Department of Psychiatry, University of Münster, Münster, Germany; Interdisciplinary Centre for Clinical Research, University of Münster, Münster, Germany.
Department of Psychiatry, University of Münster, Münster, Germany.
Biol Psychiatry. 2020 Nov 1;88(9):678-686. doi: 10.1016/j.biopsych.2020.04.027. Epub 2020 May 11.
Neuroimaging studies have consistently reported similar brain structural abnormalities across different psychiatric disorders. Yet, the extent and regional distribution of shared morphometric abnormalities between disorders remains unknown.
Here, we conducted a cross-disorder analysis of brain structural abnormalities in 6 psychiatric disorders based on effect size estimates for cortical thickness and subcortical volume differences between healthy control subjects and psychiatric patients from 11 mega- and meta-analyses from the ENIGMA (Enhancing Neuro Imaging Genetics Through Meta Analysis) consortium. Correlational and exploratory factor analyses were used to quantify the relative overlap in brain structural effect sizes between disorders and to identify brain regions with disorder-specific abnormalities.
Brain structural abnormalities in major depressive disorder, bipolar disorder, schizophrenia, and obsessive-compulsive disorder were highly correlated (r = .443 to r = .782), and one shared latent underlying factor explained between 42.3% and 88.7% of the brain structural variance of each disorder. The observed shared morphometric signature of these disorders showed little similarity with brain structural patterns related to physiological aging. In contrast, patterns of brain structural abnormalities independent of all other disorders were observed in both attention-deficit/hyperactivity disorder and autism spectrum disorder. Brain regions showing high proportions of independent variance were identified for each disorder to locate disorder-specific morphometric abnormalities.
Taken together, these results offer novel insights into transdiagnostic as well as disorder-specific brain structural abnormalities across 6 major psychiatric disorders. Limitations comprise the uncertain contribution of risk factors, comorbidities, and medication effects to the observed pattern of results that should be clarified by future research.
神经影像学研究一致报告了不同精神疾病之间存在相似的大脑结构异常。然而,不同疾病之间共享的形态计量学异常的程度和区域分布尚不清楚。
在这里,我们根据 ENIGMA(通过荟萃分析增强神经影像学遗传学)联盟的 11 项大型荟萃分析和荟萃分析中健康对照组和精神科患者之间皮质厚度和皮质下体积差异的效应量估计值,对 6 种精神疾病的大脑结构异常进行了跨疾病分析。相关和探索性因子分析用于量化疾病之间大脑结构效应大小的相对重叠,并确定具有疾病特异性异常的大脑区域。
重度抑郁症、双相情感障碍、精神分裂症和强迫症的大脑结构异常高度相关(r=0.443 至 r=0.782),一个共享的潜在因素解释了每个疾病大脑结构变异的 42.3%至 88.7%。这些疾病的观察到的共享形态计量特征与与生理衰老相关的大脑结构模式几乎没有相似性。相比之下,在注意缺陷/多动障碍和自闭症谱系障碍中观察到了独立于所有其他疾病的大脑结构异常模式。为每个疾病确定了显示高比例独立方差的大脑区域,以定位疾病特异性形态计量异常。
综上所述,这些结果为 6 种主要精神疾病的跨诊断和疾病特异性大脑结构异常提供了新的见解。局限性包括风险因素、合并症和药物治疗对观察到的结果模式的不确定贡献,这应通过未来的研究加以澄清。