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

2019 ◽  
Vol 28 (24) ◽  
pp. 4161-4172 ◽  
Author(s):  
Ying Wu ◽  
K Alaine Broadaway ◽  
Chelsea K Raulerson ◽  
Laura J Scott ◽  
Calvin Pan ◽  
...  
Keyword(s):  
Adipose Tissue ◽  
Candidate Genes ◽  
Subcutaneous Adipose Tissue ◽  
Genome Wide Association Study ◽  
Fat Distribution ◽  
Conditional Analysis ◽  
The Metabolic Syndrome ◽  
Genome Wide ◽  
Causal Variants ◽  
Subcutaneous Adipose

Abstract 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.

scholarly journals Archaic adaptive introgression in TBX15/WARS2

2015 ◽  
Author(s):  
Fernando Racimo ◽  
David Gokhman ◽  
Matteo Fumagalli ◽  
Amy Ko ◽  
Torben Hansen ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Adipose Tissue ◽  
Subcutaneous Adipose Tissue ◽  
Fat Distribution ◽  
Geographic Region ◽  
Adaptive Introgression ◽  
Genome Wide ◽  
Divergent Haplotype ◽  
Subcutaneous Adipose ◽  
Genome Wide Scan

AbstractA recent study conducted the first genome-wide scan for selection in Inuit from Greenland using SNP chip data. Here, we report that selection in the region with the second most extreme signal of positive selection in Greenlandic Inuit favored a deeply divergent haplotype that is closely related to the sequence in the Denisovan genome, and was likely introgressed from an archaic population. The region contains two genes, WARS2 and TBX15, and has previously been associated with adipose tissue differentiation and body-fat distribution in humans. We show that the adaptively introgressed allele has been under selection in a much larger geographic region than just Greenland. Furthermore, it is associated with changes in expression of WARS2 and TBX15 in multiple tissues including the adrenal gland and subcutaneous adipose tissue, and with regional DNA methylation changes in TBX15.

scholarly journals Multifaceted genome-wide study identifies novel regulatory loci for body mass index in Indians

2019 ◽  
Author(s):  
Anil K Giri ◽  
Gauri Prasad ◽  
Khushdeep Bandesh ◽  
Vaisak Parekatt ◽  
Anubha Mahajan ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Adipose Tissue ◽  
Body Mass ◽  
Subcutaneous Adipose Tissue ◽  
Regulatory Elements ◽  
Specific Gene ◽  
Genome Wide ◽  
Obesity Phenotype ◽  
Methylation Patterns ◽  
Subcutaneous Adipose

AbstractObesity, a risk factor for various human diseases originates through complex interactions between genes and prevailing environment that varies across populations. Indians exhibit a unique obesity phenotype likely attributed by specific gene pool and environmental factors. Here, we present genome-wide association study (GWAS) of 7,259 Indians to understand the genetic architecture of body mass index (BMI) in the population. Our study revealed novel association of variants in BAI3 (rs6913677) and SLC22A11 (rs2078267) at GWAS significance, and of ZNF45 (rs8100011) with near GWAS significance. As genetic loci may dictate the phenotype through modulation of epigenetic processes, we overlapped discovered genetic signatures with DNA methylation patterns of 236 Indian individuals, and analyzed expression of the candidate genes using publicly available data. The variants in BAI3 and SLC22A11 were found to dictate methylation patterns at unique CpGs harboring critical cis- regulatory elements. Further, BAI3, SLC22A11 and ZNF45 variants were found to overlie repressive chromatin, active enhancer, and active chromatin regions, in that order, in human subcutaneous adipose tissue in ENCODE database. Besides, the identified genomic regions represented potential binding sites for key transcription factors implicated in obesity and/or metabolic disorders. Interestingly, rs8100011 (ZNF45) acted as a robust cis-expression quantitative trait locus (cis-eQTL) in subcutaneous adipose tissue in GTEx portal, and ZNF45 gene expression showed an inverse correlation with BMI in skeletal muscle of Indian subjects. Further, gene-based GWAS analysis revealed CPS1 and UPP2 as additional leads regulating BMI in Indians. Our study decodes potential genomic mechanisms underlying obesity phenotype in Indians.

