Peripheral Blood Transcriptomic Signatures of Fasting Glucose and Insulin Concentrations

Construction of Multi-Modal Transcriptome-Small Molecule Interaction Networks from High-Throughput Measurements to Study Human Complex Traits

Small molecules (SMs) are integral to biological processes, influencing metabolism, homeostasis, and regulatory networks. Despite their importance, a significant knowledge gap exists regarding their downstream effects on biological pathways and gene expression, largely due to differences in scale, variability, and noise between untargeted metabolomics and sequencing-based technologies. To address these challenges, we developed a multi-omics framework comprising a machine learning-based protocol for data processing, a semi-supervised network inference approach, and network-guided analysis of complex traits. The ML protocol harmonized metabolomic, lipidomic, and transcriptomic data through batch correction, principal component analysis, and regression-based adjustments, enabling unbiased and effective integration. Building on this, we proposed a semi-supervised method to construct transcriptome-SM interaction networks (TSI-Nets) by selectively integrating SM profiles into gene-level networks using a meta-analytic approach that accounts for scale differences and missing data across omics layers. Benchmarking against three conventional unsupervised methods demonstrated the superiority of our approach in generating diverse, biologically relevant, and robust networks. While single-omics analyses identified 18 significant genes and 3 significant SMs associated with insulin sensitivity (IS), network-guided analysis revealed novel connections between these markers. The top-ranked module highlighted a cross-talk between fiber-degrading gut microbiota and immune regulatory pathways, inferred by the interaction of the protective SM, N-acetylglycine (NAG), with immune genes (FCER1A, HDC, MS4A2, and CPA3), linked to improved IS and reduced obesity and inflammation. Together, this framework offers a robust and scalable solution for multi-modal network inference and analysis, advancing SM pathway discovery and their implications for human health. Leveraging data from a population of thousands of individuals with extended longevity, the inferred TSI-Nets demonstrate generalizability across diverse conditions and complex traits. These networks are publicly available as a resource for the research community.

Multi-tissue epigenetic analysis identifies distinct associations underlying insulin resistance and Alzheimer's disease at CPT1A locus

BACKGROUND

Insulin resistance (IR) is a major risk factor for Alzheimer's disease (AD) dementia. The mechanisms by which IR predisposes to AD are not well-understood. Epigenetic studies may help identify molecular signatures of IR associated with AD, thus improving our understanding of the biological and regulatory mechanisms linking IR and AD.

METHODS

We conducted an epigenome-wide association study of IR, quantified using the homeostatic model assessment of IR (HOMA-IR) and adjusted for body mass index, in 3,167 participants from the Framingham Heart Study (FHS) without type 2 diabetes at the time of blood draw used for methylation measurement. We identified DNA methylation markers associated with IR at the genome-wide level accounting for multiple testing (P < 1.1 × 10-7) and evaluated their association with neurological traits in participants from the FHS (N = 3040) and the Religious Orders Study/Memory and Aging Project (ROSMAP, N = 707). DNA methylation profiles were measured in blood (FHS) or dorsolateral prefrontal cortex (ROSMAP) using the Illumina HumanMethylation450 BeadChip. Linear regressions (ROSMAP) or mixed-effects models accounting for familial relatedness (FHS) adjusted for age, sex, cohort, self-reported race, batch, and cell type proportions were used to assess associations between DNA methylation and neurological traits accounting for multiple testing.

RESULTS

We confirmed the strong association of blood DNA methylation with IR at three loci (cg17901584-DHCR24, cg17058475-CPT1A, cg00574958-CPT1A, and cg06500161-ABCG1). In FHS, higher levels of blood DNA methylation at cg00574958 and cg17058475 were both associated with lower IR (P = 2.4 × 10-11 and P = 9.0 × 10-8), larger total brain volumes (P = 0.03 and P = 9.7 × 10-4), and smaller log lateral ventricular volumes (P = 0.07 and P = 0.03). In ROSMAP, higher levels of brain DNA methylation at the same two CPT1A markers were associated with greater risk of cognitive impairment (P = 0.005 and P = 0.02) and higher AD-related indices (CERAD score: P = 5 × 10-4 and 0.001; Braak stage: P = 0.004 and P = 0.01).

