Polygenic Risk Scores for Subtyping of Schizophrenia

Schizophrenia is a complex disorder with many comorbid conditions. In this study, we used polygenic risk scores (PRSs) from schizophrenia and comorbid traits to explore consistent cluster structure in schizophrenia patients. With 10 comorbid traits, we found a stable 4-cluster structure in two datasets (MGS and SSCCS). When the same traits and parameters were applied for the patients in a clinical trial of antipsychotics, the CATIE study, a 5-cluster structure was observed. One of the 4 clusters found in the MGS and SSCCS was further split into two clusters in CATIE, while the other 3 clusters remained unchanged. For the 5 CATIE clusters, we evaluated their association with the changes of clinical symptoms, neurocognitive functions, and laboratory tests between the enrollment baseline and the end of Phase I trial. Class I was found responsive to treatment, with significant reduction for the total, positive, and negative symptoms (p=0.0001, 0.0099, and 0.0028, respectively), and improvement for cognitive functions (VIGILANCE, p=0.0099; PROCESSING SPEED, p=0.0006; WORKING MEMORY, p=0.0023; and REASONING, p=0.0015). Class II had modest reduction of positive symptoms (p=0.0492) and better PROCESSING SPEED (p=0.0071). Class IV had a specific reduction of negative symptoms (p=0.0111) and modest cognitive improvement for all tested domains. Interestingly, Class IV was also associated with decreased lymphocyte counts and increased neutrophil counts, an indication of ongoing inflammation or immune dysfunction. In contrast, Classes III and V showed no symptom reduction but a higher level of phosphorus. Overall, our results suggest that PRSs from schizophrenia and comorbid traits can be utilized to classify patients into subtypes with distinctive clinical features. This genetic susceptibility based subtyping may be useful to facilitate more effective treatment and outcome prediction.

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Decreased processing speed might account for working memory span deficit in schizophrenia, and might mediate the associations between working memory span and clinical symptoms

European Psychiatry ◽

10.1016/j.eurpsy.2014.02.009 ◽

2014 ◽

Vol 29 (8) ◽

pp. 473-478 ◽

Cited By ~ 7

Author(s):

G. Brébion ◽

C. Stephan-Otto ◽

E. Huerta-Ramos ◽

J. Usall ◽

M. Perez del Olmo ◽

...

Keyword(s):

Working Memory ◽

Processing Speed ◽

Memory Impairment ◽

Negative Symptoms ◽

Memory Span ◽

Clinical Symptoms ◽

Verbal Working Memory ◽

Motor Speed ◽

Speed Measure ◽

Cognitive Speed

AbstractObjectiveVerbal working memory span is decreased in patients with schizophrenia, and this might contribute to impairment in higher cognitive functions as well as to the formation of certain clinical symptoms. Processing speed has been identified as a crucial factor in cognitive efficiency in this population. We tested the hypothesis that decreased processing speed underlies the verbal working memory deficit in patients and mediates the associations between working memory span and clinical symptoms.MethodForty-nine schizophrenia inpatients recruited from units for chronic and acute patients, and forty-five healthy participants, were involved in the study. Verbal working memory span was assessed by means of the letter-number span. The Digit Copy test was used to assess motor speed, and the Digit Symbol Substitution Test to assess cognitive speed.ResultsThe working memory span was significantly impaired in patients (F(1,90) = 4.6, P < 0.05). However, the group difference was eliminated when either the motor or the cognitive speed measure was controlled (F(1,89) = 0.03, P = 0.86, and F(1,89) = 0.03, P = 0.88). In the patient group, working memory span was significantly correlated with negative symptoms (r = –0.52, P < 0.0001) and thought disorganisation (r = –0.34, P < 0.025) scores. Regression analyses showed that the association with negative symptoms was no longer significant when the motor speed measure was controlled (β = –0.12, P = 0.20), while the association with thought disorganisation was no longer significant when the cognitive speed measure was controlled (β = –0.10, P = 0.26).ConclusionsDecrement in motor and cognitive speed plays a significant role in both the verbal working memory impairment observed in patients and the associations between verbal working memory impairment and clinical symptoms.

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Discriminating bipolar depression from major depressive disorder with polygenic risk scores

Psychological Medicine ◽

10.1017/s003329172000015x ◽

2020 ◽

pp. 1-8 ◽

Cited By ~ 1

Author(s):

David T. Liebers ◽

Mehdi Pirooznia ◽

Andrea Ganna ◽

Fernando S. Goes ◽

Keyword(s):

Major Depressive Disorder ◽

Depressive Disorder ◽

Clinical Features ◽

Clinical Symptoms ◽

Bipolar Depression ◽

Risk Scores ◽

Characteristic Analysis ◽

Major Depressive ◽

Polygenic Risk ◽

Increased Risk

Abstract Background Although accurate differentiation between bipolar disorder (BD) and unipolar major depressive disorder (MDD) has important prognostic and therapeutic implications, the distinction is often challenging based on clinical grounds alone. In this study, we tested whether psychiatric polygenic risk scores (PRSs) improve clinically based classification models of BD v. MDD diagnosis. Methods Our sample included 843 BD and 930 MDD subjects similarly genotyped and phenotyped using the same standardized interview. We performed multivariate modeling and receiver operating characteristic analysis, testing the incremental effect of PRSs on a baseline model with clinical symptoms and features known to associate with BD compared with MDD status. Results We found a strong association between a BD diagnosis and PRSs drawn from BD (R2 = 3.5%, p = 4.94 × 10−12) and schizophrenia (R2 = 3.2%, p = 5.71 × 10−11) genome-wide association meta-analyses. Individuals with top decile BD PRS had a significantly increased risk for BD v. MDD compared with those in the lowest decile (odds ratio 3.39, confidence interval 2.19–5.25). PRSs discriminated BD v. MDD to a degree comparable with many individual symptoms and clinical features previously shown to associate with BD. When compared with the full composite model with all symptoms and clinical features PRSs provided modestly improved discriminatory ability (ΔC = 0.011, p = 6.48 × 10−4). Conclusions Our study demonstrates that psychiatric PRSs provide modest independent discrimination between BD and MDD cases, suggesting that PRSs could ultimately have utility in subjects at the extremes of the distribution and/or subjects for whom clinical symptoms are poorly measured or yet to manifest.

