Individual differences in susceptibility to developing asthma, a heterogeneous chronic inflammatory lung disease, are poorly understood. Whether genetics can predict asthma risk and how genetic variants modulate the complex pathophysiology of asthma are still debated.

To build polygenic risk scores for asthma risk prediction and epigenomically link predictive genetic variants to pathophysiological mechanisms.

Restricted polygenic risk scores were constructed using single nucleotide variants derived from genome-wide association studies and validated using data generated in the Rotterdam Study, a Dutch prospective cohort of 14 926 individuals. Outcomes used were asthma, childhood-onset asthma, adulthood-onset asthma, eosinophilic asthma and asthma exacerbations. Genome-wide chromatin analysis data from 19 disease-relevant cell types were used for epigenomic polygenic risk score partitioning.

The polygenic risk scores obtained predicted asthma and related outcomes, with the strongest associations observed for childhood-onset asthma (2.55 odds ratios per polygenic risk score standard deviation, area under the curve of 0.760). Polygenic risk scores allowed for the classification of individuals into high-risk and low-risk groups. Polygenic risk score partitioning using epigenomic profiles identified five clusters of variants within putative gene regulatory regions linked to specific asthma-relevant cells, genes and biological pathways.

Polygenic risk scores were associated with asthma(-related traits) in a Dutch prospective cohort, with substantially higher predictive power observed for childhood-onset than adult-onset asthma. Importantly, polygenic risk score variants could be epigenomically partitioned into clusters of regulatory variants with different pathophysiological association patterns and effect estimates, which likely represent distinct genetically driven disease pathways. Our findings have potential implications for personalised risk mitigation and treatment strategies.

人们对哮喘（一种异质性慢性炎症性肺病）易感性的个体差异知之甚少。遗传学是否可以预测哮喘风险以及遗传变异如何调节哮喘复杂的病理生理学仍然存在争议。

建立用于哮喘风险预测的多基因风险评分，并将预测性遗传变异与病理生理机制联系起来。

限制性多基因风险评分是使用源自全基因组关联研究的单核苷酸变异构建的，并使用鹿特丹研究（一个由 14926 名个体组成的荷兰前瞻性队列）生成的数据进行验证。使用的结果包括哮喘、儿童期发病的哮喘、成年期发病的哮喘、嗜酸性粒细胞性哮喘和哮喘恶化。来自 19 种疾病相关细胞类型的全基因组染色质分析数据用于表观基因组多基因风险评分划分。

多基因风险评分获得了哮喘和相关结果的预测，其中与儿童期发病的哮喘相关性最强（每多基因风险评分标准差的比值比为 2.55，曲线下面积为 0.760）。多基因风险评分允许将个体分为高风险组和低风险组。使用表观基因组图谱进行多基因风险评分划分，确定了与特定哮喘相关细胞、基因和生物途径相关的假定基因调控区域内的五组变异。

在荷兰前瞻性队列中，多基因风险评分与哮喘（相关特征）相关，观察到儿童期发病的预测能力明显高于成人发病的哮喘。重要的是，多基因风险评分变异可以在表观基因组上划分为具有不同病理生理学关联模式和效应估计的调节变异簇，这可能代表不同的遗传驱动的疾病途径。我们的研究结果对个性化风险缓解和治疗策略具有潜在影响。