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

2017 ◽  
Vol 38 (12) ◽  
pp. 5919-5930 ◽  
Author(s):  
Clara Alloza ◽  
Mark E. Bastin ◽  
Simon R. Cox ◽  
Jude Gibson ◽  
Barbara Duff ◽  
...  
Keyword(s):  
Clinical Symptoms ◽  
Risk Scores ◽  
Polygenic Risk

Discriminating bipolar depression from major depressive disorder with polygenic risk scores

2020 ◽  
pp. 1-8 ◽  
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.

scholarly journals Polygenic Risk Scores for Subtyping of Schizophrenia

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Jingchun Chen ◽  
Travis Mize ◽  
Jain-Shing Wu ◽  
Elliot Hong ◽  
Vishwajit Nimgaonkar ◽  
...  
Keyword(s):  
Processing Speed ◽  
Negative Symptoms ◽  
Clinical Symptoms ◽  
Cluster Structure ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Complex Disorder ◽  
Cognitive Improvement ◽  
Neurocognitive Functions ◽  
Class Iv

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.

scholarly journals 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

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.

scholarly journals Stress Mediating Genes in Aging, Health, and Longevity Traits: Effects of Multiple Interactions

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 286-286
Author(s):  
Anatoliy Yashin ◽  
Dequing Wu ◽  
Konstantin Arbeev ◽  
Arseniy Yashkin ◽  
Galina Gorbunova ◽  
...  
Keyword(s):  
Strong Interaction ◽  
Genetic Interaction ◽  
Interaction Effects ◽  
Genetic Interactions ◽  
Risk Scores ◽  
Data Sets ◽  
Interaction Patterns ◽  
Polygenic Risk ◽  
Drug Candidates ◽  
Aging Health

Abstract Persistent stress of external or internal origin accelerates aging, increases risk of aging related health disorders, and shortens lifespan. Stressors activate stress response genes, and their products collectively influence traits. The variability of stressors and responses to them contribute to trait heterogeneity, which may cause the failure of clinical trials for drug candidates. The objectives of this paper are: to address the heterogeneity issue; to evaluate collective interaction effects of genetic factors on Alzheimer’s disease (AD) and longevity using HRS data; to identify differences and similarities in patterns of genetic interactions within two genders; and to compare AD related genetic interaction patterns in HRS and LOADFS data. To reach these objectives we: selected candidate genes from stress related pathways affecting AD/longevity; implemented logistic regression model with interaction term to evaluate effects of SNP-pairs on these traits for males and females; constructed the novel interaction polygenic risk scores for SNPs, which showed strong interaction potential, and evaluated effects of these scores on AD/longevity; and compared patterns of genetic interactions within the two genders and within two datasets. We found there were many genes involved in highly significant interactions that were the same and that were different within the two genders. The effects of interaction polygenic risk scores on AD were strong and highly statistically significant. These conclusions were confirmed in analyses of interaction effects on longevity trait using HRS data. Comparison of HRS to LOADFS data showed that many genes had strong interaction effects on AD in both data sets.

scholarly journals Polygenic Risk Scores for Alcohol Involvement Relate to Brain Structure in Substance‐Naïve Children: Results from the ABCD Study

2021 ◽  
Author(s):  
Alexander S. Hatoum ◽  
Emma C. Johnson ◽  
David A. A. Baranger ◽  
Sarah E. Paul ◽  
Arpana Agrawal ◽  
...  
Keyword(s):  
Brain Structure ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Alcohol Involvement
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