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Latent Clinical-Anatomical Dimensions of Schizophrenia.

ABSTRACT: Widespread structural brain abnormalities have been consistently reported in schizophrenia, but their relation to the heterogeneous clinical manifestations remains unknown. In particular, it is unclear whether anatomical abnormalities in discrete regions give rise to discrete symptoms or whether distributed abnormalities give rise to the broad clinical profile associated with schizophrenia. Here, we apply a multivariate data-driven approach to investigate covariance patterns between multiple-symptom domains and distributed brain abnormalities in schizophrenia. Structural magnetic resonance imaging and clinical data were derived from one discovery sample (133 patients and 113 controls) and one independent validation sample (108 patients and 69 controls). Disease-related voxel-wise brain abnormalities were estimated using deformation-based morphometry. Partial least-squares analysis was used to comprehensively map clinical, neuropsychological, and demographic data onto distributed deformation in a single multivariate model. The analysis identified 3 latent clinical-anatomical dimensions that collectively accounted for 55% of the covariance between clinical data and brain deformation. The first latent clinical-anatomical dimension was replicated in an independent sample, encompassing cognitive impairments, negative symptom severity, and brain abnormalities within the default mode and visual networks. This cognitive-negative dimension was associated with low socioeconomic status and was represented across multiple races. Altogether, we identified a continuous cognitive-negative dimension of schizophrenia, centered on 2 intrinsic networks. By simultaneously taking into account both clinical manifestations and neuroanatomical abnormalities, the present results open new avenues for multi-omic stratification and biotyping of individuals with schizophrenia.

SUBMITTER: Kirschner M

PROVIDER: S-EPMC8496914 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Multiple sources of evidence suggest that genetic factors influence variation in clinical features of schizophrenia. The authors present the first genome-wide association study (GWAS) of dimensional symptom scores among individuals with schizophrenia.Based on the Lifetime Dimensions of Psychosis Scale ratings of 2,454 case subjects of European ancestry from the Molecular Genetics of Schizophrenia (MGS) sample, three symptom factors (positive, negative/disorganized, and mood) were identified with exploratory factor analysis. Quantitative scores for each factor from a confirmatory factor analysis were analyzed for association with 696,491 single-nucleotide polymorphisms (SNPs) using linear regression, with correction for age, sex, clinical site, and ancestry. Polygenic score analysis was carried out to determine whether case and comparison subjects in 16 Psychiatric GWAS Consortium (PGC) schizophrenia samples (excluding MGS samples) differed in scores computed by weighting their genotypes by MGS association test results for each symptom factor.No genome-wide significant associations were observed between SNPs and factor scores. Most of the SNPs producing the strongest evidence for association were in or near genes involved in neurodevelopment, neuroprotection, or neurotransmission, including genes playing a role in Mendelian CNS diseases, but no statistically significant effect was observed for any defined gene pathway. Finally, polygenic scores based on MGS GWAS results for the negative/disorganized factor were significantly different between case and comparison subjects in the PGC data set; for MGS subjects, negative/disorganized factor scores were correlated with polygenic scores generated using case-control GWAS results from the other PGC samples.The polygenic signal that has been observed in cross-sample analyses of schizophrenia GWAS data sets could be in part related to genetic effects on negative and disorganized symptoms (i.e., core features of chronic schizophrenia).

Project description:ImportanceSchizophrenia is a clinically heterogeneous disorder. It is currently unclear how variability in symptom dimensions and cognitive ability is associated with genetic liability for schizophrenia.ObjectiveTo determine whether phenotypic dimensions within schizophrenia are associated with genetic liability to schizophrenia, other neuropsychiatric disorders, and intelligence.Design, setting, and participantsIn a genetic association study, 3 cross-sectional samples of 1220 individuals with a diagnosis of schizophrenia were recruited from community, inpatient, and voluntary sector mental health services across the UK. Confirmatory factor analysis was used to create phenotypic dimensions from lifetime ratings of the Scale for the Assessment of Positive Symptoms, Scale for the Assessment of Negative Symptoms, and the MATRICS Consensus Cognitive Battery. Analyses of polygenic risk scores (PRSs) were used to assess whether genetic liability to schizophrenia, other neuropsychiatric disorders, and intelligence were associated with these phenotypic dimensions. Data collection for the cross-sectional studies occurred between 1993 and 2016. Data analysis for this study occurred between January 2019 and March 2021.Main outcomes and measuresOutcome measures included phenotypic dimensions defined from confirmatory factor analysis relating to positive symptoms, negative symptoms of diminished expressivity, negative symptoms of motivation and pleasure, disorganized symptoms, and current cognitive ability. Exposure measures included PRSs for schizophrenia, bipolar disorder, major depression, attention-deficit/hyperactivity disorder, autism spectrum disorder, and intelligence.ResultsOf the 1220 study participants, 817 were men (67.0%). Participants' mean (SD) age at interview was 43.10 (12.74) years. Schizophrenia PRS was associated with increased disorganized symptom dimension scores in both a 5-factor model (β = 0.14; 95% CI, 0.07-0.22; P = 2.80 × 10-4) and a 3-factor model across all samples (β = 0.10; 95% CI, 0.05-0.15; P = 2.80 × 10-4). Current cognitive ability was associated with genetic liability to schizophrenia (β = -0.11; 95% CI, -0.19 to -0.04; P = 1.63 × 10-3) and intelligence (β = 0.23; 95% CI, 0.16-0.30; P = 1.52 × 10-10). After controlling for estimated premorbid IQ, current cognitive performance was associated with schizophrenia PRS (β = -0.08; 95% CI, -0.14 to -0.02; P = 8.50 × 10-3) but not intelligence PRS.Conclusions and relevanceThe findings of this study suggest that genetic liability for schizophrenia is associated with higher disorganized dimension scores but not other symptom dimensions. Cognitive performance in schizophrenia appears to reflect distinct contributions from genetic liabilities to both intelligence and schizophrenia.

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Latent Clinical-Anatomical Dimensions of Schizophrenia.

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