Browsing by Subject "Polygenic risk scores"

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Open Access
Polygenic risk score increases schizophrenia liability through cognition-relevant pathways
(Oxford University Press, 2019) Toulopoulou, Timothea; Zhang, X.; Cherny, S.; Dickinson, D.; Berman, K. F.; Straub, R. E.; Sham, P.; Weinberger, D. R.
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.
Open Access
Use of schizophrenia and bipolar disorder polygenic risk scores to identify psychotic disorders
(2018) Calafato, M. S.; Thygesen, J. H.; Ranlund, S.; Zartaloudi, E.; Cahn, W.; Crespo-Facorro, B.; Díez-Revuelta, A.; Forti, M. D.; Hall, M. -H.; Iyegbe, C.; Jablensky, A.; Kahn, R.; Kalaydjieva, L.; Kravariti, E.; Lin, K.; McDonald, C.; McIntosh, A. M.; McQuillin, A.; Picchioni, M.; Rujescu, D.; Shaikh, M.; Toulopoulou, Timothea; Os, J. V.; Vassos, E.; Walshe, M.; Powell, J.; Lewis, C. M.; Murray, R. M.; Bramon, E.
Background There is increasing evidence for shared genetic susceptibility between schizophrenia and bipolar disorder. Although genetic variants only convey subtle increases in risk individually, their combination into a polygenic risk score constitutes a strong disease predictor. Aims To investigate whether schizophrenia and bipolar disorder polygenic risk scores can distinguish people with broadly defined psychosis and their unaffected relatives from controls. Method Using the latest Psychiatric Genomics Consortium data, we calculated schizophrenia and bipolar disorder polygenic risk scores for 1168 people with psychosis, 552 unaffected relatives and 1472 controls. Results Patients with broadly defined psychosis had dramatic increases in schizophrenia and bipolar polygenic risk scores, as did their relatives, albeit to a lesser degree. However, the accuracy of predictive models was modest. Conclusions Although polygenic risk scores are not ready for clinical use, it is hoped that as they are refined they could help towards risk reduction advice and early interventions for psychosis. Declaration of interest R.M.M. has received honoraria for lectures from Janssen, Lundbeck, Lilly, Otsuka and Sunovian.