Expressive

rs1121980 - FTO

Magnitude 2.2 · 8 studies on file

Reported associations

  • A cross-population atlas of genetic associations for 220 human phenotypes. - Nature genetics (2021) · Sakaue S, Kanai M, Tanigawa Y, Karjalainen J, Kurki M, Koshiba S, Narita A, Konuma T, Yamamoto K, Akiyama M, Ishigaki K, Suzuki A, Suzuki K, Obara W, Yamaji K, Takahashi K, Asai S, Takahashi Y, Suzuki T, Shinozaki N, Yamaguchi H, Minami S, Murayama S, Yoshimori K, Nagayama S, Obata D, Higashiyama M, Masumoto A, Koretsune Y, Ito K, Terao C, Yamauchi T, Komuro I, Kadowaki T, Tamiya G, Yamamoto M, Nakamura Y, Kubo M, Murakami Y, Yamamoto K, Kamatani Y, Palotie A, Rivas MA, Daly MJ, Matsuda K, Okada Y · PubMed 34594039

    Current genome-wide association studies do not yet capture sufficient diversity in populations and scope of phenotypes. To expand an atlas of genetic associations in non-European populations, we conducted 220 deep-phenotype genome-wide association studies (diseases, biomarkers and medication usage) in BioBank Japan (n = 179,000), by incorporating past medical history and text-mining of electronic medical records. Meta-analyses with the UK Biobank and FinnGen (n = 628,000) identified ~5,000 new loci, which improved the resolution of the genomic map of human traits. This atlas elucidated the landscape of pleiotropy as represented by the major histocompatibility complex locus, where we conducted HLA fine-mapping. Finally, we performed statistical decomposition of matrices of phenome-wid

  • Genetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity. - Diabetes (2021) · Yaghootkar H, Zhang Y, Spracklen CN, Karaderi T, Huang LO, Bradfield J, Schurmann C, Fine RS, Preuss MH, Kutalik Z, Wittemans LBL, Lu Y, Metz S, Willems SM, Li-Gao R, Grarup N, Wang S, Molnos S, Sandoval-Zárate AA, Nalls MA, Lange LA, Haesser J, Guo X, Lyytikäinen LP, Feitosa MF, Sitlani CM, Venturini C, Mahajan A, Kacprowski T, Wang CA, Chasman DI, Amin N, Broer L, Robertson N, Young KL, Allison M, Auer PL, Blüher M, Borja JB, Bork-Jensen J, Carrasquilla GD, Christofidou P, Demirkan A, Doege CA, Garcia ME, Graff M, Guo K, Hakonarson H, Hong J, Ida Chen YD, Jackson R, Jakupović H, Jousilahti P, Justice AE, Kähönen M, Kizer JR, Kriebel J, LeDuc CA, Li J, Lind L, Luan J, Mackey DA, Mangino M, Männistö S, Martin Carli JF, Medina-Gomez C, Mook-Kanamori DO, Morris AP, de Mutsert R, Nauck M, Prokic I, Pennell CE, Pradhan AD, Psaty BM, Raitakari OT, Scott RA, Skaaby T, Strauch K, Taylor KD, Teumer A, Uitterlinden AG, Wu Y, Yao J, Walker M, North KE, Kovacs P, Ikram MA, van Duijn CM, Ridker PM, Lye S, Homuth G, Ingelsson E, Spector TD, McKnight B, Province MA, Lehtimäki T, Adair LS, Rotter JI, Reiner AP, Wilson JG, Harris TB, Ripatti S, Grallert H, Meigs JB, Salomaa V, Hansen T, Willems van Dijk K, Wareham NJ, Grant SFA, Langenberg C, Frayling TM, Lindgren CM, Mohlke KL, Leibel RL, Loos RJF, Kilpeläinen TO · PubMed 32917775

    Leptin influences food intake by informing the brain about the status of body fat stores. Rare 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 , , , and , and one intergenic variant near The missense variant Val94Met (rs17151919) in was common in individuals of African ancestry only, and its association with lower leptin concentrations was specific to this ancestry ( =

  • Genome-wide Associations Reveal Human-Mouse Genetic Convergence and Modifiers of Myogenesis, CPNE1 and STC2. - American journal of human genetics (2020) · Hernandez Cordero AI, Gonzales NM, Parker CC, Sokolof G, Vandenbergh DJ, Cheng R, Abney M, Sko A, Douglas A, Palmer AA, Gregory JS, Lionikas A · PubMed 31761296

    Muscle bulk in adult healthy humans is highly variable even after height, age, and sex are accounted for. Low muscle mass, due to fewer and/or smaller constituent muscle fibers, would exacerbate the impact of muscle loss occurring in aging or disease. Genetic variability substantially influences muscle mass differences, but causative genes remain largely unknown. In a genome-wide association study (GWAS) on appendicular lean mass (ALM) in a population of 85,750 middle-aged (aged 38-49 years) individuals from the UK Biobank (UKB), we found 182 loci associated with ALM (p < 5 × 10 ). We replicated associations for 78% of these loci (p < 5 × 10 ) with ALM in a population of 181,862 elderly (aged 60-74 years) individuals from UKB. We also conducted a GWAS on hindlimb skeletal muscle m

