Genetic Regulation of Adipose Gene Expression and Cardio-Metabolic Traits

Genetic architecture modulates diet-induced hepatic mRNA and miRNA expression profiles in Diversity Outbred mice

Genetic approaches in model organisms have consistently demonstrated that molecular traits such as gene expression are under genetic regulation, similar to clinical traits. The resulting expression quantitative trait loci (eQTL) have revolutionized our understanding of genetic regulation and identified numerous candidate genes for clinically relevant traits. More recently, these analyses have been extended to other molecular traits such as protein abundance, metabolite levels, and miRNA expression. Here, we performed global hepatic eQTL and microRNA expression quantitative trait loci (mirQTL) analysis in a population of Diversity Outbred mice fed two different diets. We identified several key features of eQTL and mirQTL, namely differences in the mode of genetic regulation (cis or trans) between mRNA and miRNA. Approximately 50% of mirQTL are regulated by a trans-acting factor, compared to ∼25% of eQTL. We note differences in the heritability of mRNA and miRNA expression and variance explained by each eQTL or mirQTL. In general, cis-acting variants affecting mRNA or miRNA expression explain more phenotypic variance than trans-acting variants. Finally, we investigated the effect of diet on the genetic architecture of eQTL and mirQTL, highlighting the critical effects of environment on both eQTL and mirQTL. Overall, these data underscore the complex genetic regulation of two well-characterized RNA classes (mRNA and miRNA) that have critical roles in the regulation of clinical traits and disease susceptibility

A Data-Driven Transcriptional Taxonomy of Adipogenic Chemicals to Identify White and Brite Adipogens

BACKGROUND

Chemicals in disparate structural classes activate specific subsets of the transcriptional programs of peroxisome proliferator-activated receptor-γ (PPARγ) to generate adipocytes with distinct phenotypes.

OBJECTIVES

Our objectives were to a) establish a novel classification method to predict PPARγ ligands and modifying chemicals; and b) create a taxonomy to group chemicals on the basis of their effects on PPARγ's transcriptome and downstream metabolic functions. We tested the hypothesis that environmental adipogens highly ranked by the taxonomy, but segregated from therapeutic PPARγ ligands, would induce white but not brite adipogenesis.

METHODS

3T3-L1 cells were differentiated in the presence of 76 chemicals (negative controls, nuclear receptor ligands known to influence adipocyte biology, potential environmental PPARγ ligands). Differentiation was assessed by measuring lipid accumulation. mRNA expression was determined by RNA-sequencing (RNA-Seq) and validated by reverse transcription-quantitative polymerase chain reaction. A novel classification model was developed using an amended random forest procedure. A subset of environmental contaminants identified as strong PPARγ agonists were analyzed by their effects on lipid handling, mitochondrial biogenesis, and cellular respiration in 3T3-L1 cells and human preadipocytes.

RESULTS

We used lipid accumulation and RNA-Seq data to develop a classification system that a) identified PPARγ agonists; and b) sorted chemicals into likely white or brite adipogens. Expression of Cidec was the most efficacious indicator of strong PPARγ activation. 3T3-L1 cells treated with two known environmental PPARγ ligands, tetrabromobisphenol A and triphenyl phosphate, which sorted distinctly from therapeutic ligands, had higher expression of white adipocyte genes but no difference in Pgc1a and Ucp1 expression, and higher fatty acid uptake but not mitochondrial biogenesis. Moreover, cells treated with two chemicals identified as highly ranked PPARγ agonists, tonalide and quinoxyfen, induced white adipogenesis without the concomitant health-promoting characteristics of brite adipocytes in mouse and human preadipocytes.

DISCUSSION

A novel classification procedure accurately identified environmental chemicals as PPARγ ligands distinct from known PPARγ-activating therapeutics.

CONCLUSION

The computational and experimental framework has general applicability to the classification of as-yet uncharacterized chemicals. https://doi.org/10.1289/EHP6886.

Cell-type-specific effects of genetic variation on chromatin accessibility during human neuronal differentiation

Common genetic risk for neuropsychiatric disorders is enriched in regulatory elements active during cortical neurogenesis. However, it remains poorly understood as to how these variants influence gene regulation. To model the functional impact of common genetic variation on the noncoding genome during human cortical development, we performed the assay for transposase accessible chromatin using sequencing (ATAC-seq) and analyzed chromatin accessibility quantitative trait loci (QTL) in cultured human neural progenitor cells and their differentiated neuronal progeny from 87 donors. We identified significant genetic effects on 988/1,839 neuron/progenitor regulatory elements, with highly cell-type and temporally specific effects. A subset (roughly 30%) of chromatin accessibility-QTL were also associated with changes in gene expression. Motif-disrupting alleles of transcriptional activators generally led to decreases in chromatin accessibility, whereas motif-disrupting alleles of repressors led to increases in chromatin accessibility. By integrating cell-type-specific chromatin accessibility-QTL and brain-relevant genome-wide association data, we were able to fine-map and identify regulatory mechanisms underlying noncoding neuropsychiatric disorder risk loci.

Perilipin 5 links mitochondrial uncoupled respiration in brown fat to healthy white fat remodeling and systemic glucose tolerance

Exposure of mice or humans to cold promotes significant changes in brown adipose tissue (BAT) with respect to histology, lipid content, gene expression, and mitochondrial mass and function. Herein we report that the lipid droplet coat protein Perilipin 5 (PLIN5) increases markedly in BAT during exposure of mice to cold. To understand the functional significance of cold-induced PLIN5, we created and characterized gain- and loss-of-function mouse models. Enforcing PLIN5 expression in mouse BAT mimics the effects of cold with respect to mitochondrial cristae packing and uncoupled substrate-driven respiration. PLIN5 is necessary for the maintenance of mitochondrial cristae structure and respiratory function during cold stress. We further show that promoting PLIN5 function in BAT is associated with healthy remodeling of subcutaneous white adipose tissue and improvements in systemic glucose tolerance and diet-induced hepatic steatosis. These observations will inform future strategies that seek to exploit thermogenic adipose tissue as a therapeutic target for type 2 diabetes, obesity, and nonalcoholic fatty liver disease.

Perilipin 5 is a lipid droplet protein that interacts with PGC1α in the nucleus to regulate mitochondrial metabolism. Here the authors use genetically engineered mouse models to determine the physiologic role of Perilipin 5, and show that it regulates mitochondrial adaptations to cold, as well as systemic energy metabolism.

The trans-ancestral genomic architecture of glycemic traits

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

Differentially Expressed Genes and Enriched Signaling Pathways in the Adipose Tissue of Obese People

As the prevalence of obesity increases, so does the occurrence of obesity-related complications, such as cardiovascular and cerebrovascular diseases, diabetes, and some cancers. Increased adipose tissue is the main cause of harm in obesity. To better understand obesity and its related complications, we analyzed the mRNA expression profiles of adipose tissues from 126 patients with obesity and 275 non-obese controls. Using an integrated bioinformatics method, we explored the functions of 113 differentially expressed genes (DEGs) between them. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses revealed that upregulated DEGs were enriched in immune cell chemotaxis, complement-related cascade activation, and various inflammatory signaling pathways, while downregulated DEGs enriched in nutrient metabolism. The CIBERSORT algorithm indicated that an increase in macrophages may be the main cause of adipose tissue inflammation, while decreased γδ T cells reduce sympathetic action, leading to dysregulation of adipocyte thermogenesis. A protein-protein interaction network was constructed using the STRING database, and the top 10 hub genes were identified using the cytoHubba plug-in in Cytoscape. All were confirmed to be obesity-related using a separate dataset. In addition, we identified chemicals related to these hub genes that may contribute to obesity. In conclusion, we have successfully identified several hub genes in the development of obesity, which provide insights into the possible mechanisms controlling obesity and its related complications, as well as potential biomarkers and therapeutic targets for further research.

