Genome-wide association study in individuals of South Asian ancestry identifies six new type 2 diabetes susceptibility loci

Muscle Strength, Genetic Risk, and Type 2 Diabetes Among Individuals of South Asian Ancestry: A UK Biobank Study

OBJECTIVE

To examine the independent and combined associations of genetic risk and muscle strength with the risk of incident type 2 diabetes (T2D) and glycated hemoglobin (HbA1c) among individuals of South Asian ancestry.

DESIGN AND METHODS

This study included 5288 South Asian individuals (mean age 52.5 years; 52.3% men) from the UK Biobank study. Baseline assessments were conducted between 2006 and 2010. Muscle strength was assessed through a hand dynamometer and expressed relative to fat-free mass. Sex-and age-specific tertiles were used to classify muscle strength into three categories. Genetic risk of T2D was quantified using a weighted polygenic risk score calculated from 22 distinct South Asian-specific single nucleotide polymorphisms for T2D.

RESULTS

Compared to the bottom tertile of genetic risk for T2D, the highest had increased odds of incident T2D (odds ratio: 1.62; 95% confidence interval [CI]: 1.31-2.00) and HbA1c levels (β: 0.80; 95% CI 0.41-1.19). Compared to high muscle strength, low muscle strength was associated with 89% higher odds of incident T2D (odds ratio: 1.89; 95% CI 1.52-2.35) and higher HbA1c levels (β: 0.95; 95% CI 0.55-1.35), after adjustment for confounders and genetic susceptibility to T2D. Joint analyses revealed lower muscle strength was consistently associated with higher odds of incident T2D and HbA1c levels across all genetic risk strata.

CONCLUSION

Polygenic risk scores for T2D could have great prognostic value in preemptively identifying individuals of South Asian ancestry at high genetic risk of T2D. Regardless of T2D genetic risk, greater muscle strength is linked to lower T2D risk and HbA1c levels.

Genetic association studies using disease liabilities from deep neural networks

The case-control study is a widely used method for investigating the genetic underpinnings of binary traits. However, long-term, prospective cohort studies often grapple with absent or evolving health-related outcomes. Here, we propose two methods, liability and meta, for conducting genome-wide association studies (GWASs) that leverage disease liabilities calculated from deep patient phenotyping. Analyzing 38 common traits in ∼300,000 UK Biobank participants, we identified an increased number of loci in comparison to the number identified by the conventional case-control approach, and there were high replication rates in larger external GWASs. Further analyses confirmed the disease specificity of the genetic architecture; the meta method demonstrated higher robustness when phenotypes were imputed with low accuracy. Additionally, polygenic risk scores based on disease liabilities more effectively predicted newly diagnosed cases in the 2022 dataset, which were controls in the earlier 2019 dataset. Our findings demonstrate that integrating high-dimensional phenotypic data into deep neural networks enhances genetic association studies while capturing disease-relevant genetic architecture.

Cohort prevalence of young-onset type 2 diabetes in South Asia: A systematic review

BACKGROUND & AIM

The prevalence of young onset (≤30 years) type 2 diabetes (T2D) is increasing in South Asians, reflecting rise in childhood obesity. This systematic review analyses current data on thecohort prevalence of young onset T2D in South Asians.

METHODS

PubMed, Scopus,Science Direct,and Ebscohost were searched for articles published between 1990 and 2024, anda manual search identified additional articles. This study included case series, cross-sectional, retrospective cohort, or case reports.

RESULTS

Out of 5073 studies, 26 eligible studies were found including three case reports. Seventeen studies were from India, five werefrom other South Asian countries (Pakistan, Bangladesh, Nepal, Maldives), and nine were on migrant South Asians residing in different countries (UK,USA,Qatar, Canada). The cohort prevalence of young onset T2D in South Asians ranged from 0.1 % to 28.3 % (India 0.4 to 26.8 %, other SA countries 0.1 to 28.3 %, and migrant South Asians 4.1 to 18.1 %).

CONCLUSION

The burden of T2D among native South Asian children and young adults is higher than among migrant South Asians. This contrasts with traditional perceptions that T2D primarily affects older individuals and the South Asian diaspora i.e., those who have migrated from South Asia.

Excess of rare noncoding variants in several type 2 diabetes candidate genes among Asian Indian families

BACKGROUND

Type 2 diabetes (T2D) etiology is highly complex due to its multiple roots of origin. Polygenic risk scores (PRS) based on genome-wide association studies (GWAS) can partially explain T2D risk. Asian Indian people have up to six times higher risk of developing T2D than European people, and underlying causes of this disparity are unknown.

METHODS

We have performed targeted sequencing of ten T2D GWAS/candidate regions using endogamous Punjabi Sikh families and replication studies using unrelated Sikh people and families from three other Indian endogamous ethnic groups (EEGs).

RESULTS

We detect rare and ultra-rare variants (RVs) in KCNJ11-ABCC8 and HNF4A (MODY genes) cosegregated with late-onset T2D. We also identify RV enrichment in two new genes, SLC38A11 and ANPEP, associated with T2D. Gene-burden analysis reveals the highest RV burden contributed by HNF4A (p = 0.0003), followed by KCNJ11/ABCC8 (p = 0.0061) and SLC38A11 (p = 0.03). Some RVs detected in Sikh people are also found in Agarwals from Jaipur, both from Northern India, but were monomorphic in other two EEGs from South Indian people. Despite carrying a high burden of T2D and RVs, most families have a significantly lower burden of PRS. Functional studies show that an intronic regulatory variant (RV) in ABCC8 affects the binding of Pax4 and NF-kB transcription factors, influencing downstream gene regulation.

CONCLUSIONS

The high burden of T2D in these families may stem from the enrichment of noncoding RVs in a small number of major known genes (including MODY genes) with oligogenic inheritance alongside RVs from genes associated with polygenic susceptibility. These findings highlight the need to conduct deeper evaluations of families from non-European ancestries to identify potential novel therapeutics and implement preventative strategies.

Lessons Learned From Epidemiology of Type 2 Diabetes in South Asians: Kelly West Award Lecture 2024

South Asia has high prevalence rates of type 2 diabetes (T2D). Until the 1990s, the prevalence of T2D within South Asia was low but much higher in the South Asian diaspora living abroad. Today, high prevalence rates of T2D are reported among those living in South Asia. T2D in South Asians presents with unique clinical features described as the "South Asian phenotype" that include younger age at onset of diabetes than in White Europeans, much lower BMI, hyperinsulinemia and greater insulin resistance, rapid decline in β-cell function resulting in low insulin reserve, low muscle mass, and greater ectopic fat deposition, especially in the liver. Also, prevalence of impaired fasting glucose is higher among South Asians than prevalence of impaired glucose tolerance. Genetic predisposition combined with intrauterine fetal programming (low vitamin B12 intake and high folate intake) increases susceptibility to T2D, from birth. In later life, overnutrition, especially a high carbohydrate intake with refined grains of higher glycemic index, coupled with low physical activity likely triggers the T2D epidemic in South Asians. Additionally, there are emerging risk factors like air pollution. Preventing T2D in South Asians requires a multifactorial approach, including improvements in maternal and fetal nutrition with special reference to vitamin B12 and folate intake, decreasing refined carbohydrate and increasing protein and fiber intake in the diet, increasing physical activity, and control of air pollution. Lessons learned from epidemiology of T2D in South Asians could be useful to other developing countries that are in earlier stages of epidemiological transition.

Integrating Polygenic Risk Scores (PRS) for Personalized Diabetes Care: Advancing Clinical Practice with Tailored Pharmacological Approaches

The rising global prevalence of diabetes poses a serious threat to public health, national economies, and the healthcare system. Despite a high degree of disease heterogeneity and advancing techniques, there is still an unclear diagnosis of patients with diabetes compounded by the array of long-term microvascular and macrovascular complications associated with the disease. In addition to environmental variables, diabetes susceptibility is significantly influenced by genetic components. The risk stratification of genetically predisposed individuals may play an important role in disease diagnosis and management. Precision medicine methods are crucial to reducing this global burden by delivering a more personalised and patient-centric approach. Compared to the European population, genetic susceptibility variants of type 2 diabetes mellitus (T2DM) are still not fully understood in other major populations, including South Asians, Latinos, and people of African descent. Polygenic risk scores (PRS) can be used to identify individuals who are more susceptible to complex diseases such as diabetes. PRS is selective and effective in developing novel diagnostic interventions. This comprehensive predictive approach facilitates the understanding of distinct response profiles, resulting in the development of more effective management strategies. The targeted implementation of PRS is especially advantageous for people who fall into a higher-risk category for diabetes. Through early risk assessment and the creation of individualised diabetes treatment plans, the integration of PRS in clinical practice shows potential for reducing the prevalence of diabetes and its complications. Diabetes self-management depends significantly on patient empowerment, with behavioural monitoring emerging as a vital facilitator. The main aim of this review article is to formulate a more structured intervention strategy by advocating for increased awareness of the clinical utility of PRS and counseling among healthcare practitioners, patients, and individuals at risk of diabetes.

