Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.
Hum Genet. 2021 Aug;140(8):1253-1265. doi: 10.1007/s00439-021-02298-9. Epub 2021 May 31.
In the present study, we sought to identify causal relationships between obesity and other complex traits and conditions using a data-driven hypothesis-free approach that uses genetic data to infer causal associations.
We leveraged available summary-based genetic data from genome-wide association studies on 1498 phenotypes and applied the latent causal variable method (LCV) between obesity and all traits.
We identified 110 traits causally associated with obesity. Of those, 109 were causal outcomes of obesity, while only leg pain in calves was a causal determinant of obesity. Causal outcomes of obesity included 26 phenotypes associated with cardiovascular diseases, 22 anthropometric measurements, nine with the musculoskeletal system, nine with behavioural or lifestyle factors including loneliness or isolation, six with respiratory diseases, five with body bioelectric impedances, four with psychiatric phenotypes, four related to the nervous system, four with disabilities or long-standing illness, three with the gastrointestinal system, three with use of analgesics, two with metabolic diseases, one with inflammatory response and one with the neurodevelopmental disorder ADHD, among others. In particular, some causal outcomes of obesity included hypertension, stroke, ever having a period of extreme irritability, low forced vital capacity and forced expiratory volume, diseases of the musculoskeletal system, diabetes, carpal tunnel syndrome, loneliness or isolation, high leukocyte count, and ADHD.
Our results indicate that obesity causally affects a wide range of traits and comorbid diseases, thus providing an overview of the metabolic, physiological, and neuropsychiatric impact of obesity on human health.
在本研究中，我们试图使用一种数据驱动的无假设方法来识别肥胖症与其他复杂特征和状况之间的因果关系，该方法利用遗传数据来推断因果关联。
我们利用了来自 1498 种表型的全基因组关联研究中可用的基于汇总的遗传数据，并在肥胖症和所有特征之间应用了潜在因果变量方法（LCV）。
我们确定了 110 种与肥胖症因果相关的特征。其中，109 种是肥胖症的因果结果，而只有小腿腿部疼痛是肥胖症的因果决定因素。肥胖症的因果结果包括 26 种与心血管疾病相关的表型、22 种人体测量学测量值、9 种与肌肉骨骼系统相关、9 种与行为或生活方式因素（包括孤独或孤立）相关、6 种与呼吸疾病相关、5 种与身体生物电阻抗相关、4 种与精神疾病表型相关、4 种与神经系统相关、4 种与残疾或长期疾病相关、3 种与胃肠道系统相关、3 种与使用镇痛药相关、2 种与代谢疾病相关、1 种与炎症反应相关和 1 种与神经发育障碍 ADHD 相关，等等。特别是，肥胖症的一些因果结果包括高血压、中风、曾经有过极度易怒期、用力肺活量和用力呼气量低、肌肉骨骼系统疾病、糖尿病、腕管综合征、孤独或孤立、白细胞计数高和 ADHD。
我们的研究结果表明，肥胖症因果地影响了广泛的特征和合并疾病，从而全面了解肥胖症对人类健康的代谢、生理和神经精神影响。
