Meta-analysis of genome-wide association studies
 for body fat distribution in 694 649 individuals of European ancestry

Pulit, Sara L.; Stoneman, Charli; Morris, Andrew P.; Wood, Andrew R.; Glastonbury, Craig A.; Tyrrell, Jessica; Yengo, Loïc; Ferreira, Teresa; Marouli, Eirini; Ji, Yingjie; Yang, Jian; Jones, Samuel E.; Beaumont, Robin N; Croteau‐Chonka, Damien C.; Winkler, Thomas W.; Hattersley, Andrew T.; Loos, Ruth J.F.; Hirschhorn, Joel N.; Visscher, Peter M.; Frayling, Timothy M.; Yaghootkar, Hanieh; Lindgren, Cecilia M.

doi:10.1093/hmg/ddy327

Cited by 924 publications

(1,100 citation statements)

References 35 publications

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“…Of the 16 suggestive SNPs associated with WHtR, variants in or near LTBP1, PDE1C, GALNT17, DPP6, MAP4K5 and EYA2 were nominally associated with BMI or WHR in adult population 17,18,35,36 ( 37 In the present study we utilized Metabochip, a custom genotyping chip for fine-mapping and replication, which includes altogether 200 000 SNPs from loci that were associated, or were promising for several complex metabolic traits for example, type 2 diabetes, cardiovascular diseases, and their key risk factors: BMI, blood glucose, insulin land lipid concentrations and blood pressure back in 2012. 38 We created BMI-GRSs based on data of Speliotes et al, 17 and 30 of these 32 SNPs were incorporated in Metabochip.…”

Section: Top Snps Related To Bmi Z-score and Waist-toheight Ratio Imentioning

confidence: 99%

Genetic risk score predicts risk for overweight and obesity in Finnish preadolescents

et al. 2019

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Summary Common genetic variants predispose to obesity with varying contribution by age. We incorporated known genetic variants into genetic risk scores (GRSs) and investigated their associations with overweight/obesity and central obesity in preadolescents. Furthermore, we compared GRSs with lifestyle factors, and tested if they predict the change in body size and shape in a 4‐year follow‐up. We utilized 1142 subjects from the Finnish Health in Teens (Fin‐HIT) cohort. Overweight and obesity were defined with age‐ and gender‐specific body mass index (BMI) z‐score (BMIz), while central obesity by the waist‐to‐height ratio (WHtR). Background data on parental language, eating habits, leisure‐time physical activity (LTPA) and sleep duration were included. Genotyping was performed with the Metabochip platform. Weighted, standardized GRSs were derived. Of the11‐year‐old children, 25.5% were at least overweight and 90.8% had Finnish speaking background. BMI‐GRS was associated with higher risk for overweight with odds ratio (95% confidence interval) of 1.39 (1.20; 1.60) and obesity 1.41 (1.08; 1.83), but not with central obesity. BMI‐GRS was weakly and inversely associated with the changes in BMIz and WHtR in the 4‐year follow‐up. Waist‐to‐hip ratio‐GRS was not related to any obesity measures at baseline nor in the follow‐up. The effect of BMI‐GRS is similar to that of low LTPA on overweight. An interaction between parental language and BMI‐GRS was noted (P = .019): BMI‐GRS associated more strongly with overweight in Swedish than in Finnish speakers. We further identified two suggestive genetic variants near LOC101926977 and LOC105369677 associated with BMIz in preadolescents which were replicated in the adult population. In preadolescents, known genetic predisposing factors induce a risk for overweight comparable to low LTPA. However, the GRS was poor in predicting short‐term changes in BMI or WHtR.

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Section: Top Snps Related To Bmi Z-score and Waist-toheight Ratio Imentioning

confidence: 99%

Genetic risk score predicts risk for overweight and obesity in Finnish preadolescents

et al. 2019

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“…The index SNPs were expanded to give proxy SNPs in high LD (r 2 ≥ 0.8), and the sets of index and proxy SNPs were combined (index/proxy SNPs; Supplementary Material, Table S4). We separately collected sets of imputed SNPs (p < 6.6 x 10 -9 ) at this locus obtained from summary statistics from one WHRadjBMI meta-analysis of 694,649 individuals (38) and from an eBMD meta-analysis of 426,824 individuals (27) (Supplementary Material, Table S5).…”