The link between the ANPEP gene and type 2 diabetes mellitus may be mediated by the disruption of glutathione metabolism and redox homeostasis

Aminopeptidase N (ANPEP), a membrane-associated ectoenzyme, has been identified as a susceptibility gene for type 2 diabetes (T2D) by genome-wide association and transcriptome studies; however, the mechanisms by which this gene contributes to disease pathogenesis remain unclear. The aim of this study was to determine the comprehensive contribution of ANPEP polymorphisms to T2D risk and annotate the underlying mechanisms. A total of 3206 unrelated individuals including 1579 T2D patients and 1627 controls were recruited for the study. Twenty-three common functional single nucleotide polymorphisms (SNP) of ANPEP were genotyped by the MassArray-4 system. Six polymorphisms, rs11073891, rs12898828, rs12148357, rs9920421, rs7111, and rs25653, were found to be associated with type 2 diabetes (Pperm ≤ 0.05). Common haplotype rs9920421G-rs4932143G-rs7111T was strongly associated with increased risk of T2D (Pperm = 5.9 × 10-12), whereas two rare haplotypes such as rs9920421G-rs4932143C-rs7111T (Pperm = 6.5 × 10-40) and rs12442778A-rs12898828A-rs6496608T-rs11073891C (Pperm = 1.0 × 10-7) possessed strong protection against disease. We identified 38 and 109 diplotypes associated with T2D risk in males and females, respectively (FDR ≤ 0.05). ANPEP polymorphisms showed associations with plasma levels of fasting blood glucose, aspartate aminotransferase, total protein and glutathione (P < 0.05), and several haplotypes were strongly associated with the levels of reactive oxygen species and uric acid (P < 0.0001). A deep literature analysis has facilitated the formulation of a hypothesis proposing that increased plasma levels of ANPEP as well as liver enzymes such as aspartate aminotransferase, alanine aminotransferase and gammaglutamyltransferase serve as an adaptive response directed towards the restoration of glutathione deficiency in diabetics by stimulating the production of amino acid precursors for glutathione biosynthesis.

Polymorphisms of ANPEP Gene Are Associated with Microvascular Complications of Type 2 Diabetes

We studied the association of polymorphisms in the aminopeptidase N gene (ANPEP) with the development of diabetic retinopathy and nephropathy in patients with type 2 diabetes mellitus (T2DM). DNA samples from T2DM patients (n=1425) were genotyped for 23 single nucleotide polymorphisms (SNPs) using the MassARRAY system. Associations of SNP rs13380049 of the ANPEP gene with a lower risk of diabetic retinopathy (OR=0.54, 95%CI 0.36-0.82, p=0.0032) and nephropathy (OR=0.66, 95%CI 0.44-0.99, p=0.048) were found in T2DM patients. In addition, SNP rs25653 was associated with retinopathy, and polymorphisms rs6496608, rs72756574, rs9920421, and rs4932143 were associated with diabetic nephropathy. The study demonstrated the contribution of ANPEP gene polymorphisms in the determination of microvascular complications in T2DM patients.

Genetic studies of type 2 diabetes, and microvascular complications of diabetes

Genome-wide association studies (GWAS) have significantly advanced the identification of genetic susceptibility variants associated with complex diseases. As of 2023, approximately 800 variants predisposing individuals to the risk of type 2 diabetes (T2D) were identified through GWAS, and the majority of studies were predominantly conducted in European populations. Despite the shared nature of the majority of genetic susceptibility loci across diverse ethnic populations, GWAS in non-European populations, including Japanese and East Asian populations, have revealed population-specific T2D loci. Currently, polygenic risk scores (PRSs), encompassing millions of associated variants, can identify individuals with a higher T2D risk than the general population. However, GWAS focusing on microvascular complications of diabetes have identified a limited number of disease-susceptibility loci. Ongoing efforts are crucial to enhance the applicability of PRS for all ethnic groups and unravel the genetic architecture of microvascular complications of diabetes.

Polygenic Risk Score Assessment for Coronary Artery Disease in Asian Indians

We evaluated the performance of various polygenic risk score (PRS) models derived from European (EU), South Asian (SA), and Punjabi Asian Indians (AI) studies on 13,974 subjects from AI ancestry. While all models successfully predicted Coronary artery disease (CAD) risk, the AI, SA, and EU + AI were superior predictors and more transportable than the EU model; the predictive performance in training and test sets was 18% and 22% higher in AI and EU + AI models, respectively than in EU. Comparing individuals with extreme PRS quartiles, the AI and EU + AI captured individuals with high CAD risk showed 2.6 to 4.6 times higher efficiency than the EU. Interestingly, including the clinical risk score did not significantly change the performance of any genetic model. The enrichment of diversity variants in EU PRS improves risk prediction and transportability. Establishing population-specific normative and risk factors and inclusion into genetic models would refine the risk stratification and improve the clinical utility of CAD PRS.

Podocyte-specific KLF6 primes proximal tubule CaMK1D signaling to attenuate diabetic kidney disease

Diabetic kidney disease (DKD) is the main cause of chronic kidney disease worldwide. While injury to the podocytes, visceral epithelial cells that comprise the glomerular filtration barrier, drives albuminuria, proximal tubule (PT) dysfunction is the critical mediator of DKD progression. Here, we report that the podocyte-specific induction of human KLF6, a zinc-finger binding transcription factor, attenuates podocyte loss, PT dysfunction, and eventual interstitial fibrosis in a male murine model of DKD. Utilizing combination of snRNA-seq, snATAC-seq, and tandem mass spectrometry, we demonstrate that podocyte-specific KLF6 triggers the release of secretory ApoJ to activate calcium/calmodulin dependent protein kinase 1D (CaMK1D) signaling in neighboring PT cells. CaMK1D is enriched in the first segment of the PT, proximal to the podocytes, and is critical to attenuating mitochondrial fission and restoring mitochondrial function under diabetic conditions. Targeting podocyte-PT signaling by enhancing ApoJ-CaMK1D might be a key therapeutic strategy in attenuating the progression of DKD.

Gene therapy for polygenic or complex diseases

Gene therapy utilizes nucleic acid drugs to treat diseases, encompassing gene supplementation, gene replacement, gene silencing, and gene editing. It represents a distinct therapeutic approach from traditional medications and introduces novel strategies for genetic disorders. Over the past two decades, significant advancements have been made in the field of gene therapy, leading to the approval of various gene therapy drugs. Gene therapy was initially employed for treating genetic diseases and cancers, particularly monogenic conditions classified as orphan diseases due to their low prevalence rates; however, polygenic or complex diseases exhibit higher incidence rates within populations. Extensive research on the etiology of polygenic diseases has unveiled new therapeutic targets that offer fresh opportunities for their treatment. Building upon the progress achieved in gene therapy for monogenic diseases and cancers, extending its application to polygenic or complex diseases would enable targeting a broader range of patient populations. This review aims to discuss the strategies of gene therapy, methods of gene editing (mainly CRISPR-CAS9), and carriers utilized in gene therapy, and highlight the applications of gene therapy in polygenic or complex diseases focused on applications that have either entered clinical stages or are currently undergoing clinical trials.

Integrating Mendelian randomization and single-cell RNA sequencing to identify therapeutic targets of baicalin for type 2 diabetes mellitus

Background

Alternative and complementary therapies play an imperative role in the clinical management of Type 2 diabetes mellitus (T2DM), and exploring and utilizing natural products from a genetic perspective may yield novel insights into the mechanisms and interventions of the disorder.

Methods

To identify the therapeutic target of baicalin for T2DM, we conducted a Mendelian randomization study. Druggable targets of baicalin were obtained by integrating multiple databases, and target-associated cis-expression quantitative trait loci (cis-eQTL) originated from the eQTLGen consortium. Summary statistics for T2DM were derived from two independent genome-wide association studies available through the DIAGRAM Consortium (74,124 cases vs. 824,006 controls) and the FinnGen R9 repository (9,978 cases vs. 12,348 controls). Network construction and enrichment analysis were applied to the therapeutic targets of baicalin. Colocalization analysis was utilized to assess the potential for the therapeutic targets and T2DM to share causative genetic variations. Molecular docking was performed to validate the potency of baicalin. Single-cell RNA sequencing was employed to seek evidence of therapeutic targets' involvement in islet function.

