Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients
Jazyk angličtina Země Spojené státy americké Médium electronic
Typ dokumentu časopisecké články, metaanalýza, práce podpořená grantem
PubMed
34845190
PubMed Central
PMC8630000
DOI
10.1038/s41398-021-01702-2
PII: 10.1038/s41398-021-01702-2
Knihovny.cz E-zdroje
- MeSH
- bipolární porucha * farmakoterapie genetika MeSH
- deprese MeSH
- depresivní porucha unipolární * farmakoterapie genetika MeSH
- genetická predispozice k nemoci MeSH
- lidé MeSH
- lithium terapeutické užití MeSH
- multifaktoriální dědičnost MeSH
- rizikové faktory MeSH
- schizofrenie * farmakoterapie genetika MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- metaanalýza MeSH
- práce podpořená grantem MeSH
- Názvy látek
- lithium MeSH
Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium's therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi+Gen; www.ConLiGen.org ). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD.
Bipolar Center Wiener Neustadt Sigmund Freud University Medical Faculty Vienna Austria
Centro de Investigación Biomédica en Red de Salud Mental Instituto de Salud Carlos 3 Madrid Spain
Centro de Investigación Biomédica en Salud Mental Madrid Spain
Department of Adult Psychiatry Poznan University of Medical Sciences Poznan Poland
Department of Biomedical Sciences University of Cagliari Cagliari Italy
Department of Clinical Neurosciences Karolinska Institutet Stockholm Sweden
Department of Medical Epidemiology and Biostatistics Karolinska Institutet Stockholm Sweden
Department of Mental Health Johns Hopkins Bloomberg School of Public Health Baltimore MD USA
Department of Pharmacology Dalhousie University Halifax NS Canada
Department of Psychiatry and Behavioral Sciences Johns Hopkins University Baltimore MD USA
Department of Psychiatry and Psychology Mayo Clinic Rochester MN USA
Department of Psychiatry and Psychotherapy Ludwig Maximilian University Munich Munich Germany
Department of Psychiatry and Psychotherapy University of Münster Münster Germany
Department of Psychiatry Dalhousie University Halifax NS Canada
Department of Psychiatry Dokkyo Medical University School of Medicine Mibu Tochigi Japan
Department of Psychiatry Hokkaido University Graduate School of Medicine Sapporo Japan
Department of Psychiatry Lindner Center of Hope University of Cincinnati Mason OH USA
Department of Psychiatry Melbourne Medical School University of Melbourne Parkville VIC Australia
Department of Psychiatry Mood Disorders Unit HUG Geneva University Hospitals Geneva Switzerland
Department of Psychiatry Osaka University Graduate School of Medicine Osaka Japan
Department of Psychiatry University of Basel Basel Switzerland
Department of Psychiatry University of California San Diego San Diego CA USA
Department of Psychiatry University of Campania Luigi Vanvitelli Naples Italy
Department of Psychiatry University of Perugia Perugia Italy
Department of Psychiatry VA San Diego Healthcare System San Diego CA USA
Discipline of Psychiatry School of Medicine University of Adelaide Adelaide SA Australia
Douglas Mental Health University Institute McGill University Montreal QC Canada
HSL Institute for Aging Research Harvard Medical School Boston MA USA
Human Genomics Research Group Department of Biomedicine University Hospital Basel Basel Switzerland
Institut de Biomedicina de la Universitat de Barcelona Barcelona Spain
Institute of Psychiatric Phenomics and Genomics University Hospital LMU Munich Munich Germany
Mental Health Research Group IMIM Hospital del Mar Barcelona Catalonia Spain
Montreal Neurological Institute and Hospital McGill University Montreal QC Canada
Mood Disorders Center of Ottawa Ottawa ON Canada
National Institute of Mental Health Klecany Czech Republic
Neuroscience Research Australia Sydney NSW Australia
Northern Adelaide Local Health Network Mental Health Services Adelaide SA Australia
Office of Mental Health VA San Diego Healthcare System San Diego CA USA
