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:

Genetic variants associated with cardiometabolic abnormalities during treatment with selective serotonin reuptake inhibitors: a genome-wide association study

The Pharmacogenomics Journal volume 21, pages 574–585 (2021)Cite this article

Subjects

Abstract

Selective serotonin reuptake inhibitors (SSRIs) are prescribed both to patients with schizophrenia and bipolar disorder. Previous studies have shown associations between SSRI treatment and cardiometabolic alterations. The aim of the present study was to investigate genetic variants associated with cardiometabolic adverse effects in patients treated with SSRIs in a naturalistic setting, using a genome-wide cross-sectional approach in a genetically homogeneous sample. We included and genotyped 1981 individuals with schizophrenia or bipolar disorder, of whom 1180 had information available on the outcomes low-density lipoprotein cholesterol (LDL-cholesterol), high-density lipoprotein cholesterol (HDL-cholesterol), triglycerides, and body mass index (BMI) and investigated interactions between SNPs and SSRI use (N = 246) by conducting a genome-wide GxE analysis. We report 13 genome-wide significant interaction effects of SNPs and SSRI serum concentrations on LDL-cholesterol, HDL-cholesterol, and BMI, located in four distinct genomic loci. This study provides new insight into the pharmacogenetics of SSRI but warrants replication in independent populations.

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

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

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

Fig. 1: GWAS results for the gene variant—SSRI serum concentration interaction associated with the five cardiometabolic outcomes; body mass index (BMI), triglycerides, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and total cholesterol.
Fig. 2: Regional plots for loci where significant interaction effects were revealed.
Fig. 3: Differentially expressed gene sets across 30 general tissue types and 53 specific tissue types for body mass index.

Similar content being viewed by others

References

  1. Leucht S, Cipriani A, Spineli L, Mavridis D, Orey D, Richter F, et al. Comparative efficacy and tolerability of 15 antipsychotic drugs in schizophrenia: a multiple-treatments meta-analysis. Lancet. 2013;382:951–62.

    Article  CAS  PubMed  Google Scholar 

  2. Fountoulakis KN, Grunze H, Vieta E, Young A, Yatham L, Blier P, et al. The International College of Neuro-Psychopharmacology (CINP) Treatment Guidelines for Bipolar Disorder in Adults. Int J Neuropsychopharmacol. 2017;20:180–95.

    PubMed  Google Scholar 

  3. Helfer B, Samara MT, Huhn M, Klupp E, Leucht C, Zhu Y, et al. Efficacy and safety of antidepressants added to antipsychotics for schizophrenia. Am J Psychiatry. 2016;173:876–86.

    Article  PubMed  Google Scholar 

  4. Buoli M, Serati M, Ciappolino V, Altamura AC. May selective serotonin reuptake inhibitors (SSRIs) provide some benefit for the treatment of schizophrenia? Expert Opin Pharmacother. 2016;17:1375–85.

    Article  CAS  PubMed  Google Scholar 

  5. Rummel C, Kissling W, Leucht S. Antidepressants for the negative symptoms of schizophrenia. Cochrane Database Syst Rev. 2006;3:CD005581.

  6. Baldessarini RJ, Leahy L, Arcona S, Gause D, Zhang W, Hennen J. Patterns of psychotropic drug prescription for US patients with diagnoses of bipolar disorders. Psychiatr Serv. 2007;58:85–91.

    Article  PubMed  Google Scholar 

  7. Viktorin A, Lichtenstein P, Thase ME, Larsson H, Lundholm C, Magnusson PK, et al. The risk of switch to mania in patients with bipolar disorder during treatment with an antidepressant alone and in combination with a mood stabilizer. Am J Psychiatry. 2014;171:1067–73.

    Article  PubMed  Google Scholar 

  8. Keers R, Uher R. Gene–environment interaction in major depression and antidepressant treatment response. Curr Psychiatry Rep. 2012;14:129–37.

    Article  PubMed  Google Scholar 

  9. Biernacka JM, Sangkuhl K, Jenkins G, Whaley RM, Barman P, Batzler A, et al. The International SSRI Pharmacogenomics Consortium (ISPC): a genome-wide association study of antidepressant treatment response. Transl Psychiatry. 2015;5:e553.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Cipriani A, Furukawa TA, Salanti G, Geddes JR, Higgins JP, Churchill R, et al. Comparative efficacy and acceptability of 12 new-generation antidepressants: a multiple-treatments meta-analysis. Lancet. 2009;373:746–58.