Results

Eight baicalin-related targets proved to be significant in the discovery and validation cohorts. Genetic evidence indicated the expression of ANPEP, BECN1, HNF1A, and ST6GAL1 increased the risk of T2DM, and the expression of PGF, RXRA, SREBF1, and USP7 decreased the risk of T2DM. In particular, SREBF1 has significant interaction properties with other therapeutic targets and is supported by strong colocalization. Baicalin had favorable combination activity with eight therapeutic targets. The expression patterns of the therapeutic targets were characterized in cellular clusters of pancreatic tissues that exhibited a pseudo-temporal dependence on islet cell formation and development.

Conclusion

This study identified eight potential targets of baicalin for treating T2DM from a genetic perspective, contributing an innovative analytical framework for the development of natural products. We have offered fresh insights into the connections between therapeutic targets and islet cells. Further, fundamental experiments and clinical research are warranted to delve deeper into the molecular mechanisms of T2DM.

Grb7 Ablation in Mice Improved Glycemic Control, Enhanced Insulin Signaling, and Increased Abdominal fat Mass in Females

OBJECTIVES

Growth factor receptor bound protein 7 (GRB7) is a multidomain signaling adaptor. Members of the Grb7/10/14 family, specifically Gbrb10/14, have important roles in metabolism. We ablated the Grb7 gene in mice to examine its metabolic function.

METHODS

Global ablation of Grb7 in FVB/NJ mice was generated. Growth, organ weight, food intake, and glucose homeostasis were measured. Insulin signaling was examined by Western blotting. Fat and lean body mass was measured by nuclear magnetic resonance, and body composition after fasting or high-fat diet was assessed. Energy expenditure was measured by indirect calorimetry. Expression of adiposity and lipid metabolism genes was measured by quantitative PCR.

RESULTS

Grb7-null mice were viable, fertile, and without obvious phenotype. Grb7 ablation improved glycemic control and displayed sensitization to insulin signaling in the liver. Grb7-null females but not males had increased gonadal white adipose tissue mass. Following a 12-week high-fat diet, Grb7-null female mice gained fat body mass and developed relative insulin resistance. With fasting, there was less decrease in fat body mass in Grb7-null female mice. Female mice with Grb7 ablation had increased baseline food intake, less energy expenditure, and displayed a decrease in the expression of lipolysis and adipose browning genes in gonadal white adipose tissue by transcript and protein analysis.

CONCLUSION

Our study suggests that Grb7 is a negative regulator of glycemic control. Our results reveal a role for Grb7 in female mice in the regulation of the visceral adipose tissue mass, a powerful predictor of metabolic dysfunction in obesity.

Diabetes mellitus: Is Pakistan the epicenter of the next pandemic?

Estimated age-adjusted comparative diabetes prevalence in adults (20-79 years) in Pakistan from the year 2011 to 2021.

South Asia: The Missing Diverse in Diversity

South Asia, making up around 25% of the world's population, encompasses a wide range of individuals with tremendous genetic and environmental diversity. This region, which spans eight countries, is home to over 4500 anthropologically defined groups that speak numerous languages and have an array of religious beliefs and cultures, making it one of the most diverse places in the world. Much of the region's rich genetic diversity and structure is the result of a complex combination of population history, migration patterns, and endogamous practices. Despite the overwhelming size and diversity, South Asians have often been underrepresented in genetic research, making up less than 2% of the participants in genetic studies. This has led to a lack of population specific understanding of genetic disease risks. We aim to raise awareness about underlying genetic diversity in this ancestry group, call attention to the lack of representation of the group, and to highlight strategies for future studies in South Asians.

Computational Screening and Experimental Validation of Inhibitor Targeting the Complex Formation of Grb14 and Insulin Receptor

The development of drugs targeting gene products associated with insulin resistance holds the potential to enhance our understanding of type 2 diabetes mellitus (T2DM). The virtual screening, based on a three-dimensional (3D) protein structure, is a potential technique to accelerate the development of molecular target drugs. Among the targets implicated in insulin resistance, the genetic characterization and protein function of Grb14 have been clarified without contradiction. The Grb14 gene displays significant variations in T2DM, and its gene product is known to inhibit the function of the insulin receptor (IR) by directly binding to the tyrosine kinase domain. In the present study, a virtual screening, based on a 3D structure of the IR tyrosine kinase domain (IRβ) in complex with part of Grb14, was conducted to find compounds that can disrupt the complex formation between Grb14 and IRβ. First, ten compounds were selected from 154,118 compounds via hierarchical in silico structure-based drug screening, composed of grid docking-based and genetic algorithm-based programs. The experimental validations suggested that the one compound can affect the blood glucose level. The molecular dynamics simulations and co-immunoprecipitation analysis showed that the compound did not completely suppress the protein-protein interaction between Grb14 and IR, though competitively bound to IR with the tyrosine kinase pseudosubstrate region in Grb14.

Assessing the prediction of type 2 diabetes risk using polygenic and clinical risk scores in South Asian study populations

BACKGROUND

Genome-wide polygenic risk scores (PRS) have shown high specificity and sensitivity in predicting type 2 diabetes (T2D) risk in Europeans. However, the PRS-driven information and its clinical significance in non-Europeans are underrepresented. We examined the predictive efficacy and transferability of PRS models using variant information derived from genome-wide studies of Asian Indians (AIs) (PRSAI) and Europeans (PRSEU) using 13,974 AI individuals.

METHODS

Weighted PRS models were constructed and analyzed on 4602 individuals from the Asian Indian Diabetes Heart Study/Sikh Diabetes Study (AIDHS/SDS) as discovery/training and test/validation datasets. The results were further replicated in 9372 South Asian individuals from UK Biobank (UKBB). We also assessed the performance of each PRS model by combining data of the clinical risk score (CRS).

RESULTS

Both genetic models (PRSAI and PRSEU) successfully predicted the T2D risk. However, the PRSAI revealed 13.2% odds ratio (OR) 1.80 [95% confidence interval (CI) 1.63-1.97; p = 1.6 × 10-152] and 12.2% OR 1.38 (95% CI 1.30-1.46; p = 7.1 × 10-237) superior performance in AIDHS/SDS and UKBB validation sets, respectively. Comparing individuals of extreme PRS (ninth decile) with the average PRS (fifth decile), PRSAI showed about two-fold OR 20.73 (95% CI 10.27-41.83; p = 2.7 × 10-17) and 1.4-fold OR 3.19 (95% CI 2.51-4.06; p = 4.8 × 10-21) higher predictability to identify subgroups with higher genetic risk than the PRSEU. Combining PRS and CRS improved the area under the curve from 0.74 to 0.79 in PRSAI and 0.72 to 0.75 in PRSEU.

CONCLUSION

Our data suggest the need for extending genetic and clinical studies in varied ethnic groups to exploit the full clinical potential of PRS as a risk prediction tool in diverse study populations.

In silico identification and functional prediction of differentially expressed genes in South Asian populations associated with type 2 diabetes

Type 2 diabetes (T2D) is one of the major metabolic disorders in humans caused by hyperglycemia and insulin resistance syndrome. Although significant genetic effects on T2D pathogenesis are experimentally proved, the molecular mechanism of T2D in South Asian Populations (SAPs) is still limited. Hence, the current research analyzed two Gene Expression Omnibus (GEO) and 17 Genome-Wide Association Studies (GWAS) datasets associated with T2D in SAP to identify DEGs (differentially expressed genes). The identified DEGs were further analyzed to explore the molecular mechanism of T2D pathogenesis following a series of bioinformatics approaches. Following PPI (Protein-Protein Interaction), 867 potential DEGs and nine hub genes were identified that might play significant roles in T2D pathogenesis. Interestingly, CTNNB1 and RUNX2 hub genes were found to be unique for T2D pathogenesis in SAPs. Then, the GO (Gene Ontology) showed the potential biological, molecular, and cellular functions of the DEGs. The target genes also interacted with different pathways of T2D pathogenesis. In fact, 118 genes (including HNF1A and TCF7L2 hub genes) were directly associated with T2D pathogenesis. Indeed, eight key miRNAs among 2582 significantly interacted with the target genes. Even 64 genes were downregulated by 367 FDA-approved drugs. Interestingly, 11 genes showed a wide range (9-43) of drug specificity. Hence, the identified DEGs may guide to elucidate the molecular mechanism of T2D pathogenesis in SAPs. Therefore, integrating the research findings of the potential roles of DEGs and candidate drug-mediated downregulation of marker genes, future drugs or treatments could be developed to treat T2D in SAPs.