Progress in Defining the Genetic Contribution to Type 2 Diabetes in Individuals of East Asian Ancestry

PURPOSE OF REVIEW

Prevalence of type 2 diabetes (T2D) and progression of complications differ between worldwide populations. While obesity is a major contributing risk factor, variations in physiological manifestations, e.g., developing T2D at lower body mass index in some populations, suggest other contributing factors. Early T2D genetic associations were mostly discovered in European ancestry populations. This review describes the progression of genetic discoveries associated with T2D in individuals of East Asian ancestry in the last 10 years and highlights the shared genetic susceptibility between the population groups and additional insights into genetic contributions to T2D.

RECENT FINDINGS

Through increased sample size and power, new genetic associations with T2D were discovered in East Asian ancestry populations, often with higher allele frequencies than European ancestry populations. As we continue to generate maps of T2D-associated variants across diverse populations, there will be a critical need to expand and diversify other omics resources to enable integration for clinical translation.

Transcriptomic Changes of Murine Visceral Fat Exposed to Intermittent Hypoxia at Single Cell Resolution

Intermittent hypoxia (IH) is a hallmark of obstructive sleep apnea (OSA) and induces metabolic dysfunction manifesting as inflammation, increased lipolysis and insulin resistance in visceral white adipose tissues (vWAT). However, the cell types and their corresponding transcriptional pathways underlying these functional perturbations are unknown. Here, we applied single nucleus RNA sequencing (snRNA-seq) coupled with aggregate RNA-seq methods to evaluate the cellular heterogeneity in vWAT following IH exposures mimicking OSA. C57BL/6 male mice were exposed to IH and room air (RA) for 6 weeks, and nuclei from vWAT were isolated and processed for snRNA-seq followed by differential expressed gene (DEGs) analyses by cell type, along with gene ontology and canonical pathways enrichment tests of significance. IH induced significant transcriptional changes compared to RA across 14 different cell types identified in vWAT. We identified cell-specific signature markers, transcriptional networks, metabolic signaling pathways, and cellular subpopulation enrichment in vWAT. Globally, we also identify 298 common regulated genes across multiple cellular types that are associated with metabolic pathways. Deconvolution of cell types in vWAT using global RNA-seq revealed that distinct adipocytes appear to be differentially implicated in key aspects of metabolic dysfunction. Thus, the heterogeneity of vWAT and its response to IH at the cellular level provides important insights into the metabolic morbidity of OSA and may possibly translate into therapeutic targets.

Genetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity

Leptin influences food intake by informing the brain about the status of body fat stores. Rare LEP mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in LEP, ZNF800, KLHL31, and ACTL9, and one intergenic variant near KLF14. The missense variant Val94Met (rs17151919) in LEP was common in individuals of African ancestry only, and its association with lower leptin concentrations was specific to this ancestry (P = 2 × 10^-16, n = 3,901). Using in vitro analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting that leptin regulates early adiposity.

Age-induced mitochondrial DNA point mutations are inadequate to alter metabolic homeostasis in response to nutrient challenge

Mitochondrial dysfunction is frequently associated with impairment in metabolic homeostasis and insulin action, and is thought to underlie cellular aging. However, it is unclear whether mitochondrial dysfunction is a cause or consequence of insulin resistance in humans. To determine the impact of intrinsic mitochondrial dysfunction on metabolism and insulin action, we performed comprehensive metabolic phenotyping of the polymerase gamma (PolG) D257A “mutator” mouse, a model known to accumulate supraphysiological mitochondrial DNA (mtDNA) point mutations. We utilized the heterozygous PolG mutator mouse (PolG^+/mut) because it accumulates mtDNA point mutations ~ 500‐fold > wild‐type mice (WT), but fails to develop an overt progeria phenotype, unlike PolG^mut/mut animals. To determine whether mtDNA point mutations induce metabolic dysfunction, we examined male PolG^+/mut mice at 6 and 12 months of age during normal chow feeding, after 24‐hr starvation, and following high‐fat diet (HFD) feeding. No marked differences were observed in glucose homeostasis, adiposity, protein/gene markers of metabolism, or oxygen consumption in muscle between WT and PolG^+/mut mice during any of the conditions or ages studied. However, proteomic analyses performed on isolated mitochondria from 12‐month‐old PolG^+/mut mouse muscle revealed alterations in the expression of mitochondrial ribosomal proteins, electron transport chain components, and oxidative stress‐related factors compared with WT. These findings suggest that mtDNA point mutations at levels observed in mammalian aging are insufficient to disrupt metabolic homeostasis and insulin action in male mice.

A lead candidate functional single nucleotide polymorphism within the WARS2 gene associated with waist-hip-ratio does not alter RNA stability

We have prioritised a single nucleotide polymorphism (SNP) rs2645294 as one candidate functional SNP in the TBX15-WARS2 waist-hip-ratio locus using posterior probability analysis. This SNP is located in the 3' untranslated region of the WARS2 (tryptophanyl tRNA synthetase 2, mitochondrial) gene with which it has an expression quantitative trait in subcutaneous white adipose tissue. We show that transcripts of the WARS2 gene in a human white adipose cell line, heterozygous for the rs2645294 SNP, showed allelic imbalance. We tested whether the rs2645294 SNP altered WARS2 RNA stability using three different methods: actinomycin-D inhibition and RNA decay, mature and nascent RNA analysis and luciferase reporter assays. We found no evidence of a difference in RNA stability between the rs2645294 alleles indicating that the allelic expression imbalance was likely due to transcriptional regulation.

Mapping a Circular RNA-microRNA-mRNA-Signaling Regulatory Axis That Modulates Stemness Properties of Cancer Stem Cell Populations in Colorectal Cancer Spheroid Cells

Spheroidal cancer cell cultures have been used to enrich cancer stem cells (CSC), which are thought to contribute to important clinical features of tumors. This study aimed to map the regulatory networks driven by circular RNAs (circRNAs) in CSC-enriched colorectal cancer (CRC) spheroid cells. The spheroid cells established from two CRC cell lines acquired stemness properties in pluripotency gene expression and multi-lineage differentiation capacity. Genome-wide sequencing identified 1503 and 636 circRNAs specific to the CRC parental and spheroid cells, respectively. In the CRC spheroids, algorithmic analyses unveiled a core network of mRNAs involved in modulating stemness-associated signaling pathways, driven by a circRNA–microRNA (miRNA)–mRNA axis. The two major circRNAs, hsa_circ_0066631 and hsa_circ_0082096, in this network were significantly up-regulated in expression levels in the spheroid cells. The two circRNAs were predicted to target and were experimentally shown to down-regulate miR-140-3p, miR-224, miR-382, miR-548c-3p and miR-579, confirming circRNA sponging of the targeted miRNAs. Furthermore, the affected miRNAs were demonstrated to inhibit degradation of six mRNA targets, viz. ACVR1C/ALK7, FZD3, IL6ST/GP130, SKIL/SNON, SMAD2 and WNT5, in the CRC spheroid cells. These mRNAs encode proteins that are reported to variously regulate the GP130/Stat, Activin/Nodal, TGF-β/SMAD or Wnt/β-catenin signaling pathways in controlling various aspects of CSC stemness. Using the CRC spheroid cell model, the novel circRNA–miRNA–mRNA axis mapped in this work forms the foundation for the elucidation of the molecular mechanisms of the complex cellular and biochemical processes that determine CSC stemness properties of cancer cells, and possibly for designing therapeutic strategies for CRC treatment by targeting CSC.

RIPK1 gene variants associate with obesity in humans and can be therapeutically silenced to reduce obesity in mice

Obesity is a major public health burden worldwide and is characterized by chronic low-grade inflammation driven by the cooperation of the innate immune system and dysregulated metabolism in adipose tissue and other metabolic organs. Receptor-interacting serine/threonine-protein kinase 1 (RIPK1) is a central regulator of inflammatory cell function that coordinates inflammation, apoptosis and necroptosis in response to inflammatory stimuli. Here we show that genetic polymorphisms near the human RIPK1 locus associate with increased RIPK1 gene expression and obesity. We show that one of these single nucleotide polymorphisms is within a binding site for E4BP4 and increases RIPK1 promoter activity and RIPK1 gene expression in adipose tissue. Therapeutic silencing of RIPK1 in vivo in a mouse model of diet-induced obesity dramatically reduces fat mass, total body weight and improves insulin sensitivity, while simultaneously reducing macrophage and promoting invariant natural killer T cell accumulation in adipose tissue. These findings demonstrate that RIPK1 is genetically associated with obesity, and reducing RIPK1 expression is a potential therapeutic approach to target obesity and related diseases.

