The Ups and Downs of Insulin Resistance and Type 2 Diabetes: Lessons from Genomic Analyses in Humans

Common and ethnic-specific derangements in skeletal muscle transcriptome associated with obesity

BACKGROUND

Obesity is a common disease with a higher prevalence among African Americans. Obesity alters cellular function in many tissues, including skeletal muscle, and is a risk factor for many life-threatening diseases, including cardiovascular disease and diabetes. The similarities and differences in molecular mechanisms that may explain ethnic disparities in obesity between African and European ancestry individuals have not been studied.

METHODS

In this study, data from transcriptome-wide analyses on skeletal muscle tissues from well-powered human cohorts were used to compare genes and biological pathways affected by obesity in European and African ancestry populations. Data on obesity-induced differentially expressed transcripts and GWAS-identified SNPs were integrated to prioritize target genes for obesity-associated genetic variants.

RESULTS

Linear regression analysis in the FUSION (European, N = 301) and AAGMEx (African American, N = 256) cohorts identified a total of 2569 body mass index (BMI)-associated transcripts (q < 0.05), of which 970 genes (at p < 0.05) are associated in both cohorts, and the majority showed the same direction of effect on BMI. Biological pathway analyses, including over-representation and gene-set enrichment analyses, identified enrichment of protein synthesis pathways (e.g., ribosomal function) and the ceramide signaling pathway in both cohorts among BMI-associated down- and up-regulated transcripts, respectively. A comparison using the IPA-tool suggested the activation of inflammation pathways only in Europeans with obesity. Interestingly, these analyses suggested repression of the mitochondrial oxidative phosphorylation pathway in Europeans but showed its activation in African Americans. Integration of SNP-to-Gene analyses-predicted target genes for obesity-associated genetic variants (GWAS-identified SNPs) and BMI-associated transcripts suggested that these SNPs might cause obesity by altering the expression of 316 critical target genes (e.g., GRB14) in the muscle.

CONCLUSIONS

This study provides a replication of obesity-associated transcripts and biological pathways in skeletal muscle across ethnicities, but also identifies obesity-associated processes unique in either African or European ancestry populations.

miRDM-rfGA: Genetic algorithm-based identification of a miRNA set for detecting type 2 diabetes

BACKGROUND

Type 2 diabetes mellitus (T2DM) affects approximately 451 million adults globally. In this study, we identified the optimal combination of marker candidates for detecting T2DM using miRNA-Seq data from 95 samples including T2DM and healthy individuals.

METHODS

We utilized the genetic algorithm (GA) in the discovery of an optimal miRNA biomarker set. We discovered miRNA subsets consisting of three miRNAs for detecting T2DM by random forest-based GA (miRDM-rfGA) as a feature selection algorithm and created six GA parameter settings and three settings using traditional feature selection methods (F-test and Lasso). We then evaluated the prediction performance to detect T2DM in the miRNA subsets derived from each setting.

RESULTS

The miRNA subset in setting 5 using miRDM-rfGA performed the best in detecting T2DM (mean AUROC = 0.92). Target mRNA identification and functional enrichment analysis of the best miRNA subset (hsa-miR-125b-5p, hsa-miR-7-5p, and hsa-let-7b-5p) validated that this combination was involved in T2DM. We also confirmed that the targeted genes were negatively correlated with the clinical variables related to T2DM in the BxD mouse genetic reference population database.

CONCLUSIONS

Using GA in miRNA-Seq data, we identified the optimal miRNA biomarker set for T2DM detection. GA can be a useful tool for biomarker discovery and drug-target identification.

Multi-omic integration reveals cell-type-specific regulatory networks of insulin resistance in distinct ancestry populations

Our knowledge of the cell-type-specific mechanisms of insulin resistance remains limited. To dissect the cell-type-specific molecular signatures of insulin resistance, we performed a multiscale gene network analysis of adipose and muscle tissues in African and European ancestry populations. In adipose tissues, a comparative analysis revealed ethnically conserved cell-type signatures and two adipocyte subtype-enriched modules with opposite insulin sensitivity responses. The modules enriched for adipose stem and progenitor cells as well as immune cells showed negative correlations with insulin sensitivity. In muscle tissues, the modules enriched for stem cells and fibro-adipogenic progenitors responded to insulin sensitivity oppositely. The adipocyte and muscle fiber-enriched modules shared cellular-respiration-related genes but had tissue-specific rearrangements of gene regulations in response to insulin sensitivity. Integration of the gene co-expression and causal networks further pinpointed key drivers of insulin resistance. Together, this study revealed the cell-type-specific transcriptomic networks and signaling maps underlying insulin resistance in major glucose-responsive tissues. A record of this paper's transparent peer review process is included in the supplemental information.