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Central and non-central networks, cognition, clinical symptoms, and polygenic risk scores in schizophrenia

Human Brain Mapping ◽

10.1002/hbm.23798 ◽

2017 ◽

Vol 38 (12) ◽

pp. 5919-5930 ◽

Cited By ~ 10

Author(s):

Clara Alloza ◽

Mark E. Bastin ◽

Simon R. Cox ◽

Jude Gibson ◽

Barbara Duff ◽

...

Keyword(s):

Clinical Symptoms ◽

Risk Scores ◽

Polygenic Risk

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Genome-wide Association Study of Clinical Features in the Schizophrenia Psychiatric Genomics Consortium: Confirmation of Polygenic Effect on Negative Symptoms

10.1101/161349 ◽

2017 ◽

Cited By ~ 1

Author(s):

Tim B. Bigdeli ◽

Roseann E. Peterson ◽

Stephan Ripke ◽

Silviu-Alin Bacanu ◽

Richard L. Amdur ◽

...

Keyword(s):

Association Study ◽

Negative Symptom ◽

Negative Symptoms ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

European Ancestry ◽

Risk Scores ◽

Symptom Dimensions ◽

Polygenic Risk ◽

Genome Wide

AbstractSchizophrenia is a clinically heterogeneous disorder. Proposed revisions inDSM - 5included dimensional measurement of different symptom domains. We sought to identify common genetic variants influencing these dimensions, and confirm a previous association between polygenic risk of schizophrenia and the severity of negative symptoms. The Psychiatric Genomics Consortium study of schizophrenia comprised 8,432 cases of European ancestry with available clinical phenotype data. Symptoms averaged over the course of illness were assessed using theOPCRIT, PANSS, LDPS, SCAN, SCID, and CASH. Factor analyses of each constituentPGCstudy identified positive, negative, manic, and depressive symptom dimensions. We examined the relationship between the resultant symptom dimensions and aggregate polygenic risk scores indexing risk of schizophrenia. We performed genome - wide association study (GWAS) of each quantitative traits using linear regression and adjusting for significant effects of sex and ancestry. The negative symptom factor was significantly associated with polygene risk scores for schizophrenia, confirming a previous, suggestive finding by our group in a smaller sample, though explaining only a small fraction of the variance. In subsequentGWAS, we observed the strongest evidence of association for the positive and negative symptom factors, withSNPsinRFX8on 2q11.2 (P = 6.27×10-8) and upstream ofWDR72 / UNC13Con 15q21.3 (P= 7.59×10-8), respectively. We report evidence of association of novel modifier loci for schizophrenia, though no single locus attained established genome - wide significance criteria. As this may have been due to insufficient statistical power, follow - up in additional samples is warranted. Importantly, we replicated our previous finding that polygenic risk explains at least some of the variance in negative symptoms, a core illness dimension.

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Reinforcement learning as an intermediate phenotype in psychosis? Deficits sensitive to illness stage but not associated with polygenic risk of schizophrenia in the general population

10.1101/668939 ◽

2019 ◽

Author(s):

M Montagnese ◽

F Knolle ◽

J Haarsma ◽

JD Griffin ◽

A Richards ◽

...

Keyword(s):

Reinforcement Learning ◽

General Population ◽

Clinical Symptoms ◽

First Episode Psychosis ◽

Intermediate Phenotype ◽

Risk Scores ◽

First Episode ◽

Lower Sensitivity ◽

Polygenic Risk ◽

Episode Psychosis

AbstractBackgroundSchizophrenia is a complex disorder in which the causal relations between risk genes and observed clinical symptoms are not well understood and the explanatory gap is too wide to be clarified without considering an intermediary level. Thus, we aimed to test the hypothesis of a pathway from molecular polygenic influence to clinical presentation occurring via deficits in reinforcement learning.MethodsWe administered a reinforcement learning task (Go/NoGo) that measures reinforcement learning and the effect of Pavlovian bias on decision making. We modelled the behavioural data with a hierarchical Bayesian approach (hBayesDM) to decompose task performance into its underlying learning mechanisms. Study 1 included controls (n= 29, F|M=0.81), At Risk Mental State for psychosis (ARMS, n= 23, F|M=0.35) and FEP (First-episode psychosis, n= 26, F|M=0.18). Study 2 included healthy adolescents (n= 735, F|M= 1.06), 390 of whom had their polygenic risk scores for schizophrenia (PRSs) calculated.ResultsPatients with FEP showed significant impairments in overriding Pavlovian conflict, a lower learning rate and a lower sensitivity to both reward and punishment. Less widespread deficits were observed in ARMS. PRSs did not significantly predict performance on the task in the general population, which only partially correlated with measures of psychopathology.ConclusionsReinforcement learning deficits are observed in first episode psychosis and, to some extent, in those at clinical risk for psychosis, and were not predicted by molecular genetic risk for schizophrenia in healthy individuals. The study does not support the role of reinforcement learning as an intermediate phenotype in psychosis.

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