This project aims to elucidate why individuals exposed to similar traumatic experiences develop different psychiatric disorders. Trauma and adversity are established risk factors for a broad spectrum of psychopathologies, including schizophrenia, anxiety, depression, obsessive-compulsive disorder (OCD), and bipolar disorder. Notably, childhood adversities have been linked to an increased risk of psychosis and other mental health conditions.

The central question addresses why, given equivalent trauma exposure, one individual may develop schizophrenia while another develops depression without psychotic features. A prevailing hypothesis suggests that genetic predispositions interact with traumatic experiences, activating specific latent vulnerabilities that steer individuals toward particular psychopathological outcomes. This aligns with the concept of gene-environment correlation, where genetic factors influence an individual's exposure to certain environments, subsequently affecting their mental health outcomes.

Polygenic scores (PGS) offer a quantitative measure of an individual's genetic liability to various psychiatric disorders. However, these scores often capture a shared genetic "p factor", which encompasses risks for multiple disorders, complicating the isolation of disorder-specific genetic risks. For instance, a high PGS for schizophrenia may also reflect elevated risks for bipolar disorder and major depressive disorder.

Here, we isolate disorder-specific polygenic risk scores to asses the contribution of distinct genetic liability to divergent psychiatric outcomes following trauma exposure (e.g., developing schizophrenia vs bipolar disorder vs major depressive disorder). The study will utilize genomic data from the North American Prodrome Longitudinal Study (NAPLS) cohort, which provides a valuable resource for examining the interplay between trauma exposure and genetic risk in individuals at high risk for psychosis. By integrating refined polygenic risk assessments with detailed trauma histories within the NAPLS cohort, this study seeks to advance our understanding of the mechanisms that drive divergent psychiatric outcomes following trauma exposure.

• /u/project/cbearden/hughesdy/genetics/summary_statistics
• SCZ/EUR, BIP, and MDD are in the corresponding folders.
• BIP and MDD are both derived from EUR samples.

Each have a file similar to:

• MDD19_forPRSCS.txt

These may have all required columns, but if not, check the raw files.

• MDD: PGC_UKB_depression_genome-wide.txt
• BIP: daner_pgc4_bd_eur_no23andMe_neff75_dentrem_HRCfrq
• SCZ: PGC3_SCZ_wave3.european.autosome.public.v3.vcf.tsv

• /u/project/cbearden/hughesdy/NAPLS/pgs/napls3/EUR
• /u/project/cbearden/hughesdy/NAPLS/nice-data

1. In theory, we can derive the SCZ-specific risk by subtracting the shared risk among SCZ, BIP, and MDD.
   1. For example, instead of subtracting EduA from Cog, we would subtract the combined risk (SCZ+BIP+MDD) from SCZ, from BIP, and from MDD.
   2. We may need to generate the shared risk using a standard gSEM model before applying the gwas-sub model.
   3. If this approach is not statistically justified, we might instead compare SCZ minus BIP.
   4. Alternatively, we could start with standard gSEM to derive a common factor among all disorders.
2. Trauma/adversity is a broad risk factor for psychopathology.
   1. It is implicated in schizophrenia, anxiety, depression, OCD, bipolar disorder, and other conditions.
   2. The key question is: given two individuals exposed to trauma, why does one develop schizophrenia while the other develops depression without psychotic features?
      1. One possibility is that genetic factors interact with trauma to activate an underlying predisposition for a specific form of psychopathology.
   3. Although polygenic scores can measure this underlying propensity, they also capture risk for other disorders because of a shared genetic p factor.
      1. When measuring schizophrenia risk, we are also assessing risk for bipolar disorder, MDD, and more.
      2. By isolating the disorder-specific risk, we can determine whether genetic differences drive one individual with trauma toward schizophrenia versus another toward bipolar disorder.
3. Partitioned PGSs represent a promising addition within the gSEM framework.
   1. They are compatible with gSEM and integrate well with the overall analysis.
   2. Although not yet fully validated, they offer a valuable exploratory extension to conventional PGS analyses.
   3. This method is relatively easy to add at the end, minimizing the upfront work during genetic QC and gSEM syntax development.

1. Bayesian polygenic score Probability Conversion (BPC)
2. CASTom-iGEx
3. DDx-PRS
4. Genomic Structural Invariance (GSI)
5. GenomicSEM
6. GenoPred
7. GSMR2
8. GSUB
9. GWAS-by-Subtraction
10. Local Standardized Root Mean-square Difference (localSRMD)
11. pathway-PRS
12. PleioPGS
13. PRSet
14. PRSice-2
15. SBayesRC

1. A phenome-wide association study of cross-disorder genetic liability in youth genetically similar to individuals from European reference populations [14 October 2024]
2. Attention-mediated genetic influences on psychotic symptomatology in adolescence [28 October 2024]
3. Boosting Schizophrenia Genetics by Utilizing Genetic Overlap With Brain Morphology [August 15, 2022]
4. Bridging the scales: leveraging personalized disease models and deep phenotyping to dissect cognitive impairment in schizophrenia [February 27, 2025]
5. Comparison of the multivariate genetic architecture of eight major psychiatric disorders across sex [07 March 2025]
6. Distinct genetic liability profiles define clinically relevant patient strata across common diseases [July 01, 2024]
7. Distinguishing different psychiatric disorders using DDx-PRS [February 4, 2024]
8. Gene set enrichment analysis of pathophysiological pathways highlights oxidative stress in psychosis [21 September 2022]
9. Genetic analysis of psychosis Biotypes: shared Ancestry-adjusted polygenic risk and unique genomic associations [21 December 2024]
10. Genetic patterning for child psychopathology is distinct from that for adults and implicates fetal cerebellar development [18 May 2023]
11. Genetic, transcriptomic, metabolic, and neuropsychiatric underpinnings of cortical functional gradients [March 05, 2025]
12. Investigating the genetic architecture of noncognitive skills using GWAS-by-subtraction [07 January 2021]
13. Isolating transdiagnostic effects reveals specific genetic profiles in psychiatric disorders [April 11, 2024]
14. Splitting Schizophrenia: Divergent Cognitive and Educational Outcomes Revealed by Genomic Structural Equation Modelling [October 24, 2024]
15. Pathway Polygenic Risk Scores (pPRS) for the Analysis of Gene-environment Interaction [December 20, 2024]
16. Patterns of stressful life events and polygenic scores for five mental disorders and neuroticism among adults with depression [04 April 2024]
17. Polygenic Scores and Networks of Psychopathology Symptoms [June 12, 2024]
18. PRSet: Pathway-based polygenic risk score analyses and software [February 7, 2023]
19. Psychological trauma as a transdiagnostic risk factor for mental disorder: an umbrella meta-analysis [08 October 2022]
20. Using polygenic scores corrected for the general psychopathology factor to predict specific psychopathology [March 19, 2024]