rs113851554 - MEIS1

Magnitude 4.5 · 8 studies on file

Reported associations

• Genetic architecture of sleep in a genome wide association study of device measured sleep traits. - Nature communications (2026) · Portas L, Yuan H, Cai L, Smith-Byrne K, van Duijvenboden S, Kyle SD, Ray D, Howson JM, Doherty A · PubMed 41922918

  Sleep is essential for health and regulated by genetic and environmental factors. We perform genome-wide association studies of device-measured sleep duration, efficiency, and accelerometer-derived rapid eye movement (REM) and non-rapid eye movement (NREM) sleep in 80,013 UK Biobank participants. We identify 20 autosomal loci, 12 of which have not been previously reported, including genome-wide significant associations for REM and NREM sleep duration. MEIS1 shows strong opposing effects on REM and NREM durations and is intolerant to loss-of-function mutations, suggesting an essential role in the regulation of REM/NREM sleep balance. Functional enrichment analysis identifies statistically significant pathways related to chromatin remodelling, lipid metabolism, and metal ion homeostasis whil

• Genome-Wide Association Study and Genetic Correlation Scan Provide Insights into Its Genetic Architecture of Sleep Health Score in the UK Biobank Cohort. - Nature and science of sleep (2025) · Yao Y, Jia Y, Wen Y, Cheng B, Cheng S, Liu L, Yang X, Meng P, Chen Y, Li C, Zhang J, Zhang Z, Pan C, Zhang H, Wu C, Wang X, Ning Y, Wang S, Zhang F · PubMed 35023977

  Most previous genetic studies of sleep behaviors were conducted individually, without comprehensive consideration of the complexity of various sleep behaviors. Our aim is to identify the genetic architecture and potential biomarker of the sleep health score, which more powerfully represents overall sleep traits. We conducted a genome-wide association study (GWAS) of sleep health score (overall assessment of sleep duration, snoring, insomnia, chronotype, and daytime dozing) using 336,463 participants from the UK Biobank. Proteome-wide association study (PWAS) and transcriptome-wide association study (TWAS) were then performed to identify candidate genes at the protein and mRNA level, respectively. We finally used linkage disequilibrium score regression (LDSC) to estimate the genetic correla

• Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program. - Science (New York, N.Y.) (2024) · Verma A, Huffman JE, Rodriguez A, Conery M, Liu M, Ho YL, Kim Y, Heise DA, Guare L, Panickan VA, Garcon H, Linares F, Costa L, Goethert I, Tipton R, Honerlaw J, Davies L, Whitbourne S, Cohen J, Posner DC, Sangar R, Murray M, Wang X, Dochtermann DR, Devineni P, Shi Y, Nandi TN, Assimes TL, Brunette CA, Carroll RJ, Clifford R, Duvall S, Gelernter J, Hung A, Iyengar SK, Joseph J, Kember R, Kranzler H, Kripke CM, Levey D, Luoh SW, Merritt VC, Overstreet C, Deak JD, Grant SFA, Polimanti R, Roussos P, Shakt G, Sun YV, Tsao N, Venkatesh S, Voloudakis G, Justice A, Begoli E, Ramoni R, Tourassi G, Pyarajan S, Tsao P, O'Donnell CJ, Muralidhar S, Moser J, Casas JP, Bick AG, Zhou W, Cai T, Voight BF, Cho K, Gaziano JM, Madduri RK, Damrauer S, Liao KP · PubMed 39024449

  One of the justifiable criticisms of human genetic studies is the underrepresentation of participants from diverse populations. Lack of inclusion must be addressed at-scale to identify causal disease factors and understand the genetic causes of health disparities. We present genome-wide associations for 2068 traits from 635,969 participants in the Department of Veterans Affairs Million Veteran Program, a longitudinal study of diverse United States Veterans. Systematic analysis revealed 13,672 genomic risk loci; 1608 were only significant after including non-European populations. Fine-mapping identified causal variants at 6318 signals across 613 traits. One-third ( = 2069) were identified in participants from non-European populations. This reveals a broadly similar genetic architecture acro

• Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and risk prediction. - Nature genetics (2024) · Schormair B, Zhao C, Bell S, Didriksen M, Nawaz MS, Schandra N, Stefani A, Högl B, Dauvilliers Y, Bachmann CG, Kemlink D, Sonka K, Paulus W, Trenkwalder C, Oertel WH, Hornyak M, Teder-Laving M, Metspalu A, Hadjigeorgiou GM, Polo O, Fietze I, Ross OA, Wszolek ZK, Ibrahim A, Bergmann M, Kittke V, Harrer P, Dowsett J, Chenini S, Ostrowski SR, Sørensen E, Erikstrup C, Pedersen OB, Topholm Bruun M, Nielsen KR, Butterworth AS, Soranzo N, Ouwehand WH, Roberts DJ, Danesh J, Burchell B, Furlotte NA, Nandakumar P, Earley CJ, Ondo WG, Xiong L, Desautels A, Perola M, Vodicka P, Dina C, Stoll M, Franke A, Lieb W, Stewart AFR, Shah SH, Gieger C, Peters A, Rye DB, Rouleau GA, Berger K, Stefansson H, Ullum H, Stefansson K, Hinds DA, Di Angelantonio E, Oexle K, Winkelmann J · PubMed 38839884