Program for Quantitative Genomics Harvard School of Public Health Boston MA USA
Psychiatric Genetic Unit Poznan University of Medical Sciences Poznan Poland
School of Medical Sciences University of New South Wales Sydney NSW Australia
School of Psychiatry University of New South Wales Sydney Australia
Service de psychiatrie Hôpital Charles Perrens Bordeaux France
The Neuromodulation Unit McGill University Health Centre Montreal QC Canada
Unit of Clinical Pharmacology Hospital University Agency of Cagliari Cagliari Italy
Unitat de Zoologia i Antropologia Biològica University of Barcelona CIBERSAM Barcelona Spain
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Ferrari AJ, Stockings E, Khoo JP, Erskine HE, Degenhardt L, Vos T, et al. The prevalence and burden of bipolar disorder: findings from the Global Burden of Disease Study 2013. Bipolar Disord. 2016;18:440–50. doi: 10.1111/bdi.12423. PubMed DOI
Chesney E, Goodwin GM, Fazel S. Risks of all-cause and suicide mortality in mental disorders: a meta-review. World Psychiatry. 2014;13:153–60. doi: 10.1002/wps.20128. PubMed DOI PMC
Grande I, Berk M, Birmaher B, Vieta E. Bipolar disorder. Lancet. 2016;387:1561–72. doi: 10.1016/S0140-6736(15)00241-X. PubMed DOI
Miura T, Noma H, Furukawa TA, Mitsuyasu H, Tanaka S, Stockton S, et al. Comparative efficacy and tolerability of pharmacological treatments in the maintenance treatment of bipolar disorder: a systematic review and network meta-analysis. Lancet Psychiatry. 2014;1:351–9. doi: 10.1016/S2215-0366(14)70314-1. PubMed DOI
Malhi GS, Tanious M, Das P, Berk M. The science and practice of lithium therapy. Aust NZ J Psychiatry. 2012;46:192–211. doi: 10.1177/0004867412437346. PubMed DOI
Malhi GS, Adams D, Berk M. Is lithium in a class of its own? A brief profile of its clinical use. Aust NZ J Psychiatry. 2009;43:1096–104. doi: 10.3109/00048670903279937. PubMed DOI
Yildiz A, Vieta E, Leucht S, Baldessarini RJ. Efficacy of antimanic treatments: meta-analysis of randomized, controlled trials. Neuropsychopharmacology. 2011;36:375–89. doi: 10.1038/npp.2010.192. PubMed DOI PMC
Cipriani A, Barbui C, Salanti G, Rendell J, Brown R, Stockton S, et al. Comparative efficacy and acceptability of antimanic drugs in acute mania: a multiple-treatments meta-analysis. Lancet. 2011;378:1306–15. doi: 10.1016/S0140-6736(11)60873-8. PubMed DOI
Joas E, Karanti A, Song J, Goodwin GM, Lichtenstein P, Landén M. Pharmacological treatment and risk of psychiatric hospital admission in bipolar disorder. Br J Psychiatry. 2017;210:197–202. doi: 10.1192/bjp.bp.116.187989. PubMed DOI
Tondo L, Hennen J, Baldessarini RJ. Lower suicide risk with long-term lithium treatment in major affective illness: a meta-analysis. Acta Psychiatr Scand. 2001;104:163–72. doi: 10.1034/j.1600-0447.2001.00464.x. PubMed DOI
NICE. Bipolar Disorder: The Management of Bipolar Disorder in Adults, Children and Adolescents, in Primary and Secondary Care. Leicester (UK): NICE; 2006. PubMed
Yatham LN, Kennedy SH, Parikh SV, Schaffer A, Beaulieu S, Alda M, et al. Canadian Network for Mood and Anxiety Treatments (CANMAT) and International Society for Bipolar Disorders (ISBD) collaborative update of CANMAT guidelines for the management of patients with bipolar disorder: update 2013. Bipolar Disord. 2013;15:1–44. doi: 10.1111/bdi.12025. PubMed DOI
Malhi GS, Bassett D, Boyce P, Bryant R, Fitzgerald PB, Fritz K, et al. Royal Australian and New Zealand College of Psychiatrists clinical practice guidelines for mood disorders. Aust NZ J Psychiatry. 2015;49:1087–206. doi: 10.1177/0004867415617657. PubMed DOI
Goodwin GM, Haddad PM, Ferrier IN, Aronson JK, Barnes T, Cipriani A, et al. Evidence-based guidelines for treating bipolar disorder: revised third edition recommendations from the British Association for Psychopharmacology. J Psychopharmacol. 2016;30:495–553. doi: 10.1177/0269881116636545. PubMed DOI PMC
