Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Clinical characteristics indexing genetic differences in schizophrenia: a systematic review

Abstract

Genome-wide studies are among the best available tools for identifying etiologic processes underlying psychiatric disorders such as schizophrenia. However, it is widely recognized that disorder heterogeneity may limit genetic insights. Identifying phenotypes indexing genetic differences among patients with non-affective psychotic disorder will improve genome-wide studies of these disorders. The present study systematically reviews existing literature to identify phenotypes that index genetic differences among patients with schizophrenia and related disorders. We systematically reviewed family-based studies and genome-wide molecular-genetic studies investigating whether phenotypic variation in patients with non-affective psychotic disorders (according to DSM or equivalent systems) was associated with genome-wide genetic variation (PROSPERO number CRD42019136169). An electronic database search of PubMed, EMBASE, and PsycINFO from inception until 17 May 2019 resulted in 4347 published records. These records included a total of 813 relevant analyses from 264 articles. Two independent raters assessed the quality of all analyses based on methodologic rigor and power. We found moderate to strong evidence for a positive association between genetic/familial risk for non-affective psychosis and four phenotypes: early age of onset, negative/deficit symptoms, chronicity, and functional impairment. Female patients also tended to have more affected relatives. Severity of positive symptoms was not associated with genetic/familial risk for schizophrenia. We suggest that phenotypes with the most evidence for reflecting genetic difference in participating patients should be measured in future large-scale genetic studies of schizophrenia to improve power to discover causal variants and to facilitate discovery of modifying genetic variants.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Evidence from independent familial aggregation analyses relating features of schizophrenia with increased familial risk.

Similar content being viewed by others

References

  1. Sullivan PF, Kendler KS, Neale MC. Schizophrenia as a complex trait: evidence from a meta-analysis of twin studies. Arch Gen Psychiatry. 2003;60:1187–92.

    Article  Google Scholar 

  2. Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511:421–7.

    Article  Google Scholar 

  3. Marshall CR, Howrigan DP, Merico D, Thiruvahindrapuram B, Wu W, Greer DS, et al. Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects. Nat Genet. 2017;49:27–35.

    Article  CAS  Google Scholar 

  4. Howrigan DP, Rose SA, Samocha KE, Fromer M, Cerrato F, Chen WJ, et al. Exome sequencing in schizophrenia-affected parent–offspring trios reveals risk conferred by protein-coding de novo mutations. Nat Neurosci. 2020;23:185–93.

    Article  CAS  Google Scholar 

  5. Sekar A, Bialas AR, de Rivera H, Davis A, Hammond TR, Kamitaki N, et al. Schizophrenia risk from complex variation of complement component 4. Nature. 2016;530:177–83.

    Article  CAS  Google Scholar 

  6. Jablensky A. Subtyping schizophrenia: implications for genetic research. Mol Psychiatry. 2006;11:815–36.

    Article  CAS  Google Scholar 

  7. Carpenter WT Jr, Kirkpatrick B. The heterogeneity of the long-term course of schizophrenia. Schizophr Bull. 1988;14:645–52.

    Article  Google Scholar 

  8. Peterson RE, Cai N, Dahl AW, Bigdeli TB, Edwards AC, Webb BT, et al. Molecular genetic analysis subdivided by adversity exposure suggests etiologic heterogeneity in major depression. Am J Psychiatry. 2018;175:545–54.

    Article  Google Scholar 

  9. Fanous AH, Kendler KS. Genetic heterogeneity, modifier genes, and quantitative phenotypes in psychiatric illness: searching for a framework. Mol Psychiatry. 2005;10:6–13.

    Article  CAS  Google Scholar 

  10. Smoller JW, Andreassen OA, Edenberg HJ, Faraone SV, Glatt SJ, Kendler KS. Psychiatric genetics and the structure of psychopathology. Mol Psychiatry. 2019;24:409–20.

    Article  Google Scholar 

  11. Duncan LE, Ostacher M, Ballon J. How genome-wide association studies (GWAS) made traditional candidate gene studies obsolete. Neuropsychopharmacology. 2019;44:1518–23.

    Article  Google Scholar 

  12. Gottesman II, Gould TD. The endophenotype concept in psychiatry: etymology and strategic intentions. Am J Psychiatry. 2003;160:636–45.

    Article  Google Scholar 

  13. Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium. Electronic address: douglas.ruderfer@vanderbilt.edu, Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium. Genomic dissection of bipolar disorder and schizophrenia, including 28 subphenotypes. Cell. 2018;173:1705–1715.e16.

    Article  Google Scholar 

  14. Purcell SM, Moran JL, Fromer M, Ruderfer D, Solovieff N, Roussos P, et al. A polygenic burden of rare disruptive mutations in schizophrenia. Nature. 2014;506:185–90.

    Article  CAS  Google Scholar 

  15. Singh T, Walters JTR, Johnstone M, Curtis D, Suvisaari J, Torniainen M, et al. The contribution of rare variants to risk of schizophrenia in individuals with and without intellectual disability. Nat Genet. 2017;49:1167–73.

    Article  CAS  Google Scholar 

  16. Escott-Price V, Consortium IPDG, Nalls MA, Morris HR, Lubbe S, Brice A, et al. Polygenic risk of P arkinson disease is correlated with disease age at onset. Ann Neurol. 2015;77:582–91.