CONCLUSIONS

Our results suggest potentially distinct epigenetic regulatory mechanisms between peripheral blood and dorsolateral prefrontal cortex tissues underlying IR and AD at CPT1A locus.

m6A epitranscriptomic modification in diabetic microvascular complications

N6-methyladenosine (m6A) modifications are modulated by m6A methyltransferases, m6A demethylases, and m6A-binding proteins. The dynamic and reversible patterns of m6A modification control cell fate programming by regulating RNA splicing, translation, and decay. Emerging evidence demonstrates that m6A modification of coding and noncoding RNAs exerts crucial effects that influence the pathogenesis of diabetic microvascular complications that include diabetic cardiomyopathy, diabetic nephropathy, diabetic retinopathy, diabetic neuropathy, and diabetic dermatosis. In this review, we summarize the roles of m6A modification and m6A modification-related enzymes in diabetic microvascular complications and discuss potential m6A modification-related enzyme-targeting therapeutic strategies.

Bioinformatic identification and experiment validation revealed that ACTG1 is a promising prognostic signature and therapeutic target for sepsis

In the intensive care unit, sepsis is a prevalent clinical syndrome (i.e. the final pathway to death from most infections). Peripheral blood gene expression profiling is becoming more and more accepted as a potential diagnostic or prognostic tool. This work aimed to recognize genes related to sepsis, providing potential translational therapeutic targets. RNA sequencing was performed on peripheral blood mononuclear cells from 20 healthy control subjects and 51 sepsis patients. Weighted gene coexpression network analysis was employed to pick out sepsis-related and immunocyte-related gene modules. Genes in the yellow module are primarily involved in excessive inflammation and immune suppression. STRING and Cytoscape were combined to identify ACTG1 and IQGAP1 as hub genes with highest connective degree, and prognostic predication value of ACTG1 was confirmed. Both univariate and multivariate logistic regression analyses were carried out. ACTG1 messenger RNA expression was increased in animal and in cell-related sepsis models. Small interfering RNA revealed decreasing ACTG1 can reduce the in vitro sepsis model apoptosis. We have authenticated ACTG1 as a reliable signature of a poor outcome of sepsis and promising therapeutic targets for sepsis.

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.

U-shaped association between serum IGF2BP3 and T2DM: A cross-sectional study in Chinese population

OBJECTIVE

To clarify the expression of N6-methyladenosine (m⁶ A) modulators involved in the pathogenesis of type 2 diabetes mellitus (T2DM). We further explored the association of serum insulin-like growth factor 2 mRNA-binding proteins 3 (IGF2BP3) levels and odds of T2DM in a high-risk population.

METHODS

The gene expression data set GSE25724 was obtained from the Gene Expression Omnibus, and a cluster heatmap was generated by using the R package ComplexHeatmap. Differential expression analysis for 13 m⁶ A RNA methylation regulators between nondiabetic controls and T2DM subjects was performed using an unpaired t test. A cross-sectional design, including 393 subjects (131 patients with newly diagnosed T2DM, 131 age- and sex-matched subjects with prediabetes, and 131 healthy controls), was carried out. The associations between serum IGF2BP3 concentrations and T2DM were modeled by restricted cubic spline and logistic regression models.

RESULTS

Two upregulated (IGF2BP2 and IGF2BP3) and 5 downregulated (methyltransferase-like 3 [METTL3], alkylation repair homolog protein 1 [ALKBH1], YTH domain family 2 [YTHDF2], YTHDF3, and heterogeneous nuclear ribonucleoprotein [HNRNPC]) m⁶ A-related genes were found in islet samples of T2DM patients. A U-shaped association existed between serum IGF2BP3 levels and odds of T2DM according to cubic natural spline analysis models, after adjustment for body mass index, waist circumference, diastolic blood pressure, total cholesterol, and triglyeride. Multivariate logistic regression showed that progressively higher odds of T2DM were observed when serum IGF2BP3 levels were below 0.62 ng/mL (odds ratio 3.03 [95% confidence interval 1.23-7.47]) in model 4.