    Article  CAS  PubMed  Google Scholar 

  11. Fjukstad KK, Engum A, Lydersen S, Dieset I, Steen NE, Andreassen OA, et al. Metabolic abnormalities related to treatment with selective serotonin reuptake inhibitors in patients with schizophrenia or bipolar disorder. J Clin Psychopharmacol. 2016;36:615–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Beyazyuz M, Albayrak Y, Egilmez OB, Albayrak N, Beyazyuz E. Relationship between SSRIs and metabolic syndrome abnormalities in patients with generalized anxiety disorder. Psychiatry Investig. 2013;10:148–54.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Raeder MB, Bjelland I, Emil Vollset S, Steen VM. Obesity, dyslipidemia, and diabetes with selective serotonin reuptake inhibitors. J Clin Psychiatry. 2006;67:1974–82.

    Article  CAS  PubMed  Google Scholar 

  14. Kim EJ, Yu BH. Increased cholesterol levels after paroxetine treatment in patients with panic disorder. J Clin Psychopharmacol. 2005;25:597–9.

    Article  CAS  PubMed  Google Scholar 

  15. Le Melledo JM, Mailo K, Lara N, Abadia MC, Gil L, Van Ameringen M, et al. Paroxetine-induced increase in LDL cholesterol levels. J Psychopharmacol. 2009;23:826–30.

    Article  PubMed  Google Scholar 

  16. Uguz F, Sahingoz M, Gungor B, Aksoy F, Askin R. Weight gain and associated factors in patients using newer antidepressant drugs. Gen Hosp Psychiatry. 2015;37:46–8.

    Article  PubMed  Google Scholar 

  17. Zhu J, Klein‐Fedyshin M, Stevenson JM. Serotonin transporter gene polymorphisms and SSRI tolerability: review of pharmacogenetic evidence. Pharmacotherapy. 2019;37:1089–104.

  18. Tanaka M, Kobayashi D, Murakami Y, Ozaki N, Suzuki T, Iwata N, et al. Genetic polymorphisms in the 5-hydroxytryptamine type 3B receptor gene and paroxetine-induced nausea. Int J Neuropsychopharmacol. 2008;11:261–7.

    Article  CAS  PubMed  Google Scholar 

  19. Yoshida K, Naito S, Takahashi H, Sato K, Ito K, Kamata M, et al. Monoamine oxidase A gene polymorphism, 5-HT 2 A receptor gene polymorphism and incidence of nausea induced by fluvoxamine. Neuropsychobiology. 2003;48:10–3.

    Article  CAS  PubMed  Google Scholar 

  20. Sugai T, Suzuki Y, Sawamura K, Fukui N, Inoue Y, Someya T. The effect of 5-hydroxytryptamine 3 A and 3B receptor genes on nausea induced by paroxetine. Pharmacogenomics J. 2006;6:351–6.

    Article  CAS  PubMed  Google Scholar 

  21. de Klerk OL, Nolte IM, Bet PM, Bosker FJ, Snieder H, den Boer JA, et al. ABCB1 gene variants influence tolerance to selective serotonin reuptake inhibitors in a large sample of Dutch cases with major depressive disorder. Pharmacogenomics J. 2013;13:349–53.

    Article  PubMed  CAS  Google Scholar 

  22. Masiran R, Sidi H, Mohamed Z, Mohd Nazree NE, Nik Jaafar NR, Midin M, et al. Female sexual dysfunction in patients with major depressive disorder treated with selective serotonin reuptake inhibitor and its association with serotonin 2A-1438 G/A single nucleotide polymorphisms. J Sex Med. 2014;11:1047–55.

    Article  CAS  PubMed  Google Scholar 

  23. Bly MJ, Bishop JR, Thomas KL, Ellingrod VL. P-glycoprotein (PGP) polymorphisms and sexual dysfunction in female patients with depression and SSRI-associated sexual side effects. J Sex Marital Ther. 2013;39:280–8.

    Article  PubMed  Google Scholar 

  24. Zou YF, Wang Y, Liu P, Feng XL, Wang BY, Zang TH, et al. Association of brain-derived neurotrophic factor genetic Val66Met polymorphism with severity of depression, efficacy of fluoxetine and its side effects in Chinese major depressive patients. Neuropsychobiology. 2010;61:71–8.

