Epigenomic and Transcriptomic Prioritization of Candidate Obesity-Risk Regulatory GWAS SNPs

CABLES1 expression is reduced in human subcutaneous adipose tissue in obesity and type 2 diabetes but may not directly impact adipocyte glucose and lipid metabolism

Cdk5 and Abl enzyme substrate 1 (CABLES1) is a cell cycle regulator that has previously been identified as a candidate gene for obesity-related phenotypes, but little is known about its role in adipose tissue metabolism. In this study, we explore the role of CABLES1 in obesity and type 2 diabetes (T2D) in human subcutaneous adipose tissue (SAT). We performed gene expression analysis of SAT obtained from subjects with and without T2D, and from a second validation cohort consisting of subjects without T2D. We used CRISPR/Cas9 genome editing to perform CABLES1 loss-of-function studies in human primary preadipocytes and assessed them functionally after differentiation. CABLES1 gene expression in SAT was decreased in T2D by almost 25%, and inversely associated with insulin resistance markers and hyperglycaemia. mRNA levels were reduced with increasing BMI and negatively correlated with obesity markers. We found that adipocytes are likely the main CABLES1-expressing cell type in SAT, but CABLES1 depletion in adipocytes caused no phenotypical changes in regards to differentiation, glucose uptake, or expression of key genes of adipocyte function. These findings suggest that CABLES1 gene expression in SAT might be altered in obesity and T2D as a consequence of metabolic dysregulation rather than being a causal factor.

Assessing efficiency of fine-mapping obesity-associated variants through leveraging ancestry architecture and functional annotation using PAGE and UKBB cohorts

Inadequate representation of non-European ancestry populations in genome-wide association studies (GWAS) has limited opportunities to isolate functional variants. Fine-mapping in multi-ancestry populations should improve the efficiency of prioritizing variants for functional interrogation. To evaluate this hypothesis, we leveraged ancestry architecture to perform comparative GWAS and fine-mapping of obesity-related phenotypes in European ancestry populations from the UK Biobank (UKBB) and multi-ancestry samples from the Population Architecture for Genetic Epidemiology (PAGE) consortium with comparable sample sizes. In the investigated regions with genome-wide significant associations for obesity-related traits, fine-mapping in our ancestrally diverse sample led to 95% and 99% credible sets (CS) with fewer variants than in the European ancestry sample. Lead fine-mapped variants in PAGE regions had higher average coding scores, and higher average posterior probabilities for causality compared to UKBB. Importantly, 99% CS in PAGE loci contained strong expression quantitative trait loci (eQTLs) in adipose tissues or harbored more variants in tighter linkage disequilibrium (LD) with eQTLs. Leveraging ancestrally diverse populations with heterogeneous ancestry architectures, coupled with functional annotation, increased fine-mapping efficiency and performance, and reduced the set of candidate variants for consideration for future functional studies. Significant overlap in genetic causal variants across populations suggests generalizability of genetic mechanisms underpinning obesity-related traits across populations.

Non-coding RNAs: The link between maternal malnutrition and offspring metabolism

Early life nutrition is associated with the development and metabolism in later life, which is known as the Developmental Origin of Health and Diseases (DOHaD). Epigenetics have been proposed as an important explanation for this link between early life malnutrition and long-term diseases. Non-coding RNAs (ncRNAs) may play a role in this epigenetic programming. The expression of ncRNAs (such as long non-coding RNA H19, microRNA-122, and circular RNA-SETD2) was significantly altered in specific tissues of offspring exposed to maternal malnutrition. Changes in these downstream targets of ncRNAs lead to abnormal development and metabolism. This review aims to summarize the existing knowledge on ncRNAs linking the maternal nutrition condition and offspring metabolic diseases, such as obesity, type 2 diabetes (T2D) and non-alcoholic fatty liver disease (NAFLD).

Risks and rewards of big-data in epigenomics research: an interview with Melanie Ehrlich

Melanie Ehrlich, PhD, is a professor in the Tulane Cancer Center, the Tulane Center for Medical Bioinformatics and Genomics and the Hayward Human Genetics Program at Tulane Medical School, New Orleans, LA. She obtained her PhD in molecular biology in 1971 from the State University of New York at Stony Brook and completed postdoctoral research at Albert Einstein College of Medicine in 1972. She has been working on various aspects of epigenetics, starting with DNA methylation, since 1973. Her group made many first findings about DNA methylation (see below). For example, in 1982 and 1983, in collaboration with Charles Gehrke at the University of Missouri, she was the first to report tissue-specific and cancer-specific differences in overall DNA methylation in humans. In 1985, Xian-Yang Zhang and Richard Wang in her lab discovered a class of human DNA sequences specifically hypomethylated in sperm. In 1998, her group was the first to describe extensive losses of DNA methylation in pericentromeric and centromeric DNA repeats in human cancer. Her lab's many publications on the prevalence of both DNA hypermethylation and hypomethylation in the same cancers brought needed balance to our understanding of the epigenetics of cancer and to its clinical implications [1]. Besides working on cancer epigenetics, her research group has helped elucidate cytogenetic and gene expression abnormalities in the immunodeficiency, centromeric and facial anomalies (ICF) syndrome, a rare recessive disease often caused by mutations in DNMT3B. Her group also studied the epigenetics and transcriptomics of facioscapulohumeral muscular dystrophy (FSHD), whose disease locus is a tandem 3.3-kb repeat at subtelomeric 4q (that happens to be hypomethylated in ICF DNA [2]). Her study of FSHD has taken her in the direction of muscle (skeletal muscle, heart and aorta) epigenetics [3-6]. Recently, she has led research that applies epigenetics much more rigorously than usual to the evaluation of genetic variants from genome-wide association studies (GWAS) of osteoporosis and obesity. In continued collaboration with Sriharsa Pradhan at New England Biolabs and Michelle Lacey at Tulane University, she has compared 5-hydroxymethylcytosine and 5-methylcytosine clustering in various human tissues [7] and is studying myoblast methylomes that they generated by a new high-resolution enzymatic technique (enzymatic methyl-seq).