CONCLUSION

Seven significantly altered m⁶ A RNA methylation genes were identified in T2DM. There was a U-shaped association between serum IGF2BP3 levels and odds of T2DM in the general Chinese adult population. This study provides important evidence for further examination of the role of m⁶ A RNA methylation, especially serum IGF2BP3 in T2DM risk assessment.

Fetal Growth and Intrauterine Epigenetic Programming of Obesity and Cardiometabolic Disease

Epidemiologic studies have shown an association between an adverse intrauterine environment (eg, exposure to malnutrition) and an increased risk of developing cardiometabolic disease in adulthood. These studies laid the foundation for the developmental origins of health and disease hypothesis, which states that limited nutrient supply to the fetus results in physiologic and metabolic adaptations that favor survival but result in unfavorable consequences in the offspring if there is excess nutrition after birth. This discrepancy in the pre- and postnatal milieus, perceived as stress by the offspring, may confer an increased risk of developing cardiometabolic disease later in life. Thus, early life exposures result in programming or changes in cellular memory that have effects on health throughout the life course. One of the mechanisms by which programming occurs is via epigenetic modifications of genes, processes that result in functionally relevant changes in genes (ie, gene expression) without an alteration in the genotype. In this review, we will describe how fetal exposures, including under- and overnutrition, affect neonatal and childhood growth and the future risk for cardiometabolic disease.

Effects of Alkaloid-Rich Extracts Obtained from Grifola frondosa on Gut Microbiota and Glucose Homeostasis in Rats

Grifola frondosa (GF), also known as maitake (a type of mushroom), has been widely used as a food item and it exhibits various health-beneficial hypoglycemic activities. Rats fed with a...

Molecular Aspects of Lifestyle and Environmental Effects in Patients With Diabetes: JACC Focus Seminar

Diabetes is characterized as an integrated condition of dysregulated metabolism across multiple tissues, with well-established consequences on the cardiovascular system. Recent advances in precision phenotyping in biofluids and tissues in large human observational and interventional studies have afforded a unique opportunity to translate seminal findings in models and cellular systems to patients at risk for diabetes and its complications. Specifically, techniques to assay metabolites, proteins, and transcripts, alongside more recent assessment of the gut microbiome, underscore the complexity of diabetes in patients, suggesting avenues for precision phenotyping of risk, response to intervention, and potentially novel therapies. In addition, the influence of external factors and inputs (eg, activity, diet, medical therapies) on each domain of molecular characterization has gained prominence toward better understanding their role in prevention. Here, the authors provide a broad overview of the role of several of these molecular domains in human translational investigation in diabetes.

The biological function of IGF2BPs and their role in tumorigenesis

The insulin-like growth factor-2 mRNA-binding proteins (IGF2BPs) pertain to a highly conservative RNA-binding family that works as a post-transcriptional fine-tuner for target transcripts. Emerging evidence suggests that IGF2BPs regulate RNA processing and metabolism, including stability, translation, and localization, and are involved in various cellular functions and pathophysiologies. In this review, we summarize the roles and molecular mechanisms of IGF2BPs in cancer development and progression. We mainly discuss the functional relevance of IGF2BPs in embryo development, neurogenesis, metabolism, RNA processing, and tumorigenesis. Understanding IGF2BPs role in tumor progression will provide new insight into cancer pathophysiology.

