Association of Polygenic Score for Schizophrenia and HLA Antigen and Inflammation Genes With Response to Lithium in Bipolar Affective Disorder

Amare, Azmeraw T.; Schubert, Klaus Oliver; Hou, Liping; Clark, Scott; Papiol, Sergi; Heilbronner, Urs; Degenhardt, Franziska; Tekola‐Ayele, Fasil; Hsu, Yi‐Hsiang; Shekhtman, Tatyana; Adli, Mazda; Akula, Nirmala; Akiyama, Kazufumi; Ardau, Raffaella; Arias, Bárbara; Aubry, Jean‐Michel; Backlund, Lena; Bhattacharjee, Abesh Kumar; Bellivier, Frank; Benabarre, Antonio; Bengesser, Susanne; Biernacka, Joanna M.; Birner, Armin; Brichant‐Petitjean, Clara; Cervantes, Pablo; Chen, Hsi‐Chung; Chillotti, Caterina; Cichon, Sven; Cruceanu, Cristiana; Czerski, Piotr M.; Dalkner, Nina; Dayer, Alexandre; Zompo, Maria Del; DePaulo, J. Raymond; Étain, Bruno; Falkai, Peter; Forstner, Andreas J.; Frisén, Louise; Frye, Mark A.; Fullerton, Janice M.; Gard, Sébastien; Garnham, Julie; Goes, Fernando S.; Grigoroiu‐Serbanescu, Maria; Grof, Paul; Hashimoto, Ryota; Hauser, Joanna; Herms, Stefan; Hoffmann, Per; Hofmann, Andrea; Jamain, Stéphane; Jiménez, Esther; Kahn, Jean‐Pierre; Kassem, Layla; Kuo, Po-Hsiu; Kato, Takeshi; Kelsoe, John R.; Kittel‐Schneider, Sarah; Kliwicki, Sebastian; König, Barbara; Kusumi, Ichiro; Laje, Gonzalo; Landén, Mikael; Lavebratt, Catharina; Leboyer, Marion; Leckband, Susan G.; Tortorella, Alfonso; Manchia, Mirko; Martinsson, Lina; McCarthy, Michael J.; McElroy, Susan L.; Colom, Francesc; Mitjans, Marina; Mondimore, Francis M.; Monteleone, Palmiero; Nievergelt, Caroline M.; Nöthen, Markus M.; Novák, Tomáš; O′Donovan, Claire; Ozaki, Norio; Ösby, Urban; Pfennig, Andrea; Potash, James B.; Reif, Andreas; Reininghaus, Eva; Rouleau, Guy A.; Rybakowski, Janusz; Schalling, Martin; Schofield, Peter R.; Schweizer, Barbara; Severino, Giovanni; Shilling, Paul D.; Shimoda, Katzutaka; Simhandl, Christian; Slaney, Claire; Squassina, Alessio; Stamm, Thomas; Stopková, Pavla; Maj, Mario; Turecki, Gustavo; Vieta, Eduard; Volkert, Julia; Witt, Stephanie H.; Wright, Adam; Zandi, Peter P.; Mitchell, Philip B.; Bauer, Michael; Alda, Martin; Rietschel, Marcella; McMahon, Francis J.; Schulze, Thomas G.; Baune, Bernhard T.

doi:10.1001/jamapsychiatry.2017.3433

Cited by 79 publications

(74 citation statements)

References 73 publications

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“…For example, if treatment response data existed for these samples one could ask whether a genetic loading for psychosis was correlated with response to treatment. Initial work has already shown the potential of this approach using a SCZ PRS to inform lithium response in BD(Amare et al, 2018). Ultimately, the goal will be to quantify multiple genetic loadings of each individual’s illness and use those measures to inform treatment based on the outcomes of previous individuals with similar profiles.…”

Section: Discussionmentioning

confidence: 99%

Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes

Ruderfer¹,

Ripke²,

McQuillin³

et al. 2018

Cell

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Schizophrenia and bipolar disorder are two distinct diagnoses that share symptomology. Understanding the genetic factors contributing to the shared and disorder-specific symptoms will be crucial for improving diagnosis and treatment. In genetic data consisting of 53,555 cases (20,129 bipolar disorder [BD], 33,426 schizophrenia [SCZ]) and 54,065 controls, we identified 114 genome-wide significant loci implicating synaptic and neuronal pathways shared between disorders. Comparing SCZ to BD (23,585 SCZ, 15,270 BD) identified four genomic regions including one with disorder-independent causal variants and potassium ion response genes as contributing to differences in biology between the disorders. Polygenic risk score (PRS) analyses identified several significant correlations within case-only phenotypes including SCZ PRS with psychotic features and age of onset in BD. For the first time, we discover specific loci that distinguish between BD and SCZ and identify polygenic components underlying multiple symptom dimensions. These results point to the utility of genetics to inform symptomology and potential treatment.