Shared Genetic Basis and Causal Relationship Between Television Watching, Breakfast Skipping and Type 2 Diabetes: Evidence From a Comprehensive Genetic Analysis

Background

Epidemiological investigations have established unhealthy lifestyles, such as excessive leisurely sedentary behavior (especially TV/television watching) and breakfast skipping, increase the risk of type 2 diabetes (T2D), but the causal relationship is unclear. We aimed to understand how single nucleotide variants contribute to the co-occurrence of unhealthy lifestyles and T2D, thereby providing meaningful insights into disease mechanisms.

Methods

Combining summary statistics from genome-wide association studies (GWAS) on TV watching (N = 422218), breakfast skipping (N = 193860) and T2D (N = 159208) in European pedigrees, we conducted comprehensive pairwise genetic analysis, including high-definition likelihood (HDL-method), cross-phenotype association studies (CPASSOC), GWAS-eQTL colocalization analysis and transcriptome-wide association studies (TWAS), to understand the genetic overlap between them. We also performed bidirectional two-sample Mendelian randomization (MR) analysis for causal inference using genetic instrumental variables, and two-step MR mediation analysis was used to assess any effects explained by body mass index, lipid traits and glycemic traits.

Results

HDL-method showed that T2D shared a strong genetic correlation with TV watching (rg = 0.26; P = 1.63×10-29) and skipping breakfast (rg = 0.15; P =2.02×10-6). CPASSOC identifies eight independent SNPs shared between T2D and TV watching, including one novel shared locus. TWAS and CPASSOC showed that shared genes were enriched in lung, esophageal, adipose, and thyroid tissues and highlighted potential shared regulatory pathways for lipoprotein metabolism, pancreatic β-cell function, cellular senescence and multi-mediator factors. MR showed TV watching had a causal effect on T2D (βIVW = 0.629, PIVW = 1.80×10-10), but no significant results were observed between breakfast skipping and T2D. Mediation analysis provided evidence that body mass index, fasting glucose, hemoglobin A1c and high-density lipoprotein are potential factors that mediate the causal relationship between TV and T2D.

Conclusions

Our findings provide strong evidence of shared genetics and causation between TV watching and T2D and facilitate our identification of common genetic architectures shared between them.

Integrative Analysis of Glucometabolic Traits, Adipose Tissue DNA Methylation, and Gene Expression Identifies Epigenetic Regulatory Mechanisms of Insulin Resistance and Obesity in African Americans

Decline in insulin sensitivity due to dysfunction of adipose tissue (AT) is one of the earliest pathogenic events in type 2 diabetes. We hypothesize that differential DNA methylation (DNAm) controls insulin sensitivity and obesity by modulating transcript expression in AT. Integrating AT DNAm profiles with transcript profile data measured in a cohort of 230 African Americans (AAs) from the African American Genetics of Metabolism and Expression cohort, we performed cis-expression quantitative trait methylation (cis-eQTM) analysis to identify epigenetic regulatory loci for glucometabolic trait-associated transcripts. We identified significantly associated cytosine-guanine dinucleotide regions for 82 transcripts (false discovery rate [FDR]-P < 0.05). The strongest eQTM locus was observed for the proopiomelanocortin (POMC; ρ = -0.632, P = 4.70 × 10^-27) gene. Epigenome-wide association studies (EWAS) further identified 155, 46, and 168 cytosine-guanine dinucleotide regions associated (FDR-P < 0.05) with the Matsuda index, S_I, and BMI, respectively. Intersection of EWAS, transcript level to trait association, and eQTM results, followed by causal inference test identified significant eQTM loci for 23 genes that were also associated with Matsuda index, S_I, and/or BMI in EWAS. These associated genes include FERMT3, ITGAM, ITGAX, and POMC In summary, applying an integrative multiomics approach, our study provides evidence for DNAm-mediated regulation of gene expression at both previously identified and novel loci for many key AT transcripts influencing insulin resistance and obesity.

Genome Wide Association Study Identifies the HMGCS2 Locus to be Associated With Chlorthalidone Induced Glucose Increase in Hypertensive Patients

Background

Thiazide and thiazide‐like diuretics are first‐line medications for treating uncomplicated hypertension. However, their use has been associated with adverse metabolic events, including hyperglycemia and incident diabetes mellitus, with incompletely understood mechanisms. Our goal was to identify genomic variants associated with thiazide‐like diuretic/chlorthalidone‐induced glucose change.

