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

S Hong Lee, Enda M Byrne, Christina M Hultman, Anna Kähler, Anna Ae Vinkhuyzen, Stephan Ripke, Ole A Andreassen, Thomas Frisell, Alexander Gusev, Xinli Hu, Robert Karlsson, Vasilis X Mantzioris, John J McGrath, Divya Mehta, Eli A Stahl, Qiongyi Zhao, Kenneth S Kendler, Patrick F Sullivan, Alkes L Price, Michael O'DonovanYukinori Okada, Bryan J Mowry, Soumya Raychaudhuri, Naomi R Wray, William Byerley, Wiepke Cahn, Rita M Cantor, Sven Cichon, Paul Cormican, David Curtis, Srdjan Djurovic, Valentina Escott-Price, Pablo V Gejman, Lyudmila Georgieva, Ina Giegling, Thomas F Hansen, Andrés Ingason, Yunjung Kim, Bettina Konte, Phil H Lee, Andrew McIntosh, Andrew McQuillin, Derek W Morris, Markus M Nöthen, Colm O'Dushlaine, Ann Olincy, Line Olsen, Carlos N Pato, Henrik B Rasmussen, Thomas Werge, Schizophrenia Working Group of the Psychiatric Genomics Consortium and Rheumatoid Arthritis Consortium International

50 Citationer (Scopus)


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.

TidsskriftInternational Journal of Epidemiology
Udgave nummer5
Sider (fra-til)1706-1721
StatusUdgivet - okt. 2015


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