Sex differences in human adipose tissue gene expression and genetic regulation involve adipogenesis

Sex differences in adipose tissue distribution and function are associated with sex differences in cardiometabolic disease. While many studies have revealed sex differences in adipocyte cell signaling and physiology, there is a relative dearth of information regarding sex differences in transcript abundance and regulation. We investigated sex differences in subcutaneous adipose tissue transcriptional regulation using omic-scale data from ∼3000 geographically and ethnically diverse human samples. We identified 162 genes with robust sex differences in expression. Differentially expressed genes were implicated in oxidative phosphorylation and adipogenesis. We further determined that sex differences in gene expression levels could be related to sex differences in the genetics of gene expression regulation. Our analyses revealed sex-specific genetic associations, and this finding was replicated in a study of 98 inbred mouse strains. The genes under genetic regulation in human and mouse were enriched for oxidative phosphorylation and adipogenesis. Enrichment analysis showed that the associated genetic loci resided within binding motifs for adipogenic transcription factors (e.g., PPARG and EGR1). We demonstrated that sex differences in gene expression could be influenced by sex differences in genetic regulation for six genes (e.g., FADS1 and MAP1B). These genes exhibited dynamic expression patterns during adipogenesis and robust expression in mature human adipocytes. Our results support a role for adipogenesis-related genes in subcutaneous adipose tissue sex differences in the genetic and environmental regulation of gene expression.

Identification of Reproducible BCL11A Alterations in Schizophrenia Through Individual-Level Prediction of Coexpression

Previous studies have provided evidence for an alteration of genetic coexpression in schizophrenia (SCZ). However, such analyses have thus far lacked biological specificity for individual genes, which may be critical for identifying illness-relevant effects. Therefore, we applied machine learning to identify gene-specific coexpression differences at the individual subject level and compared these between individuals with SCZ, bipolar disorder, major depressive disorder (MDD), autism spectrum disorder (ASD), and healthy controls. Utilizing transcriptome-wide gene expression data from 21 independent datasets, comprising a total of 9509 participants, we identified a reproducible decrease of BCL11A coexpression across 4 SCZ datasets that showed diagnostic specificity for SCZ when compared with ASD and MDD. We further demonstrate that individual-level coexpression differences can be combined in multivariate coexpression scores that show reproducible illness classification across independent datasets in SCZ and ASD. This study demonstrates that machine learning can capture gene-specific coexpression differences at the individual subject level for SCZ and identify novel biomarker candidates.

Genetic Architecture Modulates Diet-Induced Hepatic mRNA and miRNA Expression Profiles in Diversity Outbred Mice

Genetic approaches in model organisms have consistently demonstrated that molecular traits such as gene expression are under genetic regulation, similar to clinical traits. The resulting expression quantitative trait loci (eQTL) have revolutionized our understanding of genetic regulation and identified numerous candidate genes for clinically relevant traits. More recently, these analyses have been extended to other molecular traits such as protein abundance, metabolite levels, and miRNA expression. Here, we performed global hepatic eQTL and microRNA expression quantitative trait loci (mirQTL) analysis in a population of Diversity Outbred mice fed two different diets. We identified several key features of eQTL and mirQTL, namely differences in the mode of genetic regulation (cis or trans) between mRNA and miRNA. Approximately 50% of mirQTL are regulated by a trans-acting factor, compared to ∼25% of eQTL. We note differences in the heritability of mRNA and miRNA expression and variance explained by each eQTL or mirQTL. In general, cis-acting variants affecting mRNA or miRNA expression explain more phenotypic variance than trans-acting variants. Lastly, we investigated the effect of diet on the genetic architecture of eQTL and mirQTL, highlighting the critical effects of environment on both eQTL and mirQTL. Overall, these data underscore the complex genetic regulation of two well-characterized RNA classes (mRNA and miRNA) that have critical roles in the regulation of clinical traits and disease susceptibility.

Assessing exposure effects on gene expression

In observational genomics data sets, there is often confounding of the effect of an exposure on gene expression. To adjust for confounding when estimating the exposure effect, a common approach involves including potential confounders as covariates with the exposure in a regression model of gene expression. However, when the exposure and confounders interact to influence gene expression, the fitted regression model does not necessarily estimate the overall effect of the exposure. Using inverse probability weighting (IPW) or the parametric g-formula in these instances is straightforward to apply and yields consistent effect estimates. IPW can readily be integrated into a genomics data analysis pipeline with upstream data processing and normalization, while the g-formula can be implemented by making simple alterations to the regression model. The regression, IPW, and g-formula approaches to exposure effect estimation are compared herein using simulations; advantages and disadvantages of each approach are explored. The methods are applied to a case study estimating the effect of current smoking on gene expression in adipose tissue.

ACE2 expression in adipose tissue is associated with COVID-19 cardio-metabolic risk factors and cell type composition

COVID-19 severity has varied widely, with demographic and cardio-metabolic factors increasing risk of severe reactions to SARS-CoV-2 infection, but the underlying mechanisms for this remain uncertain. We investigated phenotypic and genetic factors associated with subcutaneous adipose tissue expression of Angiotensin I Converting Enzyme 2 ( ACE2 ), which has been shown to act as a receptor for SARS-CoV-2 cellular entry. In a meta-analysis of three independent studies including up to 1,471 participants, lower adipose tissue ACE2 expression was associated with adverse cardio-metabolic health indices including type 2 diabetes (T2D) and obesity status, higher serum fasting insulin and BMI, and lower serum HDL levels (P<5.32x10 -4 ). ACE2 expression levels were also associated with estimated proportions of cell types in adipose tissue; lower ACE2 expression was associated with a lower proportion of microvascular endothelial cells (P=4.25x10 -4 ) and higher macrophage proportion (P=2.74x10 -5 ), suggesting a link to inflammation. Despite an estimated heritability of 32%, we did not identify any proximal or distal genetic variants (eQTLs) associated with adipose tissue ACE2 expression. Our results demonstrate that at-risk individuals have lower background ACE2 levels in this highly relevant tissue. Further studies will be required to establish how this may contribute to increased COVID-19 severity.

Multi-SNP mediation intersection-union test

SUMMARY

Tens of thousands of reproducibly identified GWAS (Genome-Wide Association Studies) variants, with the vast majority falling in non-coding regions resulting in no eventual protein products, call urgently for mechanistic interpretations. Although numerous methods exist, there are few, if any methods, for simultaneously testing the mediation effects of multiple correlated SNPs via some mediator (e.g. the expression of a gene in the neighborhood) on phenotypic outcome. We propose multi-SNP mediation intersection-union test (SMUT) to fill in this methodological gap. Our extensive simulations demonstrate the validity of SMUT as well as substantial, up to 92%, power gains over alternative methods. In addition, SMUT confirmed known mediators in a real dataset of Finns for plasma adiponectin level, which were missed by many alternative methods. We believe SMUT will become a useful tool to generate mechanistic hypotheses underlying GWAS variants, facilitating functional follow-up.

