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Classifying Mental Disorders Genetically: Genomic Factor Analysis
27 Pages Posted: 26 Jul 2019
More...Abstract
Background: Typically, mental disorders are defined and classified based on clinical symptoms and syndromes. Although clinically useful, current diagnostic systems for psychiatry cause concerns due to the lack of biological mechanisms. Deciphering the relationships among psychiatric traits according to their genetic basis may facilitate understanding biological mechanisms of psychiatric disorders.
Methods: Ten mental disorders were classified by genomic structural equation modeling (SEM) which leverages summary results of genome-wide association studies. Attention deficit/hyperactivity disorder (ADHD), anorexia nervosa (AN), anxiety disorder (ANX), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), posttraumatic stress disorder (PTSD), schizophrenia (SZ), and Tourette syndrome (TS) were included.
Findings: Our analysis indicates that the ten psychiatric conditions were genetically inter-correlated with one another can be separated based on their general psychopathology. Most disorders have a close partner, forming pairs of traits, including SZ with BD, MDD with ANX, ADHD with ASD, and OCD with PTSD. TS and AN are two distinctive conditions, although both of them share some common components with OCD. At a higher level, MDD, ANX, ADHD, ASD, and PTSD cluster together, while OCD, AN, and TS cluster together. Together, the ten traits may constitute a hierarchical classificatory system.
Interpretation: Our study allows inference of genetically determined classification of the ten mental disorders, which may biologically inform current diagnostic framework.
Funding: National Natural Science Foundation of China and Primary Research & Development Plan of Jiangsu Province.
Declaration of Interest: We declare no competing interests.
Ethical Approval: Missing
Keywords: mental disorders; classification; structural equation modeling; exploratory factor analysis; confirmatory factor analysis
Suggested Citation: Suggested Citation