Psychosis beyond symptoms: Cognitive and genetic biomarkers of schizophrenia

Project Type(s):

Principal Investigator(s):

Schizophrenia is a prevalent, debilitating psychiatric disorder that is diagnosed based on clinical interviews that are subjective and highly variable; in fact, two patients can have no overlapping symptoms and be diagnosed with the same disease. While cardiologists have blood tests to help diagnose heart attacks and oncologists have PET scans to find hidden cancers, psychiatrists don’t have objective diagnostic tests. This proposal will utilize machine learning to analyze cognitive tests, brain electrical activity, and genetic signatures from 1,415 patients with schizophrenia and 1,062 controls to uncover biomarkers of schizophrenia. By incorporating biomarkers into diagnostic standards, psychiatrists could one day order a simple test that could help them confidently diagnose schizophrenia and make better treatment decisions based on quantitative rather than subjective measures.

Project Period:
September 1, 2024 — August 31, 2025

Funding Type(s):
State/UW

Funder(s):
Clinician Scientist Training Program

Research Program(s):

Geographic Area(s):
University of Washington

Practice Type(s):
Outpatient

Patient Population(s):
Adults

Targeted Condition(s):
Psychosis