Xu M K, Gaysina D, Barnett J H, Scoriels L, van de Lagemaat L N, Wong A, Richards M, Croudace T J, Jones P B
Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK.
Rudd Centre for Adoption Research and Practice, School of Psychology, University of Sussex, Brighton, UK.
Transl Psychiatry. 2015 Jun 30;5(6):e593. doi: 10.1038/tp.2015.86.
Affective disorders are highly heritable, but few genetic risk variants have been consistently replicated in molecular genetic association studies. The common method of defining psychiatric phenotypes in molecular genetic research is either a summation of symptom scores or binary threshold score representing the risk of diagnosis. Psychometric latent variable methods can improve the precision of psychiatric phenotypes, especially when the data structure is not straightforward. Using data from the British 1946 birth cohort, we compared summary scores with psychometric modeling based on the General Health Questionnaire (GHQ-28) scale for affective symptoms in an association analysis of 27 candidate genes (249 single-nucleotide polymorphisms (SNPs)). The psychometric method utilized a bi-factor model that partitioned the phenotype variances into five orthogonal latent variable factors, in accordance with the multidimensional data structure of the GHQ-28 involving somatic, social, anxiety and depression domains. Results showed that, compared with the summation approach, the affective symptoms defined by the bi-factor psychometric model had a higher number of associated SNPs of larger effect sizes. These results suggest that psychometrically defined mental health phenotypes can reflect the dimensions of complex phenotypes better than summation scores, and therefore offer a useful approach in genetic association investigations.
情感障碍具有高度遗传性，但在分子遗传学关联研究中很少有基因风险变异能被一致地重复验证。在分子遗传学研究中定义精神疾病表型的常用方法是症状评分的总和或代表诊断风险的二元阈值评分。心理测量潜在变量方法可以提高精神疾病表型的精度，尤其是当数据结构不直接明了时。利用来自英国1946年出生队列的数据，我们在对27个候选基因（249个单核苷酸多态性（SNP））的关联分析中，将基于一般健康问卷（GHQ - 28）量表的情感症状的汇总评分与心理测量模型进行了比较。心理测量方法采用了双因素模型，该模型根据涉及躯体、社会、焦虑和抑郁领域的GHQ - 28的多维数据结构，将表型方差划分为五个正交的潜在变量因素。结果表明，与汇总方法相比，由双因素心理测量模型定义的情感症状具有更多效应量更大的相关SNP。这些结果表明，心理测量定义的心理健康表型比汇总评分能更好地反映复杂表型的维度，因此在基因关联研究中提供了一种有用的方法。
