Brett A. Clementz

This study identifies three psychosis neurosubtypes using imaging data, showing distinct connectivity patterns and supporting their biological validity through relative alignment.

The paper analyzes psychosis biotypes using ancestry-adjusted polygenic risk scores and identifies genomic associations with specific biotypes in brain transcriptomes.

This paper introduces regression dynamic causal modeling (rDCM) for resting-state fMRI, providing directional connectivity estimates and scalability to whole-brain networks.

The paper identifies brain-wide bi-directional connectivity alterations in cortico-striato-cerebellar circuits in schizophrenia using resting-state fMRI and validates findings with clustering and classification methods.

The paper discusses challenges in genetic analysis of deep phenotyping projects in common disorders and highlights advances in imputation and GWAS methods to address these challenges.

The paper reports GWAS findings linking common variants in NRXN1, LRP1B, and RORA to increased ventricular volumes in psychosis, using deep phenotyping data from 1,115 cases and controls.

The paper investigates the association between schizophrenia genetic risk and cognitive performance in healthy individuals, finding a link with current cognitive abilities but not with premorbid intelligence or education.