Expressive

rs117124984 - MAPT

Magnitude 2.2 · 4 studies on file

Reported associations

  • Genome-wide analysis of insomnia in 1,331,010 individuals identifies new risk loci and functional pathways. - Nature genetics (2019) · Jansen PR, Watanabe K, Stringer S, Skene N, Bryois J, Hammerschlag AR, de Leeuw CA, Benjamins JS, Muñoz-Manchado AB, Nagel M, Savage JE, Tiemeier H, White T, Tung JY, Hinds DA, Vacic V, Wang X, Sullivan PF, van der Sluis S, Polderman TJC, Smit AB, Hjerling-Leffler J, Van Someren EJW, Posthuma D · PubMed 30804565

    Insomnia is the second most prevalent mental disorder, with no sufficient treatment available. Despite substantial heritability, insight into the associated genes and neurobiological pathways remains limited. Here, we use a large genetic association sample (n = 1,331,010) to detect novel loci and gain insight into the pathways, tissue and cell types involved in insomnia complaints. We identify 202 loci implicating 956 genes through positional, expression quantitative trait loci, and chromatin mapping. The meta-analysis explained 2.6% of the variance. We show gene set enrichments for the axonal part of neurons, cortical and subcortical tissues, and specific cell types, including striatal, hypothalamic, and claustrum neurons. We found considerable genetic correlations with psychiatric tr

  • 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%

  • MRI-derived brain iron, grey matter volume, and risk of dementia and Parkinson's disease: Observational and genetic analysis in the UK Biobank cohort - Unknown journal (n.d.) · Unknown authors · PubMed 38789058

    ABSTRACT: Background: Iron overload is observed in neurodegenerative diseases, especially Alzheimer's disease (AD) and Parkinson's disease (PD). Homozygotes for the iron-overload (haemochromatosis) causing HFE p.C282Y variant have increased risk of dementia and PD. Whether brain iron deposition is causal or secondary to the neurodegenerative processes in the general population is unclear. Methods: We analysed 39,533 UK Biobank participants of European genetic ancestry with brain MRI data. We studied brain iron estimated by R2* and quantitative susceptibility mapping (QSM) in 8 subcortical regions: accumbens, amygdala, caudate, hippocampus, pallidum, putamen, substantia nigra, and thalamus. We performed genome-wide associations studies (GWAS) and used Mendelian Randomization (MR) method

  • Larger cerebral cortex is genetically correlated with greater frontal area and dorsal thickness - Unknown journal (n.d.) · Unknown authors · PubMed 36893272

    ABSTRACT: Significance Adjusting vs. retaining global measures in analysis of brain MRI data has been a long-standing question and can have important implications for genomic studies of the cortex. Adjusting for global measures ensures that results for regions of interest are not confounded by overall larger brain size. However, adjusting for globals may throw away important signal when total and regional measures are correlated. We show that retaining vs. adjusting for global brain measures in genomic studies impacts gene discovery, particularly for fronto-parietal cortex. Understanding the genetic factors that contribute to expanded association areas in the human brain, such as the prefrontal cortex, can help provide mechanistic insight into higher human cognition and its unique developm

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