Nunes Abraham, Stone William, Ardau Raffaella, Berghöfer Anne, Bocchetta Alberto, Chillotti Caterina, Deiana Valeria, Degenhardt Franziska, Forstner Andreas J, Garnham Julie S, Grof Eva, Hajek Tomas, Manchia Mirko, Mattheisen Manuel, McMahon Francis, Müller-Oerlinghausen Bruno, Nöthen Markus M, Pinna Marco, Pisanu Claudia, O'Donovan Claire, Rietschel Marcella D C, Rouleau Guy, Schulze Thomas, Severino Giovanni, Slaney Claire M, Squassina Alessio, Suwalska Aleksandra, Turecki Gustavo, Uher Rudolf, Zvolsky Petr, Cervantes Pablo, Del Zompo Maria, Grof Paul, Rybakowski Janusz, Tondo Leonardo, Trappenberg Thomas, Alda Martin
Department of Psychiatry, Dalhousie University, Halifax, NS, Canada.
Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada.
Transl Psychiatry. 2021 Jan 11;11(1):36. doi: 10.1038/s41398-020-01148-y.
Predicting lithium response (LiR) in bipolar disorder (BD) may inform treatment planning, but phenotypic heterogeneity complicates discovery of genomic markers. We hypothesized that patients with "exemplary phenotypes"-those whose clinical features are reliably associated with LiR and non-response (LiNR)-are more genetically separable than those with less exemplary phenotypes. Using clinical data collected from people with BD (n = 1266 across 7 centers; 34.7% responders), we computed a "clinical exemplar score," which measures the degree to which a subject's clinical phenotype is reliably predictive of LiR/LiNR. For patients whose genotypes were available (n = 321), we evaluated whether a subgroup of responders/non-responders with the top 25% of clinical exemplar scores (the "best clinical exemplars") were more accurately classified based on genetic data, compared to a subgroup with the lowest 25% of clinical exemplar scores (the "poor clinical exemplars"). On average, the best clinical exemplars of LiR had a later illness onset, completely episodic clinical course, absence of rapid cycling and psychosis, and few psychiatric comorbidities. The best clinical exemplars of LiR and LiNR were genetically separable with an area under the receiver operating characteristic curve of 0.88 (IQR [0.83, 0.98]), compared to 0.66 [0.61, 0.80] (p = 0.0032) among poor clinical exemplars. Variants in the Alzheimer's amyloid-secretase pathway, along with G-protein-coupled receptor, muscarinic acetylcholine, and histamine H1R signaling pathways were informative predictors. This study must be replicated on larger samples and extended to predict response to other mood stabilizers.
预测双相情感障碍（BD）的锂反应（LiR）可为治疗规划提供参考，但表型异质性使基因组标记的发现变得复杂。我们假设，具有“典型表型”的患者——其临床特征与LiR和无反应（LiNR）可靠相关——比具有较少典型表型的患者在基因上更易区分。利用从BD患者（7个中心共1266例；34.7%有反应者）收集的临床数据，我们计算了一个“临床典范分数”，该分数衡量受试者临床表型可靠预测LiR/LiNR的程度。对于有基因型数据的患者（n = 321），我们评估了临床典范分数处于前25%的反应者/无反应者亚组（“最佳临床典范”）与临床典范分数处于后25%的亚组（“较差临床典范”）相比，基于基因数据是否能更准确地分类。平均而言，LiR的最佳临床典范起病较晚，临床病程完全呈发作性，无快速循环和精神病症状，且精神科合并症较少。LiR和LiNR的最佳临床典范在基因上可区分，受试者工作特征曲线下面积为0.88（IQR [0.83, 0.98]），而较差临床典范的该面积为0.66 [0.61, 0.80]（p = 0.0032）。阿尔茨海默病淀粉样前体蛋白切割酶途径的变异以及G蛋白偶联受体、毒蕈碱型乙酰胆碱和组胺H1R信号通路是有信息量的预测指标。本研究必须在更大样本上重复，并扩展以预测对其他心境稳定剂的反应。