Exploration of the Shared Hub Genes and Biological Mechanism in Osteoporosis and Type 2 Diabetes Mellitus based on Machine Learning

A substantial amount of evidence suggests a close relationship between osteoporosis (OP) and Type 2 Diabetes Mellitus (T2DM), but the mechanisms involved remain unknown. Therefore, we conducted this study with the aim of screening for hub genes common to both diseases and conducting a preliminary exploration of common regulatory mechanisms. In the present study, we first screened genes significantly associated with OP and T2DM by the univariate logistic regression algorithm. And then, based on cross-analysis and random forest algorithm, we obtained three hub genes (ACAA2, GATAD2A, and VPS35) and validated the critical roles and predictive performance of the three genes in both diseases by differential expression analysis, receiver operating characteristic (ROC) curves, and genome wide association study (GWAS) analysis. Finally, based on gene set enrichment analysis (GSEA) and the construction of the miRNA-mRNA regulatory network, we conducted a preliminary exploration of the co-regulatory mechanisms of three hub genes in two diseases. In conclusion, this study provides promising biomarkers for predicting and treating both diseases and offers novel directions for exploring the common regulatory mechanisms of both diseases.

Genetic associations of TMEM154, PRC1 and ZFAND6 loci with type 2 diabetes in an endogamous business community of North India

BACKGROUND

More than 250 loci have been identified by genome-wide scans for type 2 diabetes in different populations. South Asians have a very different manifestation of the diseases and hence role of these loci need to be investigated among Indians with huge burden of cardio-metabolic disorders. Thus the present study aims to validate the recently identified GWAS loci in an endogamous caste population in North India.

METHODS

219 T2D cases and 184 controls were recruited from hospitals and genotyped for 15 GWAS loci of T2D. Regression models adjusted for covariates were run to examine the association for T2D and fasting glucose levels.

RESULTS

We validated three variants for T2D namely, rs11634397 at ZFAND6 (OR = 3.05, 95%CI = 1.02-9.19, p = 0.047) and rs8042680 at PRC1 (OR = 3.67, 95%CI = 1.13-11.93, p = 0.031) showing higher risk and rs6813195 at TMEM154 (OR = 0.28, 95%CI = 0.09-0.90, p = 0.033) showing protective effect. The combined risk of 9 directionally consistent variants was also found to be significantly associated with T2D (OR = 1.91, 95%CI = 1.18-3.08, p = 0.008). One variant rs10842994 at KLHDC5 was validated for 9.15mg/dl decreased fasting glucose levels (SE = -17.25-1.05, p = 0.027).

CONCLUSION

We confirm the role of ZFAND6, PRC1 and TMEM154 in the pathophysiology of type 2 diabetes among Indians. More efforts are needed with larger sample sizes to validate the diabetes GWAS loci in South Asian populations for wider applicability.

Utility of genetic risk scores in type 1 diabetes

Iterative advances in understanding of the genetics of type 1 diabetes have identified >70 genetic regions associated with risk of the disease, including strong associations across the HLA class II region that account for >50% of heritability. The increased availability of genetic data combined with the decreased costs of generating these data, have facilitated the development of polygenic scores that aggregate risk variants from associated loci into a single number: either a genetic risk score (GRS) or a polygenic risk score (PRS). PRSs incorporate the risk of many possibly correlated variants from across the genome, even if they do not reach genome-wide significance, whereas GRSs estimate the cumulative contribution of a smaller subset of genetic variants that reach genome-wide significance. Type 1 diabetes GRSs have utility in diabetes classification, aiding discrimination between type 1 diabetes, type 2 diabetes and MODY. Type 1 diabetes GRSs are also being used in newborn screening studies to identify infants at risk of future presentation of the disease. Most early studies of type 1 diabetes genetics have been conducted in European ancestry populations, but, to develop accurate GRSs across diverse ancestries, large case-control cohorts from non-European populations are still needed. The current barriers to GRS implementation within healthcare are mainly related to a lack of guidance and knowledge on integration with other biomarkers and clinical variables. Once these limitations are addressed, there is huge potential for 'test and treat' approaches to be used to tailor care for individuals with type 1 diabetes.

Differentially Expressed Genes Regulating Glutathione Metabolism, Protein-Folding, and Unfolded Protein Response in Pancreatic β-Cells in Type 2 Diabetes Mellitus

Impaired redox homeostasis in the endoplasmic reticulum (ER) may contribute to proinsulin misfolding and thus to activate the unfolded protein response (UPR) and apoptotic pathways, culminating in pancreatic β-cell loss and type 2 diabetes (T2D). The present study was designed to identify differentially expressed genes (DEGs) encoding enzymes for glutathione metabolism and their impact on the expression levels of genes regulating protein folding and UPR in β-cells of T2D patients. The GEO transcriptome datasets of β-cells of diabetics and non-diabetics, GSE20966 and GSE81608, were analyzed for 142 genes of interest using limma and GREIN software, respectively. Diabetic β-cells showed dataset-specific patterns of DEGs (FDR ≤ 0.05) implicated in the regulation of glutathione metabolism (ANPEP, PGD, IDH2, and CTH), protein-folding (HSP90AB1, HSP90AA1, HSPA1B, HSPA8, BAG3, NDC1, NUP160, RLN1, and RPS19BP1), and unfolded protein response (CREB3L4, ERP27, and BID). The GCLC gene, encoding the catalytic subunit of glutamate-cysteine ligase, the first rate-limiting enzyme of glutathione biosynthesis, was moderately down-regulated in diabetic β-cells from both datasets (p ≤ 0.05). Regression analysis established that genes involved in the de novo synthesis of glutathione, GCLC, GCLM, and GSS affect the expression levels of genes encoding molecular chaperones and those involved in the UPR pathway. This study showed for the first time that diabetic β-cells exhibit alterations in the expression of genes regulating glutathione metabolism, protein-folding, and UPR and provided evidence for the molecular crosstalk between impaired redox homeostasis and abnormal protein folding, underlying ER stress in type 2 diabetes.

Receptor Recycling by Retromer

The highly conserved retromer complex controls the fate of hundreds of receptors that pass through the endolysosomal system and is a central regulatory node for diverse metabolic programs. More than 20 years ago, retromer was discovered as an essential regulator of endosome-to-Golgi transport in yeast; since then, significant progress has been made to characterize how metazoan retromer components assemble to enable its engagement with endosomal membranes, where it sorts cargo receptors from endosomes to the trans-Golgi network or plasma membrane through recognition of sorting motifs in their cytoplasmic tails. In this review, we examine retromer regulation by exploring its assembled structure with an emphasis on how a range of adaptor proteins shape the process of receptor trafficking. Specifically, we focus on how retromer is recruited to endosomes, selects cargoes, and generates tubulovesicular carriers that deliver cargoes to target membranes. We also examine how cells adapt to distinct metabolic states by coordinating retromer expression and function. We contrast similarities and differences between retromer and its related complexes: retriever and commander/CCC, as well as their interplay in receptor trafficking. We elucidate how loss of retromer regulation is central to the pathology of various neurogenerative and metabolic diseases, as well as microbial infections, and highlight both opportunities and cautions for therapeutics that target retromer. Finally, with a focus on understanding the mechanisms that govern retromer regulation, we outline new directions for the field moving forward.

Evaluating significance of European-associated index SNPs in the East Asian population for 31 complex phenotypes

BACKGROUND

Genome-wide association studies (GWASs) have identified many single-nucleotide polymorphisms (SNPs) associated with complex phenotypes in the European (EUR) population; however, the extent to which EUR-associated SNPs can be generalized to other populations such as East Asian (EAS) is not clear.

RESULTS

By leveraging summary statistics of 31 phenotypes in the EUR and EAS populations, we first evaluated the difference in heritability between the two populations and calculated the trans-ethnic genetic correlation. We observed the heritability estimates of some phenotypes varied substantially across populations and 53.3% of trans-ethnic genetic correlations were significantly smaller than one. Next, we examined whether EUR-associated SNPs of these phenotypes could be identified in EAS using the trans-ethnic false discovery rate method while accounting for winner's curse for SNP effect in EUR and difference of sample sizes in EAS. We found on average 54.5% of EUR-associated SNPs were also significant in EAS. Furthermore, we discovered non-significant SNPs had higher effect heterogeneity, and significant SNPs showed more consistent linkage disequilibrium and allele frequency patterns between the two populations. We also demonstrated non-significant SNPs were more likely to undergo natural selection.

CONCLUSIONS

Our study revealed the extent to which EUR-associated SNPs could be significant in the EAS population and offered deep insights into the similarity and diversity of genetic architectures underlying phenotypes in distinct ancestral groups.

CaMK1D signalling in AgRP neurons promotes ghrelin-mediated food intake

Hypothalamic AgRP/NPY neurons are key players in the control of feeding behaviour. Ghrelin, a major orexigenic hormone, activates AgRP/NPY neurons to stimulate food intake and adiposity. However, cell-autonomous ghrelin-dependent signalling mechanisms in AgRP/NPY neurons remain poorly defined. Here we show that calcium/calmodulin-dependent protein kinase ID (CaMK1D), a genetic hot spot in type 2 diabetes, is activated upon ghrelin stimulation and acts in AgRP/NPY neurons to mediate ghrelin-dependent food intake. Global Camk1d-knockout male mice are resistant to ghrelin, gain less body weight and are protected against high-fat-diet-induced obesity. Deletion of Camk1d in AgRP/NPY, but not in POMC, neurons is sufficient to recapitulate above phenotypes. In response to ghrelin, lack of CaMK1D attenuates phosphorylation of CREB and CREB-dependent expression of the orexigenic neuropeptides AgRP/NPY in fibre projections to the paraventricular nucleus (PVN). Hence, CaMK1D links ghrelin action to transcriptional control of orexigenic neuropeptide availability in AgRP neurons.

