The Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, Sydney, NSW, Australia.
Leeds Institute for Data Analytics, University of Leeds, Leeds, UK.
Br J Dermatol. 2022 May;186(5):823-834. doi: 10.1111/bjd.20956. Epub 2022 Mar 31.
Previous studies suggest that polygenic risk scores (PRSs) may improve melanoma risk stratification. However, there has been limited independent validation of PRS-based risk prediction, particularly assessment of calibration (comparing predicted to observed risks).
To evaluate PRS-based melanoma risk prediction in prospective UK and Australian cohorts with European ancestry.
We analysed invasive melanoma incidence in the UK Biobank (UKB; n = 395 647, 1651 cases) and a case-cohort nested within the Melbourne Collaborative Cohort Study (MCCS, Australia; n = 4765, 303 cases). Three PRSs were evaluated: 68 single-nucleotide polymorphisms (SNPs) at 54 loci from a 2020 meta-analysis (PRS68), 50 SNPs significant in the 2020 meta-analysis excluding UKB (PRS50) and 45 SNPs at 21 loci known in 2018 (PRS45). Ten-year melanoma risks were calculated from population-level cancer registry data by age group and sex, with and without PRS adjustment.
Predicted absolute melanoma risks based on age and sex alone underestimated melanoma incidence in the UKB [ratio of expected/observed cases: E/O = 0·65, 95% confidence interval (CI) 0·62-0·68] and MCCS (E/O = 0·63, 95% CI 0·56-0·72). For UKB, calibration was improved by PRS adjustment, with PRS50-adjusted risks E/O = 0·91, 95% CI 0·87-0·95. The discriminative ability for PRS68- and PRS50-adjusted absolute risks was higher than for risks based on age and sex alone (Δ area under the curve 0·07-0·10, P < 0·0001), and higher than for PRS45-adjusted risks (Δ area under the curve 0·02-0·04, P < 0·001).
A PRS derived from a larger, more diverse meta-analysis improves risk prediction compared with an earlier PRS, and might help tailor melanoma prevention and early detection strategies to different risk levels. Recalibration of absolute risks may be necessary for application to specific populations.
先前的研究表明,多基因风险评分(PRS)可能有助于改善黑色素瘤风险分层。然而,基于 PRS 的风险预测的独立验证有限,尤其是对校准(比较预测风险与观察风险)的评估。
在具有欧洲血统的英国和澳大利亚前瞻性队列中评估基于 PRS 的黑色素瘤风险预测。
我们分析了英国生物库(UKB;n=395647,1651 例,病例)和墨尔本协作队列研究(MCCS,澳大利亚;n=4765,303 例,病例-队列嵌套)中侵袭性黑色素瘤的发病率。评估了三种 PRS:2020 年荟萃分析中 54 个位点的 68 个单核苷酸多态性(SNP;PRS68)、2020 年荟萃分析中剔除 UKB 的 50 个显著 SNP(PRS50)和 2018 年已知的 21 个位点的 45 个 SNP(PRS45)。根据年龄组和性别,从人群癌症登记处的数据计算未经 PRS 调整和调整后的十年黑色素瘤风险。
仅基于年龄和性别的预测绝对黑色素瘤风险低估了 UKB(预期/观察病例比:E/O=0.65,95%置信区间[CI]0.62-0.68)和 MCCS(E/O=0.63,95%CI 0.56-0.72)中的黑色素瘤发病率。通过 PRS 调整,UKB 的校准得到改善,PRS50 调整后的风险 E/O=0.91,95%CI 0.87-0.95。PRS68 和 PRS50 调整后的绝对风险的判别能力高于仅基于年龄和性别的风险(曲线下面积增加 0.07-0.10,P<0.0001),也高于 PRS45 调整后的风险(曲线下面积增加 0.02-0.04,P<0.001)。
与早期 PRS 相比,来自更大、更多样化荟萃分析的 PRS 衍生风险预测可改善风险预测,可能有助于根据不同风险水平调整黑色素瘤预防和早期发现策略。可能需要对绝对风险进行重新校准,以应用于特定人群。