    Article  CAS  PubMed  Google Scholar 

  25. Bishop JR, Moline J, Ellingrod VL, Schultz SK, Clayton AH. Serotonin 2 A − 1438 G/A and G-protein Beta3 subunit C825T polymorphisms in patients with depression and SSRI-associated sexual side-effects. Neuropsychopharmacology. 2006;31:2281–8.

    Article  CAS  PubMed  Google Scholar 

  26. Gordon M, Melvin G. Selective serotonin re-uptake inhibitors-a review of the side effects in adolescents. Aust Fam Physician. 2013;42:620–3.

    PubMed  Google Scholar 

  27. Laje G, Allen AS, Akula N, Manji H, John Rush A, McMahon FJ. Genome-wide association study of suicidal ideation emerging during citalopram treatment of depressed outpatients. Pharmacogenet Genom. 2009;19:666–74.

    Article  CAS  Google Scholar 

  28. Laje G, Paddock S, Manji H, Rush AJ, Wilson AF, Charney D, et al. Genetic markers of suicidal ideation emerging during citalopram treatment of major depression. Am J Psychiatry. 2007;164:1530–8.

    Article  PubMed  Google Scholar 

  29. Shams TA, Muller DJ. Antipsychotic induced weight gain: genetics, epigenetics, and biomarkers reviewed. Curr Psychiatry Rep. 2014;16:473.

    Article  PubMed  Google Scholar 

  30. Zhang JP, Lencz T, Zhang RX, Nitta M, Maayan L, John M, et al. Pharmacogenetic associations of antipsychotic drug-related weight gain: a systematic review and meta-analysis. Schizophr Bull. 2016;42:1418–37.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Noordam R, Aarts N, de Keyser CE, Hofman A, Stricker BH, Visser LE. Antidepressants with a high serotonin reuptake transporter affinity and serum lipid levels in a population-based study in older adults. J Psychopharmacol. 2015;29:1112–8.

    Article  CAS  PubMed  Google Scholar 

  32. Secher A, Bukh J, Bock C, Koefoed P, Rasmussen HB, Werge T, et al. Antidepressive-drug-induced bodyweight gain is associated with polymorphisms in genes coding for COMT and TPH1. Int Clin Psychopharmacol. 2009;24:199–203.

    Article  PubMed  Google Scholar 

  33. Reimherr F, Amsterdam J, Dunner D, Adler L, Zhang S, Williams D, et al. Genetic polymorphisms in the treatment of depression: speculations from an augmentation study using atomoxetine. Psychiatry Res. 2010;175:67–73.

    Article  CAS  PubMed  Google Scholar 

  34. Keers R, Bonvicini C, Scassellati C, Uher R, Placentino A, Giovannini C, et al. Variation in GNB3 predicts response and adverse reactions to antidepressants. J Psychopharmacol. 2011;25:867–74.

    Article  CAS  PubMed  Google Scholar 

  35. Corfitsen HT, Drago A. Insight gained from genome-wide interaction and enrichment analysis on weight gain during citalopram treatment. Neurosci Lett. 2017;637:38–43.

    Article  CAS  PubMed  Google Scholar 

  36. Amare AT, Schubert KO, Tekola-Ayele F, Hsu Y-H, Sangkuhl K, Jenkins G, et al. The association of obesity and coronary artery disease genes with response to SSRIs treatment in major depression. J Neural Transm. 2019;126:35–45.

    Article  CAS  PubMed  Google Scholar 

  37. Birkenaes AB, Opjordsmoen S, Brunborg C, Engh JA, Jonsdottir H, Ringen PA, et al. The level of cardiovascular risk factors in bipolar disorder equals that of schizophrenia: a comparative study. J Clin Psychiatry. 2007;68:917–23.

    Article  PubMed  Google Scholar 

  38. Merikangas KR, Jin R, He J-P, Kessler RC, Lee S, Sampson NA, et al. Prevalence and correlates of bipolar spectrum disorder in the world mental health survey initiative. Arch Gen Psychiatry. 2011;68:241–51.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Reis M, Aamo T, Spigset O, Ahlner J. Serum concentrations of antidepressant drugs in a naturalistic setting: compilation based on a large therapeutic drug monitoring database. Ther Drug Monit. 2009;31:42–56.

    Article  CAS  PubMed  Google Scholar 

  40. Hiemke C, Baumann P, Bergemann N, Conca A, Dietmaier O, Egberts K, et al. AGNP consensus guidelines for therapeutic drug monitoring in psychiatry: update 2011. Pharmacopsychiatry. 2011;21:195–235.

