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Author Notes:

Isotta Landi, Email: isotta.landi2@mssm.edu Alexander W. Charney: alexander.charney@mssn.edu

A.W.C conceived and supervised the study. A.W.C, I.L., D.A.K., and G.N.N. designed the study and supervised modeling. A.W.C. and I.L. implemented and ran the analyses, interpreted the results, and wrote the paper. L.C. contributed to the creation of the BioMe clinical dataset for the present work. G.B. and M.P. substantially contributed to the BioMe genetic data used in this study. P.O.R and N.D.B. extensively contributed to the discussions on methods and aim of the study. B.S.G substantially edited the manuscript. M.T.P, C.N.P., and T.B.B. substantially contributed to the preparation of GPC clinical and genetic data for the present work. T.V.V. created the NLP concept extraction tool. All other authors (i.e., R.J.F.L., E.K., E.E.S., E.D.A., P.F.B., D.L., D.P.M., S.A.M., M.H.R., and A.H.F.) extensively contributed to the creation of BioMe or GPC datasets. All authors approved all versions of the manuscript.

We would like to thank Aayushee Jain, MS, Arden Moscati, PhD, Lisheng Zhou, PhD, Quingbin Song, PhD, Stephane Wenric, PhD, and Steve Ellis, MS, all of whom are paid employees of the Icahn School of Medicine at Mount Sinai, for assisting with quality control and/or file handling for the BioMe exome sequencing and genome-wide genotyping data. The BioMe health care delivery cohort at Mount Sinai was established and maintained with a generous gift from the Andrea and Charles Bronfman Philanthropies. We would also like to thank the Genomic Psychiatry Cohort (GPC) Investigators. The GPC was supported by grants R01 MH085548, R01 MH104964, and R01 MH123451-01 from the NIMH, and genotyping of samples was provided by the Stanley Center for Psychiatric Research at Broad Institute. TBB is supported by a NARSAD Young Investigator Grant from the Brain and Behavior Research Foundation.

We declare that none of the authors have competing financial or non-financial interests.

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Research Funding:

This study was supported by grant R01 MH121923 from the National Institute of Mental Health (NIMH).

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Biochemistry & Molecular Biology
  • Cell Biology
  • Medicine, Research & Experimental
  • Research & Experimental Medicine
  • GENOME
  • PREDICTION
  • INSIGHTS
  • HEALTH

Prognostic value of polygenic risk scores for adults with psychosis

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Journal Title:

NATURE MEDICINE

Volume:

Volume 27, Number 9

Publisher:

, Pages 1576-+

Type of Work:

Article | Post-print: After Peer Review

Abstract:

Polygenic risk scores (PRS) summarize genetic liability to a disease at the individual level, and the aim is to use them as biomarkers of disease and poor outcomes in real-world clinical practice. To date, few studies have assessed the prognostic value of PRS relative to standards of care. Schizophrenia (SCZ), the archetypal psychotic illness, is an ideal test case for this because the predictive power of the SCZ PRS exceeds that of most other common diseases. Here, we analyzed clinical and genetic data from two multi-ethnic cohorts totaling 8,541 adults with SCZ and related psychotic disorders, to assess whether the SCZ PRS improves the prediction of poor outcomes relative to clinical features captured in a standard psychiatric interview. For all outcomes investigated, the SCZ PRS did not improve the performance of predictive models, an observation that was generally robust to divergent case ascertainment strategies and the ancestral background of the study participants.
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