rs11768309 - LMTK2

Magnitude 2.2 · 4 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

• 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%

• Pan-cancer and cross-population genome-wide association studies dissect shared genetic backgrounds underlying carcinogenesis - Unknown journal (n.d.) · Unknown authors · PubMed 37340002

  ABSTRACT: Integrating genomic data of multiple cancers allows de novo cancer grouping and elucidating the shared genetic basis across cancers. Here, we conduct the pan-cancer and cross-population genome-wide association study (GWAS) meta-analysis and replication studies on 13 cancers including 250,015 East Asians (Biobank Japan) and 377,441 Europeans (UK Biobank). We identify ten cancer risk variants including five pleiotropic associations (e.g., rs2076295 at DSP on 6p24 associated with lung cancer and rs2525548 at TRIM4 on 7q22 nominally associated with six cancers). Quantifying shared heritability among the cancers detects positive genetic correlations between breast and prostate cancer across populations. Common genetic components increase the statistical power, and the large-scale meta

• 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

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