Methods and Results

Genome‐wide analysis of glucose change after treatment with chlorthalidone was performed by race among the white (n=175) and black (n=135) participants from the PEAR‐2 (Pharmacogenomic Evaluation of Antihypertensive Responses‐2). Single‐nucleotide polymorphisms with P<5×10⁻⁸ were further prioritized using in silico analysis based on their expression quantitative trait loci function. Among blacks, an intronic single‐nucleotide polymorphism (rs9943291) in the HMGCS2 was associated with increase in glucose levels following chlorthalidone treatment (ß=12.5; P=4.17×10⁻⁸). G‐allele carriers of HMGCS2 had higher glucose levels (glucose change=+16.29 mg/dL) post chlorthalidone treatment compared with noncarriers of G allele (glucose change=+2.80 mg/dL). This association was successfully replicated in an independent replication cohort of hydrochlorothiazide‐treated participants from the PEAR study (ß=5.54; P=0.023). A meta‐analysis of the 2 studies was performed by race in Meta‐Analysis Helper, where this single‐nucleotide polymorphism, rs9943291, was genome‐wide significant with a meta‐analysis P value of 3.71×10⁻⁸. HMGCS2, a part of the HMG‐CoA synthase family, is important for ketogenesis and cholesterol synthesis pathways that are essential in glucose homeostasis.

Conclusions

These results suggest that HMGCS2 is a promising candidate gene involved in chlorthalidone and Hydrochlorothiazide (HCTZ)‐induced glucose change. This may provide insights into the mechanisms involved in thiazide‐induced hyperglycemia that may ultimately facilitate personalized approaches to antihypertensive selection for hypertension treatment.

Clinical Trial Registration

URL: http://www.clinicaltrials.gov. Unique identifiers: NCT00246519 and NCT01203852.

Transcriptional Regulatory Mechanisms in Adipose and Muscle Tissue Associated with Composite Glucometabolic Phenotypes

OBJECTIVE

Tissue-specific gene expression is associated with individual metabolic measures. However, these measures may not reflect the true but latent underlying biological phenotype. This study reports gene expression associations with multidimensional glucometabolic characterizations of obesity, glucose homeostasis, and lipid traits.

METHODS

Factor analysis was computed by using orthogonal rotation to construct composite phenotypes (CPs) from 23 traits in 256 African Americans without diabetes. Genome-wide transcript expression data from adipose and muscle were tested for association with CPs, and expression quantitative trait loci (eQTLs) were identified by associations between cis-acting single-nucleotide polymorphisms (SNPs) and gene expression.

RESULTS

The factor analysis identified six CPs. CPs 1 through 6 individually explained 34%, 12%, 9%, 8%, 6%, and 5% of the variation in 23 glucometabolic traits studied. There were 3,994 and 929 CP-associated transcripts identified in adipose and muscle tissue, respectively; CP2 had the largest number of associated transcripts. Pathway analysis identified multiple canonical pathways from the CP-associated transcripts. In adipose and muscle, significant cis-eQTLs were identified for 558 and 164 CP-associated transcripts (q-value < 0.01), respectively.

CONCLUSIONS

Adipose and muscle transcripts comprehensively define pathways involved in regulating glucometabolic disorders. Cis-eQTLs for CP-associated genes may act as primary causal determinants of glucometabolic phenotypes by regulating transcription of key genes.

Obesity Associated Modulation of miRNA and Co-Regulated Target Transcripts in Human Adipose Tissue of Non-Diabetic Subjects

OBJECTIVE

Micro RNAs (miRNAs) are a class of non-coding regulatory RNAs. We performed a transcriptome-wide analysis of subcutaneous adipose tissue and in vitro studies to identify miRNAs and co-regulated target transcripts associated with insulin sensitivity (SI) and obesity in human.

METHODS

We selected 20 insulin-resistant (IR, SI=2.0±0.7) and 20 insulin-sensitive (IS, SI=7.2±2.3) subjects from a cohort of 117 metabolically characterized non-diabetic Caucasians for comparison.

RESULTS

After global profiling, 3 miRNAs had marginally different expressions between IR and IS subjects. A total of 14 miRNAs were significantly correlated with %fat mass, body mass index (BMI), or SI. The qRT-PCR validated the correlation of miR-148a-3p with BMI (r=-0.70, P=2.73X10(-6)). MiRNA target filtering analysis identified DNA methyltransferase 1 (DNMT1) as one of the target genes of miR-148a-3p. DNMT1 expression in adipose tissue was positively correlated with BMI (r=0.47, p=8.42X10(-7)) and was inversely correlated with miR-148a-3p (r=-0.34). Differentiation of SGBS preadipocytes showed up-regulation of miR-148a-3p and down-regulation of DNMT1 in differentiated adipocytes. After transfecting miR-148a-3p mimics into HeLa-S3 cells, DNMT1 was down-regulated, while transfection of adipose stem cells with miR-148a-3p inhibitor up-regulated DNMT1.

CONCLUSIONS

Our results indicate that miR-148a-3pmediated regulation of DNMT1 expression may play a mechanistic role in obesity.

Tissue-Specific and Genetic Regulation of Insulin Sensitivity-Associated Transcripts in African Americans

Integrative multiomics analyses of adipose and muscle tissue transcripts, S, and genotypes revealed novel genetic regulatory mechanisms of insulin resistance in African Americans.