Diagnosing migraine from genome-wide genotype data: a machine learning analysis.

ABSTRACT: Migraine has an assumed polygenic basis, but the genetic risk variants identified in genome-wide association studies only explain a proportion of the heritability. We aimed to develop machine learning models, capturing non-additive and interactive effects, to address the missing heritability. This was a cross-sectional population-based study of participants in the second and third Trøndelag Health Study. Individuals underwent genome-wide genotyping and were phenotyped based on validated modified criteria of the International Classification of Headache Disorders. Four datasets of increasing numbers of genetic variants were created using different thresholds of linkage disequilibrium and univariate genome-wide associated P-values. A series of machine learning and deep learning methods were o

SUBMITTER: Danelakis A 

PROVIDER: S-EPMC12782171 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature