Dataset Information

Immunogenetics of lithium response and psychiatric phenotypes in patients with bipolar disorder.

ABSTRACT: The link between bipolar disorder (BP) and immune dysfunction remains controversial. While epidemiological studies have long suggested an association, recent research has found only limited evidence of such a relationship. To clarify this, we investigated the contributions of immune-relevant genetic factors to the response to lithium (Li) treatment and the clinical presentation of BP. First, we assessed the association of a large collection of immune-related genes (4,925) with Li response, defined by the Retrospective Assessment of the Lithium Response Phenotype Scale (Alda scale), and clinical characteristics in patients with BP from the International Consortium on Lithium Genetics (ConLi ⁺ Gen, N = 2,374). Second, we calculated here previously published polygenic scores (PGSs) for immune-related traits and evaluated their associations with Li response and clinical features. We found several genes associated with Li response at p < 1x10 ^- 4 values, including HAS3 , CNTNAP5 and NFIB . Network and functional enrichment analyses uncovered an overrepresentation of pathways involved in cell adhesion and intercellular communication, which appear to converge on the well-known Li-induced inhibition of GSK-3β. We also found various genes associated with BP's age-at-onset, number of mood episodes, and presence of psychosis, substance abuse and/or suicidal ideation at the exploratory threshold. These included RTN4 , XKR4 , NRXN1 , NRG1/3 and GRK5 . Additionally, PGS analyses suggested serum FAS, ECP, TRANCE and cytokine ligands, amongst others, might represent potential circulating biomarkers of Li response and clinical presentation. Taken together, our results support the notion of a relatively weak association between immunity and clinically relevant features of BP at the genetic level.

SUBMITTER: Herrera-Rivero M

PROVIDER: S-EPMC10350128 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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Immunogenetics of lithium response and psychiatric phenotypes in patients with bipolar disorder.

Herrera-Rivero Marisol M Gutiérrez-Fragoso Karina K Thalamuthu Anbupalam A Amare Azmeraw T AT Adli Mazda M Akiyama Kazufumi K Akula Nirmala N Ardau Raffaella R Arias Bárbara B Aubry Jean-Michel JM Backlund Lena L Bellivier Frank F Benabarre Antonio A Bengesser Susanne S Abesh Bhattacharjee B Biernacka Joanna J Birner Armin A Cearns Micah M Cervantes Pablo P Chen Hsi-Chung HC Chillotti Caterina C Cichon Sven S Clark Scott S Colom Francesc F Cruceanu Cristiana C Czerski Piotr P Dalkner Nina N Degenhardt Franziska F Del Zompo Maria M DePaulo J Raymond JR Etain Bruno B Falkai Peter P Ferensztajn-Rochowiak Ewa E Forstner Andreas J AJ Frank Josef J Frisen Louise L Frye Mark M Fullerton Janice J Gallo Carla C Gard Sebastien S Garnham Julie J Goes Fernando F Grigoroiu-Serbanescu Maria M Grof Paul P Hashimoto Ryota R Hasler Roland R Hauser Joanna J Heilbronner Urs U Herms Stefan S Hoffmann Per P Hou Liping L Hsu YiHsiang Y Jamain Stéphane S Jiménez Esther E Kahn Jean-Pierre JP Kassem Layla L Kato Tadafumi T Kelsoe John J Kittel-Schneider Sarah S Kuo Po-Hsiu PH Kurtz Joachim J Kusumi Ichiro I König Barbara B Laje Gonzalo G Landén Mikael M Lavebratt Catharina C Leboyer Marion M Leckband Susan S Maj Mario M Manchia Mirko M Marie-Claire Cynthia C Martinsson Lina L McCarthy Michael M McElroy Susan L SL Millischer Vincent V Mitjans Marina M Mondimore Francis F Monteleone Palmiero P Nievergelt Caroline C Novak Tomas T Nöthen Markus M Odonovan Claire C Ozaki Norio N Papiol Sergi S Pfennig Andrea A Pisanu Claudia C Potash James J Reif Andreas A Reininghaus Eva E Richard-Lepouriel Hélène H Roberts Gloria G Rouleau Guy G Rybakowski Janusz K JK Schalling Martin M Schofield Peter P Schubert Klaus Oliver KO Schulte Eva E Schweizer Barbara B Severino Giovanni G Shekhtman Tatyana T Shilling Paul P Shimoda Kazutaka K Simhandl Christian C Slaney Claire C Squassina Alessio A Stamm Thomas T Stopkova Pavla P Streit Fabian F Ayele Fasil F Tortorella Alfonso A Turecki Gustavo G Veeh Julia J Vieta Eduard E Viswanath Biju B Witt Stephanie S Zandi Peter P Alda Martin M Bauer Michael M McMahon Francis F Mitchell Philip P Rietschel Marcella M Schulze Thomas T Baune Bernhard B

