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The relationship between familial-genetic risk and pharmacological treatment in a Swedish national sample of patients with major depression, bipolar disorder, and schizophrenia

Abstract

Using Swedish registers, we examine whether the prescription of and the response to antidepressants (AD), mood stabilizers (MS), and antipsychotics (AP) in the treatment of, respectively, major depression (MD), bipolar disorder (BD), and schizophrenia (SZ), are influenced by familial-genetic risk. We examined individuals born in Sweden 1960–1995 with a first diagnosis of MD (n = 257,177), BD (n = 23,032), and SZ (n = 4248) from 2006 to 2018. Drug classes and Defined Daily Dose (DDD) were obtained from the Pharmacy register using the Anatomical Therapeutic Chemical system. We utilized the Familial Genetic Risk Scores (FGRS) calculated from morbidity risks in first- through fifth degree relatives. Treatment with antidepressants (AD) in MD, mood-stabilizers (MS) in BD, and antipsychotics (AP) in SZ were associated with significantly higher disorder-specific familial-genetic risks. Using dosage trajectory analysis of AD, MS, and AP treatment for MD, BD, and SZ, respectively, familial-genetic risk was positively associated with higher and/or increasing drug dosages over time. For MD and BD, examining cases started on the most common pharmacologic treatment class (SSRIs for MD and “other anti-epileptics” for BD), familial-genetic risks were significantly lower in those who did not versus did later receive treatment from other AD and MS classes, respectively. Higher familial-genetic risk for BD predicted switching AD medication in cases of MD. Among pharmacologically treated cases of BD, familial-genetic risk was significantly higher for those treated with lithium. In a large population-based patient cohort, we found evidence of a wide-spread association between higher familial-genetic risk and i) increased likelihood of receiving pharmacologic treatment but 2) responding more poorly to it—as indicated by a switching of medications -- and/or requiring higher doses. Further investigations into the clinical utility of genetic risk scores in the clinical managements of MD, BD, and SZ are warranted.

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Fig. 1: Genetic risk scores for cases of major depression who did versus did not receive antidepressants.
Fig. 2: Dosage trajectories and genetic risk scores for pharmacologic treatment of cases of depression, bipolar disorder and schizophrenia.
Fig. 3: Genetic risk scores for different sequences of antidepressant treatment.
Fig. 4: Genetic risk scores for cases of depression, bipolar disorder and schizophrenia who received only standard treatment versus were switched to a second agent.

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Data availability

Jan Sundquist MD, Ph.D. had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

References

  1. Grof P, Duffy A, Cavazzoni P, Grof E, Garnham J, MacDougall M, et al. Is response to prophylactic lithium a familial trait? J Clin Psychiatry. 2002;63:942–7.

    Article  CAS  PubMed  Google Scholar 

  2. Uher R. Genes, environment, and individual differences in responding to treatment for depression. Harv Rev Psychiatry. 2011;19:109–24.

    Article  PubMed  Google Scholar 

  3. Franchini L, Serretti A, Gasperini M, Smeraldi E. Familial concordance of fluvoxamine response as a tool for differentiating mood disorder pedigrees. J Psychiatr Res. 1998;32:255–9.

    Article  CAS  PubMed  Google Scholar 

  4. Malhotra AK, Murphy GM Jr, Kennedy JL. Pharmacogenetics of psychotropic drug response. Am J Psychiatry. 2004;161:780–96.

    Article  PubMed  Google Scholar 

  5. Johnson D, Wilke MA, Lyle SM, Kowalec K, Jorgensen A, Wright GE, et al. A systematic review and analysis of the use of polygenic scores in pharmacogenomics. Clin Pharmacol Ther. 2022;111:919–30.

    Article  PubMed  Google Scholar 

  6. Meerman JJ, Ter Hark SE, Janzing JG, Coenen MJ. The potential of polygenic risk scores to predict antidepressant treatment response in major depression: a systematic review. J Affect Disord. 2022;304:1–11.

    Article  CAS  PubMed  Google Scholar 

  7. Fabbri C, Serretti A. Genetics of treatment outcomes in major depressive disorder: present and future. Clin Psychopharmacol Neurosci. 2020;18:1–9.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Pain O, Hodgson K, Trubetskoy V, Ripke S, Marshe VS, Adams MJ, et al. Identifying the common genetic basis of antidepressant response. Biol Psychiatry Glob Open Sci. 2022;2:115–26.

    Article  PubMed  Google Scholar 

  9. Nøhr AK, Forsingdal A, Moltke I, Howes OD, Vitezic M, Albrechtsen A, et al. Polygenic heterogeneity in antidepressant treatment and placebo response. Transl Psychiatry. 2022;12:456.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Wimberley T, Gasse C, Meier SM, Agerbo E, MacCabe JH, Horsdal HT. Polygenic risk score for schizophrenia and treatment-resistant schizophrenia. Schizophr Bull. 2017;43:1064–9.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Werner MCF, Wirgenes KV, Haram M, Bettella F, Lunding SH, Rødevand L, et al. Indicated association between polygenic risk score and treatment-resistance in a naturalistic sample of patients with schizophrenia spectrum disorders. Schizophr Res. 2020;218:55–62.

