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Transcriptome-wide Association Study in Frontotemporal Dementia Identifies New Disease Loci by In Silico Analysis

  • Christina M. Lill
    Correspondence
    Address correspondence to Christina M. Lill, M.D., M.S.
    Affiliations
    Translational Epidemiology Group, Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
    Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, London, United Kingdom
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      Over the past decade, genetics research has experienced tremendous progress owing to the advent (and application) of high-throughput technologies allowing for profiling of the genome at unprecedented resolution. First and foremost, this relates to interrogating DNA sequence variants using large-scale genotyping with the aim to search for novel disease risk genes in the context of genome-wide association studies (GWASs). GWAS data have subsequently become even more valuable by integrating them with data from other “-omics” domains. This was aided by ultra–high-throughput sequencing technologies (i.e., next-generation sequencing) that allowed researchers to produce readouts of the human genome and transcriptome at base-pair resolution. One of the first—and still one of the most valuable—next-generation sequencing applications was to assess gene expression levels on a genome-wide scale (i.e., the transcriptome) via RNA sequencing. Particularly powerful is the combined application of genome and transcriptome sequencing in the same individual, which is the focus of the GTEx (Genotype-Tissue Expression) project (
      GTEx Consortium
      The GTEx Consortium atlas of genetic regulatory effects across human tissues.
      ). GTEx has now reached its eighth build, featuring data from 54 nondiseased tissue sites across nearly 1000 individuals (all data are freely available at https://www.gtexportal.org). Along with these technical advances came innovative and powerful computational approaches allowing the integration and interrogation of GWAS and other human -omics data that are increasingly becoming available. This allowed researchers to derive novel inferences on the correlations between the genome, the transcriptome, and clinical phenotypes. In the current issue of Biological Psychiatry, Reus et al. (
      • Reus L.M.
      • Pasaniuc B.
      • Posthuma D.
      • Boltz T.
      • Pijnenburg Y.A.L.
      • Ophoff R.A.
      International FTD-Genomics Consortium
      Gene expression imputation across multiple tissue types provides insight into the genetic architecture of frontotemporal dementia and its clinical subtypes.
      ) showcase the power of modern -omics research by applying all of the above to advance our understanding of the genetic underpinnings of frontotemporal dementia (FTD), the most common cause of dementia in people <65 years of age (
      • Hogan D.B.
      • Jetté N.
      • Fiest K.M.
      • Roberts J.I.
      • Pearson D.
      • Smith E.E.
      • et al.
      The prevalence and incidence of frontotemporal dementia: A systematic review.
      ).
      SEE CORRESPONDING ARTICLE ON PAGE 825
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