  Restless legs syndrome (RLS) affects up to 10% of older adults. Their healthcare is impeded by delayed diagnosis and insufficient treatment. To advance disease prediction and find new entry points for therapy, we performed meta-analyses of genome-wide association studies in 116,647 individuals with RLS (cases) and 1,546,466 controls of European ancestry. The pooled analysis increased the number of risk loci eightfold to 164, including three on chromosome X. Sex-specific meta-analyses revealed largely overlapping genetic predispositions of the sexes (r = 0.96). Locus annotation prioritized druggable genes such as glutamate receptors 1 and 4, and Mendelian randomization indicated RLS as a causal risk factor for diabetes. Machine learning approaches combining genetic and nongenetic informat

• Genomic Analysis Identifies Risk Factors in Restless Legs Syndrome. - Annals of neurology (2024) · Akçimen F, Chia R, Saez-Atienzar S, Ruffo P, Rasheed M, Ross JP, Liao C, Ray A, Dion PA, Scholz SW, Rouleau GA, Traynor BJ · PubMed 39078117

  Restless legs syndrome (RLS) is a neurological condition that causes uncomfortable sensations in the legs and an irresistible urge to move them, typically during periods of rest. The genetic basis and pathophysiology of RLS are incompletely understood. We sought to identify additional novel genetic risk factors associated with RLS susceptibility. We performed a whole-genome sequencing and genome-wide association meta-analysis of RLS cases (n = 9,851) and controls (n = 38,957) in 3 population-based biobanks (All of Us, Canadian Longitudinal Study on Aging, and CARTaGENE). Genome-wide association analysis identified 9 independent risk loci, of which 8 had been previously reported, and 1 was a novel risk locus (LMX1B, rs35196838, OR 1.14, 95% CI 1.09-1.19, p value = 2.2 × 10

• The genetic etiology of periodic limb movement in sleep. - Sleep (2023) · Edelson JL, Schneider LD, Amar D, Brink-Kjaer A, Cederberg KL, Kutalik Z, Hagen EW, Peppard PE, Tempaku PF, Tufik S, Evans DS, Stone K, Tranah G, Cade B, Redline S, Haba-Rubio J, Heinzer R, Marques-Vidal P, Vollenweider P, Winkelmann J, Zou J, Mignot E · PubMed 35670608

  Periodic limb movement in sleep is a common sleep phenotype characterized by repetitive leg movements that occur during or before sleep. We conducted a genome-wide association study (GWAS) of periodic limb movements in sleep (PLMS) using a joint analysis (i.e., discovery, replication, and joint meta-analysis) of four cohorts (MrOS, the Wisconsin Sleep Cohort Study, HypnoLaus, and MESA), comprised of 6843 total subjects. The MrOS study and Wisconsin Sleep Cohort Study (N = 1745 cases) were used for discovery. Replication in the HypnoLaus and MESA cohorts (1002 cases) preceded joint meta-analysis. We also performed LD score regression, estimated heritability, and computed genetic correlations between potentially associated traits such as restless leg syndrome (RLS) and insomnia. The caus

• Genome-wide association studies and cross-population meta-analyses investigating short and long sleep duration. - Nature communications (2023) · Austin-Zimmerman I, Levey DF, Giannakopoulou O, Deak JD, Galimberti M, Adhikari K, Zhou H, Denaxas S, Irizar H, Kuchenbaecker K, McQuillin A, Concato J, Buysse DJ, Gaziano JM, Gottlieb DJ, Polimanti R, Stein MB, Bramon E, Gelernter J · PubMed 37770476

  Sleep duration has been linked to a wide range of negative health outcomes and to reduced life expectancy. We present genome-wide association studies of short ( ≤ 5 h) and long ( ≥ 10 h) sleep duration in adults of European (N = 445,966), African (N = 27,785), East Asian (N = 3141), and admixed-American (N = 16,250) ancestry from UK Biobank and the Million Veteran Programme. In a cross-population meta-analysis, we identify 84 independent loci for short sleep and 1 for long sleep. We estimate SNP-based heritability for both sleep traits in each ancestry based on population derived linkage disequilibrium (LD) scores using cov-LDSC. We identify positive genetic correlation between short and long sleep traits (r = 0.16 ± 0.04; p = 0.0002), as well as si

• Genome-wide association studies of 27 accelerometry-derived physical activity measurements identified novel loci and genetic mechanisms. - Genetic epidemiology (2022) · Qi G, Dutta D, Leroux A, Ray D, Muschelli J, Crainiceanu C, Chatterjee N · PubMed 35043453

  Physical inactivity (PA) is an important risk factor for a wide range of diseases. Previous genome-wide association studies (GWAS), based on self-reported data or a small number of phenotypes derived from accelerometry, have identified a limited number of genetic loci associated with habitual PA and provided evidence for involvement of central nervous system in mediating genetic effects. In this study, we derived 27 PA phenotypes from wrist accelerometry data obtained from 88,411 UK Biobank study participants. Single-variant association analysis based on mixed-effects models and transcriptome-wide association studies (TWAS) together identified 5 novel loci that were not detected by previous studies of PA, sleep duration and self-reported chronotype. For both novel and previously known loci

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