Comparison of heritability estimates on resting state fMRI connectivity phenotypes using the ENIGMA analysis pipeline

BACKGROUND: We measured and compared heritability estimates for measures of functional brain connectivity extracted using the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) rsfMRI analysis pipeline in two cohorts: the GOBS (Genetics of Brain Structure) cohort and the HCP (the Human Connectome Project) cohort. These two cohorts were assessed using conventional (GOBS) and advanced (HCP) rsfMRI protocols, offering a test case for harmonization of rsfMRI phenotypes, and to determine measures that show consistent heritability for in-depth genome-wide analysis. METHODS: The GOBS cohort consisted of 334 Mexican-American individuals (124M/210F, average age=47.9±13.2 years) from 29 extended pedigrees (average family size=9 people; range 5–32). The GOBS rsfMRI data was collected using a 7.5-minute acquisition sequence (spatial resolution=1.72×1.72×3 mm(3)). The HCP cohort consisted of 518 twins and family members (240M/278F; average age=28.7± 3.7 years). rsfMRI data was collected using 28.8-minute sequence (spatial resolution=2×2×2 mm(3)). We used the single-modality ENIGMA rsfMRI preprocessing pipeline to estimate heritability values for measures from eight major functional networks, using (1) seed-based connectivity and (2) dual regression approaches. RESULTS: We observed significant heritability (h(2)=0.2–0.4, p