Human intelectin-1 (ITLN1) genetic variation and intestinal expression

Intelectins are ancient carbohydrate binding proteins, spanning chordate evolution and implicated in multiple human diseases. Previous GWAS have linked SNPs in ITLN1 (also known as omentin) with susceptibility to Crohn's disease (CD); however, analysis of possible functional significance of SNPs at this locus is lacking. Using the Ensembl database, pairwise linkage disequilibrium (LD) analyses indicated that several disease-associated SNPs at the ITLN1 locus, including SNPs in CD244 and Ly9, were in LD. The alleles comprising the risk haplotype are the major alleles in European (67%), but minor alleles in African superpopulations. Neither ITLN1 mRNA nor protein abundance in intestinal tissue, which we confirm as goblet-cell derived, was altered in the CD samples overall nor when samples were analyzed according to genotype. Moreover, the missense variant V109D does not influence ITLN1 glycan binding to the glycan β-D-galactofuranose or protein-protein oligomerization. Taken together, our data are an important step in defining the role(s) of the CD-risk haplotype by determining that risk is unlikely to be due to changes in ITLN1 carbohydrate recognition, protein oligomerization, or expression levels in intestinal mucosa. Our findings suggest that the relationship between the genomic data and disease arises from changes in CD244 or Ly9 biology, differences in ITLN1 expression in other tissues, or an alteration in ITLN1 interaction with other proteins.

RNA m6A reader IMP2/IGF2BP2 promotes pancreatic β-cell proliferation and insulin secretion by enhancing PDX1 expression

BACKGROUND

Type 2 diabetes (T2D) is a common metabolic disease. Variants in human IGF2 mRNA binding protein 2 (IMP2/IGF2BP2) are associated with increased risk of T2D. IMP2 contributes to T2D susceptibility primarily through effects on insulin secretion. However, the underlying mechanism is not known.

METHODS

To understand the role of IMP2 in insulin secretion and T2D pathophysiology, we generated Imp2 pancreatic β-cell specific knockout mice (βIMP2KO) by recombining the Imp2^flox allele with Cre recombinase driven by the rat insulin 2 promoter. We further characterized metabolic phenotypes of βIMP2KO mice and assessed their β-cell functions.

RESULTS

The deletion of IMP2 in pancreatic β-cells leads to reduced compensatory β-cell proliferation and function. Mechanically, IMP2 directly binds to Pdx1 mRNA and stimulates its translation in an m6A dependent manner. Moreover, IMP2 orchestrates IGF2-AKT-GSK3β-PDX1 signaling to stable PDX1 polypeptides. In human EndoC-βH1 cells, the over-expression of IMP2 is capable to enhance cell proliferation, PDX1 protein level and insulin secretion.

CONCLUSION

Our work therefore reveals IMP2 as a critical regulator of pancreatic β-cell proliferation and function; highlights the importance of posttranscriptional gene expression in T2D pathology.

Association of Genetic Variants in IGF2-Related Genes With Risk of Metabolic Syndrome in the Chinese Han Population

AIMS

To explore associations between polymorphisms of IGF2-related genes including H19, IGF2, IGF2BP2 and IGF2R and Metabolic syndrome (MetS) susceptibility in the Chinese Han population.

METHODS

66 subjects with MetS and 257 control subjects were collected for inclusion in a case-control study. PCR-RFLP was used to investigate polymorphisms in the H19, IGF2, IGF2BP2 and IGF2R genes. Elisa was used to detect the serum IGF2 concentrations.

RESULTS

Females carrying the GG and AG genotypes of rs680 (IGF2) exhibited a lower risk of MetS, compared with those harboring AA (adjusted OR = 0.388, p = 0.027), while GG and AG genotypes were associated with lower fasting glucose and HbA1c. In males, the Waist-to-Hip Ratio (WHR) and the level of TG were significantly higher in GG and AG genotypes than in the AA genotype of rs680 in IGF2. Levels of HDL-c were lower in men with GG and AG genotypes compared with those carrying the AA genotype. Serum IGF2 concentrations did not change among different genotypes. Finally, multifactor dimensionality reduction (MDR) analysis identified interactions between four polymorphisms: rs3741279 (H19), rs680 (IGF2), rs1470579 (IGF2BP2) and rs629849 (IGF2R).