    Article  CAS  Google Scholar 

  17. Baldessarini RJ, Tondo L, Vazquez GH, Undurraga J, Bolzani L, Yildiz A, et al. Age at onset versus family history and clinical outcomes in 1,665 international bipolar-I disorder patients. World Psychiatry. 2012;11:40–46.

    Article  Google Scholar 

  18. Klein DN, Schatzberg AF, McCullough JP, Dowling F, Goodman D, Howland RH, et al. Age of onset in chronic major depression: relation to demographic and clinical variables, family history, and treatment response. J Affect Disord. 1999;55:149–57.

    Article  CAS  Google Scholar 

  19. Grant BF. The impact of a family history of alcoholism on the relationship between age at onset of alcohol use and DSM-IV alcohol dependence: results from the National Longitudinal Alcohol Epidemiologic Survey. Alcohol Health Res World. 1998;22:144–7.

    CAS  Google Scholar 

  20. Monsén U, Broström O, Nordenvall B, Sörstad J, Hellers G. Prevalence of inflammatory bowel disease among relatives of patients with ulcerative colitis. Scand J Gastroenterol. 1987;22:214–8.

    Article  Google Scholar 

  21. Scheuner MT, Whitworth WC, McGruder H, Yoon PW, Khoury MJ. Expanding the definition of a positive family history for early-onset coronary heart disease. Genet Med. 2006;8:491–501.

    Article  Google Scholar 

  22. Immonen J, Jääskeläinen E, Korpela H, Miettunen J. Age at onset and the outcomes of schizophrenia: a systematic review and meta-analysis. Early Inter Psychiatry. 2017;11:453–60.

    Article  Google Scholar 

  23. Kendler KS. The development of Kraepelin’s mature diagnostic concept of hebephrenia: a close reading of relevant texts of Hecker, Daraszkiewicz, and Kraepelin. Mol Psychiatry. 2020;25:180–93.

    Article  Google Scholar 

  24. Robinson EB, Lichtenstein P, Anckarsäter H, Happé F, Ronald A. Examining and interpreting the female protective effect against autistic behavior. Proc Natl Acad Sci USA. 2013;110:5258–62.

    Article  CAS  Google Scholar 

  25. McGrath J, Saha S, Welham J, El Saadi O, MacCauley C, Chant D. A systematic review of the incidence of schizophrenia: the distribution of rates and the influence of sex, urbanicity, migrant status and methodology. BMC Med. 2004;2:13.

    Article  Google Scholar 

  26. Leung MD DA, Chue MRC Psych DP. Sex differences in schizophrenia, a review of the literature. Acta Psychiatr Scand. 2000;101:3–38.

    Article  Google Scholar 

  27. Salvatore JE, Cho SB, Dick DM. Genes, environments, and sex differences in alcohol research. J Stud Alcohol Drugs. 2017;78:494–501.

    Article  Google Scholar 

  28. Merikangas AK, Almasy L. Using the tools of genetic epidemiology to understand sex differences in neuropsychiatric disorders. Genes Brain Behav. 2020;19:e12660.

    Article  Google Scholar 

  29. Peralta V, Cuesta MJ. Familial liability and schizophrenia phenotypes: a polydiagnostic approach. Schizophr Res. 2007;96:125–34.

    Article  Google Scholar 

  30. Bergen SE, Ploner A, Howrigan D, CNV Analysis Group and the Schizophrenia Working Group of the Psychiatric Genomics Consortium, O’Donovan MC, Smoller JW, et al. Joint contributions of rare copy number variants and common SNPs to risk for schizophrenia. Am J Psychiatry. 2019;176:29–35.

    Article  Google Scholar 

  31. Genovese G, Fromer M, Stahl EA, Ruderfer DM, Chambert K, Landén M, et al. Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia. Nat Neurosci. 2016;19:1433–41.

    Article  CAS  Google Scholar 

  32. Halvorsen M, Huh R, Oskolkov N, Wen J, Netotea S, Giusti-Rodriguez P, et al. Increased burden of ultra-rare structural variants localizing to boundaries of topologically associated domains in schizophrenia. Nat Commun. 2020;11:1842.

    Article  CAS  Google Scholar 

  33. Robins E, Guze SB. Establishment of diagnostic validity in psychiatric illness: its application to schizophrenia. Am J Psychiatry. 1970;126:983–7.

    Article  CAS  Google Scholar 

Download references

Funding

This study is supported in part by the Stanley Center for Psychiatric Research. HVL was supported by a VENI grant from the Talent Programme of the Netherlands Organization of Scientific Research (NWO-ZonMW 09150161810021).

Author information

Authors and Affiliations

Authors

Contributions

JT, YADV, HVL and KSK conceived and designed the study. JT, YADV, and HVL performed the literature review and data coding. KSK oversaw the project. JT drafted the first version of the manuscript and YADV, HVL and KSK revised it. All authors reviewed and approved the final version.

Corresponding author

Correspondence to Kenneth S. Kendler.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Taylor, J., de Vries, Y.A., van Loo, H.M. et al. Clinical characteristics indexing genetic differences in schizophrenia: a systematic review. Mol Psychiatry 28, 883–890 (2023). https://doi.org/10.1038/s41380-022-01850-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41380-022-01850-x

This article is cited by

Search

Quick links