Miller F, Tanenbaum JH, Griffin A, Ritvo E. Prediction of treatment response in bipolar, manic disorder. J Affect Disord. 1991;21:75–77. doi: 10.1016/0165-0327(91)90052-T. PubMed DOI
Machado-Vieira R, Luckenbaugh DA, Soeiro-de-Souza MG, Marca G, Henter ID, Busnello JV, et al. Early improvement with lithium in classic mania and its association with later response. J Affect Disord. 2013;144:160–4. doi: 10.1016/j.jad.2012.05.039. PubMed DOI PMC
Hou L, Heilbronner U, Degenhardt F, Adli M, Akiyama K, Akula N, et al. Genetic variants associated with response to lithium treatment in bipolar disorder: a genome-wide association study. Lancet. 2016;387:1085–93. doi: 10.1016/S0140-6736(16)00143-4. PubMed DOI PMC
Schubert KO, Wisdom A. Should the Australian Therapeutic Goods Administration recommend rapid dosing of lithium carbonate in acute mania? Aust NZ J Psychiatry. 2017. https://pubmed.ncbi.nlm.nih.gov/29216733/. PubMed
Kessing LV, Hellmund G, Andersen PK. Predictors of excellent response to lithium: results from a nationwide register-based study. Int Clin Psychopharmacol. 2011;26:323–8. doi: 10.1097/YIC.0b013e32834a5cd0. PubMed DOI
Calkin CV, Ruzickova M, Uher R, Hajek T, Slaney CM, Garnham JS, et al. Insulin resistance and outcome in bipolar disorder. Br J Psychiatry. 2015;206:52–57. doi: 10.1192/bjp.bp.114.152850. PubMed DOI
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. doi: 10.4088/JCP.v63n1013. PubMed DOI
International Consortium on Lithium Genetics. Amare AT, Schubert KO, Hou L, Clark SR, Papiol S, 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 PMC
Amare AT, Schubert KO, Hou L, Clark SR, Papiol S, Cearns M, et al. Association of polygenic score for major depression with response to lithium in patients with bipolar disorder. Mol Psychiatry. 2020. https://pubmed.ncbi.nlm.nih.gov/32203155/. PubMed
Cross-Disorder Group of the Psychiatric Genomics Consortium. et al. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nat Genet. 2013;45:984–94. doi: 10.1038/ng.2711. PubMed DOI PMC
Brainstorm Consortium, et al. Analysis of shared heritability in common disorders of the brain. Science. 2018;360. https://pubmed.ncbi.nlm.nih.gov/29930110/. PubMed PMC
Schizophrenia Working Group of the Psychiatric Genomics C. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511:421–7. doi: 10.1038/nature13595. PubMed DOI PMC
Gandal MJ, Haney JR, Parikshak NN, Leppa V, Ramaswami G, Hartl C, et al. Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap. Science. 2018;359:693–7. doi: 10.1126/science.aad6469. PubMed DOI PMC
Maier R, Moser G, Chen G-B, Ripke S, Cross-Disorder Working Group of the Psychiatric Genomics Consortium. Coryell W, et al. Joint analysis of psychiatric disorders increases accuracy of risk prediction for schizophrenia, bipolar disorder, and major depressive disorder. Am J Hum Genet. 2015;96:283–94. doi: 10.1016/j.ajhg.2014.12.006. PubMed DOI PMC
van Rheenen W, Peyrot WJ, Schork AJ, Lee SH, Wray NR. Genetic correlations of polygenic disease traits: from theory to practice. Nat Rev Genet. 2019;20:567–81. doi: 10.1038/s41576-019-0137-z. PubMed DOI
Wray NR, Ripke S, Mattheisen M, Trzaskowski M, Byrne EM, Abdellaoui A, et al. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat Genet. 2018;50:668–81. doi: 10.1038/s41588-018-0090-3. PubMed DOI PMC
Stahl EA, Breen G, Forstner AJ, McQuillin A, Ripke S, Trubetskoy V, et al. Genome-wide association study identifies 30 loci associated with bipolar disorder. Nat Genet. 2019;51:793–803. doi: 10.1038/s41588-019-0397-8. PubMed DOI PMC
Southam L, Gilly A, Süveges D, Farmaki A-E, Schwartzentruber J, Tachmazidou I, et al. Whole genome sequencing and imputation in isolated populations identify genetic associations with medically-relevant complex traits. Nat Commun. 2017;8:15606. doi: 10.1038/ncomms15606. PubMed DOI PMC
Lin DY, Sullivan PF. Meta-analysis of genome-wide association studies with overlapping subjects. Am J Hum Genet. 2009;85:862–72. doi: 10.1016/j.ajhg.2009.11.001. PubMed DOI PMC
