Section of Hematology and Oncology, Department of Medicine, Baylor College of Medicine, Houston, TX.
Department of Statistics, Rice University, Houston, TX.
JCO Precis Oncol. 2024 Mar;8:e2300355. doi: 10.1200/PO.23.00355.
Pancreatic cancer (PC) is a deadly disease most often diagnosed in late stages. Identification of high-risk subjects could both contribute to preventative measures and help diagnose the disease at earlier timepoints. However, known risk factors, assessed independently, are currently insufficient for accurately stratifying patients. We use large-scale data from the UK Biobank (UKB) to identify genetic variant-smoking interaction effects and show their importance in risk assessment.
We draw data from 15,086,830 genetic variants and 315,512 individuals in the UKB. There are 765 cases of PC. Crucially, robust resampling corrections are used to overcome well-known challenges in hypothesis testing for interactions. Replication analysis is conducted in two independent cohorts totaling 793 cases and 570 controls. Integration of functional annotation data and construction of polygenic risk scores (PRS) demonstrate the additional insight provided by interaction effects.
We identify the genome-wide significant variant rs77196339 on chromosome 2 (per minor allele odds ratio in never-smokers, 2.31 [95% CI, 1.69 to 3.15]; per minor allele odds ratio in ever-smokers, 0.53 [95% CI, 0.30 to 0.91]; = 3.54 × 10) as well as eight other loci with suggestive evidence of interaction effects ( < 5 × 10). The rs77196339 region association is validated ( < .05) in the replication sample. PRS incorporating interaction effects show improved discriminatory ability over PRS of main effects alone.
This study of genome-wide germline variants identified smoking to modify the effect of rs77196339 on PC risk. Interactions between known risk factors can provide critical information for identifying high-risk subjects, given the relative inadequacy of models considering only main effects, as demonstrated in PRS. Further studies are necessary to advance toward comprehensive risk prediction approaches for PC.
胰腺癌(PC)是一种致命疾病,通常在晚期诊断。鉴定高危人群不仅有助于采取预防措施,还能帮助更早地诊断疾病。然而,目前已知的风险因素单独评估还不足以准确分层患者。我们利用英国生物库(UKB)的大规模数据来确定遗传变异与吸烟的相互作用效应,并展示其在风险评估中的重要性。
我们从 UKB 中的 15086830 个遗传变异和 315512 个人中提取数据。有 765 例 PC 病例。至关重要的是,我们使用稳健的重采样校正来克服相互作用假设检验中的已知挑战。在两个独立的队列中进行了复制分析,总共包括 793 例病例和 570 例对照。功能注释数据的整合和多基因风险评分(PRS)的构建证明了相互作用效应提供的额外见解。
我们确定了位于 2 号染色体上的全基因组显著变异 rs77196339(从不吸烟者中每个次要等位基因的优势比为 2.31[95%CI,1.69 至 3.15];吸烟者中每个次要等位基因的优势比为 0.53[95%CI,0.30 至 0.91]; = 3.54×10),以及其他 8 个具有相互作用效应提示证据的位点(<5×10)。rs77196339 区域的关联在复制样本中得到验证(<0.05)。纳入相互作用效应的 PRS 显示出比仅考虑主要效应的 PRS 更好的区分能力。
本研究对全基因组种系变异进行了研究,发现吸烟改变了 rs77196339 对 PC 风险的影响。已知风险因素之间的相互作用可以提供关键信息,用于鉴定高危人群,因为仅考虑主要效应的模型相对不足,这在 PRS 中得到了验证。需要进一步的研究来推进 PC 的综合风险预测方法。