    Article  PubMed  Google Scholar 

  12. Kowalec K, Lu Y, Sariaslan A, Song J, Ploner A, Dalman C, et al. Increased schizophrenia family history burden and reduced premorbid IQ in treatment-resistant schizophrenia: a Swedish National Register and Genomic Study. Mol Psychiatry. 2021;26:4487–95.

    Article  PubMed  Google Scholar 

  13. Zhang J-P, Robinson D, Yu J, Gallego J, Fleischhacker WW, Kahn RS, et al. Schizophrenia polygenic risk score as a predictor of antipsychotic efficacy in first-episode psychosis. Am J Psychiatry. 2019;176:21–8.

    Article  PubMed  Google Scholar 

  14. Gasse C, Wimberley T, Wang Y, Mors O, Børglum A, Als TD, et al. Schizophrenia polygenic risk scores, urbanicity and treatment-resistant schizophrenia. Schizophr Res. 2019;212:79–85.

    Article  PubMed  Google Scholar 

  15. Fusar-Poli L, Rutten BP, van Os J, Aguglia E, Guloksuz S. Polygenic risk scores for predicting outcomes and treatment response in psychiatry: hope or hype? Int Rev Psychiatry. 2022;34:663–75.

  16. Kendler KS, Ohlsson H, Sundquist J, Sundquist K. Family genetic risk scores and the genetic architecture of major affective and psychotic disorders in a Swedish national sample. JAMA Psychiatry. 2021;78:735–43.

    Article  PubMed  Google Scholar 

  17. Kendler KS, Ohlsson H, Sundquist J, Sundquist K. The patterns of family genetic risk scores for eleven major psychiatric and substance use disorders in a Swedish national sample. Transl Psychiatry. 2021;11:1–8.

    Article  Google Scholar 

  18. Kendler K, Ohlsson H, Sundquist J, Sundquist K. The impact of sex, age at onset, recurrence, mode of ascertainment and medical complications on the family genetic risk score profiles for alcohol use disorder. Psychol Med. 2023;53:1732–40.

    Article  PubMed  Google Scholar 

  19. Kendler KS, Ohlsson H, Mościcki EK, Sundquist J, Edwards AC, Sundquist K. Genetic liability to suicide attempt, suicide death and psychiatric and substance use disorders on the risk for suicide attempt and suicide death: a Swedish national study. Psychol Med. 2023;53:1639–48.

    Article  PubMed  Google Scholar 

  20. Kendler KS, Ohlsson H, Bacanu S, Sundquist J, Sundquist K. Differences in genetic risk score profiles for drug use disorder, major depression and ADHD as a function of sex, age at onset, recurrence, mode of ascertainment and treatment. Psychol Med. 2023;53:3448–60.

    Article  PubMed  Google Scholar 

  21. Kendler KS, Ohlsson H, Sundquist J, Sundquist K. The moderation of the genetic risk for alcohol and drug use disorders in a swedish national sample by the genetic aptitude for educational attainment. Psychol Med. 2023;53:3077–84.

    Article  PubMed  Google Scholar 

  22. Kendler KS, Rosmalen JGM, Ohlsson H, Sundquist J, Sundquist K. A distinctive profile of family genetic risk scores in a Swedish national sample of cases of fibromyalgia, irritable bowel syndrome, and chronic fatigue syndrome compared to rheumatoid arthritis and major depression. Psychol Med. 2023;53:3879–86.

    Article  PubMed  Google Scholar 

  23. Fanelli G, Benedetti F, Kasper S, Zohar J, Souery D, Montgomery S, et al. Higher polygenic risk scores for schizophrenia may be suggestive of treatment non-response in major depressive disorder. Prog Neuro-Psychopharmacol Biol Psychiatry. 2021;108:110170.

    Article  CAS  Google Scholar 

  24. Amare AT, Schubert KO, Hou L, Clark SR, Papiol S, Heilbronner U, et al. Association of polygenic score for schizophrenia and HLA antigen and inflammation genes with response to lithium in bipolar affective disorder: a genome-wide association study. JAMA Psychiatry. 2018;75:65–74.

    PubMed  Google Scholar 

  25. Lin BD, Pinzón-Espinosa J, Blouzard E, Van Der Horst MZ, Okhuijsen-Pfeifer C, Van Eijk KR, et al. Associations between polygenic risk score loading, psychosis liability, and clozapine use among individuals with schizophrenia. JAMA Psychiatry. 2023;80:181–5.

    Article  PubMed  Google Scholar 

  26. WHO Collaborating Centre for Drug Statistics Methodology. Definition and general consideration 2023 [Available from: http://www.whocc.no/ddd/definition_and_general_considera/.

  27. FASS [Available from: https://www.fass.se/LIF/startpage?userType=0.

  28. Grunze H, Schlösser S, Amann B, Walden J. Anticonvulsant drugs in bipolar disorder. Dialog Clin Neurosci. 1999;1:24–40.

  29. Kato T. Current understanding of bipolar disorder: toward integration of biological basis and treatment strategies. Psychiatry Clin Neurosci. 2019;73:526–40.