Transcription factor HNF4α2 promotes osteogenesis and prevents bone abnormalities in mice with renal osteodystrophy

Renal osteodystrophy (ROD) is a disorder of bone metabolism that affects virtually all patients with chronic kidney disease (CKD) and is associated with adverse clinical outcomes including fractures, cardiovascular events, and death. In this study, we showed that hepatocyte nuclear factor 4α (HNF4α), a transcription factor mostly expressed in the liver, is also expressed in bone, and that osseous HNF4α expression was dramatically reduced in patients and mice with ROD. Osteoblast-specific deletion of Hnf4α resulted in impaired osteogenesis in cells and mice. Using multi-omics analyses of bones and cells lacking or overexpressing Hnf4α1 and Hnf4α2, we showed that HNF4α2 is the main osseous Hnf4α isoform that regulates osteogenesis, cell metabolism, and cell death. As a result, osteoblast-specific overexpression of Hnf4α2 prevented bone loss in mice with CKD. Our results showed that HNF4α2 is a transcriptional regulator of osteogenesis, implicated in the development of ROD.

A non-coding variant linked to metabolic obesity with normal weight affects actin remodelling in subcutaneous adipocytes

Recent large-scale genomic association studies found evidence for a genetic link between increased risk of type 2 diabetes and decreased risk for adiposity-related traits, reminiscent of metabolically obese normal weight (MONW) association signatures. However, the target genes and cellular mechanisms driving such MONW associations remain to be identified. Here, we systematically identify the cellular programmes of one of the top-scoring MONW risk loci, the 2q24.3 risk locus, in subcutaneous adipocytes. We identify a causal genetic variant, rs6712203, an intronic single-nucleotide polymorphism in the COBLL1 gene, which changes the conserved transcription factor motif of POU domain, class 2, transcription factor 2, and leads to differential COBLL1 gene expression by altering the enhancer activity at the locus in subcutaneous adipocytes. We then establish the cellular programme under the genetic control of the 2q24.3 MONW risk locus and the effector gene COBLL1, which is characterized by impaired actin cytoskeleton remodelling in differentiating subcutaneous adipocytes and subsequent failure of these cells to accumulate lipids and develop into metabolically active and insulin-sensitive adipocytes. Finally, we show that perturbations of the effector gene Cobll1 in a mouse model result in organismal phenotypes matching the MONW association signature, including decreased subcutaneous body fat mass and body weight along with impaired glucose tolerance. Taken together, our results provide a mechanistic link between the genetic risk for insulin resistance and low adiposity, providing a potential therapeutic hypothesis and a framework for future identification of causal relationships between genome associations and cellular programmes in other disorders.

Progress in genetics of type 2 diabetes and diabetic complications

Type 2 diabetes results from a complex interaction between genetic and environmental factors. Precision medicine for type 2 diabetes using genetic data is expected to predict the risk of developing diabetes and complications and to predict the effects of medications and life-style intervention more accurately for individuals. Genome-wide association studies (GWAS) have been conducted in European and Asian populations and new genetic loci have been identified that modulate the risk of developing type 2 diabetes. Novel loci were discovered by GWAS in diabetic complications with increasing sample sizes. Large-scale genome-wide association analysis and polygenic risk scores using biobank information is making it possible to predict the development of type 2 diabetes. In the ADVANCE clinical trial of type 2 diabetes, a multi-polygenic risk score was useful to predict diabetic complications and their response to treatment. Proteomics and metabolomics studies have been conducted and have revealed the associations between type 2 diabetes and inflammatory signals and amino acid synthesis. Using multi-omics analysis, comprehensive molecular mechanisms have been elucidated to guide the development of targeted therapy for type 2 diabetes and diabetic complications.

Genetic Variants of HNF4A, WFS1, DUSP9, FTO, and ZFAND6 Genes Are Associated with Prediabetes Susceptibility and Inflammatory Markers in the Saudi Arabian Population

Prediabetes is a reversible, intermediate stage of type 2 diabetes mellitus (T2DM). Lifestyle changes that include healthy diet and exercise can substantially reduce progression to T2DM. The present study explored the association of 37 T2DM- and obesity-linked single nucleotide polymorphisms (SNPs) with prediabetes risk in a homogenous Saudi Arabian population. A total of 1129 Saudi adults [332 with prediabetes (29%) and 797 normoglycemic controls] were randomly selected and genotyped using the KASPar SNP genotyping method. Anthropometric and various serological parameters were measured following standard procedures. Heterozygous GA of HNF4A-rs4812829 (0.64; 95% CI 0.47–0.86; p < 0.01), heterozygous TC of WFS1-rs1801214 (0.60; 95% confidence interval (CI) 0.44–0.80; p < 0.01), heterozygous GA of DUSP9-rs5945326 (0.60; 95% CI 0.39–0.92; p = 0.01), heterozygous GA of ZFAND6-rs11634397 (0.75; 95% CI 0.56–1.01; p = 0.05), and homozygous AA of FTO-rs11642841 (1.50; 95% CI 0.8–1.45; p = 0.03) were significantly associated with prediabetes, independent of age and body mass index (BMI). Additionally, C-reactive protein (CRP) levels in rs11634397 (AA) with a median of 5389.0 (2767.4–7412.8) were significantly higher than in the heterozygous GA genotype with a median of 1736.3 (1024.4–4452.0) (p < 0.01). In conclusion, only five of the 37 genetic variants previously linked to T2DM and obesity in the Saudi Arabian population [HNF4A-rs4812829, WFS1-rs1801214, DUSP9-rs5945326, ZFAND6-rs11634397, FTO-rs11642841] were associated with prediabetes susceptibility. Prospective studies are needed to confirm the potential clinical value of the studied genetic variants of interest.

Organ and cell-specific biomarkers of Long-COVID identified with targeted proteomics and machine learning

BACKGROUND

Survivors of acute COVID-19 often suffer prolonged, diffuse symptoms post-infection, referred to as "Long-COVID". A lack of Long-COVID biomarkers and pathophysiological mechanisms limits effective diagnosis, treatment and disease surveillance. We performed targeted proteomics and machine learning analyses to identify novel blood biomarkers of Long-COVID.

METHODS

A case-control study comparing the expression of 2925 unique blood proteins in Long-COVID outpatients versus COVID-19 inpatients and healthy control subjects. Targeted proteomics was accomplished with proximity extension assays, and machine learning was used to identify the most important proteins for identifying Long-COVID patients. Organ system and cell type expression patterns were identified with Natural Language Processing (NLP) of the UniProt Knowledgebase.

RESULTS

Machine learning analysis identified 119 relevant proteins for differentiating Long-COVID outpatients (Bonferonni corrected P < 0.01). Protein combinations were narrowed down to two optimal models, with nine and five proteins each, and with both having excellent sensitivity and specificity for Long-COVID status (AUC = 1.00, F1 = 1.00). NLP expression analysis highlighted the diffuse organ system involvement in Long-COVID, as well as the involved cell types, including leukocytes and platelets, as key components associated with Long-COVID.

CONCLUSIONS

Proteomic analysis of plasma from Long-COVID patients identified 119 highly relevant proteins and two optimal models with nine and five proteins, respectively. The identified proteins reflected widespread organ and cell type expression. Optimal protein models, as well as individual proteins, hold the potential for accurate diagnosis of Long-COVID and targeted therapeutics.

Epigenetics in Obesity and Diabetes Mellitus: New Insights

A long-term complication of obesity is the development of type 2 diabetes (T2D). Patients with T2D have been described as having epigenetic modifications. Epigenetics is the post-transcriptional modification of DNA or associated factors containing genetic information. These environmentally-influenced modifications, maintained during cell division, cause stable changes in gene expression. Epigenetic modifications of T2D are DNA methylation, acetylation, ubiquitylation, SUMOylation, and phosphorylation at the lysine residue at the amino terminus of histones, affecting DNA, histones, and non-coding RNA. DNA methylation has been shown in pancreatic islets, adipose tissue, skeletal muscle, and the liver. Furthermore, epigenetic changes have been observed in chronic complications of T2D, such as diabetic nephropathy, diabetic retinopathy, and diabetic neuropathy. Recently, a new drug has been developed which acts on bromodomains and extraterminal (BET) domain proteins, which operate like epigenetic readers and communicate with chromatin to make DNA accessible for transcription by inhibiting them. This drug (apabetalone) is being studied to prevent major adverse cardiovascular events in people with T2D, low HDL cholesterol, chronic kidney failure, and recent coronary events. This review aims to describe the relationship between obesity, long-term complications such as T2D, and epigenetic modifications and their possible treatments.

