Literature DB >> 28719030

Polygenic risk for schizophrenia and neurocognitive performance in patients with schizophrenia.

S-H Wang1, P-C Hsiao2, L-L Yeh3, C-M Liu4, C-C Liu4, T-J Hwang4, M H Hsieh4, Y-L Chien4, Y-T Lin4, S D Chandler5, S V Faraone6, N Laird7, B Neale8, S A McCarroll8, S J Glatt6, M T Tsuang5, H-G Hwu2,4,9, W J Chen2,9,10,11.   

Abstract

Both neurocognitive deficits and schizophrenia are highly heritable. Genetic overlap between neurocognitive deficits and schizophrenia has been observed in both the general population and in the clinical samples. This study aimed to examine if the polygenic architecture of susceptibility to schizophrenia modified neurocognitive performance in schizophrenia patients. Schizophrenia polygenic risk scores (PRSs) were first derived from the Psychiatric Genomics Consortium (PGC) on schizophrenia, and then the scores were calculated in our independent sample of 1130 schizophrenia trios, who had PsychChip data and were part of the Schizophrenia Families from Taiwan project. Pseudocontrols generated from the nontransmitted parental alleles of the parents in these trios were compared with alleles in schizophrenia patients in assessing the replicability of PGC-derived susceptibility variants. Schizophrenia PRS at the P-value threshold (PT) of 0.1 explained 0.2% in the variance of disease status in this Han-Taiwanese samples, and the score itself had a P-value 0.05 for the association test with the disorder. Each patient underwent neurocognitive evaluation on sustained attention using the continuous performance test and executive function using the Wisconsin Card Sorting Test. We applied a structural equation model to construct the neurocognitive latent variable estimated from multiple measured indices in these 2 tests, and then tested the association between the PRS and the neurocognitive latent variable. Higher schizophrenia PRS generated at the PT of 0.1 was significantly associated with poorer neurocognitive performance with explained variance 0.5%. Our findings indicated that schizophrenia susceptibility variants modify the neurocognitive performance in schizophrenia patients.
© 2017 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Entities:  

Keywords:  Continuous Performance Test; GWAS; PLINK; Polygenic risk score; Psychiatric Genomics Consortium; Wisconsin Card Sorting Test; factor analyses; neurocognitive performance; schizophrenia; trios

Mesh:

Year:  2017        PMID: 28719030     DOI: 10.1111/gbb.12401

Source DB:  PubMed          Journal:  Genes Brain Behav        ISSN: 1601-183X            Impact factor:   3.449


  13 in total

1.  Polygenic approaches to detect gene-environment interactions when external information is unavailable.

Authors:  Wan-Yu Lin; Ching-Chieh Huang; Yu-Li Liu; Shih-Jen Tsai; Po-Hsiu Kuo
Journal:  Brief Bioinform       Date:  2019-11-27       Impact factor: 11.622

2.  Polygenic liability for schizophrenia predicts shifting-specific executive function deficits and tobacco use in a moderate drinking community sample.

Authors:  Alex P Miller; Ian R Gizer; William A Fleming Iii; Jacqueline M Otto; Joseph D Deak; Jorge S Martins; Bruce D Bartholow
Journal:  Psychiatry Res       Date:  2019-06-18       Impact factor: 3.222

Review 3.  Polygenic Risk Scores in Clinical Psychology: Bridging Genomic Risk to Individual Differences.

Authors:  Ryan Bogdan; David A A Baranger; Arpana Agrawal
Journal:  Annu Rev Clin Psychol       Date:  2018-05-07       Impact factor: 18.561

4.  Validation of a microRNA target site polymorphism in H3F3B that is potentially associated with a broad schizophrenia phenotype.

Authors:  William Manley; Michael P Moreau; Marco Azaro; Stephen K Siecinski; Gillian Davis; Steven Buyske; Veronica Vieland; Anne S Bassett; Linda Brzustowicz
Journal:  PLoS One       Date:  2018-03-12       Impact factor: 3.240

5.  Adaptive combination of Bayes factors as a powerful method for the joint analysis of rare and common variants.

Authors:  Wan-Yu Lin; Wei J Chen; Chih-Min Liu; Hai-Gwo Hwu; Steven A McCarroll; Stephen J Glatt; Ming T Tsuang
Journal:  Sci Rep       Date:  2017-10-24       Impact factor: 4.379

6.  Genetic Variability of TCF4 in Schizophrenia of Southern Chinese Han Population: A Case-Control Study.

Authors:  Jingwen Yin; Dongjian Zhu; You Li; Dong Lv; Huajun Yu; Chunmei Liang; Xudong Luo; Xusan Xu; Jiawu Fu; Haifeng Yan; Zhun Dai; Xia Zhou; Xia Wen; Susu Xiong; Zhixiong Lin; Juda Lin; Bin Zhao; Yajun Wang; Keshen Li; Guoda Ma
Journal:  Front Genet       Date:  2019-05-28       Impact factor: 4.599

Review 7.  Treatment-Resistant Schizophrenia: Insights From Genetic Studies and Machine Learning Approaches.

Authors:  Claudia Pisanu; Alessio Squassina
Journal:  Front Pharmacol       Date:  2019-05-29       Impact factor: 5.810

8.  Performing different kinds of physical exercise differentially attenuates the genetic effects on obesity measures: Evidence from 18,424 Taiwan Biobank participants.

Authors:  Wan-Yu Lin; Chang-Chuan Chan; Yu-Li Liu; Albert C Yang; Shih-Jen Tsai; Po-Hsiu Kuo
Journal:  PLoS Genet       Date:  2019-08-01       Impact factor: 5.917

9.  Polygenic Risk Scores Shed Light on the Relationship between Schizophrenia and Cognitive Functioning: Review and Meta-Analysis.

Authors:  Jasmina Mallet; Yann Le Strat; Caroline Dubertret; Philip Gorwood
Journal:  J Clin Med       Date:  2020-01-25       Impact factor: 4.241

10.  Polygenic Risk Score Contribution to Psychosis Prediction in a Target Population of Persons at Clinical High Risk.

Authors:  Diana O Perkins; Loes Olde Loohuis; Jenna Barbee; John Ford; Clark D Jeffries; Jean Addington; Carrie E Bearden; Kristin S Cadenhead; Tyrone D Cannon; Barbara A Cornblatt; Daniel H Mathalon; Thomas H McGlashan; Larry J Seidman; Ming Tsuang; Elaine F Walker; Scott W Woods
Journal:  Am J Psychiatry       Date:  2019-11-12       Impact factor: 18.112

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