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Novel disease associations with schizophrenia genetic risk revealed in ~400,000 UK Biobank participants

Molecular Psychiatry volume 27, pages 1448–1454 (2022)Cite this article

Subjects

Abstract

Schizophrenia is a serious mental disorder with considerable somatic and psychiatric morbidity. It is unclear whether comorbid health conditions predominantly arise due to shared genetic risk or consequent to having schizophrenia. To explore the contribution of genetic risk for schizophrenia, we analysed the effect of schizophrenia polygenic risk scores (PRS) on a broad range of health problems in 406 929 individuals with no schizophrenia diagnosis from the UK Biobank. Diagnoses were derived from linked health data including primary care, hospital inpatient records, and registers with information on cancer and deaths. Schizophrenia PRS were generated and tested for associations with general health conditions, 16 ICD10 main chapters, and 603 diseases using linear and logistic regressions. Higher schizophrenia PRS was significantly associated with poorer overall health ratings, more hospital inpatient diagnoses, and more unique illnesses. It was also significantly positively associated with 4 ICD10 chapters: mental disorders; respiratory diseases; digestive diseases; and pregnancy, childbirth and the puerperium, but negatively associated with musculoskeletal disorders. Thirty-one specific phenotypes were significantly associated with schizophrenia PRS, and the 19 novel findings include several musculoskeletal diseases, respiratory diseases, digestive diseases, varicose veins, pituitary hyperfunction, and other peripheral nerve disorders. These findings extend knowledge of the pleiotropic effect of genetic risk for schizophrenia and offer insight into how some conditions often comorbid with schizophrenia arise. Additional studies incorporating the genetic basis of hormone regulation and involvement of immune mechanisms in the pathophysiology of schizophrenia may further elucidate the biological mechanisms underlying schizophrenia and its comorbid conditions.

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Fig. 1: Odds ratios for ICD10 main chapters corresponding to 1 standard deviation increase in schizophrenia PRS-PC1.
Fig. 2: Schizophrenia PRS-PC1 phenome-wide association study Manhattan plot.

Code availability

All code used for data preparation and analysis are available upon request.

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Acknowledgements

This work is supported by the US National Institute of Mental Health to SEB (R21MH116188). RZ receives support from the Chinese Scholarship Council (grant number CSC201700260258); CMB is supported by NIMH (R01MH120170; R01MH119084; R01MH118278; U01MH109528); Brain and Behavior Research Foundation Distinguished Investigator Grant; Swedish Research Council (Vetenskapsrådet, award: 538-2013-8864); Lundbeck Foundation (Grant no. R276-2018-4581). We acknowledge and thank Prof Patrick Sullivan for advice regarding the study design. Participation of the UK Biobank subjects is gratefully appreciated. We also acknowledge UK Biobank team for collecting and preparing data for analyses.

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Authors and Affiliations

  1. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

    Ruyue Zhang, Arvid Sjölander, Alexander Ploner, Donghao Lu, Cynthia M. Bulik & Sarah E. Bergen

  2. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Donghao Lu

  3. Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Cynthia M. Bulik

  4. Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Cynthia M. Bulik

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  1. Ruyue Zhang
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  2. Arvid Sjölander
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  3. Alexander Ploner
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  4. Donghao Lu
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  6. Sarah E. Bergen
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Contributions

SEB conceived of the study idea and supervised its implementation. RZ, AS, CMB, and SEB designed the study. AS extensively contributed to the discussions on methods. AP contributed to the creation of the PRS-PC method for the present work. DL provided the protocol and scripts for PRS computation. RZ implemented and ran all analyses. RZ, AS, CMB, and SEB interpreted the results. RZ drafted the paper. All authors discussed and commented on the paper.

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Correspondence to Sarah E. Bergen.

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CMB reports: Shire (grant recipient, Scientific Advisory Board member); Idorsia (consultant); Lundbeckfonden (grant recipient); Pearson (author, royalty recipient).

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Zhang, R., Sjölander, A., Ploner, A. et al. Novel disease associations with schizophrenia genetic risk revealed in ~400,000 UK Biobank participants. Mol Psychiatry 27, 1448–1454 (2022). https://doi.org/10.1038/s41380-021-01387-5

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