AVAILABILITY AND IMPLEMENTATION

The R package SMUT is publicly available from CRAN at https://CRAN.R-project.org/package=SMUT.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Colocalization of GWAS and eQTL signals at loci with multiple signals identifies additional candidate genes for body fat distribution

Integration of genome-wide association study (GWAS) signals with expression quantitative trait loci (eQTL) studies enables identification of candidate genes. However, evaluating whether nearby signals may share causal variants, termed colocalization, is affected by the presence of allelic heterogeneity, different variants at the same locus impacting the same phenotype. We previously identified eQTL in subcutaneous adipose tissue from 770 participants in the Metabolic Syndrome in Men (METSIM) study and detected 15 eQTL signals that colocalized with GWAS signals for waist-hip ratio adjusted for body mass index (WHRadjBMI) from the Genetic Investigation of Anthropometric Traits consortium. Here, we reevaluated evidence of colocalization using two approaches, conditional analysis and the Bayesian test COLOC, and show that providing COLOC with approximate conditional summary statistics at multi-signal GWAS loci can reconcile disagreements in colocalization classification between the two tests. Next, we performed conditional analysis on the METSIM subcutaneous adipose tissue data to identify conditionally distinct or secondary eQTL signals. We used the two approaches to test for colocalization with WHRadjBMI GWAS signals and evaluated the differences in colocalization classification between the two tests. Through these analyses, we identified four GWAS signals colocalized with secondary eQTL signals for FAM13A, SSR3, GRB14 and FMO1. Thus, at loci with multiple eQTL and/or GWAS signals, analyzing each signal independently enabled additional candidate genes to be identified.

Systems Genetics for Mechanistic Discovery in Heart Diseases

Cardiovascular diseases are the leading cause of death worldwide. Complex diseases with highly heterogenous disease progression among patient populations, cardiovascular diseases feature multifactorial contributions from both genetic and environmental stressors. Despite significant effort utilizing multiple approaches from molecular biology to genome-wide association studies, the genetic landscape of cardiovascular diseases, particularly for the nonfamilial forms of heart failure, is still poorly understood. In the past decade, systems-level approaches based on omics technologies have become an important approach for the study of complex traits in large populations. These advances create opportunities to integrate genetic variation with other biological layers to identify and prioritize candidate genes, understand pathogenic pathways, and elucidate gene-gene and gene-environment interactions. In this review, we will highlight some of the recent progress made using systems genetics approaches to uncover novel mechanisms and molecular bases of cardiovascular pathophysiological manifestations. The key technology and data analysis platforms necessary to implement systems genetics will be described, and the current major challenges and future directions will also be discussed. For complex cardiovascular diseases, such as heart failure, systems genetics represents a powerful strategy to obtain mechanistic insights and to develop individualized diagnostic and therapeutic regiments, paving the way for precision cardiovascular medicine.

RSPO3 impacts body fat distribution and regulates adipose cell biology in vitro

Fat distribution is an independent cardiometabolic risk factor. However, its molecular and cellular underpinnings remain obscure. Here we demonstrate that two independent GWAS signals at RSPO3, which are associated with increased body mass index-adjusted waist-to-hip ratio, act to specifically increase RSPO3 expression in subcutaneous adipocytes. These variants are also associated with reduced lower-body fat, enlarged gluteal adipocytes and insulin resistance. Based on human cellular studies RSPO3 may limit gluteofemoral adipose tissue (AT) expansion by suppressing adipogenesis and increasing gluteal adipocyte susceptibility to apoptosis. RSPO3 may also promote upper-body fat distribution by stimulating abdominal adipose progenitor (AP) proliferation. The distinct biological responses elicited by RSPO3 in abdominal versus gluteal APs in vitro are associated with differential changes in WNT signalling. Zebrafish carrying a nonsense rspo3 mutation display altered fat distribution. Our study identifies RSPO3 as an important determinant of peripheral AT storage capacity.

Identification of type 2 diabetes loci in 433,540 East Asian individuals

Meta-analyses of genome-wide association studies (GWAS) have identified more than 240 loci that are associated with type 2 diabetes (T2D)1,2; however, most of these loci have been identified in analyses of individuals with European ancestry. Here, to examine T2D risk in East Asian individuals, we carried out a meta-analysis of GWAS data from 77,418 individuals with T2D and 356,122 healthy control individuals. In the main analysis, we identified 301 distinct association signals at 183 loci, and across T2D association models with and without consideration of body mass index and sex, we identified 61 loci that are newly implicated in predisposition to T2D. Common variants associated with T2D in both East Asian and European populations exhibited strongly correlated effect sizes. Previously undescribed associations include signals in or near GDAP1, PTF1A, SIX3, ALDH2, a microRNA cluster, and genes that affect the differentiation of muscle and adipose cells3. At another locus, expression quantitative trait loci at two overlapping T2D signals affect two genes-NKX6-3 and ANK1-in different tissues4-6. Association studies in diverse populations identify additional loci and elucidate disease-associated genes, biology, and pathways.

Transcription Factor KLF14 and Metabolic Syndrome

Metabolic syndrome (MetSyn) is a combination of metabolic abnormalities that lead to the development of cardiovascular disease (CVD) and Type 2 Diabetes (T2D). Although various criteria for defining MetSyn exist, common abnormalities include abdominal obesity, elevated serum triglyceride, insulin resistance, and blood glucose, decreased high-density lipoprotein cholesterol (HDL-C), and hypertension. MetSyn prevalence has been increasing with the rise of obesity worldwide, with significantly higher prevalence in women compared with men and in Hispanics compared with Whites. Affected individuals are at a higher risk of developing T2D (5-fold) and CVD (2-fold). Heritability estimates for individual components of MetSyn vary between 40 and 70%, suggesting a strong contribution of an individual's genetic makeup to disease pathology. The advent of next-generation sequencing technologies has enabled large-scale genome-wide association studies (GWAS) into the genetics underlying MetSyn pathogenesis. Several such studies have implicated the transcription factor KLF14, a member of the Krüpple-like factor family (KLF), in the development of metabolic diseases, including obesity, insulin resistance, and T2D. How KLF14 regulates these metabolic traits and increases the risk of developing T2D, atherosclerosis, and liver dysfunction is still unknown. There have been some debate and controversial results with regards to its expression profile and functionality in various tissues, and a systematic review of current knowledge on KLF14 is lacking. Here, we summarize the research progress made in understanding the function of KLF14 and describe common attributes of its biochemical, physiological, and pathophysiological roles. We also discuss the current challenges in understanding the role of KLF14 in metabolism and provide suggestions for future directions.

Genome-wide association study of adipocyte lipolysis in the GENetics of adipocyte lipolysis (GENiAL) cohort

OBJECTIVES

Lipolysis, hydrolysis of triglycerides to fatty acids in adipocytes, is tightly regulated, poorly understood, and, if perturbed, can lead to metabolic diseases including obesity and type 2 diabetes. The goal of this study was to identify the genetic regulators of lipolysis and elucidate their molecular mechanisms.

METHODS

Adipocytes from abdominal subcutaneous adipose tissue biopsies were isolated and were incubated without (spontaneous lipolysis) or with a catecholamine (stimulated lipolysis) to analyze lipolysis. DNA was extracted and genome-wide genotyping and imputation conducted. After quality control, 939 samples with genetic and lipolysis data were available. Genome-wide association studies of spontaneous and stimulated lipolysis were conducted. Subsequent in vitro gene expression analyses were used to identify candidate genes and explore their regulation of adipose tissue biology.

RESULTS

One locus on chromosome 19 demonstrated genome-wide significance with spontaneous lipolysis. 60 loci showed suggestive associations with spontaneous or stimulated lipolysis, of which many influenced both traits. In the chromosome 19 locus, only HIF3A was expressed in the adipocytes and displayed genotype-dependent gene expression. HIF3A knockdown in vitro increased lipolysis and the expression of key lipolysis-regulating genes.

CONCLUSIONS

In conclusion, we identified a genetic regulator of spontaneous lipolysis and provided evidence of HIF3A as a novel key regulator of lipolysis in subcutaneous adipocytes as the mechanism through which the locus influences adipose tissue biology.

FAM13A affects body fat distribution and adipocyte function

Genetic variation in the FAM13A (Family with Sequence Similarity 13 Member A) locus has been associated with several glycemic and metabolic traits in genome-wide association studies (GWAS). Here, we demonstrate that in humans, FAM13A alleles are associated with increased FAM13A expression in subcutaneous adipose tissue (SAT) and an insulin resistance-related phenotype (e.g. higher waist-to-hip ratio and fasting insulin levels, but lower body fat). In human adipocyte models, knockdown of FAM13A in preadipocytes accelerates adipocyte differentiation. In mice, Fam13a knockout (KO) have a lower visceral to subcutaneous fat (VAT/SAT) ratio after high-fat diet challenge, in comparison to their wild-type counterparts. Subcutaneous adipocytes in KO mice show a size distribution shift toward an increased number of smaller adipocytes, along with an improved adipogenic potential. Our results indicate that GWAS-associated variants within the FAM13A locus alter adipose FAM13A expression, which in turn, regulates adipocyte differentiation and contribute to changes in body fat distribution.

