A fine-mapping study of central obesity loci incorporating functional annotation and imputation

Aging reveals a sex-dependent susceptibility of sarcospan-deficient mice to cardiometabolic disease

Numerous genes including sarcospan (SSPN) have been designated as obesity-susceptibility genes by human genome-wide association studies. Variants in the SSPN locus have been linked with sex-dependent obesity-associated traits; however, this association has not been investigated in vivo. To delineate the role SSPN plays in regulating metabolism with potential to impact cardiac function, we subjected young and aged global SSPN-deficient (SSPN-/-) male and female mice to obesogenic conditions (60% fat diet). We hypothesized that loss of SSPN combined with metabolic stress would increase susceptibility of mice to cardiometabolic disease. Baseline and end-point assessments of several anthropometric parameters were performed including weight, glucose tolerance, and fat distribution of mice fed control (CD) and high-fat (HFD) diet. Doppler echocardiography was used to monitor cardiac function. White adipose and cardiac tissues were assessed for inflammation by histological, gene expression, and cytokine analysis. Overall, SSPN deficiency protected both sexes and ages from diet-induced obesity, with a greater effect in females. SSPN-/- HFD mice gained less weight than wild-type (WT) cohorts, while SSPN-/- CD groups increased weight. Furthermore, aged SSPN-/- mice developed glucose intolerance regardless of diet. Echocardiography showed preserved systolic function for all groups; however, aged SSPN-/- males exhibited significant increases in left ventricular mass (CD) and signs of diastolic dysfunction (HFD). Cytokine analysis revealed significantly increased IL-1α and IL-17Α in white adipose tissue from young SSPN-/- male mice, which may be protective from diet-induced obesity. Overall, these studies suggest that several sex-dependent mechanisms influence the role SSPN plays in metabolic responses that become evident with age.NEW & NOTEWORTHY Young and aged sarcospan (SSPN)-deficient mice were examined to assess the role of SSPN in obesity and cardiometabolic disease. Both sexes displayed a "leaner" phenotype in response to high-fat diet (HFD). Notably, several sex differences were identified in aged SSPN-deficient mice: 1) females developed glucose intolerance (control and HFD) and 2) males exhibited increased left ventricular mass (control) and diastolic dysfunction (HFD). Therefore, we conclude that SSPN exerts a sex-dependent influence on obesity-associated diseases.

echolocatoR: an automated end-to-end statistical and functional genomic fine-mapping pipeline

SUMMARY

echolocatoR integrates a diverse suite of statistical and functional fine-mapping tools to identify, test enrichment in, and visualize high-confidence causal consensus variants in any phenotype. It requires minimal input from users (a summary statistics file), can be run in a single R function, and provides extensive access to relevant datasets (e.g. reference linkage disequilibrium panels, quantitative trait loci, genome-wide annotations, cell-type-specific epigenomics), thereby enabling rapid, robust and scalable end-to-end fine-mapping investigations.

AVAILABILITY AND IMPLEMENTATION

echolocatoR is an open-source R package available through GitHub under the GNU General Public License (Version 3) license: https://github.com/RajLabMSSM/echolocatoR.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Established and emerging strategies to crack the genetic code of obesity

Tremendous progress has been made in the genetic elucidation of obesity over the past two decades, driven largely by technological, methodological and organizational innovations. Current strategies for identifying obesity-predisposing loci/genes, including cytogenetics, linkage analysis, homozygosity mapping, admixture mapping, candidate gene studies, genome-wide association studies, custom genotyping arrays, whole-exome sequencing and targeted exome sequencing, have achieved differing levels of success, and the identified loci in aggregate explain only a modest fraction of the estimated heritability of obesity. This review outlines the successes and limitations of these approaches and proposes novel strategies, including the use of exceptionally large sample sizes, the study of diverse ethnic groups and deep phenotypes and the application of innovative methods and study designs, to identify the remaining obesity-predisposing genes. The use of both established and emerging strategies has the potential to crack the genetic code of obesity in the not-too-distant future. The resulting knowledge is likely to yield improvements in obesity prediction, prevention and care.