Abstract MP63: Fine-mapping and Characterization of Adiponectin Gwas Loci Harboring Extensive Allelic Heterogeneity

Circulation ◽  
2018 ◽  
Vol 137 (suppl_1) ◽  
Author(s):  
Cassandra N Spracklen ◽  
Anne U Jackson ◽  
Apoorva Iyengar ◽  
Swarooparani Vadlamudi ◽  
Heather Stringham ◽  
...  
Keyword(s):  
Adipose Tissue ◽  
Fine Mapping ◽  
Transcriptional Activity ◽  
Molecular Mechanisms ◽  
Mixed Model ◽  
Genome Wide Association Study ◽  
Regulatory Element ◽  
Regulatory Elements ◽  
The Metabolic Syndrome ◽  
Genome Wide

Background: Elevated levels of adiponectin, an adipose-tissue derived hormone, are associated with a decreased risk for development of obesity, cardiovascular disease, and type 2 diabetes. We sought to fine-map and characterize loci from an adiponectin genome-wide association study (GWAS) to better understand the genes, variants, and mechanisms that contribute to adiponectin levels. Methods: We performed a GWAS of plasma adiponectin levels in 9,262 nondiabetic Finnish men from the Metabolic Syndrome in Men (METSIM) study using an efficient mixed model (EPACTS) to account for cryptic relatedness among the subjects. To identify multiple association signals within 1 Mb of each other, we used stepwise conditional analyses and Genome-wide Complex Trait Analysis (GCTA). We annotated association signals using regulatory elements based on chromatin marks from adipocyte nuclei (Epigenomic Roadmap) and ATAC-seq data from adipose tissue (METSIM) and SGBS preadipocyte cells. We also evaluated expression quantitative trait loci (eQTL) in subcutaneous adipose RNA-seq data from 387 METSIM samples. To test for allele-specific effects on transcriptional activity, we performed transcriptional reporter assays in HeLa cells. Results: We identified 5 loci associated with adiponectin ( P <5x10 -8 ): CDH13, ADIPOQ , IRS1, PBRM1, and EPHA3. Two loci ( CDH13 and ADIPOQ ) contained 2 and 7 association signals ( P <1x10 -5 ), respectively. At CDH13 , the first signal contained the lead adipose eQTL variant for CDH13 . At the novel second signal at CDH13 , rs4782722 is located in a regulatory element and the G-allele showed increased transcriptional activity compared to the T-allele, suggesting a functional role for this variant. At ADIPOQ , the first association signal also contained the lead adipose eQTL variant for ADIPOQ. All signals at ADIPOQ contained ≥1 variant in a putative enhancer, and the 7th signal includes rs62625753, a coding variant (G90S; P init =3x10 -3 , P cond =6x10 -4 ) predicted to be deleterious (SIFT) and probably damaging (PolyPhen). Accounting for multiple signals resulted in a 1.6-fold increase in variance explained over the lead signals alone (5.9 vs 9.4%). Conclusions: Fine-mapping, annotation, and experimental validation of GWAS signals and variants provide novel insight into the molecular mechanisms underlying genetic association signals, leading to a clearer biological basis for disease.

Subcutaneous Adipose Tissue Pattern in Lean and Obese Women with Polycystic Ovary Syndrome

2003 ◽  
Vol 228 (6) ◽  
pp. 710-716 ◽  
Author(s):  
E. Tafeit ◽  
R. Möller ◽  
S. Rackl ◽  
A. Giuliani ◽  
W. Urdl ◽  
...  
Keyword(s):  
Adipose Tissue ◽  
Body Fat ◽  
Subcutaneous Adipose Tissue ◽  
Polycystic Ovary ◽  
Fat Distribution ◽  
Body Fat Distribution ◽  
Healthy Controls ◽  
Type Ii ◽  
Ovary Syndrome ◽  
Subcutaneous Adipose

