Molecular Genetic Risk for Psychosis Is Associated With Psychosis Risk Symptoms in a Population-Based UK Cohort: Findings From Generation Scotland
Molecular Genetic Risk for Psychosis Is Associated With Psychosis Risk Symptoms in a Population-Based UK Cohort: Findings From Generation Scotland
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DOI：
10.1093/schbul/sbaa042
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发表时间：
2020-09-01
影响因子：
6.6
通讯作者：
Kendler, Kenneth S.
中科院分区：
文献类型：
--
作者：
Docherty, Anna R.;Shabalin, Andrey A.;Kendler, Kenneth S.
目的：普通人群中阈下精神病危险症状可能与精神病的分子遗传风险相关。本研究试图通过适当考虑人群分层、因素结构和性别，在英国一个以人群为基础的大型队列中（N = 9104名18-65岁的个体）优化风险症状与精神病遗传风险的关联。方法：新扩展的一代苏格兰：苏格兰家庭健康研究纳入5391名女性和3713名男性，年龄为M [SD] = 45.2[13]，包括风险症状数据和遗传数据。阈下精神病症状采用分裂型人格问卷（SPQ-B）进行测量，精神分裂症多基因风险计算基于11 425 349个通过质量控制的输入常见遗传变异。其他遗传风险的随访检查包括注意缺陷多动障碍（ADHD）、自闭症、双相情感障碍、重度抑郁症和神经质。结果：经验得出的症状因子得分反映人际/阴性症状，并与精神分裂症的多基因风险呈正相关。这种信号很大程度上是性别特有的，仅限于雄性。无论男女，得分都与神经质和重度抑郁症呈正相关。结论：数据驱动的表型分析能够在基于人群的样本中检测与精神分裂症遗传风险的关联。多个多基因风险信号和重要的性别差异表明，遗传数据可能有助于改善未来的表型风险评估。
Objective: Subthreshold psychosis risk symptoms in the general population may be associated with molecular genetic risk for psychosis. This study sought to optimize the association of risk symptoms with genetic risk for psychosis in a large population-based cohort in the UK (N = 9104 individuals 18-65 years of age) by properly accounting for population stratification, factor structure, and sex.Methods: The newly expanded Generation Scotland: Scottish Family Health Study includes 5391 females and 3713 males with age M [SD] = 45.2 [13] with both risk symptom data and genetic data. Subthreshold psychosis symptoms were measured using the Schizotypal Personality Questionnaire-Brief (SPQ-B) and calculation of polygenic risk for schizophrenia was based on 11 425 349 imputed common genetic variants passing quality control. Follow-up examination of other genetic risks included attention-deficit hyperactivity disorder (ADHD), autism, bipolar disorder, major depression, and neuroticism.Results: Empirically derived symptom factor scores reflected interpersonal/negative symptoms and were positively associated with polygenic risk for schizophrenia. This signal was largely sex specific and limited to males. Across both sexes, scores were positively associated with neuroticism and major depressive disorder.Conclusions: A data-driven phenotypic analysis enabled detection of association with genetic risk for schizophrenia in a population-based sample. Multiple polygenic risk signals and important sex differences suggest that genetic data may be useful in improving future phenotypic risk assessment.