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Section: Discussionmentioning

confidence: 99%

Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes

Ruderfer¹,

Ripke²,

McQuillin³

et al. 2018

Cell

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644

254

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“…In the cross-trait meta-analyses, we applied the O’Brien’s (OB) method and the direct Linear Combination of dependent test statistics (dLC) approach ( 39 , 44 , 45 ), which are implemented in the C ++ eLX package. Briefly, the OB method and the dLC approach help to combine GWAS effect estimates of genome-wide SNPs, obtained from univariate GWASs and generated two test statistics and associated p -values—one for the OB method and one for the dLC method.…”

Section: Methodsmentioning

confidence: 99%

“…It has been shown that the genetic architecture of personality traits is highly polygenic, in which several genes of small effect contribute to the overall phenotype ( 35 , 37 ). Thus, a polygenic score (PGS) analysis approach proposed by the schizophrenia consortium ( 38 ) and later applied in several studies ( 16 , 39 ), is potentially powerful to investigate the genetic influence of each of the Big Five personality traits on antidepressant treatment outcomes. A PGS for each of the Big five personality traits quantifies the combined effects of genetic variants across the whole genome, computed as a weighted summation of effect sizes obtained from genome-wide association studies (GWASs).…”

Section: Introductionmentioning

confidence: 99%

“…A PGS for each of the Big five personality traits quantifies the combined effects of genetic variants across the whole genome, computed as a weighted summation of effect sizes obtained from genome-wide association studies (GWASs). A successful multi-trait polygenic model may assist for an early screening of diseases risk, clinical diagnosis, and the prediction of treatment response and prognosis ( 38 , 39 ).…”

Section: Introductionmentioning

confidence: 99%

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Association of the Polygenic Scores for Personality Traits and Response to Selective Serotonin Reuptake Inhibitors in Patients with Major Depressive Disorder

et al. 2018

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Studies reported a strong genetic correlation between the Big Five personality traits and major depressive disorder (MDD). Moreover, personality traits are thought to be associated with response to antidepressants treatment that might partly be mediated by genetic factors. In this study, we examined whether polygenic scores (PGSs) derived from the Big Five personality traits predict treatment response and remission in patients with MDD who were prescribed selective serotonin reuptake inhibitors (SSRIs). In addition, we performed meta-analyses of genome-wide association studies (GWASs) on these traits to identify genetic variants underpinning the cross-trait polygenic association. The PGS analysis was performed using data from two cohorts: the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS, n = 529) and the International SSRI Pharmacogenomics Consortium (ISPC, n = 865). The cross-trait GWAS meta-analyses were conducted by combining GWAS summary statistics on SSRIs treatment outcome and on the personality traits. The results showed that the PGS for openness and neuroticism were associated with SSRIs treatment outcomes at p < 0.05 across PT thresholds in both cohorts. A significant association was also found between the PGS for conscientiousness and SSRIs treatment response in the PGRN-AMPS sample. In the cross-trait GWAS meta-analyses, we identified eight loci associated with (a) SSRIs response and conscientiousness near YEATS4 gene and (b) SSRI remission and neuroticism eight loci near PRAG1, MSRA, XKR6, ELAVL2, PLXNC1, PLEKHM1, and BRUNOL4 genes. An assessment of a polygenic load for personality traits may assist in conjunction with clinical data to predict whether MDD patients might respond favorably to SSRIs.

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“…For example, high bipolar PRS in depressive patients is associated with more episodes and earlier age at onset . High schizophrenia PRS was associated with poor lithium response and psychotic symptoms in BD…”

Section: Geneticsmentioning

confidence: 99%

Current understanding of bipolar disorder: Toward integration of biological basis and treatment strategies

Kato

2019

Psychiatry Clin Neurosci

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Biological studies of bipolar disorder initially focused on the mechanism of action for antidepressants and antipsychotic drugs, and the roles of monoamines (e.g., serotonin, dopamine) have been extensively studied. Thereafter, based on the mechanism of action of lithium, intracellular signal transduction systems, including inositol metabolism and intracellular calcium signaling, have drawn attention. Involvement of intracellular calcium signaling has been supported by genetics and cellular studies. Elucidation of the neural circuits affected by calcium signaling abnormalities is critical, and our previous study suggested a role of the paraventricular thalamic nucleus. The genetic vulnerability of mitochondria causes calcium dysregulation and results in the hyperexcitability of serotonergic neurons, which are suggested to be susceptible to oxidative stress. Efficacy of anticonvulsants, animal studies of candidate genes, and studies using induced pluripotent stem cell‐derived neurons have suggested a relation between bipolar disorder and the hyperexcitability of neurons. Recent genetic findings suggest the roles of polyunsaturated acids. At the systems level, social rhythm therapy targets circadian rhythm abnormalities, and cognitive behavioral therapy may target emotion/cognition (E/C) imbalance. In the future, pharmacological and psychosocial treatments may be combined and optimized based on the biological basis of each patient, which will realize individualized treatment.

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Association of Polygenic Score for Schizophrenia and HLA Antigen and Inflammation Genes With Response to Lithium in Bipolar Affective Disorder

Abstract: This study provides evidence for a negative association between high genetic loading for SCZ and poor response to lithium in patients with BPAD. These results suggest the potential for translational research aimed at personalized prescribing of lithium.

Cited by 79 publications

References 73 publications

Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes

Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes

Association of the Polygenic Scores for Personality Traits and Response to Selective Serotonin Reuptake Inhibitors in Patients with Major Depressive Disorder

Current understanding of bipolar disorder: Toward integration of biological basis and treatment strategies

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