CONCLUSIONS

Our study suggests that IGF2-related genes including H19, IGF2, IGF2BP2 and IGF2R genes may play pivotal roles in the development of MetS.

Genome-Wide Association Analysis of Pancreatic Beta-Cell Glucose Sensitivity

CONTEXT

Pancreatic beta-cell glucose sensitivity is the slope of the plasma glucose-insulin secretion relationship and is a key predictor of deteriorating glucose tolerance and development of type 2 diabetes. However, there are no large-scale studies looking at the genetic determinants of beta-cell glucose sensitivity.

OBJECTIVE

To understand the genetic determinants of pancreatic beta-cell glucose sensitivity using genome-wide meta-analysis and candidate gene studies.

DESIGN

We performed a genome-wide meta-analysis for beta-cell glucose sensitivity in subjects with type 2 diabetes and nondiabetic subjects from 6 independent cohorts (n = 5706). Beta-cell glucose sensitivity was calculated from mixed meal and oral glucose tolerance tests, and its associations between known glycemia-related single nucleotide polymorphisms (SNPs) and genome-wide association study (GWAS) SNPs were estimated using linear regression models.

RESULTS

Beta-cell glucose sensitivity was moderately heritable (h2 ranged from 34% to 55%) using SNP and family-based analyses. GWAS meta-analysis identified multiple correlated SNPs in the CDKAL1 gene and GIPR-QPCTL gene loci that reached genome-wide significance, with SNP rs2238691 in GIPR-QPCTL (P value = 2.64 × 10-9) and rs9368219 in the CDKAL1 (P value = 3.15 × 10-9) showing the strongest association with beta-cell glucose sensitivity. These loci surpassed genome-wide significance when the GWAS meta-analysis was repeated after exclusion of the diabetic subjects. After correction for multiple testing, glycemia-associated SNPs in or near the HHEX and IGF2B2 loci were also associated with beta-cell glucose sensitivity.

CONCLUSION

We show that, variation at the GIPR-QPCTL and CDKAL1 loci are key determinants of pancreatic beta-cell glucose sensitivity.

DNA methylation and body mass index from birth to adolescence: meta-analyses of epigenome-wide association studies

BACKGROUND

DNA methylation has been shown to be associated with adiposity in adulthood. However, whether similar DNA methylation patterns are associated with childhood and adolescent body mass index (BMI) is largely unknown. More insight into this relationship at younger ages may have implications for future prevention of obesity and its related traits.

METHODS

We examined whether DNA methylation in cord blood and whole blood in childhood and adolescence was associated with BMI in the age range from 2 to 18 years using both cross-sectional and longitudinal models. We performed meta-analyses of epigenome-wide association studies including up to 4133 children from 23 studies. We examined the overlap of findings reported in previous studies in children and adults with those in our analyses and calculated enrichment.

RESULTS

DNA methylation at three CpGs (cg05937453, cg25212453, and cg10040131), each in a different age range, was associated with BMI at Bonferroni significance, P < 1.06 × 10-7, with a 0.96 standard deviation score (SDS) (standard error (SE) 0.17), 0.32 SDS (SE 0.06), and 0.32 BMI SDS (SE 0.06) higher BMI per 10% increase in methylation, respectively. DNA methylation at nine additional CpGs in the cross-sectional childhood model was associated with BMI at false discovery rate significance. The strength of the associations of DNA methylation at the 187 CpGs previously identified to be associated with adult BMI, increased with advancing age across childhood and adolescence in our analyses. In addition, correlation coefficients between effect estimates for those CpGs in adults and in children and adolescents also increased. Among the top findings for each age range, we observed increasing enrichment for the CpGs that were previously identified in adults (birth Penrichment = 1; childhood Penrichment = 2.00 × 10-4; adolescence Penrichment = 2.10 × 10-7).

CONCLUSIONS

There were only minimal associations of DNA methylation with childhood and adolescent BMI. With the advancing age of the participants across childhood and adolescence, we observed increasing overlap with altered DNA methylation loci reported in association with adult BMI. These findings may be compatible with the hypothesis that DNA methylation differences are mostly a consequence rather than a cause of obesity.

