Patrick M. Sleiman, Hui‐Qi Qu, John J. Connolly, Frank Mentch, Alexandre Pereira, Paulo A. Lotufo, Stephen Tollman, Ananyo Choudhury, Michele Ramsay, Norihiro Kato, Kouichi Ozaki, Risa Mitsumori, Jae‐Pil Jeon, Chang Hyung Hong, Sang Joon Son, Hyun Woong Roh, Dong‐gi Lee, Naaheed Mukadam, Isabelle F. Foote, Charles R. Marshall, Adam Butterworth, Bram P. Prins, Joseph T. Glessner, Hakon Hakonarson,

Trans‐ethnic genomic informed risk assessment for Alzheimer's disease: An International Hundred K+ Cohorts Consortium study

  • Psychiatry and Mental health
  • Cellular and Molecular Neuroscience
  • Geriatrics and Gerontology
  • Neurology (clinical)
  • Developmental Neuroscience
  • Health Policy
  • Epidemiology
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AbstractBACKGROUNDAs a collaboration model between the International HundredK+ Cohorts Consortium (IHCC) and the Davos Alzheimer's Collaborative (DAC), our aim was to develop a trans‐ethnic genomic informed risk assessment (GIRA) algorithm for Alzheimer's disease (AD).METHODSThe GIRA model was created to include polygenic risk score calculated from the AD genome‐wide association study loci, the apolipoprotein E haplotypes, and non‐genetic covariates including age, sex, and the first three principal components of population substructure.RESULTSWe validated the performance of the GIRA model in different populations. The proteomic study in the participant sites identified proteins related to female infertility and autoimmune thyroiditis and associated with the risk scores of AD.CONCLUSIONSAs the initial effort by the IHCC to leverage existing large‐scale datasets in a collaborative setting with DAC, we developed a trans‐ethnic GIRA for AD with the potential of identifying individuals at high risk of developing AD for future clinical applications.

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