S D Patel

TL;DR: This work maps the genomic and biological landscape for schizophrenia, providing leads towards a better understanding of illness, diagnostics and therapeutics, and reveals the significant genetic overlap with other major psychiatric disorder domains, suggesting the need for improved nosology.

TL;DR: A predictive score developed based on a panel of 10 top candidate biomarkers shows sensitivity and specificity for high mood and low mood states, in two independent cohorts suggest that blood biomarkers may offer an unexpectedly informative window into brain functioning and disease state.

TL;DR: This analysis is the most comprehensive integration of genetics and functional genomics to date in the field of bipolar disorder, yielding a series of novel candidate genes, blood biomarkers, as well as a comprehensive identification of pathways and mechanisms.

TL;DR: Predictive scores show good sensitivity and negative predictive value for detecting high psychosis states in the original cohort as well as in three additional cohorts, with implications for the development of objective laboratory tests to measure illness severity and response to treatment in devastating disorders such as schizophrenia.

TL;DR: A comprehensive convergent analysis of brain gene expression data from a relevant pharmacogenomic mouse model and human genetic linkage data and human postmortem brain data suggests that schizophrenia is primarily a disorder of brain functional and structural connectivity, with GABA neurotransmission playing a prominent role.