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The link between bipolar disorder (BP) and immune dysfunction remains controversial. While epidemiological studies have long suggested an association, recent research has found only limited evidence of such a relationship. To clarify this, we investigated the contributions of immune-relevant genetic factors to the response to lithium (Li) treatment and the clinical presentation of BP. First, we assessed the association of a large collection of immune-related genes (4,925) with Li response, defin ...[more]

PMID: 37461719

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Project description:BackgroundIndividuals with co-existing serious mental illness and non-psychiatric medical illness are at high risk of acute care utilization. Mining of electronic health record data can help identify and categorize predictors of psychiatric hospital readmission in this population.ObjectiveThis study aimed to identify modifiable predictors of psychiatric readmission among individuals with comorbid bipolar disorder and medical illness. This goal was accomplished by applying objective variable selection via machine learning techniques.MethodThis was a retrospective analysis of electronic health record data derived from 77,296 episodes of care from 2006 to 2016 within the University of California Health Care System. Data included 1,250 episodes of care involving patients with bipolar disorder and serious comorbid medical illnesses (defined by transfer between medicine and psychiatry services or concomitant primary medical and psychiatric admission diagnoses). Machine learning (classification trees) was used to identify potential predictors of 30-day psychiatric readmission across hospital encounters. Predictors included demographics, medical and psychiatric diagnoses, medication regimen, and disposition. The algorithm was internally validated using 10-fold cross-validation.ResultsThe model predicted 30-day readmission with high accuracy (98% unbalanced model, 88% balanced model). Modifiable predictors of readmission were length of stay, transfers between medical and psychiatric services, discharge disposition to home, and all-cause acute health service utilization in the year before the index hospitalization.ConclusionAmong bipolar disorder patients with comorbid medical conditions, characteristics of the index hospitalization (e.g., duration, transfer, and disposition) emerged as more predictive than static properties of the patient (e.g., sociodemographic factors and psychiatric comorbidity burden). Findings identified phenotypes of patients at high risk for rehospitalization and suggest potential ways of modifying the risk of early readmission.

Project description:Bipolar disorder (BD) is a common, highly heritable neuropsychiatric disease characterized by recurrent episodes of mania and depression. Lithium is the best-established long-term treatment for BD, even though individual response is highly variable. Evidence suggests that some of this variability has a genetic basis. This is supported by the largest genome-wide association study (GWAS) of lithium response to date conducted by the International Consortium on Lithium Genetics (ConLiGen). Recently, we performed the first genome-wide analysis of the involvement of miRNAs in BD and identified nine BD-associated miRNAs. However, it is unknown whether these miRNAs are also associated with lithium response in BD. In the present study, we therefore tested whether common variants at these nine candidate miRNAs contribute to the variance in lithium response in BD. Furthermore, we systematically analyzed whether any other miRNA in the genome is implicated in the response to lithium. For this purpose, we performed gene-based tests for all known miRNA coding genes in the ConLiGen GWAS dataset (n = 2,563 patients) using a set-based testing approach adapted from the versatile gene-based test for GWAS (VEGAS2). In the candidate approach, miR-499a showed a nominally significant association with lithium response, providing some evidence for involvement in both development and treatment of BD. In the genome-wide miRNA analysis, 71 miRNAs showed nominally significant associations with the dichotomous phenotype and 106 with the continuous trait for treatment response. A total of 15 miRNAs revealed nominal significance in both phenotypes with miR-633 showing the strongest association with the continuous trait (p = 9.80E-04) and miR-607 with the dichotomous phenotype (p = 5.79E-04). No association between miRNAs and treatment response to lithium in BD in either of the tested conditions withstood multiple testing correction. Given the limited power of our study, the investigation of miRNAs in larger GWAS samples of BD and lithium response is warranted.

Dataset Information

Immunogenetics of lithium response and psychiatric phenotypes in patients with bipolar disorder.

Publications

Immunogenetics of lithium response and psychiatric phenotypes in patients with bipolar disorder.

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