Literature DB >> 30535067

Polygenic risk score increases schizophrenia liability through cognition-relevant pathways.

Timothea Toulopoulou1,2,3,4, Xiaowei Zhang5, Stacey Cherny4,5, Dwight Dickinson6, Karen F Berman6, Richard E Straub7, Pak Sham4,5, Daniel R Weinberger7,8.   

Abstract

Cognitive deficit is thought to represent, at least in part, genetic mechanisms of risk for schizophrenia, with recent evidence from statistical modelling of twin data suggesting direct causality from the former to the latter. However, earlier evidence was based on inferences from twin not molecular genetic data and it is unclear how much genetic influence 'passes through' cognition on the way to diagnosis. Thus, we included direct measurements of genetic risk (e.g. schizophrenia polygenic risk scores) in causation models to assess the extent to which cognitive deficit mediates some of the effect of polygenic risk scores on the disorder. Causal models of family data tested relationships among key variables and allowed parsing of genetic variance components. Polygenic risk scores were calculated from summary statistics from the current largest genome-wide association study of schizophrenia and were represented as a latent trait. Cognition was also modelled as a latent trait. Participants were 1313 members of 1078 families: 416 patients with schizophrenia, 290 unaffected siblings, and 607 controls. Modelling supported earlier findings that cognitive deficit has a putatively causal role in schizophrenia. In total, polygenic risk score explained 8.07% [confidence interval (CI) 5.45-10.74%] of schizophrenia risk in our sample. Of this, more than a third (2.71%, CI 2.41-3.85%) of the polygenic risk score influence was mediated through cognition paths, exceeding the direct influence of polygenic risk score on schizophrenia risk (1.43%, CI 0.46-3.08%). The remainder of the polygenic risk score influence (3.93%, CI 2.37-4.48%) reflected reciprocal causation between schizophrenia liability and cognition (e.g. mutual influences in a cyclical manner). Analysis of genetic variance components of schizophrenia liability indicated that 26.87% (CI 21.45-32.57%) was associated with cognition-related pathways not captured by polygenic risk score. The remaining variance in schizophrenia was through pathways other than cognition-related and polygenic risk score. Although our results are based on inference through statistical modelling and do not provide an absolute proof of causality, we find that cognition pathways mediate a significant part of the influence of cumulative genetic risk on schizophrenia. We estimate from our model that 33.51% (CI 27.34-43.82%) of overall genetic risk is mediated through influences on cognition, but this requires further studies and analyses as the genetics of schizophrenia becomes better characterized.

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Year:  2019        PMID: 30535067      PMCID: PMC6359897          DOI: 10.1093/brain/awy279

Source DB:  PubMed          Journal:  Brain        ISSN: 0006-8950            Impact factor:   13.501


  81 in total

1.  Polygenic Risk of Schizophrenia and Cognition in a Population-Based Survey of Older Adults.

Authors:  David T Liebers; Mehdi Pirooznia; Fayaz Seiffudin; Katherine L Musliner; Peter P Zandi; Fernando S Goes
Journal:  Schizophr Bull       Date:  2016-02-12       Impact factor: 9.306

2.  A population-based study of shared genetic variation between premorbid IQ and psychosis among male twin pairs and sibling pairs from Sweden.

Authors:  Tom Fowler; Stanley Zammit; Michael J Owen; Finn Rasmussen
Journal:  Arch Gen Psychiatry       Date:  2012-05

3.  Differential effects of common variants in SCN2A on general cognitive ability, brain physiology, and messenger RNA expression in schizophrenia cases and control individuals.

Authors:  Dwight Dickinson; Richard E Straub; Joey W Trampush; Yuan Gao; Ningping Feng; Bin Xie; Joo Heon Shin; Hun Ki Lim; Gianluca Ursini; Kristin L Bigos; Bhaskar Kolachana; Ryota Hashimoto; Masatoshi Takeda; Graham L Baum; Dan Rujescu; Joseph H Callicott; Thomas M Hyde; Karen F Berman; Joel E Kleinman; Daniel R Weinberger
Journal:  JAMA Psychiatry       Date:  2014-06       Impact factor: 21.596

4.  The inheritance of neuropsychological dysfunction in twins discordant for schizophrenia.

Authors:  T D Cannon; M O Huttunen; J Lonnqvist; A Tuulio-Henriksson; T Pirkola; D Glahn; J Finkelstein; M Hietanen; J Kaprio; M Koskenvuo
Journal:  Am J Hum Genet       Date:  2000-07-03       Impact factor: 11.025

5.  Childhood cognitive functioning in schizophrenia patients and their unaffected siblings: a prospective cohort study.

Authors:  T D Cannon; C E Bearden; J M Hollister; I M Rosso; L E Sanchez; T Hadley
Journal:  Schizophr Bull       Date:  2000       Impact factor: 9.306

Review 6.  Arguments for the sake of endophenotypes: examining common misconceptions about the use of endophenotypes in psychiatric genetics.