Inferring Regulatory Networks From Mixed Observational Data Using Directed Acyclic Graphs

Construction of regulatory networks using cross-sectional expression profiling of genes is desired, but challenging. The Directed Acyclic Graph (DAG) provides a general framework to infer causal effects from observational data. However, most existing DAG methods assume that all nodes follow the same type of distribution, which prohibit a joint modeling of continuous gene expression and categorical variables. We present a new mixed DAG (mDAG) algorithm to infer the regulatory pathway from mixed observational data containing both continuous variables (e.g. expression of genes) and categorical variables (e.g. categorical phenotypes or single nucleotide polymorphisms). Our method can identify upstream causal factors and downstream effectors closely linked to a variable and generate hypotheses for causal direction of regulatory pathways. We propose a new permutation method to test the conditional independence of variables of mixed types, which is the key for mDAG. We also utilize an L₁ regularization in mDAG to ensure it can recover a large sparse DAG with limited sample size. We demonstrate through extensive simulations that mDAG outperforms two well-known methods in recovering the true underlying DAG. We apply mDAG to a cross-sectional immunological study of Chlamydia trachomatis infection and successfully infer the regularity network of cytokines. We also apply mDAG to a large cohort study, generating sensible mechanistic hypotheses underlying plasma adiponectin level. The R package mDAG is publicly available from CRAN at https://CRAN.R-project.org/package=mDAG.

Single-cell analysis of human adipose tissue identifies depot and disease specific cell types

The complex relationship between metabolic disease risk and body fat distribution in humans involves cellular characteristics which are specific to body fat compartments. Here we show depot-specific differences in the stromal vascual fraction of visceral and subcutaneous adipose tissue by performing single-cell RNA sequencing of tissue specimen from obese individuals. We characterize multiple immune cells, endothelial cells, fibroblasts, adipose and hematopoietic stem cell progenitors. Subpopulations of adipose-resident immune cells are metabolically active and associated with metabolic disease status and those include a population of potential dysfunctional CD8+ T cells expressing metallothioneins. We identify multiple types of adipocyte progenitors that are common across depots, including a subtype enriched in individuals with type 2 diabetes. Depot-specific analysis reveals a class of adipocyte progenitors unique to visceral adipose tissue, which shares common features with beige preadipocytes. Our human single-cell transcriptome atlas across fat depots provides a resource to dissect functional genomics of metabolic disease.

Sex Differences in Genomic Drivers of Adipose Distribution and Related Cardiometabolic Disorders: Opportunities for Precision Medicine

This review focuses on the human genetics, epidemiology, and molecular pathophysiology of sex differences in central obesity, adipose distribution, and related cardiometabolic disorders. Distribution of fat is important for cardiometabolic health, with peripheral fat depots having a protective effect and central visceral fat depots conferring a detrimental effect on health. There are important sex differences in fat distribution that are masked when studying body mass index as a measure of obesity. From epidemiological, murine, and in vitro studies, several mechanisms have been proposed to explain the sex differences in adipose distribution, including sex hormonal effects, cell-intrinsic properties, and the microenvironment in fat depots. More recently, human genetics have revealed hundreds of loci for central obesity providing disruptive opportunities for mechanistic discoveries and clinical translation. A striking feature is that over one-third of these loci have reproducible but poorly understood sexual dimorphic associations with central obesity, most having stronger effects in women. Understanding the genetic and molecular mechanisms of adipose distribution and its sexual dimorphism in humans provides a unique opportunity to promote the use of precision medicine for early identification of at-risk individuals, and the development of novel therapeutic strategies for central obesity and related cardiometabolic disorders.

Functional Screening of Candidate Causal Genes for Insulin Resistance in Human Preadipocytes and Adipocytes

Rationale: Genome-wide association studies have identified genetic loci associated with insulin resistance (IR) but pinpointing the causal genes of a risk locus has been challenging. Objective: To identify candidate causal genes for IR, we screened regional and biologically plausible genes (16 in total) near the top 10 IR-loci in risk-relevant cell types, namely preadipocytes and adipocytes. Methods and Results: We generated 16 human Simpson-Golabi-Behmel syndrome preadipocyte knockout lines each with a single IR-gene knocked out by lentivirus-mediated CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 system. We evaluated each gene knockout by screening IR-relevant phenotypes in the 3 insulin-sensitizing mechanisms, including adipogenesis, lipid metabolism, and insulin signaling. We performed genetic analyses using data on the genotype-tissue expression portal expression quantitative trait loci database and accelerating medicines partnership type 2 diabetes mellitus Knowledge Portal to evaluate whether candidate genes prioritized by our in vitro studies were expression quantitative trait loci genes in human subcutaneous adipose tissue, and whether expression of these genes is associated with risk of IR, type 2 diabetes mellitus, and cardiovascular diseases. We further validated the functions of 3 new adipose IR genes by overexpression-based phenotypic rescue in the Simpson-Golabi-Behmel syndrome preadipocyte knockout lines. Twelve genes, PPARG, IRS-1, FST, PEPD, PDGFC, MAP3K1, GRB14, ARL15, ANKRD55, RSPO3, COBLL1, and LYPLAL1, showed diverse phenotypes in the 3 insulin-sensitizing mechanisms, and the first 7 of these genes could affect all the 3 mechanisms. Five out of 6 expression quantitative trait loci genes are among the top candidate causal genes and the abnormal expression levels of these genes (IRS-1, GRB14, FST, PEPD, and PDGFC) in human subcutaneous adipose tissue could be associated with increased risk of IR, type 2 diabetes mellitus, and cardiovascular disease. Phenotypic rescue by overexpression of the candidate causal genes (FST, PEPD, and PDGFC) in the Simpson-Golabi-Behmel syndrome preadipocyte knockout lines confirmed their function in adipose IR. Conclusions: Twelve genes showed diverse phenotypes indicating differential roles in insulin sensitization, suggesting mechanisms bridging the association of their genomic loci with IR. We prioritized PPARG, IRS-1, GRB14, MAP3K1, FST, PEPD, and PDGFC as top candidate genes. Our work points to novel roles for FST, PEPD, and PDGFC in adipose tissue, with consequences for cardiometabolic diseases.

Natural human genetic variation determines basal and inducible expression of PM20D1, an obesity-associated gene

PM20D1 is a candidate thermogenic enzyme in mouse fat, with its expression cold-induced and enriched in brown versus white adipocytes. Thiazolidinedione (TZD) antidiabetic drugs, which activate the peroxisome proliferator-activated receptor-γ (PPARγ) nuclear receptor, are potent stimuli for adipocyte browning yet fail to induce Pm20d1 expression in mouse adipocytes. In contrast, PM20D1 is one of the most strongly TZD-induced transcripts in human adipocytes, although not in cells from all individuals. Two putative PPARγ binding sites exist near the gene's transcription start site (TSS) in human but not mouse adipocytes. The -4 kb upstream site falls in a segmental duplication of a nearly identical intronic region +2.5 kb downstream of the TSS, and this duplication occurred in the primate lineage and not in other mammals, like mice. PPARγ binding and gene activation occur via this upstream duplicated site, thus explaining the species difference. Furthermore, this functional upstream PPARγ site exhibits genetic variation among people, with 1 SNP allele disrupting a PPAR response element and giving less activation by PPARγ and TZDs. In addition to this upstream variant that determines PPARγ regulation of PM20D1 in adipocytes, distinct variants downstream of the TSS have strong effects on PM20D1 expression in human fat as well as other tissues. A haplotype of 7 tightly linked downstream SNP alleles is associated with very low PMD201 expression and correspondingly high DNA methylation at the TSS. These PM20D1 low-expression variants may account for human genetic associations in this region with obesity as well as neurodegenerative diseases.