Network reconstruction for trans acting genetic loci using multi-omics data and prior information

BACKGROUND

Molecular measurements of the genome, the transcriptome, and the epigenome, often termed multi-omics data, provide an in-depth view on biological systems and their integration is crucial for gaining insights in complex regulatory processes. These data can be used to explain disease related genetic variants by linking them to intermediate molecular traits (quantitative trait loci, QTL). Molecular networks regulating cellular processes leave footprints in QTL results as so-called trans-QTL hotspots. Reconstructing these networks is a complex endeavor and use of biological prior information can improve network inference. However, previous efforts were limited in the types of priors used or have only been applied to model systems. In this study, we reconstruct the regulatory networks underlying trans-QTL hotspots using human cohort data and data-driven prior information.

METHODS

We devised a new strategy to integrate QTL with human population scale multi-omics data. State-of-the art network inference methods including BDgraph and glasso were applied to these data. Comprehensive prior information to guide network inference was manually curated from large-scale biological databases. The inference approach was extensively benchmarked using simulated data and cross-cohort replication analyses. Best performing methods were subsequently applied to real-world human cohort data.

RESULTS

Our benchmarks showed that prior-based strategies outperform methods without prior information in simulated data and show better replication across datasets. Application of our approach to human cohort data highlighted two novel regulatory networks related to schizophrenia and lean body mass for which we generated novel functional hypotheses.

CONCLUSIONS

We demonstrate that existing biological knowledge can improve the integrative analysis of networks underlying trans associations and generate novel hypotheses about regulatory mechanisms.

Evaluation of Personalized Skincare Through in-silico Gene Interactive Networks and Cellular Responses to UVR and Oxidative Stress

Purpose

Personalized approaches in dermatology are designed to match the specific requirements based on the individual genetic makeup. One major factor accounting for the differences in skin phenotypes is single nucleotide polymorphism (SNP) within several genes with diverse roles that extend beyond skin tone and pigmentation. Therefore, the cellular sensitivities to the environmental stress and damage linked to extrinsic aging could also underlie the individual characteristics of the skin and dictate the unique skin care requirements. This study aimed to identify the likely biomarkers and molecular signatures expressed in skin cells of different ethnic backgrounds, which could aid further the design of personalized skin products based on specific demands.

Methods

Using data mining and in-silico modeling, the association of SNP-affected genes with three major skin types of European, Asian and African origin was analyzed and compared within the structure-function gene interaction networks. Cultured dermal fibroblasts were subsequently subjected to ultraviolet radiation and oxidative stress and analyzed for DNA damage and senescent markers. The protective applications of two cosmetic ingredients, Resveratrol and Quercetin, were validated in both cellular and in-silico models.

Results

Each skin type was characterized by the presence of SNPs in the genes controlling facultative and constitutive pigmentation, which could also underlie the major differences in responses to photodamage, such as oxidative stress, inflammation, and barrier homeostasis. Skin-type-specific dermal fibroblasts cultured in-vitro demonstrated distinctive sensitivities to ultraviolet radiation and oxidative stress, which could be modulated further by the bioactive compounds with the predicted capacities to interact with some of the genes in the in-silico models.

Conclusion

Evaluation of the SNP-affected gene networks and likely sensitivities of skin cells, defined as low threshold levels to extrinsic stress factors, can provide a valuable tool for the design and formulation of personalized skin products that match more accurately diverse ethnic backgrounds.

Unique attributes of obesity in India: A narrative review

Obesity has become a burgeoning epidemic in India, even though the country is still dealing with undernutrition. As a significant determinant of the Metabolic Syndrome (MetS) and non-communicable diseases (NCDs) such as type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD), understanding the Indian context of the problem and learning how to deal with the obesity epidemic in this country has gained paramount importance. This narrative review points to the unique features of the obesity epidemic in India and its associated contributing factors, including the evolving nature of the Indian diet, the peculiarity of the increased adiposity at lower BMIs, unique obesity-associated genetic variants in Indians, the contribution of the gut microbiome, the impact of chronic inflammation and the role of ambient air pollution, and the contribution of decreased physical activity levels concerning the rapid urbanisation and the built environment. We believe that disseminating our insights into these unique features influencing the development of obesity in India will help increase global awareness and pave the way for better control and management of this obesity epidemic.

The high mobility group protein HMG20A cooperates with the histone reader PHF14 to modulate TGFβ and Hippo pathways

High mobility group (HMG) proteins are chromatin regulators with essential functions in development, cell differentiation and cell proliferation. The protein HMG20A is predicted by the AlphaFold2 software to contain three distinct structural elements, which we have functionally characterized: i) an amino-terminal, intrinsically disordered domain with transactivation activity; ii) an HMG box with higher binding affinity for double-stranded, four-way-junction DNA than for linear DNA; and iii) a long coiled-coil domain. Our proteomic study followed by a deletion analysis and structural modeling demonstrates that HMG20A forms a complex with the histone reader PHF14, via the establishment of a two-stranded alpha-helical coiled-coil structure. siRNA-mediated knockdown of either PHF14 or HMG20A in MDA-MB-231 cells causes similar defects in cell migration, invasion and homotypic cell-cell adhesion ability, but neither affects proliferation. Transcriptomic analyses demonstrate that PHF14 and HMG20A share a large subset of targets. We show that the PHF14-HMG20A complex modulates the Hippo pathway through a direct interaction with the TEAD1 transcription factor. PHF14 or HMG20A deficiency increases epithelial markers, including E-cadherin and the epithelial master regulator TP63 and impaired normal TGFβ-trigged epithelial-to-mesenchymal transition. Taken together, these data indicate that PHF14 and HMG20A cooperate in regulating several pathways involved in epithelial-mesenchymal plasticity.

Genetic variation in ST6GAL1 is a determinant of capecitabine and oxaliplatin induced hand-foot syndrome

Cancer patients treated with capecitabine and oxaliplatin (XELOX) often develop hand-foot syndrome (HFS) or palmar-plantar erythrodysesthesia. Genetic variation in ST6GAL1 is a risk factor for type-2 diabetes (T2D), a disease also associated with HFS. We analysed genome-wide association data for 10 toxicities in advanced colorectal cancer (CRC) patients from the COIN and COIN-B trials. One thousand and fifty-five patients were treated with XELOX ± cetuximab and 745 with folinic acid, fluorouracil and oxaliplatin ± cetuximab. We also analysed rs6783836 in ST6GAL1 with HFS in CRC patients from QUASAR2. Using UK Biobank data, we sought to confirm an association between ST6GAL1 and T2D (17 384 cases, 317 887 controls) and analysed rs6783836 against markers of diabetes, inflammation and psoriasis. We found that 68% of patients from COIN and COIN-B with grade 2-3 HFS responded to treatment as compared to 58% with grade 0-1 HFS (odds ratio [OR] = 1.1, 95% confidence interval [CI] = 1.02-1.2, P = 2.0 × 10^-4 ). HFS was also associated with improved overall survival (hazard ratio = 0.92, 95% CI = 0.84-0.99, P = 4.6 × 10^-2 ). rs6783836 at ST6GAL1 was associated with HFS in patients treated with XELOX (OR = 3.1, 95% CI = 2.1-4.6, P = 4.3 × 10^-8 ) and was borderline significant in patients receiving capecitabine from QUASAR2, but with an opposite allele effect (OR = 0.66, 95% CI = 0.42-1.03, P = .05). ST6GAL1 was associated with T2D (lead SNP rs3887925, OR = 0.94, 95% CI = 0.92-0.96, P = 1.2 × 10^-8 ) and the rs6783836-T allele was associated with lowered HbA1c levels (P = 5.9 × 10^-3 ) and lymphocyte count (P = 2.7 × 10^-3 ), and psoriasis (P = 7.5 × 10^-3 ) beyond thresholds for multiple testing. In conclusion, HFS is a biomarker of treatment outcome and rs6783836 in ST6GAL1 is a potential biomarker for HFS with links to T2D and inflammation.

