Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK; Centre of Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
Leeds Institute of Health Sciences, Division of Psychological and Social Medicine, Faculty of Medicine and Health, University of Leeds, Leeds, UK.
Lancet Psychiatry. 2023 Aug;10(8):623-631. doi: 10.1016/S2215-0366(23)00186-4. Epub 2023 Jul 9.
Current definitions and clinical heterogeneity in bipolar disorder are major concerns as they obstruct aetiological research and impede drug development. Therefore, stratification of bipolar disorder is a high priority. To inform stratification, our analysis aimed to examine the patterns and relationships between polygenic liability for bipolar disorder, major depressive disorder (MDD), and schizophrenia with multidimensional symptom representations of bipolar disorder.
In this analysis, data from the UK Bipolar Disorder Research Network (BDRN) were assessed with the Operational Checklist for Psychotic Disorders. Individuals with bipolar disorder as defined in DSM-IV, of European ancestry (self-reported), aged 18 years or older at time of interview, living in the UK, and registered with the BDRN were eligible for inclusion. Psychopathological variables obtained via interview by trained research psychologists or psychiatrists and psychiatric case notes were used to identify statistically distinct symptom dimensions, calibrated with exploratory factor analysis and validated with confirmatory factor analysis (CFA). CFA was extended to include three polygenic risk scores (PRSs) indexing liability for bipolar disorder, MDD, and schizophrenia in a multiple indicator multiple cause (MIMIC) structural equation model to estimate PRS relationships with symptom dimensions.
Of 4198 individuals potentially eligible for inclusion, 4148 (2804 [67·6%] female individuals and 1344 [32·4%] male individuals) with a mean age at interview of 45 years (SD 12·03) were available for analysis. Three reliable dimensions (mania, depression, and psychosis) were identified. The MIMIC model fitted the data well (root mean square error of approximation 0·021, 90% CI 0·019-0·023; comparative fit index 0·99) and suggests statistically distinct symptom dimensions also have distinct polygenic profiles. The PRS for MDD was strongly associated with the depression dimension (standardised β 0·125, 95% CI 0·080-0·171) and the PRS for schizophrenia was strongly associated with the psychosis dimension (0·108, 0·082-0·175). For the mania dimension, the PRS for bipolar disorder was weakly associated (0·050, 0·002-0·097).
Our findings support the hypothesis that genetic heterogeneity underpins clinical heterogeneity, suggesting that different symptom dimensions within bipolar disorder have partly distinct causes. Furthermore, our results suggest that a specific symptom dimension has a similar cause regardless of the primary psychiatric diagnosis, supporting the use of symptom dimensions in precision psychiatry.
Wellcome Trust and UK Medical Research Council.
目前双相情感障碍的定义和临床异质性是主要关注点，因为它们阻碍了病因研究并阻碍了药物开发。因此，双相情感障碍的分层是当务之急。为了提供信息，我们的分析旨在检查双相情感障碍、重度抑郁症 (MDD) 和精神分裂症的多基因易感性与双相情感障碍多维症状表现之间的模式和关系。
在这项分析中，使用英国双相情感障碍研究网络 (BDRN) 的数据进行了精神病性障碍操作检查表评估。符合 DSM-IV 定义的双相情感障碍患者、欧洲血统（自述）、在访谈时年满 18 岁、居住在英国并在 BDRN 注册的患者有资格入选。通过受过培训的研究心理学家或精神科医生的访谈以及精神病学病例记录获得的精神病理学变量，用于通过探索性因素分析确定具有统计学意义的不同症状维度，并通过验证性因素分析 (CFA) 进行校准。CFA 扩展到包括三个多基因风险评分 (PRS)，以在多指标多原因 (MIMIC) 结构方程模型中索引双相情感障碍、MDD 和精神分裂症的易感性，以估计 PRS 与症状维度的关系。
在 4198 名可能符合入选条件的个体中，有 4148 名（2804 名 [67.6%] 女性和 1344 名 [32.4%] 男性）的平均年龄为 45 岁（标准差 12.03）可用于分析。确定了三个可靠的维度（躁狂、抑郁和精神病）。MIMIC 模型很好地拟合了数据（均方根误差近似值 0.021，90%CI 0.019-0.023；比较拟合指数 0.99），并表明具有统计学意义的不同症状维度也具有不同的多基因特征。MDD 的 PRS 与抑郁维度密切相关（标准化β 0.125，95%CI 0.080-0.171），精神分裂症的 PRS 与精神病维度密切相关（0.108，0.082-0.175）。对于躁狂维度，双相情感障碍的 PRS 与轻微相关（0.050，0.002-0.097）。
我们的研究结果支持遗传异质性是临床异质性基础的假设，这表明双相情感障碍内的不同症状维度具有部分不同的病因。此外，我们的结果表明，无论主要的精神诊断如何，特定的症状维度都有类似的病因，这支持了在精准精神病学中使用症状维度。
惠康信托基金会和英国医学研究理事会。