Section: Tbx15 Enhancer or Promoter Chromatinmentioning

confidence: 99%

“…There are two obesity missense variants in TBX15, namely, rs10494217 (G/T, 0.84/0.16; H156N) in exon 3 and rs61730011 (A/C, 0.96/0.04; M566R) in exon 8 ( Fig. 1B, double arrows) (13,38,40). The meta-analysis by Justice et al (13) involving 476,546 individuals (88% EUR) found a highly significant association of both rs10494217 (p = 2 x 10 -14 ) and rs61730011 (p = 3 x 10 -21 ) with WHRadjBMI, and similar results were obtained for the former SNP in the study of Pullit et al (38) Table S5).…”

Section: Obesity-related Non-synonymous Codon Variants In Tbx15 Exonsmentioning

confidence: 99%

“…1B, double arrows) (13,38,40). The meta-analysis by Justice et al (13) involving 476,546 individuals (88% EUR) found a highly significant association of both rs10494217 (p = 2 x 10 -14 ) and rs61730011 (p = 3 x 10 -21 ) with WHRadjBMI, and similar results were obtained for the former SNP in the study of Pullit et al (38) Table S5). Rs61730011 is in a codon for an amino acid in the large C-terminal portion of TBX15, which is of unknown function, and has no human paralogs (as determined by BLASTP, https://blast.ncbi.nlm.nih.gov/).…”

Section: Obesity-related Non-synonymous Codon Variants In Tbx15 Exonsmentioning

confidence: 99%

“…The index SNPs were expanded to a set of proxy SNPs (r 2 ≥ 0.8 in a 1-Mb window, EUR population from the 1000 Genome Project Phase 3; (75)) by using PLINK v1.9 (76). In addition, we retrieved summary statistics datasets for WHRadjBMI (38) and eBMD (27), which are the largest publicly available summary statistics for these traits, and extracted imputed significant SNPs (p < 6.6 x 10 -9 ) for TBX15 (chr1:118,717,862-119,916,299) and for TBX18 (chr6:84,921,843-86,171,855). For subdividing the Tier-1 SNPs into thinned LD groups (pairwise r 2 > 0.2), EUR, we used the SNPclip function of the LDlink suite (52).…”

Section: Gwas-derived Snps and Ld Analysismentioning

confidence: 99%

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Osteoporosis- and obesity-risk interrelationships: An epigenetic analysis of GWAS-derived SNPs at the developmental geneTBX15

Zhang

Ehrlich

et al. 2019

Preprint

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A major challenge in translating findings from genome-wide association studies (GWAS) to biological mechanisms is pinpointing functional variants because only a very small percentage of variants associated with a given trait actually impact the trait. We used an extensive epigenetics, transcriptomics, and genetics analysis of the TBX15/WARS2 neighborhood to prioritize this region's best-candidate causal variants for the genetic risk of osteoporosis (estimated bone density, eBMD) and obesity (waist-hip ratio or waist circumference adjusted for body mass index). TBX15 encodes a transcription factor that is important in bone development and adipose biology. Manual curation of 692 GWAS-derived variants gave eight strong candidates for causal SNPs that modulate TBX15 transcription in subcutaneous adipose tissue (SAT) or osteoblasts, which highly and specifically express this gene. None of these SNPs were prioritized by Bayesian fine-mapping. The eight regulatory causal SNPs were in enhancer or promoter chromatin seen preferentially in SAT or osteoblasts at TBX15 intron-1 or upstream. They overlap strongly predicted, allele-specific transcription factor binding sites. Our analysis suggests that these SNPs act independently of two missense SNPs in TBX15. Remarkably, five of the regulatory SNPs were associated with eBMD and obesity and had the same trait-increasing allele for both. We found that WARS2 obesity-related SNPs can be ascribed to high linkage disequilibrium with TBX15 intron-1 SNPs. Our findings from GWAS index, proxy, and imputed SNPs suggest that a few SNPs, including three in a 0.7-kb cluster, act as causal regulatory variants to fine-tune TBX15 expression and, thereby, affect both obesity and osteoporosis risk.Recently, whole-genome profiles of epigenetics features, such as promoter-type or enhancer-type chromatin, have been used to help discriminate likely causal variants from bystander SNPs in high LD with them (15,17,18).GWAS SNPs, including those for obesity-related traits (9), are generally enriched in enhancer chromatin or promoter regions (14,15,19,20). In GWAS of (mostly) individuals of European ancestry (EUR) (13, 21) or of East Asians (6, 11), SNPs linked to TBX15 were identified as significantly associated with BMI, WHRadjBMI or WCadjBMI in mixed sex populations, or separately in women or men (Supplementary Material, Table S1). TBX15 codes for a Tbox transcription factor (TF) that may be involved in various aspects of adipose development and maintenance (22)(23)(24) and is known to be important in formation of the skeletal system (25,26). SNPs in or near TBX15 are significantly associated not only with obesity traits but also with estimated heel bone mineral density (eBMD), a useful indicator of hip and non-spine fractures that is used as a proxy for osteoporosis risk (27).Our study of the relationships in GWAS of TBX15 to both adipose and bone biology provides novel insights into the developmental relationships between two related tissue lineages converging on one gene. Both adipocytes and oste...