Authors:  David C Glahn; Emma E M Knowles; D Reese McKay; Emma Sprooten; Henriette Raventós; John Blangero; Irving I Gottesman; Laura Almasy
Journal:  Am J Med Genet B Neuropsychiatr Genet       Date:  2014-01-24       Impact factor: 3.568

7.  The MR-Base platform supports systematic causal inference across the human phenome.

Authors:  Gibran Hemani; Jie Zheng; Benjamin Elsworth; Tom R Gaunt; Philip C Haycock; Kaitlin H Wade; Valeriia Haberland; Denis Baird; Charles Laurin; Stephen Burgess; Jack Bowden; Ryan Langdon; Vanessa Y Tan; James Yarmolinsky; Hashem A Shihab; Nicholas J Timpson; David M Evans; Caroline Relton; Richard M Martin; George Davey Smith
Journal:  Elife       Date:  2018-05-30       Impact factor: 8.140

8.  Meta-analysis of the P300 and P50 waveforms in schizophrenia.

Authors:  Elvira Bramon; Sophia Rabe-Hesketh; Pak Sham; Robin M Murray; Sophia Frangou
Journal:  Schizophr Res       Date:  2004-10-01       Impact factor: 4.939

Review 9.  Assessing the utility of intermediate phenotypes for genetic mapping of psychiatric disease.

Authors:  Jonathan Flint; Nicholas Timpson; Marcus Munafò
Journal:  Trends Neurosci       Date:  2014-09-09       Impact factor: 13.837

10.  Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank (N=112 151) and 24 GWAS consortia.

Authors:  S P Hagenaars; S E Harris; G Davies; W D Hill; D C M Liewald; S J Ritchie; R E Marioni; C Fawns-Ritchie; B Cullen; R Malik; B B Worrall; C L M Sudlow; J M Wardlaw; J Gallacher; J Pell; A M McIntosh; D J Smith; C R Gale; I J Deary
Journal:  Mol Psychiatry       Date:  2016-01-26       Impact factor: 15.992

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  17 in total

1.  The interplay between genetics, cognition and schizophrenia.

Authors:  Maria Stella Calafato; Elvira Bramon
Journal:  Brain       Date:  2019-02-01       Impact factor: 13.501

2.  Development and validation of a novel survival model for acute myeloid leukemia based on autophagy-related genes.

Authors:  Li Huang; Lier Lin; Xiangjun Fu; Can Meng
Journal:  PeerJ       Date:  2021-08-12       Impact factor: 2.984

3.  Contribution of schizophrenia polygenic burden to longitudinal phenotypic variance in 22q11.2 deletion syndrome.

Authors:  Maris Alver; Valentina Mancini; Kristi Läll; Maude Schneider; Luciana Romano; Reedik Mägi; Emmanouil T Dermitzakis; Stephan Eliez; Alexandre Reymond
Journal:  Mol Psychiatry       Date:  2022-06-29       Impact factor: 13.437

4.  Brain-wide versus genome-wide vulnerability biomarkers for severe mental illnesses.

Authors:  Peter Kochunov; Yizhou Ma; Kathryn S Hatch; Neda Jahanshad; Paul M Thompson; Bhim M Adhikari; Heather Bruce; Andrew Van der Vaart; Eric L Goldwaser; Aris Sotiras; Mark D Kvarta; Tianzhou Ma; Shuo Chen; Thomas E Nichols; L Elliot Hong
Journal:  Hum Brain Mapp       Date:  2022-08-30       Impact factor: 5.399

5.  Cortical Gyrification, Psychotic-Like Experiences, and Cognitive Performance in Nonclinical Subjects.

Authors:  Ulrika Evermann; Christian Gaser; Bianca Besteher; Kerstin Langbein; Igor Nenadić
Journal:  Schizophr Bull       Date:  2020-12-01       Impact factor: 9.306

6.  Accurate and Scalable Construction of Polygenic Scores in Large Biobank Data Sets.

Authors:  Sheng Yang; Xiang Zhou
Journal:  Am J Hum Genet       Date:  2020-04-23       Impact factor: 11.025

7.  Polygenic Risk Scores Differentiating Schizophrenia From Bipolar Disorder Are Associated With Premorbid Intelligence in Schizophrenia Patients and Healthy Subjects.

Authors:  Kazutaka Ohi; Daisuke Nishizawa; Shunsuke Sugiyama; Kentaro Takai; Ayumi Kuramitsu; Junko Hasegawa; Midori Soda; Kiyoyuki Kitaichi; Ryota Hashimoto; Kazutaka Ikeda; Toshiki Shioiri
Journal:  Int J Neuropsychopharmacol       Date:  2021-07-23       Impact factor: 5.176

Review 8.  Integrative omics of schizophrenia: from genetic determinants to clinical classification and risk prediction.

Authors:  Fanglin Guan; Tong Ni; Weili Zhu; L Keoki Williams; Long-Biao Cui; Ming Li; Justin Tubbs; Pak-Chung Sham; Hongsheng Gui
Journal:  Mol Psychiatry       Date:  2021-06-30       Impact factor: 15.992

9.  Polygenetic Risk Scores for Major Psychiatric Disorders Among Schizophrenia Patients, Their First-Degree Relatives, and Healthy Participants.

Authors:  Kazutaka Ohi; Daisuke Nishizawa; Takamitsu Shimada; Yuzuru Kataoka; Junko Hasegawa; Toshiki Shioiri; Yasuhiro Kawasaki; Ryota Hashimoto; Kazutaka Ikeda
Journal:  Int J Neuropsychopharmacol       Date:  2020-04-21       Impact factor: 5.176

Review 10.  Developmental Genes and Regulatory Proteins, Domains of Cognitive Impairment in Schizophrenia Spectrum Psychosis and Implications for Antipsychotic Drug Discovery: The Example of Dysbindin-1 Isoforms and Beyond.

Authors:  John L Waddington; Xuechu Zhen; Colm M P O'Tuathaigh
Journal:  Front Pharmacol       Date:  2020-01-29       Impact factor: 5.810

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