    Article  PubMed  Google Scholar 

  30. Nagin DS, Odgers CL. Group-based trajectory modeling in clinical research. Annu Rev Clin Psychol. 2010;6:109–38.

    Article  PubMed  Google Scholar 

  31. Vrieze SI. Model selection and psychological theory: a discussion of the differences between the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). Psychol Methods. 2012;17:228–43.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Côté S, Tremblay RE, Nagin D, Zoccolillo M, Vitaro F. The development of impulsivity, fearfulness, and helpfulness during childhood: Patterns of consistency and change in the trajectories of boys and girls. J Child Psychol Psychiatry. 2002;43:609–18.

    Article  PubMed  Google Scholar 

  33. Rahman S, Wiberg M, Alexanderson K, Jokinen J, Tanskanen A, Mittendorfer-Rutz E. Trajectories of antidepressant medication use in individuals before and after being granted disability pension due to common mental disorders-a nationwide register-based study. BMC Psychiatry. 2018;18:1–10.

  34. SAS Institute I. SAS/STAT® online documentation, version 9.4. Cary, N.C.: SAS Institute, Inc; 2012.

    Google Scholar 

  35. 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  PubMed  Google Scholar 

  36. McGuffin P, Rijsdijk F, Andrew M, Sham P, Katz R, Cardno A. The heritability of bipolar affective disorder and the genetic relationship to unipolar depression. Arch Gen Psychiatry. 2003;60:497–502.

    Article  PubMed  Google Scholar 

  37. Sullivan PF, Neale MC, Kendler KS. Genetic epidemiology of major depression: review and meta-analysis. Am J Psychiatry. 2000;157:1552–62.

    Article  CAS  PubMed  Google Scholar 

  38. Facal F, Costas J. Polygenic risk scores for schizophrenia and treatment resistance: new data, systematic review and meta-analysis. Schizophr Res. 2023;252:189–97.

    Article  CAS  PubMed  Google Scholar 

  39. Lichtenstein P, Bjork C, Hultman CM, Scolnick E, Sklar P, Sullivan PF. Recurrence risks for schizophrenia in a Swedish national cohort. Psychol Med. 2006;36:1417–25.

    Article  PubMed  Google Scholar 

  40. Sellgren C, Landen M, Lichtenstein P, Hultman CM, Langstrom N. Validity of bipolar disorder hospital discharge diagnoses: file review and multiple register linkage in Sweden. Acta Psychiatr Scand. 2011;124:447–53.

    Article  CAS  PubMed  Google Scholar 

  41. Ekholm B, Ekholm A, Adolfsson R, Vares M, Osby U, Sedvall GC, et al. Evaluation of diagnostic procedures in Swedish patients with schizophrenia and related psychoses. Nord J Psychiatry. 2005;59:457–64.

    Article  PubMed  Google Scholar 

  42. Kendler KS, Ohlsson H, Lichtenstein P, Sundquist J, Sundquist K. The genetic epidemiology of treated major depression in Sweden. Am J Psychiatry. 2018;175:1137–44.

    Article  PubMed  Google Scholar 

  43. Sundquist J, Ohlsson H, Sundquist K, Kendler KS. Common adult psychiatric disorders in Swedish primary care (where most mental health patients are treated). BMC Psychiatry. 2017;17:235.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Bech P. Diagnostic and classification tradition of mental disorders in the 20th century in Scandinavia. In: Satorius N, editor. Sources and traditions of classification in psychiatry. Toronto: Hogrefe & Huber; 1990. p. 153–70.

  45. Langfeldt G. Diagnosis and prognosis of schizophrenia. Proc R Soc Med. 1960;53:1047–52.

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Fors BM, Isacson D, Bingefors K, Widerlöv B. Mortality among persons with schizophrenia in Sweden: an epidemiological study. Nord J Psychiatry. 2007;61:252–9.

    Article  PubMed  Google Scholar 

  47. Hujoel ML, Gazal S, Loh P-R, Patterson N, Price AL. Liability threshold modeling of case–control status and family history of disease increases association power. Nat Genet. 2020;52:541–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Krebs MB Appadurai V, Hellberg KLJ, Ohlsson H, Steinbach J, Pedersen EM, et al. The relationship between genotype- and phenotype-based estimates of genetic liability to human psychiatric disorders, in practice and in theory. medRxiv. 2023:epub.

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Acknowledgements

Location of where work was done: Lund University, Virginia Commonwealth University.

Funding

This project was supported by grants from the Swedish Research Council (2020-01175).

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KSK developed the hypothesis and HO performed the statistical analyses. KSK drafted the manuscript with input from JS, KS, and HO, who all reviewed the MS. JS and KS oversaw and kept updated the registry resources needed for these analyses.

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Correspondence to Kenneth S. Kendler.

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Kendler, K.S., Ohlsson, H., Sundquist, J. et al. The relationship between familial-genetic risk and pharmacological treatment in a Swedish national sample of patients with major depression, bipolar disorder, and schizophrenia. Mol Psychiatry (2023). https://doi.org/10.1038/s41380-023-02365-9

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