  • Association analyses of East Asian individuals and trans-ancestry analyses with European individuals reveal new loci associated with cholesterol and triglyceride levels. - Human molecular genetics (2017) · Spracklen CN, Chen P, Kim YJ, Wang X, Cai H, Li S, Long J, Wu Y, Wang YX, Takeuchi F, Wu JY, Jung KJ, Hu C, Akiyama K, Zhang Y, Moon S, Johnson TA, Li H, Dorajoo R, He M, Cannon ME, Roman TS, Salfati E, Lin KH, Guo X, Sheu WHH, Absher D, Adair LS, Assimes TL, Aung T, Cai Q, Chang LC, Chen CH, Chien LH, Chuang LM, Chuang SC, Du S, Fan Q, Fann CSJ, Feranil AB, Friedlander Y, Gordon-Larsen P, Gu D, Gui L, Guo Z, Heng CK, Hixson J, Hou X, Hsiung CA, Hu Y, Hwang MY, Hwu CM, Isono M, Juang JJ, Khor CC, Kim YK, Koh WP, Kubo M, Lee IT, Lee SJ, Lee WJ, Liang KW, Lim B, Lim SH, Liu J, Nabika T, Pan WH, Peng H, Quertermous T, Sabanayagam C, Sandow K, Shi J, Sun L, Tan PC, Tan SP, Taylor KD, Teo YY, Toh SA, Tsunoda T, van Dam RM, Wang A, Wang F, Wang J, Wei WB, Xiang YB, Yao J, Yuan JM, Zhang R, Zhao W, Chen YI, Rich SS, Rotter JI, Wang TD, Wu T, Lin X, Han BG, Tanaka T, Cho YS, Katsuya T, Jia W, Jee SH, Chen YT, Kato N, Jonas JB, Cheng CY, Shu XO, He J, Zheng W, Wong TY, Huang W, Kim BJ, Tai ES, Mohlke KL, Sim X · PubMed 28334899

    Large-scale meta-analyses of genome-wide association studies (GWAS) have identified >175 loci associated with fasting cholesterol levels, including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). With differences in linkage disequilibrium (LD) structure and allele frequencies between ancestry groups, studies in additional large samples may detect new associations. We conducted staged GWAS meta-analyses in up to 69,414 East Asian individuals from 24 studies with participants from Japan, the Philippines, Korea, China, Singapore, and Taiwan. These meta-analyses identified (P < 5 × 10-8) three novel loci associated with HDL-C near CD163-APOBEC1 (P = 7.4 × 10-9), NCOA2 (P = 1.6 

  • Common variants near MC4R are associated with fat mass, weight and risk of obesity - Unknown journal (n.d.) · Unknown authors · PubMed 18454148

    ABSTRACT: To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 × 10−6) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 × 10−15) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 × 10−8). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 × 10−11). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 famil

  • New role of fat-free mass in cancer risk linked with genetic predisposition - Unknown journal (n.d.) · Unknown authors · PubMed 38538606

    ABSTRACT: Cancer risk is associated with the widely debated measure body mass index (BMI). Fat mass and fat-free mass measurements from bioelectrical impedance may further clarify this association. The UK Biobank is a rare resource in which bioelectrical impedance and BMI data was collected on ~ 500,000 individuals. Using this dataset, a comprehensive analysis using regression, principal component and genome-wide genetic association, provided multiple levels of evidence that increasing whole body fat (WBFM) and fat-free mass (WBFFM) are both associated with increased post-menopausal breast cancer risk, and colorectal cancer risk in men. WBFM was inversely associated with prostate cancer. We also identified rs615029[T] and rs1485995[G] as associated in independent analyses with both PMB

  • Genomic analysis of male puberty timing highlights shared genetic basis with hair colour and lifespan - Unknown journal (n.d.) · Unknown authors · PubMed 32210231

    ABSTRACT: The timing of puberty is highly variable and is associated with long-term health outcomes. To date, understanding of the genetic control of puberty timing is based largely on studies in women. Here, we report a multi-trait genome-wide association study for male puberty timing with an effective sample size of 205,354 men. We find moderately strong genomic correlation in puberty timing between sexes (rg = 0.68) and identify 76 independent signals for male puberty timing. Implicated mechanisms include an unexpected link between puberty timing and natural hair colour, possibly reflecting common effects of pituitary hormones on puberty and pigmentation. Earlier male puberty timing is genetically correlated with several adverse health outcomes and Mendelian randomization analyses s

  • A scalable variational inference approach for increased mixed-model association power - Unknown journal (n.d.) · Unknown authors · PubMed 39789286

    ABSTRACT: The rapid growth of modern biobanks is creating new opportunities for large-scale genome-wide association studies (GWASs) and the analysis of complex traits. However, performing GWASs on millions of samples often leads to trade-offs between computational efficiency and statistical power, reducing the benefits of large-scale data collection efforts. We developed Quickdraws, a method that increases association power in quantitative and binary traits without sacrificing computational efficiency, leveraging a spike-and-slab prior on variant effects, stochastic variational inference and graphics processing unit acceleration. We applied Quickdraws to 79 quantitative and 50 binary traits in 405,088 UK Biobank samples, identifying 4.97% and 3.25% more associations than REGENIE and 22.71%

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