    Google Scholar 

  41. WHO Collaborating Centre for Drug Statistics Methodology. ATC/DDD Index 2020. Available at: http://www.whocc.no/atc_ddd_index/ [DDD]. Accessed Nov 2020.

  42. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81:559–75.

  43. Li Y, Willer C, Sanna S, Abecasis G. Genotype imputation. Annu Rev Genomics Hum Genet. 2009;10:387–406.

  44. Das S, Forer L, Schönherr S, Sidore C, Locke AE, Kwong A, et al. Next-generation genotype imputation service and methods. Nat Genet. 2016;48:1284.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience. 2015;4:7.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  46. Watanabe K, Taskesen E, van Bochoven A, Posthuma D. Functional mapping and annotation of genetic associations with FUMA. Nat Commun. 2017;8:1826.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  47. Ronn LC, Berezin V, Bock E. The neural cell adhesion molecule in synaptic plasticity and ageing. Int J Dev Neurosci. 2000;18:193–9.

    Article  CAS  PubMed  Google Scholar 

  48. Yu P, Zhao J, Jiang H, Liu M, Yang X, Zhang B, et al. Neural cell adhesion molecule-1 may be a new biomarker of coronary artery disease. Int J Cardiol. 2018;257:238–42.

    Article  PubMed  Google Scholar 

  49. Ghosh S, Vivar J, Nelson CP, Willenborg C, Segrè AV, Mäkinen V-P, et al. Systems genetics analysis of genome-wide association study reveals novel associations between key biological processes and coronary artery disease. Arterioscler Thromb Vasc Biol. 2015;35:1712–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Ayalew M, Le-Niculescu H, Levey DF, Jain N, Changala B, Patel SD, et al. Convergent functional genomics of schizophrenia: from comprehensive understanding to genetic risk prediction. Mol Psychiatry. 2012;17:887–905.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Nguyen TT, Dev SI, Chen G, Liou SC, Martin AS, Irwin MR, et al. Abnormal levels of vascular endothelial biomarkers in schizophrenia. Eur Arch Psychiatry Clin Neurosci. 2017;268:849–60.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Goldstein BI, Young LT. Toward clinically applicable biomarkers in bipolar disorder: focus on BDNF, inflammatory markers, and endothelial function. Curr Psychiatry Rep. 2013;15:425.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Wu X, Zhang Q, Xu S, Jin P, Luan P, Li Y, et al. Differential expression of six chicken genes associated with fatness traits in a divergently selected broiler population. Mol Cell Probes. 2016;30:1–5.

    Article  PubMed  CAS  Google Scholar 

  54. Pasquo A, Consalvi V, Knapp S, Alfano I, Ardini M, Stefanini S, et al. Structural stability of human protein tyrosine phosphatase rho catalytic domain: effect of point mutations. PLoS ONE. 2012;7:e32555.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Feng X, Scott A, Wang Y, Wang L, Zhao Y, Doerner S, et al. PTPRT regulates high-fat diet-induced obesity and insulin resistance. PLoS ONE. 2014;9:e100783.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Bates SH, Stearns WH, Dundon TA, Schubert M, Tso AW, Wang Y, et al. STAT3 signalling is required for leptin regulation of energy balance but not reproduction. Nature. 2003;421:856–9.

    Article  CAS  PubMed  Google Scholar 

  57. Potkin SG, Turner JA, Guffanti G, Lakatos A, Fallon JH, Nguyen DD, et al. A genome-wide association study of schizophrenia using brain activation as a quantitative phenotype. Schizophr Bull. 2009;35:96–108.

    Article  PubMed  Google Scholar 

  58. Meng Y, Eirin A, Zhu XY, Tang H, Chanana P, Lerman A, et al. Obesity‐induced mitochondrial dysfunction in porcine adipose tissue‐derived mesenchymal stem cells. J Cell Physiol. 2018;233:5926–36.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Manichaikul A, Wang Q, Shi YL, Zhang Z, Leitinger N, Shi W. Characterization of Ath29, a major mouse atherosclerosis susceptibility locus, and identification of Rcn2 as a novel regulator of cytokine expression. Am J Physiol-Heart Circulatory Physiol. 2011;301:H1056–61.

    Article  CAS  Google Scholar 

  60. Niu T, Chen X, Xu X. Angiotensin converting enzyme gene insertion/deletion polymorphism and cardiovascular disease: therapeutic implications. Drugs. 2002;62:977–93.