HMG20A Inhibit Adipogenesis by Transcriptional and Epigenetic Regulation of MEF2C Expression

Obesity and its associated metabolic disease do serious harm to human health. The transcriptional cascade network with transcription factors as the core is the focus of current research on adipogenesis and its mechanism. Previous studies have found that HMG domain protein 20A (HMG20A) is highly expressed in the early stage of adipogenic differentiation of porcine intramuscular fat (IMF), which may be involved in regulating adipogenesis. In this study, HMG20A was found to play a key negative regulatory role in adipogenesis. Gain- and loss-of-function studies revealed that HMG20A inhibited the differentiation of SVF cells and C3H10T1/2 cells into mature adipocytes. RNA-seq was used to screen differentially expressed genes after HMG20A knockdown. qRT-PCR and ChIP-PCR confirmed that MEF2C was the real target of HMG20A, and HMG20A played a negative regulatory role through MEF2C. HMG20A binding protein LSD1 was found to alleviate the inhibitory effect of HMG20A on adipogenesis. Further studies showed that HMG20A could cooperate with LSD1 to increase the H3K4me2 of the MEF2C promoter and then increase the expression of MEF2C. Collectively, these findings highlight a role for HMG20A-dependent transcriptional and epigenetic regulation in adipogenesis.

Genetic evidence for a causal relationship between type 2 diabetes and peripheral artery disease in both Europeans and East Asians

BACKGROUND

Observational studies have revealed that type 2 diabetes (T2D) is associated with an increased risk of peripheral artery disease (PAD). However, whether the two diseases share a genetic basis and whether the relationship is causal remain unclear. It is also unclear as to whether these relationships differ between ethnic groups.

METHODS

By leveraging large-scale genome-wide association study (GWAS) summary statistics of T2D (European-based: N_case = 21,926, N_control = 342,747; East Asian-based: N_case = 36,614, N_control = 155,150) and PAD (European-based: N_case = 5673, N_control = 359,551; East Asian-based: N_case = 3593, N_control = 208,860), we explored the genetic correlation and putative causal relationship between T2D and PAD in both Europeans and East Asians using linkage disequilibrium score regression and seven Mendelian randomization (MR) models. We also performed multi-trait analysis of GWAS and two gene-based analyses to reveal candidate variants and risk genes involved in the shared genetic basis between T2D and PAD.

RESULTS

We observed a strong genetic correlation (r_g) between T2D and PAD in both Europeans (r_g = 0.51; p-value = 9.34 × 10^-15) and East Asians (r_g = 0.46; p-value = 1.67 × 10^-12). The MR analyses provided consistent evidence for a causal effect of T2D on PAD in both ethnicities (odds ratio [OR] = 1.05 to 1.28 for Europeans and 1.15 to 1.27 for East Asians) but not PAD on T2D. This putative causal effect was not influenced by total cholesterol, body mass index, systolic blood pressure, or smoking initiation according to multivariable MR analysis, and the genetic overlap between T2D and PAD was further explored employing an independent European sample through polygenic risk score regression. Multi-trait analysis of GWAS revealed two novel European-specific single nucleotide polymorphisms (rs927742 and rs1734409) associated with the shared genetic basis of T2D and PAD. Gene-based analyses consistently identified one gene ANKFY1 and gene-gene interactions (e.g., STARD10 [European-specific] to AP3S2 [East Asian-specific]; KCNJ11 [European-specific] to KCNQ1 [East Asian-specific]) associated with the trans-ethnic genetic overlap between T2D and PAD, reflecting a common genetic basis for the co-occurrence of T2D and PAD in both Europeans and East Asians.

CONCLUSIONS

Our study provides the first evidence for a genetically causal effect of T2D on PAD in both Europeans and East Asians. Several candidate variants and risk genes were identified as being associated with this genetic overlap. Our findings emphasize the importance of monitoring PAD status in T2D patients and suggest new genetic biomarkers for screening PAD risk among patients with T2D.

In silico functional and pathway analysis of risk genes and SNPs for type 2 diabetes in Asian population

Type 2 diabetes (T2D) has earned widespread recognition as a primary cause of death, disability, and increasing healthcare costs. There is compelling evidence that hereditary factors contribute to the development of T2D. Clinical trials in T2D have mostly focused on genes and single nucleotide polymorphisms (SNPs) in protein-coding areas. Recently, it was revealed that SNPs located in noncoding areas also play a significant impact on disease vulnerability. It is required for cell type-specific gene expression. However, the precise mechanism by which T2D risk genes and SNPs work remains unknown. We integrated risk genes and SNPs from genome-wide association studies (GWASs) and performed comprehensive bioinformatics analyses to further investigate the functional significance of these genes and SNPs. We identified four intriguing transcription factors (TFs) associated with T2D. The analysis revealed that the SNPs are engaged in chromatin interaction regulation and/or may have an effect on TF binding affinity. The Gene Ontology (GO) study revealed high enrichment in a number of well-characterized signaling pathways and regulatory processes, including the STAT3 and JAK signaling pathways, which are both involved in T2D metabolism. Additionally, a detailed KEGG pathway analysis identified two major T2D genes and their prospective therapeutic targets. Our findings underscored the potential functional significance of T2D risk genes and SNPs, which may provide unique insights into the disease’s pathophysiology.

Racial Disparities in Cardiovascular Risk and Cardiovascular Care in Women

PURPOSE OF REVIEW

Research on sex and gender aspects cardiovascular disease has contributed to a reduction in cardiovascular mortality in women. However, cardiovascular disease remains the leading cause of death of women in the United States. Disparities in cardiovascular risk and outcomes among women overall persist and are amplified for women of certain ethnic and racial subgroups. We review the evidence of racial and ethnic differences in cardiovascular risk and care among women and describe a path forward to achieve equitable cardiovascular care for women of racial and ethnic minority groups.

RECENT FINDINGS

There is a disproportionate effect on cardiovascular outcomes in women and certain racial and ethnic groups in part due to disparities in triage, diagnosis, treatment, which lead to amplification of inequalities in women of minority racial and ethnic background. Data suggest gender and racial bias, underappreciation of nontraditional risk factors, underrepresentation of women in clinical trials and undertreatment of disease contributes to persistent differences in cardiovascular disease outcomes in women of color. Understanding the myriad of factors that contribute to increased cardiovascular risk, and disparities in treatment and outcomes among women from racial/ethnic minority backgrounds is imperative to improving cardiovascular care for this patient population.

Pathophysiology, phenotypes and management of type 2 diabetes mellitus in Indian and Chinese populations

Nearly half of all adults with type 2 diabetes mellitus (T2DM) live in India and China. These populations have an underlying predisposition to deficient insulin secretion, which has a key role in the pathogenesis of T2DM. Indian and Chinese people might be more susceptible to hepatic or skeletal muscle insulin resistance, respectively, than other populations, resulting in specific forms of insulin deficiency. Cluster-based phenotypic analyses demonstrate a higher frequency of severe insulin-deficient diabetes mellitus and younger ages at diagnosis, lower β-cell function, lower insulin resistance and lower BMI among Indian and Chinese people compared with European people. Individuals diagnosed earliest in life have the most aggressive course of disease and the highest risk of complications. These characteristics might contribute to distinctive responses to glucose-lowering medications. Incretin-based agents are particularly effective for lowering glucose levels in these populations; they enhance incretin-augmented insulin secretion and suppress glucagon secretion. Sodium-glucose cotransporter 2 inhibitors might also lower blood levels of glucose especially effectively among Asian people, while α-glucosidase inhibitors are better tolerated in east Asian populations versus other populations. Further research is needed to better characterize and address the pathophysiology and phenotypes of T2DM in Indian and Chinese populations, and to further develop individualized treatment strategies.

Diabetes risk loci-associated pathways are shared across metabolic tissues

Aims/hypothesis

Numerous genome-wide association studies have been performed to understand the influence of genetic variation on type 2 diabetes etiology. Many identified risk variants are located in non-coding and intergenic regions, which complicates understanding of how genes and their downstream pathways are influenced. An integrative data approach will help to understand the mechanism and consequences of identified risk variants.

Methods

In the current study we use our previously developed method CONQUER to overlap 403 type 2 diabetes risk variants with regulatory, expression and protein data to identify tissue-shared disease-relevant mechanisms.

Results

One SNP rs474513 was found to be an expression-, protein- and metabolite QTL. Rs474513 influenced LPA mRNA and protein levels in the pancreas and plasma, respectively. On the pathway level, in investigated tissues most SNPs linked to metabolism. However, in eleven of the twelve tissues investigated nine SNPs were linked to differential expression of the ribosome pathway. Furthermore, seven SNPs were linked to altered expression of genes linked to the immune system. Among them, rs601945 was found to influence multiple HLA genes, including HLA-DQA2, in all twelve tissues investigated.

Conclusion

Our results show that in addition to the classical metabolism pathways, other pathways may be important to type 2 diabetes that show a potential overlap with type 1 diabetes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08587-5.

Integrating polygenic risk scores in the prediction of type 2 diabetes risk and subtypes in British Pakistanis and Bangladeshis: A population-based cohort study

BACKGROUND

Type 2 diabetes (T2D) is highly prevalent in British South Asians, yet they are underrepresented in research. Genes & Health (G&H) is a large, population study of British Pakistanis and Bangladeshis (BPB) comprising genomic and routine health data. We assessed the extent to which genetic risk for T2D is shared between BPB and European populations (EUR). We then investigated whether the integration of a polygenic risk score (PRS) for T2D with an existing risk tool (QDiabetes) could improve prediction of incident disease and the characterisation of disease subtypes.

