Latent Clinical-Anatomical Dimensions of Schizophrenia.
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ABSTRACT:
SUBMITTER: Kirschner M
PROVIDER: S-EPMC8496914 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Bipolar disorder and schizophrenia are two often severe disorders with high heritabilities. Recent studies have demonstrated a large overlap of genetic risk loci between these disorders but diagnostic and molecular distinctions still remain. Here, we perform a combined genome-wide association study (GWAS) of 19 779 bipolar disorder (BP) and schizophrenia (SCZ) cases versus 19 423 controls, in addition to a direct comparison GWAS of 7129 SCZ cases versus 9252 BP cases. In our case-control analysis, we identify five previously identified regions reaching genome-wide significance (CACNA1C, IFI44L, MHC, TRANK1 and MAD1L1) and a novel locus near PIK3C2A. We create a polygenic risk score that is significantly different between BP and SCZ and show a significant correlation between a BP polygenic risk score and the clinical dimension of mania in SCZ patients. Our results indicate that first, combining diseases with similar genetic risk profiles improves power to detect shared risk loci and second, that future direct comparisons of BP and SCZ are likely to identify loci with significant differential effects. Identifying these loci should aid in the fundamental understanding of how these diseases differ biologically. These findings also indicate that combining clinical symptom dimensions and polygenic signatures could provide additional information that may someday be used clinically.
| S-EPMC4033708 | biostudies-literature
Project description:Cellular signal transduction is coordinated by modifications of many proteins within cells. Protein modifications are not independent, because some are connected through shared signaling cascades and others jointly converge upon common cellular functions. This coupling creates a hidden structure within a signaling network that can point to higher level organizing principles of interest to systems biology. One can identify important covariations within large-scale datasets by using mathematical models that extract latent dimensions-the key structural elements of a measurement set. In this paper, we introduce two principal component-based methods for identifying and interpreting latent dimensions. Principal component analysis provides a starting point for unbiased inspection of the major sources of variation within a dataset. Partial least-squares regression reorients these dimensions toward a specific hypothesis of interest. Both approaches have been used widely in studies of cell signaling, and they should be standard analytical tools once highly multivariate datasets become straightforward to accumulate.
| S-EPMC3769421 | biostudies-literature
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).
| S-EPMC3646712 | biostudies-literature
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.
| S-EPMC8340009 | biostudies-literature
Project description:Recent research has described the structure of psychopathology as including one general and multiple specific factors, and this structure has been found in samples across development. However, little work has examined whether this structure is consistent across time, particularly in young children, within the same sample. Further, few studies have examined factors that influence the magnitude of the stability of latent dimensions of psychopathology. In the present study, we examine these issues in a community sample of 545 children assessed at ages 3 and 6. In addition, we explored child temperament, parental history of psychopathology, and parenting behaviors as potential moderators of the longitudinal stability of latent dimensions of psychopathology. We found that the same bifactor model structure identified at age 3 provided an adequate fit to the data at age 6. Further, our model revealed significant homotypic stability of the general, internalizing, and externalizing specific factors. We also found evidence of differentiation of psychopathology over time with the general factor at age 3 predicting the externalizing factor at age 6. However, we failed to identify moderators of the longitudinal associations between psychopathology latent factors. Overall, our results bolster support for the bifactor structure of psychopathology, particularly in early childhood.
| S-EPMC6056348 | biostudies-literature
Project description:In classical statistics, much thought has been put into experimental design and data collection. In the high-dimensional setting, however, experimental design has been less of a focus. In this paper, we stress the importance of collecting multiple replicates for each subject in this setting. We consider learning the structure of a graphical model with latent variables, under the assumption that these variables take a constant value across replicates within each subject. By collecting multiple replicates for each subject, we are able to estimate the conditional dependence relationships among the observed variables given the latent variables. To test the null hypothesis of conditional independence between two observed variables, we propose a pairwise decorrelated score test. Theoretical guarantees are established for parameter estimation and for this test. We show that our proposal is able to estimate latent variable graphical models more accurately than some existing proposals, and apply the proposed method to a brain imaging dataset.
