Frontiers in Statistical Genetics for NIAMS Researchers

NIAMS 研究人员的统计遗传学前沿

• 批准号: 7106649
• 负责人: Hemant K. Tiwari
• 金额: $ 3万
• 依托单位: UNIVERSITY OF ALABAMA AT BIRMINGHAM
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-06-01 至 2006-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7106649
• 关键词: human population genetics; meeting /conference /symposium; quantitative trait loci; statistics /biometry; travel

DESCRIPTION (provided by applicant): Obesity is associated with diseases such as diabetes and heart disease and with decreased longevity. This might suggest that, among obese individuals, weight loss will increase longevity, but this has yet to be demonstrated. Most epidemiologic studies find that weight loss predicts decreased longevity. However, an emerging body of research suggests that, when analyses are confined to obese individuals who profess an intention to lose weight, subsequent weight loss is associated with no harmful effect and perhaps a very modest decrease in mortality rate. We hypothesize that this very modest (at best) beneficial association of weight loss with reduced mortality rate among people who intend to lose weight results from the fact that, even among people who intend to lose weight, subsequent weight change is a mixture of intentional weight loss (IWL) and unintentional weight loss (UWL). The UWL may have opposing effects to IWL, thereby canceling out beneficial effects of IWL that may exist. Unfortunately, for any individual, we cannot directly observe how much of their weight change was due to their intention and how much was due to factors beyond their intention. This makes it impossible to directly estimate effects of IWL in epidemiologic studies or, for that matter, in randomized clinical trials and even animal studies of caloric restriction and aging. We have developed a novel statistical method that can place plausible boundaries around the effects of IWL on mortality rate (or any other measurable outcome). Preliminary studies suggest that the actual effect of IWL on mortality rate may be strongly beneficial. Here, we propose to expand our method from its current incarnation in ordinary least squares to a Cox-regression context to facilitate application to a broader range of circumstances. Moreover, we propose expanding the method to allow for calculation of confidence intervals and standard errors, allowing for non-linearity in relationships, tightening the plausible boundaries of estimated effects, rigorously evaluating the properties of the method by simulation studies, and applying the methods to data from a longevity study of experimental organisms and a human epidemiologic study. Our proposed research not only has value in and of itself, but can add value to many studies of,weight loss in humans and caloric restriction in experimental models, thereby increasing the value of NIH s substantial ongoing investment in such studies.

描述（由申请人提供）： 肥胖与糖尿病和心脏病等疾病以及寿命缩短有关。这可能表明，在肥胖者中，减肥会延长寿命，但这尚未得到证实。大多数流行病学研究发现，体重减轻预示寿命缩短。然而，一项新兴研究表明，当分析仅限于声称有意减肥的肥胖个体时，随后的体重减轻不会产生有害影响，而且死亡率可能会略有下降。我们假设，对于打算减肥的人来说，减肥与死亡率降低之间这种非常适度的（充其量是）有益的关联是由于以下事实：即使是打算减肥的人，随后的体重变化也是有意减肥的混合体。体重减轻（IWL）和无意识体重减轻（UWL）。 UWL 可能与 IWL 产生相反的影响，从而抵消 IWL 可能存在的有益影响。不幸的是，对于任何个人来说，我们无法直接观察到他们的体重变化有多少是由于他们的意图造成的，有多少是由于他们意图之外的因素造成的。这使得不可能在流行病学研究中直接估计 IWL 的影响，或者在随机临床试验中甚至在热量限制和衰老的动物研究中直接估计 IWL 的影响。我们开发了一种新颖的统计方法，可以为 IWL 对死亡率（或任何其他可测量结果）的影响设定合理的界限。初步研究表明，IWL 对死亡率的实际影响可能是非常有益的。在这里，我们建议将我们的方法从当前的普通最小二乘法扩展到 Cox 回归环境，以方便应用于更广泛的情况。此外，我们建议扩展该方法以允许计算置信区间和标准误差，允许关系中的非线性，收紧估计效果的合理边界，通过模拟研究严格评估该方法的属性，并将该方法应用于来自实验生物体寿命研究和人类流行病学研究的数据。我们提出的研究不仅本身具有价值，而且可以为人类减肥和实验模型中热量限制的许多研究增加价值，从而增加 NIH 在此类研究中持续大量投资的价值。