Smoking-related changes in DNA methylation and gene expression are associated with cardio-metabolic traits

BACKGROUND

Tobacco smoking is a well-known modifiable risk factor for many chronic diseases, including cardiovascular disease (CVD). One of the proposed underlying mechanism linking smoking to disease is via epigenetic modifications, which could affect the expression of disease-associated genes. Here, we conducted a three-way association study to identify the relationship between smoking-related changes in DNA methylation and gene expression and their associations with cardio-metabolic traits.

RESULTS

We selected 2549 CpG sites and 443 gene expression probes associated with current versus never smokers, from the largest epigenome-wide association study and transcriptome-wide association study to date. We examined three-way associations, including CpG versus gene expression, cardio-metabolic trait versus CpG, and cardio-metabolic trait versus gene expression, in the Rotterdam study. Subsequently, we replicated our findings in The Cooperative Health Research in the Region of Augsburg (KORA) study. After correction for multiple testing, we identified both cis- and trans-expression quantitative trait methylation (eQTM) associations in blood. Specifically, we found 1224 smoking-related CpGs associated with at least one of the 443 gene expression probes, and 200 smoking-related gene expression probes to be associated with at least one of the 2549 CpGs. Out of these, 109 CpGs and 27 genes were associated with at least one cardio-metabolic trait in the Rotterdam Study. We were able to replicate the associations with cardio-metabolic traits of 26 CpGs and 19 genes in the KORA study. Furthermore, we identified a three-way association of triglycerides with two CpGs and two genes (GZMA; CLDND1), and BMI with six CpGs and two genes (PID1; LRRN3). Finally, our results revealed the mediation effect of cg03636183 (F2RL3), cg06096336 (PSMD1), cg13708645 (KDM2B), and cg17287155 (AHRR) within the association between smoking and LRRN3 expression.

CONCLUSIONS

Our study indicates that smoking-related changes in DNA methylation and gene expression are associated with cardio-metabolic risk factors. These findings may provide additional insights into the molecular mechanisms linking smoking to the development of CVD.

The Diverse Functions of IMP2/IGF2BP2 in Metabolism

The human insulin-like growth factor 2 (IGF2) mRNA binding protein family (IMPs/IGF2BPs) is involved in a spectrum of biological processes, including development, tumorigenesis, and stemness. IMPs play a major role in post-transcriptional regulation of RNAs through the ribonucleoprotein complex (RNP). They have emerged as direct mammalian target of rapamycin (mTOR) substrates that coordinate nutrient stimulation and RNA life cycle control. IMP2 is a human type 2 diabetes (T2D) gene associated with impaired insulin secretion. Recently, using murine models, the substantial progress in understanding disease mechanisms has highlighted the significance of IMP2 in metabolism. This new knowledge may have the potential for therapeutic benefit.

Genetic polymorphisms associated with type 2 diabetes in the Arab world: A systematic review and meta-analysis

AIMS

T2DM reach epidemic levels in the Arab countries. In this study, we aimed to perform a systematic review and meta-analysis to underline the susceptibility genetic profile of Arab patients with T2DM that result from SNPs.

METHODS

We searched four literature databases (PubMed, Scopus, Science Direct and Web of Science) through January 2019. We included all SNPs in candidate genes with an OR > 1 that were associated with T2DM among Arab patients with T2DM. Statistical programs such as software Review Manager (Version 5.02) and STATA (Version 15.1) were used. The pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated with a random effects model or a fixed effect model depending on the heterogeneity among studies. I² statistics and Egger's tests were performed to assess heterogeneity and publication bias.

RESULTS

Out of 2245 studies, 47 were used for meta-analysis. We captured 31,307 cases and 26,464 controls in which we collected 71 SNPs in 32 genes. A pooled meta-analysis demonstrated 24-69% increase in T2DM risk. Among the 57 SNPs (in 32 genes) that were not included in the meta-analysis, the OR for diabetes ranged from 1.02 to 5.10, with a median of 1.38 (interquartile range 1.33-2.09). Ten studies examined the association between the TCF7L2 polymorphism rs7903146 and T2DM, leading to an aggregated OR of 1.34 (95%CI 1.27-1.41).

