Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 Jan 25;9(2):341.
doi: 10.3390/jcm9020341.

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

Jasmina Mallet  1   2 , Yann Le Strat  1   2 , Caroline Dubertret  1   2 , Philip Gorwood  2   3
Affiliations

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

Jasmina Mallet et al. J Clin Med. .

Abstract

Schizophrenia is a multifactorial disease associated with widespread cognitive impairment. Although cognitive deficits are one of the factors most strongly associated with functional impairment in schizophrenia (SZ), current treatment strategies hardly tackle these impairments. To develop more efficient treatment strategies in patients, a better understanding of their pathogenesis is needed. Recent progress in genetics, driven by large genome-wide association studies (GWAS) and the use of polygenic risk scores (PRS), has provided new insights about the genetic architecture of complex human traits, including cognition and SZ. Here, we review the recent findings examining the genetic links between SZ and cognitive functions in population-based samples as well as in participants with SZ. The performed meta-analysis showed a negative correlation between the polygenetic risk score of schizophrenia and global cognition (p < 0.001) when the samples rely on general and healthy participants, while no significant correlation was detected when the three studies devoted to schizophrenia patients were meta-analysed (p > 0.05). Our review and meta-analysis therefore argues against universal pleiotropy for schizophrenia alleles and cognition, since cognition in SZ patients would be underpinned by the same genetic factors than in the general population, and substantially independent of common variant liability to the disorder.

Keywords: cognition; educational attainment; genetics; genome wide association study (GWAS); intelligence; polygenic risk score; schizophrenia.

PubMed Disclaimer

Conflict of interest statement

P.G. received during the last 5 years fees for presentations at congresses or participation in scientific boards from Alcediag-Alcen, Angelini, GSK, Jansse, Lundbeck, Otsuka, SAGE and Servier. The other authors declare no conflict of interest

Figures

Figure 1
Figure 1
Forest plots of correlation between the genetic risk of schizophrenia and cognition in general and healthy participants. Error bars represent the 95% confidence intervals of the mean.
Figure 2
Figure 2
Funnel plot of the meta-analysis on general population and healthy samples. Each plotted point represents the standard error and the correlation coefficient between the SZ PRS and global cognitive functioning for a single study. The white triangle represents the region where 95% of the data points would lie in the absence of a publication bias. The vertical line represents the average correlation coefficient found in the meta-analysis.
Figure 3
Figure 3
Forest plots of correlation between schizophrenia genetic risk and cognition in schizophrenia patients, Forest plot. Error bars represent the 95% confidence intervals of the mean.
Figure 4
Figure 4
Funnel plot of the meta-analysis in schizophrenia patients. Each plotted point represents the standard error and the correlation coefficient between the SZ PRS and global cognitive functioning for a single study. The white triangle represents the region where 95% of the data points would lie in the absence of a publication bias. The vertical line represents the average correlation coefficient found in the meta-analysis.
See this image and copyright information in PMC

References

    1. Deary I.J., Weiss A., Batty G.D. Intelligence and Personality as Predictors of Illness and Death: How Researchers in Differential Psychology and Chronic Disease Epidemiology Are Collaborating to Understand and Address Health Inequalities. Psychol. Sci. Public Interest J. Am. Psychol. Soc. 2010;11:53–79. doi: 10.1177/1529100610387081. - DOI - PubMed
    1. Gale C.R., Hatch S.L., Batty G.D., Deary I.J. Intelligence in childhood and risk of psychological distress in adulthood: The 1958 National Child Development Survey and the 1970 British Cohort Study. Intelligence. 2009;37:592–599. doi: 10.1016/j.intell.2008.09.002. - DOI
    1. Gale C.R., Batty G.D., Tynelius P., Deary I.J., Rasmussen F. Intelligence in early adulthood and subsequent hospitalisation and admission rates for the whole range of mental disorders: Longitudinal study of 1,049,663 men. Epidemiol. Camb. Mass. 2010;21:70–77. doi: 10.1097/EDE.0b013e3181c17da8. - DOI - PMC - PubMed
    1. Maccabe J.H. Population-based cohort studies on premorbid cognitive function in schizophrenia. Epidemiol. Rev. 2008;30:77–83. doi: 10.1093/epirev/mxn007. - DOI - PubMed
    1. Lichtenstein P., Yip B.H., Björk C., Pawitan Y., Cannon T.D., Sullivan P.F., Hultman C.M. Common genetic determinants of schizophrenia and bipolar disorder in Swedish families: A population-based study. Lancet Lond. Engl. 2009;373:234–239. doi: 10.1016/S0140-6736(09)60072-6. - DOI - PMC - PubMed

LinkOut - more resources