4.7 Article

New data and an old puzzle: the negative association between schizophrenia and rheumatoid arthritis

Journal

INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
Volume 44, Issue 5, Pages 1706-1721

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/ije/dyv136

Keywords

Schizophrenia; rheumatoid arthritis; genetic relationship; pleiotropy

Funding

  1. Australian Research Council [DE130100614]
  2. National Health and Medical Research Council [613602, 1078901, 1047956, 1053639]
  3. Arthritis Foundation
  4. Doris Duke Foundation
  5. National Institutes of Health [1R01AR063759-01A1, 1U01HG0070033, 5U01GM092691-04, R01 MH077139]
  6. Karolinska Institutet
  7. Karolinska University Hospital
  8. Swedish Research Council
  9. Netherlands Scientific Organization [NWO 480-05-003]
  10. Dutch Brain Foundation
  11. VU University Amsterdam
  12. Vanderbilt CTSA from NCATS/NIH [ULTR000445]
  13. Australian Research Council [DE130100614] Funding Source: Australian Research Council
  14. MRC [G0800509, MR/K006215/1, MR/L023784/2] Funding Source: UKRI
  15. Lundbeck Foundation [R155-2014-1724] Funding Source: researchfish
  16. Medical Research Council [G0800509, MR/L010305/1, MR/K006215/1, MR/L023784/2] Funding Source: researchfish

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Background: A long-standing epidemiological puzzle is the reduced rate of rheumatoid arthritis (RA) in those with schizophrenia (SZ) and vice versa. Traditional epidemiological approaches to determine if this negative association is underpinned by genetic factors would test for reduced rates of one disorder in relatives of the other, but sufficiently powered data sets are difficult to achieve. The genomics era presents an alternative paradigm for investigating the genetic relationship between two uncommon disorders. Methods: We use genome-wide common single nucleotide polymorphism (SNP) data from independently collected SZ and RA case-control cohorts to estimate the SNP correlation between the disorders. We test a genotype X environment (GxE) hypothesis for SZ with environment defined as winter- vs summer-born. Results: We estimate a small but significant negative SNP-genetic correlation between SZ and RA (-0.046, s.e. 0.026,P = 0.036). The negative correlation was stronger for the SNP set attributed to coding or regulatory regions (-0.174, s.e. 0.071, P = 0.0075). Our analyses led us to hypothesize a gene-environment interaction for SZ in the form of immune challenge. We used month of birth as a proxy for environmental immune challenge and estimated the genetic correlation between winter-born and non-winter born SZ to be significantly less than 1 for coding/regulatory region SNPs (0.56, s.e. 0.14,P = 0.00090). Conclusions: Our results are consistent with epidemiological observations of a negative relationship between SZ and RA reflecting, at least in part, genetic factors. Results of the month of birth analysis are consistent with pleiotropic effects of genetic variants dependent on environmental context.

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