CONCLUSION

The genetic profile that confer susceptibility to T2DM in Arab patients is diverse. This study may serve as a platform for designing a gene panel for testing the susceptibility to T2DM.

Overview of genomics and post-genomics research on type 2 diabetes mellitus: Future perspectives and a framework for further studies

In this review, we briefly outlined salient features of pathophysiology and results of the genetic association studies hitherto conducted on type 2 diabetes. Primarily focusing on the current status of genomic research, we briefly discussed the limited progress made during the post-genomic era and tried to identify the limitations of the post-genomic research strategies. We suggested reanalysis of the existing genomic data through advanced statistical and computational methods and recommended integrated genomics-metabolomics approaches for future studies to facilitate understanding of the gene-environment interactions in the manifestation of the disease. We also propose a framework for research that may be apt for determining the effects of urbanization and changing lifestyles in the manifestation of complex genetic disorders like type 2 diabetes in the Indian populations and offset the confounding effects of both genetic and environmental factors in the natural way.

Genetic aetiology of glycaemic traits: approaches and insights

Glycaemic traits such as fasting and post-challenge glucose and insulin measures, as well as glycated haemoglobin (HbA1c), are used to diagnose and monitor diabetes. These traits are risk factors for cardiovascular disease even below the diabetic threshold, and their study can additionally yield insights into the pathophysiology of type 2 diabetes. To date, a diverse set of genetic approaches have led to the discovery of over 97 loci influencing glycaemic traits. In this review, we will focus on recent advances in the genetic aetiology of glycaemic traits, and the resulting biological insights. We will provide a brief overview of results ranging from common, to low- and rare-frequency variant-trait association studies, studies leveraging the diversity across populations, and studies harnessing the power of genetic and genomic approaches to gain insights into the biological underpinnings of these traits.

The Rotterdam Study: 2018 update on objectives, design and main results

The Rotterdam Study is a prospective cohort study ongoing since 1990 in the city of Rotterdam in The Netherlands. The study targets cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, otolaryngological, locomotor, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. Since 2016, the cohort is being expanded by persons aged 40 years and over. The findings of the Rotterdam Study have been presented in over 1500 research articles and reports (see www.erasmus-epidemiology.nl/rotterdamstudy ). This article gives the rationale of the study and its design. It also presents a summary of the major findings and an update of the objectives and methods.

Single-cell transcriptomics of East-Asian pancreatic islets cells

Single-cell RNA-seq (scRNA-seq) of pancreatic islets have reported on α- and β-cell gene expression in mice and subjects of predominantly European ancestry. We aimed to assess these findings in East-Asian islet-cells. 448 islet-cells were captured from three East-Asian non-diabetic subjects for scRNA-seq. Hierarchical clustering using pancreatic cell lineage genes was used to assign cells into cell-types. Differentially expressed transcripts between α- and β-cells were detected using ANOVA and in silico replications of mouse and human islet cell genes were performed. We identified 118 α, 105 β, 6 δ endocrine cells and 47 exocrine cells. Besides INS and GCG, 26 genes showed differential expression between α- and β-cells. 10 genes showed concordant expression as reported in rodents, while FAM46A was significantly discordant. Comparing our East-Asian data with data from primarily European subjects, we replicated several genes implicated in nuclear receptor activations, acute phase response pathway, glutaryl-CoA/tryptophan degradations and EIF2/AMPK/mTOR signaling. Additionally, we identified protein ubiquitination to be associated among East-Asian β-cells. We report on East-Asian α- and β-cell gene signatures and substantiate several genes/pathways. We identify expression signatures in East-Asian β-cells that perhaps reflects increased susceptibility to cell-death and warrants future validations to fully appreciate their role in East-Asian diabetes pathogenesis.