Adipose Tissue Gene Expression Associations Reveal Hundreds of Candidate Genes for Cardiometabolic Traits

Genome-wide association studies (GWASs) have identified thousands of genetic loci associated with cardiometabolic traits including type 2 diabetes (T2D), lipid levels, body fat distribution, and adiposity, although most causal genes remain unknown. We used subcutaneous adipose tissue RNA-seq data from 434 Finnish men from the METSIM study to identify 9,687 primary and 2,785 secondary cis-expression quantitative trait loci (eQTL; <1 Mb from TSS, FDR < 1%). Compared to primary eQTL signals, secondary eQTL signals were located further from transcription start sites, had smaller effect sizes, and were less enriched in adipose tissue regulatory elements compared to primary signals. Among 2,843 cardiometabolic GWAS signals, 262 colocalized by LD and conditional analysis with 318 transcripts as primary and conditionally distinct secondary cis-eQTLs, including some across ancestries. Of cardiometabolic traits examined for adipose tissue eQTL colocalizations, waist-hip ratio (WHR) and circulating lipid traits had the highest percentage of colocalized eQTLs (15% and 14%, respectively). Among alleles associated with increased cardiometabolic GWAS risk, approximately half (53%) were associated with decreased gene expression level. Mediation analyses of colocalized genes and cardiometabolic traits within the 434 individuals provided further evidence that gene expression influences variant-trait associations. These results identify hundreds of candidate genes that may act in adipose tissue to influence cardiometabolic traits.

Open Chromatin Profiling in Adipose Tissue Marks Genomic Regions with Functional Roles in Cardiometabolic Traits

Identifying the regulatory mechanisms of genome-wide association study (GWAS) loci affecting adipose tissue has been restricted due to limited characterization of adipose transcriptional regulatory elements. We profiled chromatin accessibility in three frozen human subcutaneous adipose tissue needle biopsies and preadipocytes and adipocytes from the Simpson Golabi-Behmel Syndrome (SGBS) cell strain using an assay for transposase-accessible chromatin (ATAC-seq). We identified 68,571 representative accessible chromatin regions (peaks) across adipose tissue samples (FDR < 5%). GWAS loci for eight cardiometabolic traits were enriched in these peaks (P < 0.005), with the strongest enrichment for waist-hip ratio. Of 110 recently described cardiometabolic GWAS loci colocalized with adipose tissue eQTLs, 59 loci had one or more variants overlapping an adipose tissue peak. Annotated variants at the SNX10 waist-hip ratio locus and the ATP2A1-SH2B1 body mass index locus showed allelic differences in regulatory assays. These adipose tissue accessible chromatin regions elucidate genetic variants that may alter adipose tissue function to impact cardiometabolic traits.

Human Genetics of Obesity and Type 2 Diabetes Mellitus: Past, Present, and Future

Type 2 diabetes mellitus (T2D) and obesity already represent 2 of the most prominent risk factors for cardiovascular disease, and are destined to increase in importance given the global changes in lifestyle. Ten years have passed since the first round of genome-wide association studies for T2D and obesity. During this decade, we have witnessed remarkable developments in human genetics. We have graduated from the despair of candidate gene-based studies that generated few consistently replicated genotype-phenotype associations, to the excitement of an exponential harvest of loci robustly associated with medical outcomes through ever larger genome-wide association study meta-analyses. As well as discovering hundreds of loci, genome-wide association studies have provided transformative insights into the genetic architecture of T2D and other complex traits, highlighting the extent of polygenicity and the tiny effect sizes of many common risk alleles. Genome-wide association studies have also provided a critical starting point for discovering new biology relevant to these traits. Expectations are high that these discoveries will foster development of more effective strategies for intervention, through optimization of precision medicine approaches. In this article, we review current knowledge and provide suggestions for the next steps in genetic research for T2D and obesity. We focus on four areas relevant to precision medicine: genetic architecture, pharmacogenetics and other gene-environment interactions, mechanistic inference, and drug development. As we describe, the genetic architecture of complex traits has major implications for the prospects of precision medicine, rendering some anticipated approaches decidedly unrealistic. We highlight obstacles to the translation of human genetic findings into mechanism inference but are optimistic that, as these are overcome, there is untapped potential for novel drugs and more effective strategies for treating and preventing T2D and obesity.

Exome-Derived Adiponectin-Associated Variants Implicate Obesity and Lipid Biology

Circulating levels of adiponectin, an adipocyte-secreted protein associated with cardiovascular and metabolic risk, are highly heritable. To gain insights into the biology that regulates adiponectin levels, we performed an exome array meta-analysis of 265,780 genetic variants in 67,739 individuals of European, Hispanic, African American, and East Asian ancestry. We identified 20 loci associated with adiponectin, including 11 that had been reported previously (p < 2 × 10^-7). Comparison of exome array variants to regional linkage disequilibrium (LD) patterns and prior genome-wide association study (GWAS) results detected candidate variants (r² > .60) spanning as much as 900 kb. To identify potential genes and mechanisms through which the previously unreported association signals act to affect adiponectin levels, we assessed cross-trait associations, expression quantitative trait loci in subcutaneous adipose, and biological pathways of nearby genes. Eight of the nine loci were also associated (p < 1 × 10^-4) with at least one obesity or lipid trait. Candidate genes include PRKAR2A, PTH1R, and HDAC9, which have been suggested to play roles in adipocyte differentiation or bone marrow adipose tissue. Taken together, these findings provide further insights into the processes that influence circulating adiponectin levels.

Genetic Regulation of Enoyl-CoA Hydratase Domain-Containing 3 in Adipose Tissue Determines Insulin Sensitivity in African Americans and Europeans

Insulin resistance (IR) is a harbinger of type 2 diabetes (T2D) and partly determined by genetic factors. However, genetically regulated mechanisms of IR remain poorly understood. Using gene expression, genotype, and insulin sensitivity data from the African American Genetics of Metabolism and Expression (AAGMEx) cohort, we performed transcript-wide correlation and expression quantitative trait loci (eQTL) analyses to identify IR-correlated cis-regulated transcripts (cis-eGenes) in adipose tissue. These IR-correlated cis-eGenes were tested in the European ancestry individuals in the Metabolic Syndrome in Men (METSIM) cohort for trans-ethnic replication. Comparison of Matsuda index-correlated transcripts in AAGMEx with the METSIM study identified significant correlation of 3,849 transcripts, with concordant direction of effect for 97.5% of the transcripts. cis-eQTL for 587 Matsuda index-correlated genes were identified in both cohorts. Enoyl-CoA hydratase domain-containing 3 (ECHDC3) was the top-ranked Matsuda index-correlated cis-eGene. Expression levels of ECHDC3 were positively correlated with Matsuda index, and regulated by cis-eQTL, rs34844369 being the top cis-eSNP in AAGMEx. Silencing of ECHDC3 in adipocytes significantly reduced insulin-stimulated glucose uptake and Akt Ser⁴⁷³ phosphorylation. RNA sequencing analysis identified 691 differentially expressed genes in ECHDC3-knockdown adipocytes, which were enriched in γ-linolenate biosynthesis, and known IR genes. Thus, our studies elucidated genetic regulatory mechanisms of IR and identified genes and pathways in adipose tissue that are mechanistically involved in IR.