METHODS AND FINDINGS

In this observational cohort study, we assessed whether common genetic loci associated with T2D in EUR individuals were replicated in 22,490 BPB individuals in G&H. We replicated fewer loci in G&H (n = 76/338, 22%) than would be expected given power if all EUR-ascertained loci were transferable (n = 101, 30%; p = 0.001). Of the 27 transferable loci that were powered to interrogate this, only 9 showed evidence of shared causal variants. We constructed a T2D PRS and combined it with a clinical risk instrument (QDiabetes) in a novel, integrated risk tool (IRT) to assess risk of incident diabetes. To assess model performance, we compared categorical net reclassification index (NRI) versus QDiabetes alone. In 13,648 patients free from T2D followed up for 10 years, NRI was 3.2% for IRT versus QDiabetes (95% confidence interval (CI): 2.0% to 4.4%). IRT performed best in reclassification of individuals aged less than 40 years deemed low risk by QDiabetes alone (NRI 5.6%, 95% CI 3.6% to 7.6%), who tended to be free from comorbidities and slim. After adjustment for QDiabetes score, PRS was independently associated with progression to T2D after gestational diabetes (hazard ratio (HR) per SD of PRS 1.23, 95% CI 1.05 to 1.42, p = 0.028). Using cluster analysis of clinical features at diabetes diagnosis, we replicated previously reported disease subgroups, including Mild Age-Related, Mild Obesity-related, and Insulin-Resistant Diabetes, and showed that PRS distribution differs between subgroups (p = 0.002). Integrating PRS in this cluster analysis revealed a Probable Severe Insulin Deficient Diabetes (pSIDD) subgroup, despite the absence of clinical measures of insulin secretion or resistance. We also observed differences in rates of progression to micro- and macrovascular complications between subgroups after adjustment for confounders. Study limitations include the absence of an external replication cohort and the potential biases arising from missing or incorrect routine health data.

CONCLUSIONS

Our analysis of the transferability of T2D loci between EUR and BPB indicates the need for larger, multiancestry studies to better characterise the genetic contribution to disease and its varied aetiology. We show that a T2D PRS optimised for this high-risk BPB population has potential clinical application in BPB, improving the identification of T2D risk (especially in the young) on top of an established clinical risk algorithm and aiding identification of subgroups at diagnosis, which may help future efforts to stratify care and treatment of the disease.

Extending precision medicine tools to populations at high risk of type 2 diabetes

In this Perspective, Shivani Misra and Jose C Florez discuss the application of precision medicine tools in under-represented populations.

Metabolomic Analysis of Serum and Tear Samples from Patients with Obesity and Type 2 Diabetes Mellitus

Metabolomics strategies are widely used to examine obesity and type 2 diabetes (T2D). Patients with obesity (n = 31) or T2D (n = 26) and sex- and age-matched controls (n = 28) were recruited, and serum and tear samples were collected. The concentration of 23 amino acids and 10 biogenic amines in serum and tear samples was analyzed. Statistical analysis and Pearson correlation analysis along with network analysis were carried out. Compared to controls, changes in the level of 6 analytes in the obese group and of 10 analytes in the T2D group were statistically significant. For obesity, the energy generation, while for T2D, the involvement of NO synthesis and its relation to insulin signaling and inflammation, were characteristic. We found that BCAA and glutamine metabolism, urea cycle, and beta-oxidation make up crucial parts of the metabolic changes in T2D. According to our data, the retromer-mediated retrograde transport, the ethanolamine metabolism, and, consequently, the endocannabinoid signaling and phospholipid metabolism were characteristic of both conditions and can be relevant pathways to understanding and treating insulin resistance. By providing potential therapeutic targets and new starting points for mechanistic studies, our results emphasize the importance of complex data analysis procedures to better understand the pathomechanism of obesity and diabetes.

Burden of Type 2 Diabetes and Associated Cardiometabolic Traits and Their Heritability Estimates in Endogamous Ethnic Groups of India: Findings From the INDIGENIUS Consortium

To assess the burden of type 2 diabetes (T2D) and its genetic profile in endogamous populations of India given the paucity of data, we aimed to determine the prevalence of T2D and estimate its heritability using family-based cohorts from three distinct Endogamous Ethnic Groups (EEGs) representing Northern (Rajasthan [Agarwals: AG]) and Southern (Tamil Nadu [Chettiars: CH] and Andhra Pradesh [Reddys: RE]) states of India. For comparison, family-based data collected previously from another North Indian Punjabi Sikh (SI) EEG was used. In addition, we examined various T2D-related cardiometabolic traits and determined their heritabilities. These studies were conducted as part of the Indian Diabetes Genetic Studies in collaboration with US (INDIGENIUS) Consortium. The pedigree, demographic, phenotypic, covariate data and samples were collected from the CH, AG, and RE EEGs. The status of T2D was defined by ADA guidelines (fasting glucose ≥ 126 mg/dl or HbA1c ≥ 6.5% and/or use of diabetes medication/history). The prevalence of T2D in CH (N = 517, families = 21, mean age = 47y, mean BMI = 27), AG (N = 530, Families = 25, mean age = 43y, mean BMI = 27), and RE (N = 500, Families = 22, mean age = 46y, mean BMI = 27) was found to be 33%, 37%, and 36%, respectively, Also, the study participants from these EEGs were found to be at increased cardiometabolic risk (e.g., obesity and prediabetes). Similar characteristics for the SI EEG (N = 1,260, Families = 324, Age = 51y, BMI = 27, T2D = 75%) were obtained previously. We used the variance components approach to carry out genetic analyses after adjusting for covariate effects. The heritability (h2) estimates of T2D in the CH, RE, SI, and AG were found to be 30%, 46%, 54%, and 82% respectively, and statistically significant (P ≤ 0.05). Other T2D related traits (e.g., BMI, lipids, blood pressure) in AG, CH, and RE EEGs exhibited strong additive genetic influences (h2 range: 17% [triglycerides/AG and hs-CRP/RE] - 86% [glucose/non-T2D/AG]). Our findings highlight the high burden of T2D in Indian EEGs with significant and differential additive genetic influences on T2D and related traits.

Identification of genetic effects underlying type 2 diabetes in South Asian and European populations

South Asians are at high risk of developing type 2 diabetes (T2D). We carried out a genome-wide association meta-analysis with South Asian T2D cases (n = 16,677) and controls (n = 33,856), followed by combined analyses with Europeans (neff = 231,420). We identify 21 novel genetic loci for significant association with T2D (P = 4.7 × 10-8 to 5.2 × 10-12), to the best of our knowledge at the point of analysis. The loci are enriched for regulatory features, including DNA methylation and gene expression in relevant tissues, and highlight CHMP4B, PDHB, LRIG1 and other genes linked to adiposity and glucose metabolism. A polygenic risk score based on South Asian-derived summary statistics shows ~4-fold higher risk for T2D between the top and bottom quartile. Our results provide further insights into the genetic mechanisms underlying T2D, and highlight the opportunities for discovery from joint analysis of data from across ancestral populations.

Identification of genetic loci simultaneously associated with multiple cardiometabolic traits

BACKGROUND AND AIMS

Cardiometabolic disorders (CMD) arise from a constellation of features such as increased adiposity, hyperlipidemia, hypertension and compromised glucose control. Many genetic loci have shown associations with individual CMD-related traits, but no investigations have focused on simultaneously identifying loci showing associations across all domains. We therefore sought to identify loci associated with risk across seven continuous CMD-related traits.

METHODS AND RESULTS

We conducted separate genome-wide association studies (GWAS) for systolic and diastolic blood pressure (SBP/DBP), hemoglobin A1c (HbA1c), low- and high- density lipoprotein cholesterol (LDL-C/HDL-C), waist-to-hip-ratio (WHR), and triglycerides (TGs) in the UK Biobank (N = 356,574-456,823). Multiple loci reached genome-wide levels of significance (N = 145-333) for each trait, but only four loci (in/near VEGFA, GRB14-COBLL1, KLF14, and RGS19-OPRL1) were associated with risk across all seven traits (P < 5 × 10^-8). We sought replication of these four loci in an independent set of seven trait-specific GWAS meta-analyses. GRB14-COBLL1 showed the most consistent replication, revealing nominally significant associations (P < 0.05) with all traits except DBP.

CONCLUSIONS

Our analyses suggest that very few loci are associated in the same direction of risk with traits representing the full spectrum of CMD features. We identified four such loci, and an understanding of the pathways between these loci and CMD risk may eventually identify factors that can be used to identify pathologic disturbances that represent broadly beneficial therapeutic targets.