    Article  CAS  PubMed  Google Scholar 

  61. Burrell LM, Harrap SB, Velkoska E, Patel SK. The ACE2 gene: its potential as a functional candidate for cardiovascular disease. Clin Sci. 2013;124:65–76.

    Article  CAS  Google Scholar 

  62. Kutikhin AG, Yuzhalin AE, Brusina EB, Ponasenko AV, Golovkin AS, Barbarash OL. Genetic predisposition to calcific aortic stenosis and mitral annular calcification. Mol Biol Rep. 2014;41:5645–63.

    Article  CAS  PubMed  Google Scholar 

  63. Song GG, Kim JH, Lee YH. Associations between the insertion/deletion polymorphism of the angiotensin-converting enzyme and susceptibility to aortic aneurysms. J Renin Angiotensin Aldosterone Syst. 2015;16:211–8.

    Article  CAS  PubMed  Google Scholar 

  64. Kiehl T-R, Nechiporuk A, Figueroa KP, Keating MT, Huynh DP, Pulst S-M. Generation and characterization of Sca2 (ataxin-2) knockout mice. Biochem Biophys Res Commun. 2006;339:17–24.

    Article  CAS  PubMed  Google Scholar 

  65. Su Z, Tsaih S-w, Szatkiewicz J, Shen Y, Paigen B. Candidate genes for plasma triglyceride, FFA, and glucose revealed from an intercross between inbred mouse strains NZB/B1NJ and NZW/LacJ. J Lipid Res. 2008;49:1500–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Ma L, Hanson RL, Traurig MT, Muller YL, Kaur BP, Perez JM, et al. Evaluation of A2BP1 as an obesity gene. Diabetes. 2010;59:2837–45.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Dong L, Yan H, Huang X, Hu X, Yang Y, Ma C, et al. A2BP1 gene polymorphisms association with olanzapine-induced weight gain. Pharmacol Res. 2015;99:155–61.

    Article  CAS  PubMed  Google Scholar 

  68. Nordestgaard BG, Langsted A, Mora S, Kolovou G, Baum H, Bruckert E, et al. Fasting is not routinely required for determination of a lipid profile: clinical and laboratory implications including flagging at desirable concentration cut-points-a joint consensus statement from the European Atherosclerosis Society and European Federation of Clinical Chemistry and Laboratory Medicine. Eur Heart J. 2016;37:1944–58.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Mora S. Nonfasting for routine lipid testing: from evidence to action. JAMA Intern Med. 2016;176:1005–6.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Department of Medical Biochemistry at Oslo University Hospital Ullevaal, Norway for their analyzes of blood samples.

Author information

Author notes

  1. These authors contributed equally: Katrine K. Fjukstad, Lavinia Athanasiu

Authors and Affiliations

  1. Clinic for Mental Health and Substance Abuse, Nord-Trøndelag Hospital Trust, Levanger Hospital, Levanger, Norway

    Katrine K. Fjukstad

  2. Department of Mental Health, Norwegian University of Science and Technology, Trondheim, Norway

    Katrine K. Fjukstad

  3. NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway

    Lavinia Athanasiu, Shahram Bahrami, Kevin S. O’Connell, Dennis van der Meer, Francesco Bettella, Ingrid Dieset, Nils Eiel Steen & Ole A. Andreassen

  4. Department of Medical Genetics, Oslo University Hospital, Oslo, Norway

    Srdjan Djurovic

  5. NORMENT, KG Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway

    Srdjan Djurovic

  6. Department of Clinical Pharmacology, St. Olav University Hospital, Trondheim, Norway

    Olav Spigset

  7. Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway

    Olav Spigset

Authors
  1. Katrine K. Fjukstad
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lavinia Athanasiu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shahram Bahrami
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kevin S. O’Connell
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Dennis van der Meer
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Francesco Bettella
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ingrid Dieset
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Nils Eiel Steen
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Srdjan Djurovic
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Olav Spigset
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Ole A. Andreassen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Katrine K. Fjukstad.

Ethics declarations

Conflict of interest

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

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fjukstad, K.K., Athanasiu, L., Bahrami, S. et al. Genetic variants associated with cardiometabolic abnormalities during treatment with selective serotonin reuptake inhibitors: a genome-wide association study. Pharmacogenomics J 21, 574–585 (2021). https://doi.org/10.1038/s41397-021-00234-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41397-021-00234-8

Search

Advanced search

Quick links