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Classification of Schizophrenia, Bipolar Disorder and Major Depressive Disorder with Comorbid Traits and Deep
Xiangning Chen1, Yimei Liu2, Joan Cue2
1The university of Texas Health Science Center at Houston.
Research Square
|March 18, 2024
Summary
Shared genetic risks from 42 comorbid traits can classify and differentiate schizophrenia (SCZ), bipolar disorder (BIP), and major depressive disorder (MDD) using polygenic risk scores (PRSs) and deep neural networks (DNNs). This suggests objective diagnosis may be possible using these genetic markers.
Area of Science:
- Psychiatric Genetics
- Computational Psychiatry
- Machine Learning in Medicine
Background:
- Genome-wide association studies (GWASs) reveal shared genetic liabilities among comorbid psychiatric disorders.
- The utility of these shared genetic factors for precise classification and differentiation of disorders like schizophrenia, bipolar disorder, and major depressive disorder remains largely unexplored.
Conclusions:
- Shared genetic liabilities from comorbid traits alone appear sufficient for classifying and differentiating SCZ, BIP, and MDD.
- These findings support the feasibility of developing objective, data-driven diagnostic methods for these psychiatric disorders based on genetic information.
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