Cell-Type Heterogeneity in Adipose Tissue Is Associated with Complex Traits and Reveals Disease-Relevant Cell-Specific eQTLs

Adipose tissue is an important endocrine organ with a role in many cardiometabolic diseases. It is comprised of a heterogeneous collection of cell types that can differentially impact disease phenotypes. Cellular heterogeneity can also confound -omic analyses but is rarely taken into account in analysis of solid-tissue transcriptomes. Here, we investigate cell-type heterogeneity in two population-level subcutaneous adipose-tissue RNA-seq datasets (TwinsUK, n = 766 and the Genotype-Tissue Expression project [GTEx], n = 326) by estimating the relative proportions of four distinct cell types (adipocytes, macrophages, CD4+ T cells, and micro-vascular endothelial cells). We find significant cellular heterogeneity within and between the TwinsUK and GTEx adipose datasets. We find that adipose cell-type composition is heritable and confirm the positive association between adipose-resident macrophage proportion and obesity (high BMI), but we find a stronger BMI-independent association with dual-energy X-ray absorptiometry (DXA) derived body-fat distribution traits. We benchmark the impact of adipose-tissue cell composition on a range of standard analyses, including phenotype-gene expression association, co-expression networks, and cis-eQTL discovery. Our results indicate that it is critical to account for cell-type composition when combining adipose transcriptome datasets in co-expression analysis and in differential expression analysis with obesity-related traits. We applied gene expression by cell-type proportion interaction models (G × Cell) to identify 26 cell-type-specific expression quantitative trait loci (eQTLs) in 20 genes, including four autoimmune disease genome-wide association study (GWAS) loci. These results identify cell-specific eQTLs and demonstrate the potential of in silico deconvolution of bulk tissue to identify cell-type-restricted regulatory variants.

Mouse genome-wide association and systems genetics identifies Lhfp as a regulator of bone mass

Bone mineral density (BMD) is a strong predictor of osteoporotic fracture. It is also one of the most heritable disease-associated quantitative traits. As a result, there has been considerable effort focused on dissecting its genetic basis. Here, we performed a genome-wide association study (GWAS) in a panel of inbred strains to identify associations influencing BMD. This analysis identified a significant (P = 3.1 x 10⁻¹²) BMD locus on Chromosome 3@52.5 Mbp that replicated in two separate inbred strain panels and overlapped a BMD quantitative trait locus (QTL) previously identified in a F2 intercross. The association mapped to a 300 Kbp region containing four genes; Gm2447, Gm20750, Cog6, and Lhfp. Further analysis found that Lipoma HMGIC Fusion Partner (Lhfp) was highly expressed in bone and osteoblasts. Furthermore, its expression was regulated by a local expression QTL (eQTL), which overlapped the BMD association. A co-expression network analysis revealed that Lhfp was strongly connected to genes involved in osteoblast differentiation. To directly evaluate its role in bone, Lhfp deficient mice (Lhfp^-/-) were created using CRISPR/Cas9. Consistent with genetic and network predictions, bone marrow stromal cells (BMSCs) from Lhfp^-/- mice displayed increased osteogenic differentiation. Lhfp^-/- mice also had elevated BMD due to increased cortical bone mass. Lastly, we identified SNPs in human LHFP that were associated (P = 1.2 x 10⁻⁵) with heel BMD. In conclusion, we used GWAS and systems genetics to identify Lhfp as a regulator of osteoblast activity and bone mass.

Osteoporosis is a common, chronic disease characterized by low bone mineral density (BMD) that puts millions of Americans at high risk of fracture. Variation in BMD in the general population is, in large part, determined by genetic factors. To identify novel genes influencing BMD, we performed a genome-wide association study in a panel of inbred mouse strains. We identified a locus on Chromosome 3 strongly associated with BMD. Using a combination of systems genetics approaches, we connected the expression of the Lhfp gene with BMD-associated genetic variants and predicted it influenced BMD by altering the activity of bone-forming osteoblasts. Using mice deficient in Lhfp, we demonstrated that Lhfp negatively regulates bone formation and BMD. These data suggest that inhibiting Lhfp may represent a novel therapeutic strategy to increase BMD and decrease the risk of fracture.

Genomic annotation of disease-associated variants reveals shared functional contexts

Variation in non-coding DNA, encompassing gene regulatory regions such as enhancers and promoters, contributes to risk for complex disorders, including type 2 diabetes. While genome-wide association studies have successfully identified hundreds of type 2 diabetes loci throughout the genome, the vast majority of these reside in non-coding DNA, which complicates the process of determining their functional significance and level of priority for further study. Here we review the methods used to experimentally annotate these non-coding variants, to nominate causal variants and to link them to diabetes pathophysiology. In recent years, chromatin profiling, massively parallel sequencing, high-throughput reporter assays and CRISPR gene editing technologies have rapidly become indispensable tools. Rather than treating individual variants in isolation, we discuss the importance of accounting for context, both genetic (such as flanking DNA sequence) and environmental (such as cellular state or environmental exposure). Incorporating these features shows promise in terms of revealing biologically convergent molecular signatures across distant and seemingly unrelated loci. Studying regulatory elements in the proper context will be crucial for interpreting the functional significance of disease-associated variants and applying the resulting knowledge to improve patient care.

Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF <5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants.

Epigenome-wide association in adipose tissue from the METSIM cohort

Most epigenome-wide association studies to date have been conducted in blood. However, metabolic syndrome is mediated by a dysregulation of adiposity and therefore it is critical to study adipose tissue in order to understand the effects of this syndrome on epigenomes. To determine if natural variation in DNA methylation was associated with metabolic syndrome traits, we profiled global methylation levels in subcutaneous abdominal adipose tissue. We measured association between 32 clinical traits related to diabetes and obesity in 201 people from the Metabolic Syndrome in Men cohort. We performed epigenome-wide association studies between DNA methylation levels and traits, and identified associations for 13 clinical traits in 21 loci. We prioritized candidate genes in these loci using expression quantitative trait loci, and identified 18 high confidence candidate genes, including known and novel genes associated with diabetes and obesity traits. Using methylation deconvolution, we examined which cell types may be mediating the associations, and concluded that most of the loci we identified were specific to adipocytes. We determined whether the abundance of cell types varies with metabolic traits, and found that macrophages increased in abundance with the severity of metabolic syndrome traits. Finally, we developed a DNA methylation-based biomarker to assess type 2 diabetes risk in adipose tissue. In conclusion, our results demonstrate that profiling DNA methylation in adipose tissue is a powerful tool for understanding the molecular effects of metabolic syndrome on adipose tissue, and can be used in conjunction with traditional genetic analyses to further characterize this disorder.

The E3 ligase MARCH5 is a PPARγ target gene that regulates mitochondria and metabolism in adipocytes

Mitochondrial dynamics refers to the constant remodeling of mitochondrial populations by multiple cellular pathways that help maintain mitochondrial health and function. Disruptions in mitochondrial dynamics often lead to mitochondrial dysfunction, which is frequently associated with disease in rodents and humans. Consistent with this, obesity is associated with reduced mitochondrial function in white adipose tissue, partly via alterations in mitochondrial dynamics. Several proteins, including the E3 ubiquitin ligase membrane-associated RING-CH-type finger 5 (MARCH5), are known to regulate mitochondrial dynamics; however, the role of these proteins in adipocytes has been poorly studied. Here, we show that MARCH5 is regulated by peroxisome proliferator-activated receptor-γ (PPARγ) during adipogenesis and is correlated with fat mass across a panel of genetically diverse mouse strains, in ob/ob mice, and in humans. Furthermore, manipulation of MARCH5 expression in vitro and in vivo alters mitochondrial function, affects cellular metabolism, and leads to differential regulation of several metabolic genes. Thus our data demonstrate an association between mitochondrial dynamics and metabolism that defines MARCH5 as a critical link between these interconnected pathways.