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Cardiovascular Significance and Genetics of Epicardial and Pericardial Adiposity

Rämö,

Kany,

Hou

et al. 2024

JAMA Cardiol

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ImportanceEpicardial and pericardial adipose tissue (EPAT) has been associated with cardiovascular diseases such as atrial fibrillation or flutter (AF) and coronary artery disease (CAD), but studies have been limited in sample size or drawn from selected populations. It has been suggested that the association between EPAT and cardiovascular disease could be mediated by local or paracrine effects.ObjectiveTo evaluate the association of EPAT with prevalent and incident cardiovascular disease and to elucidate the genetic basis of EPAT in a large population cohort.Design, Setting, and ParticipantsA deep learning model was trained to quantify EPAT area from 4-chamber magnetic resonance images using semantic segmentation. Cross-sectional and prospective cardiovascular disease associations were evaluated, controlling for sex and age. Prospective associations were additionally controlled for abdominal visceral adipose tissue (VAT) volumes. A genome-wide association study was performed, and a polygenic score (PGS) for EPAT was examined in independent FinnGen cohort study participants. Data analyses were conducted from March 2022 to December 2023.ExposuresThe primary exposures were magnetic resonance imaging–derived continuous measurements of epicardial and pericardial adipose tissue area and visceral adipose tissue volume.Main Outcomes and MeasuresPrevalent and incident CAD, AF, heart failure (HF), stroke, and type 2 diabetes (T2D).ResultsAfter exclusions, this study included 44 475 participants (mean [SD] age, 64.1 [7.7] years; 22 972 female [51.7%]) from the UK Biobank. Cross-sectional and prospective cardiovascular disease associations were evaluated for a mean (SD) of 3.2 (1.5) years of follow-up. Prospective associations were additionally controlled for abdominal VAT volumes for 38 527 participants. A PGS for EPAT was examined in 453 733 independent FinnGen cohort study participants. EPAT was positively associated with male sex (β = +0.78 SD in EPAT; P &lt; 3 × 10−324), age (Pearson r = 0.15; P = 9.3 × 10−229), body mass index (Pearson r = 0.47; P &lt; 3 × 10−324), and VAT (Pearson r = 0.72; P &lt; 3 × 10−324). EPAT was more elevated in prevalent HF (β = +0.46 SD units) and T2D (β = +0.56) than in CAD (β = +0.23) or AF (β = +0.18). EPAT was associated with incident HF (hazard ratio [HR], 1.29 per +1 SD in EPAT; 95% CI, 1.17-1.43), T2D (HR, 1.63; 95% CI, 1.51-1.76), and CAD (HR, 1.19; 95% CI, 1.11-1.28). However, the associations were no longer significant when controlling for VAT. Seven genetic loci were identified for EPAT, implicating transcriptional regulators of adipocyte morphology and brown adipogenesis (EBF1, EBF2, and CEBPA) and regulators of visceral adiposity (WARS2 and TRIB2). The EPAT PGS was associated with T2D (odds ratio [OR], 1.06; 95% CI, 1.05-1.07; P =3.6 × 10−44), HF (OR, 1.05; 95% CI, 1.04-1.06; P =4.8 × 10−15), CAD (OR, 1.04; 95% CI, 1.03-1.05; P =1.4 × 10−17), AF (OR, 1.04; 95% CI, 1.03-1.06; P =7.6 × 10−12), and stroke in FinnGen (OR, 1.02; 95% CI, 1.01-1.03; P =3.5 × 10−3) per 1 SD in PGS.Conclusions and RelevanceResults of this cohort study suggest that epicardial and pericardial adiposity was associated with incident cardiovascular diseases, but this may largely reflect a metabolically unhealthy adiposity phenotype similar to abdominal visceral adiposity.

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Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry

Cited by 924 publications

References 35 publications

Genetic risk score predicts risk for overweight and obesity in Finnish preadolescents

Genetic risk score predicts risk for overweight and obesity in Finnish preadolescents

Osteoporosis- and obesity-risk interrelationships: An epigenetic analysis of GWAS-derived SNPs at the developmental geneTBX15

Cardiovascular Significance and Genetics of Epicardial and Pericardial Adiposity

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