| S-EPMC5520622 | biostudies-literature
Project description:BackgroundDeficit schizophrenia (DS) has been proposed as a pathophysiologically distinct subgroup within schizophrenia. Earlier studies focusing on neurocognitive function of DS patients have yielded inconsistent findings ranging from substantial deficits to no significant difference relative to non-deficit schizophrenia patients (NDS). The present study investigated the severity and characteristic patterns of neurocognitive impairments in DS and NDS patients and their relationships with clinical variables.MethodsAttention, ideation fluency, cognitive flexibility and visuospatial memory function were assessed in 40 DS patients, 57 NDS patients, and 52 healthy controls by a comprehensive neuropsychological battery.ResultsBoth schizophrenia subgroups had overall more severe cognitive impairments than controls while DS performed worse on every neuropsychological measure except the Stroop interference than the NDS patients with age and education as the covariates. Profile analysis found significantly different patterns of cognitive profiles between two patients group mainly due to their differences in attention and cognitive flexibility functions. Age, education, illness duration and negative symptoms were found to have the correlations with cognitive impairments in the NDS group, while only age and the negative symptoms were correlated with the cognitive impairments in the DS group. Multiple regression analyses revealed that sustained attention and cognitive flexibility were the core impaired cognitive domains mediating other cognitive functions in DS and NDS patients respectively.ConclusionsDS patients exemplified worse in almost all cognitive domains than NDS patients. Sustained attention and cognitive flexibility might be the key impaired cognitive domains for DS and NDS patients respectively. The present study suggested the DS as a specific subgroup of schizophrenia.
| S-EPMC4575183 | biostudies-literature
Project description:Anatomical connectivity between the thalamus and cortex, including the prefrontal cortex (PFC), is abnormal in schizophrenia. Overlapping phenotypes, including deficits in executive cognitive abilities dependent on PFC-thalamic circuitry, suggest dysrupted thalamocortical anatomical connectivity may extend to psychotic bipolar disorder. We tested this hypothesis and examined the impact of illness stage to inform when in the illness course thalamocortical dysconnectivity emerges. Diffusion-weighted imaging data were collected on 70 healthy individuals and 124 people with a psychotic disorder (schizophrenia spectrum = 75; psychotic bipolar disorder = 49), including 62 individuals in the early stage of psychosis. Anatomical connectivity between major divisions of the cortex and thalamus was quantified using probabilistic tractography and compared between groups. Associations between PFC-thalamic anatomical connectivity and executive cognitive abilities were examined using regression analysis. Psychosis was associated with lower PFC-thalamic and elevated somatosensory-thalamic anatomical connectivity. Follow-up analyses established that lower PFC-thalamic and elevated somatosensory-thalamic anatomical connectivity were present in both schizophrenia and psychotic bipolar disorder. Lower PFC-thalamic anatomical connectivity was also present in early-stage and chronic psychosis. Contrary to expectations, lower PFC-thalamic anatomical connectivity was not associated with impaired executive cognitive abilities. Altered thalamocortical anatomical connectivity, especially reduced PFC-thalamic connectivity, is a transdiagnostic feature of psychosis detectable in the early stage of illness. Further work is required to elucidate the functional consequences of the full spectrum of thalamocortical connectivity abnormalities in psychosis.
