Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia.
Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Genet Epidemiol. 2024 Dec;48(8):433-447. doi: 10.1002/gepi.22555. Epub 2024 Mar 19.
Young breast and bowel cancers (e.g., those diagnosed before age 40 or 50 years) have far greater morbidity and mortality in terms of years of life lost, and are increasing in incidence, but have been less studied. For breast and bowel cancers, the familial relative risks, and therefore the familial variances in age-specific log(incidence), are much greater at younger ages, but little of these familial variances has been explained. Studies of families and twins can address questions not easily answered by studies of unrelated individuals alone. We describe existing and emerging family and twin data that can provide special opportunities for discovery. We present designs and statistical analyses, including novel ideas such as the VALID (Variance in Age-specific Log Incidence Decomposition) model for causes of variation in risk, the DEPTH (DEPendency of association on the number of Top Hits) and other approaches to analyse genome-wide association study data, and the within-pair, ICE FALCON (Inference about Causation from Examining FAmiliaL CONfounding) and ICE CRISTAL (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLysis) approaches to causation and familial confounding. Example applications to breast and colorectal cancer are presented. Motivated by the availability of the resources of the Breast and Colon Cancer Family Registries, we also present some ideas for future studies that could be applied to, and compared with, cancers diagnosed at older ages and address the challenges posed by young breast and bowel cancers.
年轻的乳腺癌和肠癌（例如，在 40 或 50 岁之前诊断出的癌症）在生命损失年限方面的发病率和死亡率更高，且发病率呈上升趋势，但研究较少。对于乳腺癌和肠癌，家族相对风险，以及特定年龄的对数（发病率）的家族方差，在较年轻时更大，但这些家族方差的大部分仍未得到解释。对家庭和双胞胎的研究可以解决仅通过对无关个体进行研究不易回答的问题。我们描述了现有的和新兴的家庭和双胞胎数据，这些数据可以为发现提供特殊机会。我们提出了设计和统计分析，包括用于风险变异原因的 VALID（年龄特异性对数发病率分解方差）模型等新想法、DEPTH（依赖于顶级命中数量的关联）和其他分析全基因组关联研究数据的方法，以及用于因果关系和家族性混杂的配对内 ICE FALCON（通过检查家族性混杂来推断因果关系）和 ICE CRISTAL（通过检查回归系数变化和创新的统计分析来推断因果关系）方法。我们提出了乳腺癌和结直肠癌的应用示例。鉴于乳腺和结肠癌症家族登记处资源的可用性，我们还提出了一些未来研究的想法，可以应用于和比较老年诊断的癌症，并解决年轻乳腺癌和肠癌带来的挑战。
