Genetic liability estimated from large-scale family data improves genetic prediction, risk score profiling, and gene mapping for major depression.

doi:10.1016/j.ajhg.2024.09.009

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Article

Genetic liability estimated from large-scale family data improves genetic prediction, risk score profiling, and gene mapping for major depression.

American journal of human genetics - 7 Nov 2024

Dybdahl Krebs Morten, Georgii Hellberg Kajsa-Lotta, Lundberg Mischa, Appadurai Vivek, Ohlsson Henrik, Pedersen Emil, Steinbach Jette, Matthews Jamie, Border Richard, LaBianca Sonja, Calle Xabier, Meijsen Joeri J, Ingason Andrés, Buil Alfonso, Vilhjálmsson Bjarni J, Flint Jonathan, Bacanu Silviu-Alin, Cai Na, Dahl Andy, Zaitlen Noah, Werge Thomas, Kendler Kenneth S, Schork Andrew J

Abstract excerpt

Large biobank samples provide an opportunity to integrate broad phenotyping, familial records, and molecular genetics data to study complex traits and diseases. We introduce Pearson-Aitken Family Genetic Risk Scores (PA-FGRS), a method for estimating disease liability from patterns of diagnoses in extended, age-censored genealogical records. We then apply the method to study a paradigmatic complex disorder, major...

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PMID: 39471805
DOI: 10.1016/j.ajhg.2024.09.009
PMCID: PMC11568754

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