439 as potential genetic markers that may explain the higher risk of CVD in hemodialysis patients.

Emerging Targets for Cardiovascular Disease Prevention in Diabetes

Type 1 and type 2 diabetes mellitus (T1DM and T2DM) increase the risk of atherosclerotic cardiovascular disease (CVD), resulting in acute cardiovascular events, such as heart attack and stroke. Recent clinical trials point toward new treatment and prevention strategies for cardiovascular complications of T2DM. New antidiabetic agents show unexpected cardioprotective benefits. Moreover, genetic and reverse translational strategies have revealed potential novel targets for CVD prevention in diabetes, including inhibition of apolipoprotein C3 (APOC3). Modeling and pharmacology-based approaches to improve insulin action provide additional potential strategies to combat CVD. The development of new strategies for improved diabetes and lipid control fuels hope for future prevention of CVD associated with diabetes.

Association between GLP-1 receptor gene polymorphisms with reward learning, anhedonia and depression diagnosis

BACKGROUND

Glucagon-like peptide-1 receptors (GLP-1Rs) are widely expressed in the brain. Evidence suggests that they may play a role in reward responses and neuroprotection. However, the association of GLP-1R with anhedonia and depression diagnosis has not been studied. Here, we examined the association of GLP-1R polymorphisms with objective and subjective measures of anhedonia, as well as depression diagnosis.

METHODS

Objective [response bias assessed by the probabilistic reward task (PRT)] and subjective [Snaith-Hamilton Pleasure Scale (SHAPS)] measures of anhedonia, clinical variables and DNA samples were collected from 100 controls and 164 patients at McLean Hospital. An independent sample genotyped as part of the Psychiatric Genomics Consortium (PGC) was used to study the effect of putative GLP-1R polymorphisms linked to response bias in PRT on depression diagnosis.

RESULTS

The C allele in rs1042044 was significantly associated with increased PRT response bias, when controlling for age, sex, case-control status and PRT discriminability. AA genotype of rs1042044 showed higher anhedonia phenotype based on SHAPS scores. However, analysis of PGC major depressive disorder data showed no association between rs1042044 and depression diagnosis.

CONCLUSION

Findings suggest a possible association of rs1042044 with anhedonia but no association with depression diagnosis.

GLP1R Single-Nucleotide Polymorphisms rs3765467 and rs10305492 Affect β Cell Insulin Secretory Capacity and Apoptosis Through GLP-1

The increased secretion of glucagon-like peptide-1 (GLP-1) after Roux-en-Y gastric bypass (RYGB) is regarded as the main reason for the improvement of blood glucose. However, the single-nucleotide polymorphisms (SNPs) of GLP-1 Receptor (GLP1R) impair receptor function, subsequently affecting β cell insulin secretion function, ultimately affecting the efficacy of RYGB. In this study, we revealed that two SNPs in GLP1R gene, rs3765467 and rs10305492, could significantly reduce the insulin secreted by β cells and the cyclic AMP concentration, whereas promote β cell apoptosis. Under high glucose exposure, rs3765467 and rs10305492 impaired β cell secretion of insulin and β cell viability in the same way; in other words, GLP1R rs3765467 and rs10305492 exert an effect on pancreatic β cell glucose-stimulated insulin secretion. Moreover, GLP-1 antagonist Exendin (9-39) further enhanced, whereas GLP-1 agonist Exendin-4 partially attenuated the effects of SNPs on the functions and apoptosis of β cells. In conclusion, the rs3765467 and rs10305492 SNPs in GLP1R show to exert a critical effect on regulating insulin secretory capacity of β cells and β cell mass. Through leading to the dysfunction and apoptosis of β cells, GLP1R rs3765467 and rs10305492 might also impair GLP-1 interaction with GLP1R, therefore attenuating the therapeutic effect of RYGB.

Heterogeneous Effects of Calorie Content and Nutritional Components Underlie Dietary Influence on Pancreatic Cancer Susceptibility

Pancreatic cancer is a rare but fatal form of cancer, the fourth highest in absolute mortality. Known risk factors include obesity, diet, and type 2 diabetes; however, the low incidence rate and interconnection of these factors confound the isolation of individual effects. Here, we use epidemiological analysis of prospective human cohorts and parallel tracking of pancreatic cancer in mice to dissect the effects of obesity, diet, and diabetes on pancreatic cancer. Through longitudinal monitoring and multi-omics analysis in mice, we found distinct effects of protein, sugar, and fat dietary components, with dietary sugars increasing Mad2l1 expression and tumor proliferation. Using epidemiological approaches in humans, we find that dietary sugars give a MAD2L1 genotype-dependent increased susceptibility to pancreatic cancer. The translation of these results to a clinical setting could aid in the identification of the at-risk population for screening and potentially harness dietary modification as a therapeutic measure.