Province MA, Borecki IB. A correlated meta-analysis strategy for data mining “OMIC” scans. Pac Symp Biocomput. 2013:236–46. https://pubmed.ncbi.nlm.nih.gov/23424128/. PubMed PMC
Duffy A, Alda M, Milin R, Grof P. A consecutive series of treated affected offspring of parents with bipolar disorder: is response associated with the clinical profile? Can J Psychiatry. 2007;52:369–76. doi: 10.1177/070674370705200606. PubMed DOI
Garnham J, Munro A, Slaney C, Macdougall M, Passmore M, Duffy A, et al. Prophylactic treatment response in bipolar disorder: results of a naturalistic observation study. J Affect Disord. 2007;104:185–90. doi: 10.1016/j.jad.2007.03.003. PubMed DOI
Manchia M, Adli M, Akula N, Ardau R, Aubry J-M, Backlund L, et al. Assessment of response to lithium maintenance treatment in bipolar disorder: A Consortium on Lithium Genetics (ConLiGen) Report. PLoS ONE. 2013;8:e65636. doi: 10.1371/journal.pone.0065636. PubMed DOI PMC
Scott J, Etain B, Manchia M, Brichant-Petitjean C, Geoffroy PA, Schulze T, et al. An examination of the quality and performance of the Alda scale for classifying lithium response phenotypes. Bipolar Disord. 2019. https://pubmed.ncbi.nlm.nih.gov/31466131/. PubMed
Delaneau O, Zagury JF, Marchini J. Improved whole-chromosome phasing for disease and population genetic studies. Nat Methods. 2013;10:5–6. doi: 10.1038/nmeth.2307. PubMed DOI
Fuchsberger C, Abecasis GR, Hinds DA. minimac2: faster genotype imputation. Bioinformatics. 2015;31:782–4. doi: 10.1093/bioinformatics/btu704. PubMed DOI PMC
Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ, et al. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience. 2015;4:7. doi: 10.1186/s13742-015-0047-8. PubMed DOI PMC
Ge T, Chen CY, Ni Y, Feng YA, Smoller JW. Polygenic prediction via Bayesian regression and continuous shrinkage priors. Nat Commun. 2019;10:1776. doi: 10.1038/s41467-019-09718-5. PubMed DOI PMC
rsq: R-Squared and Related Measures. R package version 2.0. https://CRAN.R-project.org/package=rsq, 2020.
Team RC. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2019.
Dudbridge F. Power and predictive accuracy of polygenic risk scores. PLoS Genet. 2013;9:e1003348. doi: 10.1371/journal.pgen.1003348. PubMed DOI PMC
Wray NR, Yang J, Goddard ME, Visscher PM. The genetic interpretation of area under the ROC curve in genomic profiling. PLoS Genet. 2010;6:e1000864. doi: 10.1371/journal.pgen.1000864. PubMed DOI PMC
Wang K, Li M, Hakonarson H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010;38:e164. doi: 10.1093/nar/gkq603. PubMed DOI PMC
Gardea-Resendez M, Kucuker MU, Blacker CJ, Ho AM-C, Croarkin PE, Frye MA, et al. Dissecting the epigenetic changes induced by non-antipsychotic mood stabilizers on schizophrenia and affective disorders: a systematic review. Front Pharmacol. 2020;11:467. doi: 10.3389/fphar.2020.00467. PubMed DOI PMC
Marie-Claire C, Lejeune FX, Mundwiller E, Ulveling D, Moszer I, Bellivier F, et al. A DNA methylation signature discriminates between excellent and non-response to lithium in patients with bipolar disorder type 1. Sci Rep. 2020;10:12239. doi: 10.1038/s41598-020-69073-0. PubMed DOI PMC
Lee RS, Pirooznia M, Guintivano J, Ly M, Ewald ER, Tamashiro KL, et al. Search for common targets of lithium and valproic acid identifies novel epigenetic effects of lithium on the rat leptin receptor gene. Transl Psychiatry. 2015;5:e600. doi: 10.1038/tp.2015.90. PubMed DOI PMC
Ookubo M, Kanai H, Aoki H, Yamada N. Antidepressants and mood stabilizers effects on histone deacetylase expression in C57BL/6 mice: brain region specific changes. J Psychiatr Res. 2013;47:1204–14. doi: 10.1016/j.jpsychires.2013.05.028. PubMed DOI
Nunes A, Ardau R, Berghöfer A, Bocchetta A, Chillotti C, Deiana V, et al. Prediction of lithium response using clinical data. Acta Psychiatr Scand. 2020;141:131–41. doi: 10.1111/acps.13122. PubMed DOI
Exploring the genetics of lithium response in bipolar disorders