The new optical device, Lipometer, permits the noninvasive, quick, safe, and precise measurement of the thickness of subcutaneous adipose tissue (SAT) layers at any given site of the human body. Fifteen anatomically well-defined body sites from neck to calf describe the SAT topography (SAT-Top) like an individual “fingerprint.” SAT-Top was examined in 33 women with polycystic ovary syndrome (PCOS), in 87 age-matched healthy controls and in 20 Type-II diabetic women. SAT-Top differences of these three groups were described, and, based on a hierarchical cluster analysis, two distinctly different groups of PCOS women, a lean (PCOSL) and an obese (PCOSO) cluster, were found. For visual comparison of the different types of body fat distribution, the 15-dimensional body fat information was condensed to a two-dimensional factor plot by factor analysis. For comparison of the PCOS like body fat distribution with the “healthy” fat pattern, the (previously published) SAT-Top results of 590 healthy women and men (20-70 years old) and 162 healthy girls and boys (7-11 years old) were added to the factor plot. PCOSO women showed a SAT-Top pattern very similar to that of women with Type-II diabetes, even though the diabetic women were on average 30 years older. Compared with their healthy controls, SAT-Top of these PCOSO patients was strongly skewed into the android direction, providing significantly decreased leg SAT development and significantly higher upper body obesity. Compared with healthy women, PCOSL patients had significantly lower total SAT development (even though height, weight, and body mass index did not deviate significantly), showing a slightly lowered amount of body fat in the upper region and a highly significant leg SAT reduction. This type of fat pattern is the same as found in girls and boys before developing their sex specific body fat distribution. We conclude that women with PCOS develop an android SAT-Top, but compared in more detail, we found two typical types of body fat distribution: the “childlike” SAT pattern in lean PCOS patients, and the “diabetic” body fat distribution in obese PCOS women.

scholarly journals The Effect of Fat Distribution on the Inflammatory Response of Multiple Trauma Patients—A Retrospective Study

Life ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 1243
Author(s):  
Zhaoxiong Chen ◽  
Silvan Wittenberg ◽  
Timo Alexander Auer ◽  
Maxim Bashkuev ◽  
Pimrapat Gebert ◽  
...  
Keyword(s):  
Adipose Tissue ◽  
Retrospective Study ◽  
Inflammatory Response ◽  
Hospital Stay ◽  
Subcutaneous Adipose Tissue ◽  
Fat Distribution ◽  
Independent Factor ◽  
Polytrauma Patients ◽  
Male Patients ◽  
Subcutaneous Adipose

Objectives In recent years; increasing evidence pointed out the clinical importance of adipose tissue (AT) distribution in various patient populations. In particular, visceral adipose tissue (VAT), when compared to subcutaneous adipose tissue (SAT), was found to play a pivotal role in the development of inflammatory reaction. The aim of the present study was to examine whether body fat distribution has an impact on the development of systemic inflammatory response syndrome (SIRS) in patients with polytrauma. Methods In our retrospective study; we filtered our institution records of the German Trauma Registry (Trauma Register DGU) from November 2018 to April 2021 and included 132 adult polytrauma patients with injury severity score (ISS) >16. Subsequently; we measured the visceral and subcutaneous adipose tissue area based on whole-body CT scan and calculated the ratio of VAT to SAT (VSr). Thereafter, the patient population was evenly divided into three groups; respectively VSr value less than 0.4 for the first group (low ratio), 0.4–0.84 for the second group (intermediate ratio), and greater than 0.84 for the third group (high ratio). Considering the other influencing factors; the groups were further divided into subgroups in the respective analysis according to gender (male/female), BMI (<25 or ≥25), and ISS (<26 or ≥26). Result VSr was an independent factor from body mass index (BMI) (r2 = 0.003; p = 0.553). VSr in male patients was significantly higher (p < 0.001). Patients with low VSr had higher ISS scores (p = 0.028). Polytrauma patients with higher VSr tended to have lower SIRS scores and significant differences of SIRS score were found on multiple days during the whole hospitalization period. In the low VAT/SAT group, male patients, and patients with BMI greater than 25, both exhibited higher SIRS scores during hospital stay (day 16: p = 0.01; day 22: p = 0.048 and p = 0.011; respectively). During hospitalization, patients with higher ISS score (≥26) in the low VSr group was found to have higher SIRS score (day 16; p = 0.007). Over the hospital stay; serum markers of CRP; CK; and leukocyte in patients with low VSr were higher than those in patients in the intermediate and high VSr groups; with significant difference discovered on multiple days (day 16: 0.014; day 22: p = 0.048). Conclusion Lower VSr is associated with increased inflammatory response and worse clinical outcome in patients with polytrauma. Furthermore; VSr is an independent factor providing additional information to BMI.

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