Risk genes influence the chance of an individual developing disease over their lifetime, although the age at onset (AAO) genes influence disease timing. These two categories are not disjoint; a gene that influences AAO might also appear to influence the risk. When an allele influences both AAO and risk, a reasonable question is whether we would have more power to detect association using a statistical test based on risk or AAO. To address this question, we compared power analytically for the Cochran–Armitage trend case–control test for risk and a linear regression case‐only test for AAO. We also used simulations to compare the power of these tests with a 2‐degree of freedom joint test (which combines the risk and AAO statistics) and the Cox proportional hazards survival model testing AAO (with censored data in controls). We found that when there is little heterogeneity, the case–control risk test has more power than the case‐only AAO test (with equivalent sample sizes), but when the model is complex (e.g., with heterogeneity or reduced penetrance), the relationship reverses. The joint test generally outperforms the risk or AAO test alone and ultimately is our recommendation as a powerful alternative in many scenarios.

中文翻译：

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探索疾病风险和发病年龄的遗传关联测试

风险基因影响个体在其一生中患疾病的机会，尽管 发病年龄(AAO) 基因影响疾病发生时间。这两个类别并非不相交；影响 AAO 的基因似乎也会影响风险。当等位基因同时影响 AAO 和风险时，一个合理的问题是，我们是否更有能力使用基于风险或 AAO 的统计检验来检测关联。为了解决这个问题，我们对风险的 Cochran-Armitage 趋势案例控制检验和 AAO 的线性回归仅案例检验的功效进行了分析比较。我们还使用模拟来比较这些测试与 2 自由度联合测试（结合风险和 AAO 统计数据）和 Cox 比例风险生存模型测试 AAO（在控制中使用删失数据）的功效。我们发现，当异质性很小时，病例对照风险检验比仅病例 AAO 检验（具有相同的样本量）具有更大的效力，但当模型复杂时（例如，异质性或外显率降低），这种关系就会逆转。联合测试通常优于单独的风险或 AAO 测试，最终我们建议将其作为许多场景中的强大替代方案。