Polygenic signal for symptom dimensions and cognitive performance in patients with chronic schizophrenia.
- Authors
- Xavier, Rose Mary; Dungan, Jennifer R; Keefe, Richard S E; Vorderstrasse, Allison
- Year
- 2018
- Journal
- Schizophrenia research. Cognition
- PMID
- 29552508
- DOI
- 10.1016/j.scog.2018.01.001
- PMCID
- PMC5852279
Genetic etiology of psychopathology symptoms and cognitive performance in schizophrenia is supported by candidate gene and polygenic risk score (PRS) association studies. Such associations are reported to be dependent on several factors - sample characteristics, illness phase, illness severity etc. We aimed to examine if schizophrenia PRS predicted psychopathology symptoms and cognitive performance in patients with chronic schizophrenia. We also examined if schizophrenia associated autosomal loci were associated with specific symptoms or cognitive domains. Case-only analysis using data from the Clinical Antipsychotics Trials of Intervention Effectiveness-Schizophrenia trials ( = 730). PRS was constructed using Psychiatric Genomics Consortium (PGC) leave one out genome wide association analysis as the discovery data set. For candidate region analysis, we selected 105-schizophrenia associated autosomal loci from the PGC study. We found a significant effect of PRS on positive symptoms at -threshold ( ) of 0.5 ( = 0.007, = 0.029, empirical = 0.029) and negative symptoms at of 1e-07 ( = 0.005, = 0.047, empirical = 0.048). For models that additionally controlled for neurocognition, best fit PRS predicted positive (threshold 0.01, 0.007, 0.013, empirical = 0.167) and negative symptoms (threshold 0.1, 0.012, 0.004, empirical = 0.329). No associations were seen for overall neurocognitive and social cognitive performance tests. Post-hoc analyses revealed that PRS predicted working memory and vigilance performance but did not survive correction. No candidate regions that survived multiple testing corrections were associated with either symptoms or cognitive performance. Our findings point to potentially distinct pathogenic mechanisms for schizophrenia symptoms.
Model 1 fit for polygenic risk score predictions on positive and negative symptom dimensions. The plots show model 1 results of 13 analyses based on SNP set without linkage disequilibrium. For each PT, SNPs are selected if significant at that threshold and coefficients and effect sizes estimated. Values above each bar are unadjusted p-values of phenotype from regression analyses. For 1A, the best fit PRS for negative symptoms is at the PT of 1e-07 and explains roughly 0.5% of the variance. For 1B, the best fit PRS for positive symptoms is at PT of 0.5 and roughly explains 0.7% of the variance.
Model 2 fit for polygenic risk score predictions on positive and negative symptom dimensions. The plots show model 2 results of 13 analyses based on SNP set without linkage disequilibrium. For each PT, SNPs are selected if significant at that threshold and coefficients and effect sizes estimated. Values above each bar are unadjusted p-values of phenotype from regression analyses. For 2A, the best fit PRS for negative symptoms is at PT of 0.1 and explains roughly 1.2% of the variance. For 2B, the best fit PRS for positive symptoms is at PT of 0.01 and roughly explains 0.7% of the variance.
Model fit for polygenic risk score predictions of neurocognitive domains (working memory and vigilance) from post hoc analyses. The plots show the results of 13 analyses per variable based on SNP set without linkage disequilibrium. For each PT, SNPs are selected if significant at that threshold and coefficients and effect sizes estimated. Values above each bar are unadjusted p-values of phenotype from regression analyses. For 3A, the best fit PRS for working memory is at PT of 1e-05 and explains roughly 0.6% of the variance. For 3B, the best fit PRS for vigilance is at PT of 1e-04 and roughly explains 0.8% of the variance.
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| The continuity of effect of schizophrenia polygenic risk score and patterns of cannabis use on transdiagnostic symptom dimensions at first-episode psychosis: findings from the EU-GEI study. | Quattrone D et al. | — | 2021 | → |
| Association of schizophrenia polygenic risk score with data-driven cognitive subtypes: A six-year longitudinal study in patients, siblings and controls. | Habtewold TD et al. | — | 2020 | → |
| CHIMGEN: a Chinese imaging genetics cohort to enhance cross-ethnic and cross-geographic brain research. | Xu Q et al. | — | 2020 | → |
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| Rare copy number variants in individuals at clinical high risk for psychosis: Enrichment of synaptic/brain-related functional pathways. | Jagannath V et al. | — | 2020 | → |
| Developmental Genes and Regulatory Proteins, Domains of Cognitive Impairment in Schizophrenia Spectrum Psychosis and Implications for Antipsychotic Drug Discovery: The Example of Dysbindin-1 Isoforms and Beyond. | Waddington JL et al. | — | 2019 | → |
| Prefrontal Coexpression of Schizophrenia Risk Genes Is Associated With Treatment Response in Patients. | Pergola G et al. | — | 2019 | → |
| Schizophrenia polygenic risk score and cannabis use modify psychosis expression in first episode psychosis patients and population controls | Quattrone D et al. | — | 2019 | — |