Lee-Hughes Rosa, Lancaster Thomas M
Department of Psychology, University of Bath, Bath, UK.
Schizophr Bull Open. 2023 Nov 4;4(1):sgad031. doi: 10.1093/schizbullopen/sgad031. eCollection 2023 Jan.
Schizophrenia and bipolar disorder share a common structural brain alteration profile. However, there is considerable between- and within-diagnosis variability in these features, which may underestimate informative individual differences. Using a recently established morphometric risk score (MRS) approach, we aim to provide confirmation that individual MRS scores are higher in individuals with a psychosis diagnosis, helping to parse individual heterogeneity. Using the Human Connectome Project Early Psychosis ( = 124), we estimate MRS for psychosis and specifically for bipolar/schizophrenia using T1-weighted MRI data and prior meta-analysis effect sizes. We confirm associations in an independent replication sample ( = 69). We assess (1) the impact of diagnosis on these MRS, (2) compare effect sizes of MRS to all individual, cytoarchitecturally defined brain regions, and (3) perform negative control analyses to assess MRS specificity. The MRS specifically for SCZ was higher in the whole psychosis group (Cohen's = 0.56; = 0.003) and outperformed any single region of interest in standardized mean difference (Z = 2.597; = 0.009) and correlated with previously reported effect sizes (P < 0.005). MRS without Enhancing Neuroimaging Genomics through Meta-Analysis weights did not delineate groups with empirically null associations ( = 2.29; = 0.02). We replicate MRS specifically for SCZ associations in the independent sample. Akin to polygenic risk scoring and individual allele effect sizes, these observations suggest that assessing the combined impact of regional structural alterations may be more informative than any single cytoarchitecturally constrained cortical region, where well-powered, meta-analytical samples are informative in the delineation of diagnosis and within psychosis case differences, in smaller independent samples.
精神分裂症和双相情感障碍具有共同的大脑结构改变特征。然而，这些特征在诊断之间和诊断内部存在相当大的变异性，这可能会低估个体间有价值的差异。使用最近建立的形态测量风险评分（MRS）方法，我们旨在证实精神病诊断个体的个体MRS评分更高，这有助于剖析个体异质性。利用人类连接组计划早期精神病样本（n = 124），我们使用T1加权MRI数据和先前的荟萃分析效应大小来估计精神病以及双相情感障碍/精神分裂症的MRS。我们在一个独立的复制样本（n = 69）中证实了相关性。我们评估（1）诊断对这些MRS的影响，（2）将MRS的效应大小与所有个体的、细胞结构定义的脑区进行比较，以及（3）进行阴性对照分析以评估MRS的特异性。在整个精神病组中，专门针对精神分裂症的MRS更高（科恩d = 0.56；P = 0.003），在标准化平均差异方面优于任何单个感兴趣区域（Z = 2.597；P = 0.009），并且与先前报道的效应大小相关（P < 0.005）。没有通过荟萃分析权重增强神经影像基因组学的MRS未能区分具有经验性零关联的组（P = 2.29；P = 0.02）。我们在独立样本中复制了专门针对精神分裂症相关性的MRS。类似于多基因风险评分和个体等位基因效应大小，这些观察结果表明，评估区域结构改变的综合影响可能比任何单个细胞结构受限的皮质区域更具信息量，在较小的独立样本中，样本量充足的荟萃分析样本在诊断的界定和精神病病例内部差异方面具有指导意义。
