Socrates Adam, Maxwell Jessye, Glanville Kylie P, Di Forti Marta, Murray Robin M, Vassos Evangelos, O'Reilly Paul F
SGDP Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
NPJ Schizophr. 2021 Jan 22;7(1):2. doi: 10.1038/s41537-020-00131-2.
To characterise the trait-effects of increased genetic risk for schizophrenia, and highlight potential risk mediators, we test the association between schizophrenia polygenic risk scores (PRSs) and 529 behavioural traits (personality, psychological, lifestyle, nutritional) in the UK Biobank. Our primary analysis is performed on individuals aged 38-71 with no history of schizophrenia or related disorders, allowing us to report the effects of schizophrenia genetic risk in the sub-clinical general population. Higher schizophrenia PRSs were associated with a range of traits, including lower verbal-numerical reasoning (P = 6 × 10), higher nervous feelings (P = 1 × 10) and higher self-reported risk-taking (P = 3 × 10). We follow-up the risk-taking association, hypothesising that the association may be due to a genetic propensity for risk-taking leading to greater migration, urbanicity or drug-taking - reported environmental risk factors for schizophrenia, and all positively associated with risk-taking in these data. Next, to identify potential disorder or medication effects, we compare the PRS-trait associations in the general population to the trait values in 599 medicated and non-medicated individuals diagnosed with schizophrenia in the biobank. This analysis highlights, for example, levels of BMI, physical activity and risk-taking in cases in the opposite directions than expected from the PRS-trait associations in the general population. Our analyses offer simple yet potentially revealing insights into the possible causes of observed trait-disorder associations, which can complement approaches such as Mendelian Randomisation. While we urge caution in causal interpretations in PRS cross-trait studies that are highly powered to detect weak horizontal pleiotropy or population structure, we propose that well-designed polygenic score analyses have the potential to highlight modifiable risk factors that lie on the path between genetic risk and disorder.
为了描述精神分裂症遗传风险增加的特质效应，并突出潜在的风险介导因素，我们在英国生物银行中测试了精神分裂症多基因风险评分（PRS）与529种行为特质（人格、心理、生活方式、营养）之间的关联。我们对年龄在38 - 71岁且无精神分裂症或相关疾病史的个体进行了初步分析，从而能够报告精神分裂症遗传风险在亚临床普通人群中的影响。较高的精神分裂症PRS与一系列特质相关，包括较低的言语数字推理能力（P = 6×10）、较高的紧张情绪（P = 1×10）以及较高的自我报告冒险行为（P = 3×10）。我们对冒险行为的关联进行了追踪，推测这种关联可能是由于冒险的遗传倾向导致更多的迁移、城市化或吸毒行为——这些都是已报道的精神分裂症环境风险因素，并且在这些数据中均与冒险行为呈正相关。接下来，为了识别潜在的疾病或药物影响，我们将普通人群中的PRS - 特质关联与生物银行中599名被诊断为精神分裂症的服药和未服药个体的特质值进行了比较。例如，该分析突出了病例中的体重指数、身体活动水平和冒险行为水平与普通人群中PRS - 特质关联所预期的方向相反。我们的分析为观察到的数据关联的可能原因提供了简单但可能具有启发性的见解，这可以补充孟德尔随机化等方法。虽然我们敦促在PRS跨特质研究中对因果解释持谨慎态度，因为这类研究有很大能力检测到微弱的水平多效性或群体结构，但我们认为精心设计的多基因评分分析有可能突出位于遗传风险和疾病之间路径上的可改变风险因素。
