Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients.
Klaus Oliver SchubertAnbupalam ThalamuthuAzmeraw T AmareJoseph FrankFabian StreitMazda AdlNirmala AkulaKazufumi AkiyamaRaffaella ArdauBárbara AriasJean-Michel AubryLena BacklundAbesh Kumar BhattacharjeeFrank BellivierAntonio BenabarreSusanne BengesserJoanna M BiernackaArmin BirnerCynthia Marie-ClaireMicah CearnsPablo CervantesHsi-Chung ChenCaterina ChillottiSven CichonScott Richard ClarkCristiana CruceanuPiotr M CzerskiNina DalknerAlexandre DayerFranziska DegenhardtMaria Del ZompoJ Raymond DePauloBruno ÉtainPeter FalkaiAndreas J ForstnerLouise FrisenMark A FryeJanice M FullertonSébastien GardJulie S GarnhamFernando S GoesMaria Grigoroiu-SerbanescuPaul GrofRyota HashimotoJoanna HauserUrs HeilbronnerStefan HermsPer HoffmannLiping HouYi-Hsiang HsuStéphane JamainEsther JiménezJean-Pierre KahnLayla KassemPo-Hsiu KuoTadafumi KatoJohn R KelsoeSarah Kittel-SchneiderEwa Ferensztajn-RochowiakBarbara KönigIchiro KusumiGonzalo LajeMikaél LandénCatharina LavebrattMarion LeboyerSusan G LeckbandMario Majnull nullMirko ManchiaLina MartinssonMichael J McCarthySusan McElroyFrancesc ColomMarina MitjansFrancis M MondimorePalmiero MonteleoneCaroline M NievergeltMarkus Maria NöthenTomáš NovákClaire O'DonovanNorio OzakiUrban ÖsbySergi PapiolAndrea PfennigClaudia PisanuJames B PotashAndreas ReifEva ReininghausGuy A RouleauJanusz K RybakowskiMartin SchallingPeter R SchofieldBarbara W SchweizerGiovanni SeverinoTatyana ShekhtmanPaul D ShillingKatzutaka ShimodaChristian SimhandlClaire M SlaneyAlessio SquassinaThomas StammPavla StopkovaFasil Tekola-AyeleAlfonso TortorellaGustavo TureckiJulia VeehEduard VietaStephanie-H WittGloria RobertsPeter P ZandiMartin AldaMichael BauerFrancis J McMahonPhilip B MitchellThomas G SchulzeMarcella D C RietschelBernhard T BaunePublished in: Translational psychiatry (2021)
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.
Keyphrases
- bipolar disorder
- tyrosine kinase
- solid state
- genome wide
- major depressive disorder
- systematic review
- copy number
- end stage renal disease
- newly diagnosed
- ejection fraction
- molecular dynamics
- chronic kidney disease
- randomized controlled trial
- healthcare
- type diabetes
- depressive symptoms
- prognostic factors
- metabolic syndrome
- mental health
- machine learning
- single cell
- single molecule
- data analysis
- case control