| S-EPMC7505173 | biostudies-literature
Project description:ObjectiveThe purpose of the study was to define the latent structure of parent-reported manic symptoms and their association with functional impairment and familial risk in a community sample of Brazilian children.MethodWe screened for manic symptoms in a community sample of 2,512 children 6 to 12 years of age. Parents of children with "episodes of going abnormally high" completed a detailed mania section (n = 479; 19.1%). Confirmatory factor analysis (CFA) tested a solution with "Under-Control (UC)" and "Exuberant (EX)" dimensions, investigating the severity (threshold) and factor loading of each symptom. We also used latent class analysis (LCA) to evaluate the latent categorical structure of manic symptoms. Associations of these latent constructs with psychiatric comorbidity, psychosocial impairment, and family history of psychopathology were tested.ResultsThe 2-dimensional model fit the data well. Only the UC dimension was associated with psychiatric morbidity, psychosocial impairment, and a family history of mania, depression, or suicide attempts. Both UC and EX items discriminated subjects with "episodes of going abnormally high," but EX items lay at the mild end of the severity spectrum, whereas UC items lay at the severe end. The LCA yielded a small group of children with high levels of manic symptoms and a distinct profile of psychiatric comorbidity and impairment ("high-symptom group").ConclusionIn a large, community-based sample, we found a 2-dimensional latent structure for parent-reported manic symptoms in youth, and demonstrated familial associations between the UC dimension and affective disorders. Both UC and EX items are clinically useful, but their contributions vary with symptom severity.
| S-EPMC4477846 | biostudies-literature
Project description:ImportanceNegative symptoms are associated with a range of poor clinical outcomes, and currently available treatments generally do not produce a clinically meaningful response. Limited treatment progress may be owing in part to poor clarity regarding latent structure. Prior studies have inferred latent structure using exploratory factor analysis, which has led to the conclusion that there are 2 dimensions reflecting motivation and pleasure (MAP) and diminished expressivity (EXP) factors. However, whether these conclusions are statistically justified remains unclear because exploratory factor analysis does not test latent structure. Confirmatory factor analysis (CFA) is needed to test competing models regarding the latent structure of a construct.ObjectiveTo evaluate the fit of 4 models of the latent structure of negative symptoms in schizophrenia using CFA.Design, setting, and participantsThree cross-sectional studies were conducted on outpatients with schizophrenia who were rated on the 3 most conceptually contemporary measures: Scale for the Assessment of Negative Symptoms (SANS), Brief Negative Symptom Scale (BNSS), and Clinical Assessment Interview for Negative Symptoms (CAINS). Confirmatory factor analysis evaluated the following 4 models: (1) a 1-factor model; (2) a 2-factor model with EXP and MAP factors; (3) a 5-factor model with separate factors for the 5 domains of the National Institute of Mental Health consensus development conference (blunted affect, alogia, anhedonia, avolition, and asociality); and (4) a hierarchical model with 2 second-order factors reflecting EXP and MAP and 5 first-order factors reflecting the 5 consensus domains.Main outcomes and measuresOutcomes included CFA model fit statistics derived from symptom severity scores on the SANS, BNSS, and CAINS.ResultsThe study population included 860 outpatients with schizophrenia (68.0% male; mean [SD] age, 43.0 [11.4] years). Confirmatory factor analysis was conducted on each scale, including 268 patients for the SANS, 192 for the BNSS, and 400 for the CAINS. The 1- and 2-factor models provided poor fit for the SANS, BNSS, and CAINS as indicated by comparative fit indexes (CFIs) and Tucker Lewis indexes (TLIs) less than 0.950, RMSEAs that exceeded the 0.080 threshold, and WRMRs greater than 1.00. The 5-factor and hierarchical models provided excellent fit, with the 5-factor model being more parsimonious. The CFIs and TLIs met the 0.95 threshold and the 1.00 threshold for both factor models with all 3 measures. Interestingly, the RMSEAs for the 5-factor model and the hierarchical model fell under the 0.08 threshold for the BNSS and the CAINS but not the SANS.Conclusions and relevanceThese findings suggest that the recent trend toward conceptualizing the latent structure of negative symptoms as 2 distinct dimensions does not adequately capture the complexity of the construct. The latent structure of negative symptoms is best conceptualized in relation to the 5 consensus domains. Implications for identifying pathophysiological mechanisms and targeted treatments are discussed.
| S-EPMC6583036 | biostudies-literature