Martin Joanna, Tilling Kate, Hubbard Leon, Stergiakouli Evie, Thapar Anita, Davey Smith George, O'Donovan Michael C, Zammit Stanley
Am J Epidemiol. 2016 Jun 15;183(12):1149-58. doi: 10.1093/aje/kww009. Epub 2016 May 10.
Progress has recently been made in understanding the genetic basis of schizophrenia and other psychiatric disorders. Longitudinal studies are complicated by participant dropout, which could be related to the presence of psychiatric problems and associated genetic risk. We tested whether common genetic variants implicated in schizophrenia were associated with study nonparticipation among 7,867 children and 7,850 mothers from the Avon Longitudinal Study of Parents and Children (ALSPAC; 1991-2007), a longitudinal population cohort study. Higher polygenic risk scores for schizophrenia were consistently associated with noncompletion of questionnaires by study mothers and children and nonattendance at data collection throughout childhood and adolescence (ages 1-15 years). These associations persisted after adjustment for other potential correlates of nonparticipation. Results suggest that persons at higher genetic risk for schizophrenia are likely to be underrepresented in cohort studies, which will underestimate risk of this and related psychiatric, cognitive, and behavioral phenotypes in the population. Statistical power to detect associations with these phenotypes will be reduced, while analyses of schizophrenia-related phenotypes as outcomes may be biased by the nonrandom missingness of these phenotypes, even if multiple imputation is used. Similarly, in complete-case analyses, collider bias may affect associations between genetic risk and other factors associated with missingness.
最近在理解精神分裂症和其他精神疾病的遗传基础方面取得了进展。纵向研究因参与者退出而变得复杂，这可能与精神问题的存在及相关遗传风险有关。我们在“埃文亲子纵向研究”（ALSPAC；1991 - 2007年）中，对7867名儿童和7850名母亲进行了测试，以检验与精神分裂症相关的常见基因变异是否与研究未参与情况有关，该研究是一项纵向人群队列研究。母亲和儿童的精神分裂症多基因风险评分越高，与问卷未完成以及在整个童年和青少年时期（1至15岁）未参加数据收集的情况始终相关。在对其他可能的未参与相关因素进行调整后，这些关联依然存在。结果表明，精神分裂症遗传风险较高的人群在队列研究中的代表性可能不足，这将低估该人群中这种及相关精神、认知和行为表型的风险。检测与这些表型关联的统计效力将会降低，而将精神分裂症相关表型作为结果进行分析时，可能会因这些表型的非随机缺失而产生偏差，即便使用多重填补法也是如此。同样，在完全病例分析中，对撞机偏差可能会影响遗传风险与其他与缺失相关因素之间的关联。