KLF14 potentiates oxidative adaptation via modulating HO-1 signaling in castrate-resistant prostate cancer

Insights into the mechanisms by which key factors stimulate cell growth under androgen-depleted conditions is a premise to the development of effective treatments with clinically significant activity in patients with castration-resistant prostate cancer (CRPC). Herein, we report that, the expression of Krüppel-like factor 14 (KLF14), a master transcription factor in the regulation of lipid metabolism, was significantly induced in castration-insensitive PCa cells and tumor tissues from a mouse xenograft model of CRPC. KLF14 upregulation in PCa cells, which was stimulated upstream by oxidative stress, was dependent on multiple pathways including PI3K/AKT, p42/p44 MAPK, AMPK and PKC pathways. By means of ectopic overexpression and genetic inactivation, we further show that KLF14 promoted cell growth via positive regulation of the antioxidant response under androgen-depleted conditions. Mechanistically, KLF14 coupled to p300 and CBP to enhance the transcriptional activation of HMOX1, the gene encoding the antioxidative enzyme heme oxygenase-1 (HO-1) that is one of the most important mechanisms of cell adaptation to stress. Transient knockdown of HMOX1 is sufficient to overcome KLF14 overexpression-potentiated PCa cell growth under androgen-depleted conditions. From a pharmacological standpoint, in vivo administration of ZnPPIX (a specific inhibitor of HO-1) effectively attenuates castration-resistant progression in the mouse xenograft model, without changing KLF14 level. Together, these results provide comprehensive insight into the KLF14-dependent regulation of antioxidant response and subsequent pathogenesis of castration resistance and indicate that interventions targeting the KLF14/HO-1 adaptive mechanism should be further explored for CRPC treatment.

Deciphering the Emerging Complexities of Molecular Mechanisms at GWAS Loci

Genome-wide association studies (GWASs) have identified thousands of loci associated with hundreds of complex diseases and traits, and progress is being made toward elucidating the causal variants and genes underlying these associations. Functional characterization of mechanisms at GWAS loci is a multi-faceted challenge. Challenges include linkage disequilibrium and allelic heterogeneity at each locus, the noncoding nature of most loci, and the time and cost needed for experimentally evaluating the potential mechanistic contributions of genes and variants. As GWAS sample sizes increase, more loci are identified, and the complexities of individual loci emerge. Loci can consist of multiple association signals, each of which can reflect the influence of multiple variants, inseparable by association analyses. Each signal within a locus can influence the same or different target genes. Experimental studies of genes and variants can differ on the basis of cell type, cellular environment, or other context-specific variables. In this review, we describe the complexity of mechanisms at GWAS loci-including multiple signals, multiple variants, and/or multiple genes-and the implications these complexities hold for experimental study design and interpretation of GWAS mechanisms.

Adipose Tissue Transferrin and Insulin Resistance

Context

Excessive body iron stores are a risk factor for decreased insulin sensitivity (SI) and diabetes. We hypothesized that transcriptional dysregulation of genes involved in iron metabolism in adipocytes causes insulin resistance.

Objective and Design

To define the genetic regulation of iron metabolism and its role in SI, we used gene expression, genotype, and SI data from an African American cohort (N = 256). Replication studies were performed in independent European ancestry cohorts. In vitro studies in human adipocytes were performed to define the role of a selected gene in causing insulin resistance.

Results

Among 62 transcripts representing iron homeostasis genes, expression of 30 in adipose tissue were correlated with SI. Transferrin (TF) and ferritin heavy polypeptide were most positively and negatively associated with SI, respectively. These observations were replicated in two independent European ancestry adipose data sets. The strongest cis-regulatory variant for TF expression (rs6785596; P = 7.84 × 10-18) was identified in adipose but not muscle or liver tissue. Variants significantly affected the normal relationship of serum ferritin to insulin resistance. Knockdown of TF in differentiated Simpson-Golabi-Behmel syndrome adipocytes by short hairpin RNA decreased intracellular iron, reduced maximal insulin-stimulated glucose uptake, and reduced Akt phosphorylation. Knockdown of TF caused differential expression of 465 genes, including genes involved in glucose transport, mitochondrial function, Wnt-pathway/ SI, chemokine activity, and obesity. Iron chelation recapitulated key changes in the expression profile induced by TF knockdown.

Conclusion

Genetic regulation of TF expression in adipose tissue plays a novel role in regulating SI.

Gene regulation in the 3D genome

The spatial organization of the genome is essential for the precise control of gene expression. Recent advances in sequencing and imaging technologies allow us to explore the 3D genome and its relationship to gene regulation at an unprecedented scale. In this review, we provide an overview of lessons learned from studying the chromatin structure and their implications in communications between gene promoters and distal cis-regulatory elements, such as enhancers. We first review the current knowledge of general genome organization, followed by the importance of chromatin folding in gene regulation. Next, we proceed to a brief survey of the recently developed chromosome conformation capture technologies, as well as most widely adopted read-outs from such data. We then introduce two emerging models that offer explanations regarding how distal enhancers achieve transcriptional control of target genes in the 3D genome. Last, we discuss the promising prospects of leveraging knowledge in chromatin spatial organization for studying complex diseases and traits.

Identification and functional analysis of glycemic trait loci in the China Health and Nutrition Survey

To identify genetic contributions to type 2 diabetes (T2D) and related glycemic traits (fasting glucose, fasting insulin, and HbA1c), we conducted genome-wide association analyses (GWAS) in up to 7,178 Chinese subjects from nine provinces in the China Health and Nutrition Survey (CHNS). We examined patterns of population structure within CHNS and found that allele frequencies differed across provinces, consistent with genetic drift and population substructure. We further validated 32 previously described T2D- and glycemic trait-loci, including G6PC2 and SIX3-SIX2 associated with fasting glucose. At G6PC2, we replicated a known fasting glucose-associated variant (rs34177044) and identified a second signal (rs2232326), a low-frequency (4%), probably damaging missense variant (S324P). A variant within the lead fasting glucose-associated signal at SIX3-SIX2 co-localized with pancreatic islet expression quantitative trait loci (eQTL) for SIX3, SIX2, and three noncoding transcripts. To identify variants functionally responsible for the fasting glucose association at SIX3-SIX2, we tested five candidate variants for allelic differences in regulatory function. The rs12712928-C allele, associated with higher fasting glucose and lower transcript expression level, showed lower transcriptional activity in reporter assays and increased binding to GABP compared to the rs12712928-G, suggesting that rs12712928-C contributes to elevated fasting glucose levels by disrupting an islet enhancer, resulting in reduced gene expression. Taken together, these analyses identified multiple loci associated with glycemic traits across China, and suggest a regulatory mechanism at the SIX3-SIX2 fasting glucose GWAS locus.

Regulatory variants at KLF14 influence type 2 diabetes risk via a female-specific effect on adipocyte size and body composition

Individual risk of type 2 diabetes (T2D) is modified by perturbations to the mass, distribution and function of adipose tissue. To investigate the mechanisms underlying these associations, we explored the molecular, cellular and whole-body effects of T2D-associated alleles near KLF14. We show that KLF14 diabetes-risk alleles act in adipose tissue to reduce KLF14 expression and modulate, in trans, the expression of 385 genes. We demonstrate, in human cellular studies, that reduced KLF14 expression increases pre-adipocyte proliferation but disrupts lipogenesis, and in mice, that adipose tissue-specific deletion of Klf14 partially recapitulates the human phenotype of insulin resistance, dyslipidemia and T2D. We show that carriers of the KLF14 T2D risk allele shift body fat from gynoid stores to abdominal stores and display a marked increase in adipocyte cell size, and that these effects on fat distribution, and the T2D association, are female specific. The metabolic risk associated with variation at this imprinted locus depends on the sex both of the subject and of the parent from whom the risk allele derives.

The TMAO-Producing Enzyme Flavin-Containing Monooxygenase 3 Regulates Obesity and the Beiging of White Adipose Tissue

Emerging evidence suggests that microbes resident in the human intestine represent a key environmental factor contributing to obesity-associated disorders. Here, we demonstrate that the gut microbiota-initiated trimethylamine N-oxide (TMAO)-generating pathway is linked to obesity and energy metabolism. In multiple clinical cohorts, systemic levels of TMAO were observed to strongly associate with type 2 diabetes. In addition, circulating TMAO levels were associated with obesity traits in the different inbred strains represented in the Hybrid Mouse Diversity Panel. Further, antisense oligonucleotide-mediated knockdown or genetic deletion of the TMAO-producing enzyme flavin-containing monooxygenase 3 (FMO3) conferred protection against obesity in mice. Complimentary mouse and human studies indicate a negative regulatory role for FMO3 in the beiging of white adipose tissue. Collectively, our studies reveal a link between the TMAO-producing enzyme FMO3 and obesity and the beiging of white adipose tissue.