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有关，也与寿命缩短有关。这可能表明，在肥胖者中，体重减轻将延长寿命，但这一点尚未得到证实。大多数流行病学研究发现，体重减轻预示着寿命的缩短。然而，一项新兴的研究表明，当分析仅限于声称有减肥意图的肥胖者时，随后的减肥与有害影响无关，而且死亡率可能会非常温和地下降。我们假设，在打算减肥的人中，这种非常温和(充其量)有益的减肥与降低死亡率之间的关联是因为，即使在打算减肥的人中，随后的体重变化也是有意减肥(IWL)和无意减肥(UWL)的混合体。UWL可能具有与IWL相反的影响，从而抵消了可能存在的IWL的有益影响。不幸的是，对于任何一个人来说，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，有多少是由于他们意图之外的因素。这使得在流行病学研究中，或在随机临床试验中，甚至在限制卡路里和衰老的动物研究中，不可能直接估计IWL的效果。我们已经开发了一种新的统计方法，可以围绕IWL对死亡率(或任何其他可测量的结果)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目前在普通最小二乘中的体现扩展到Cox回归的背景下，以便于在更广泛的情况下应用。此外，我们建议扩展该方法，以允许计算可信区间和标准误差，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性质，并将该方法应用于实验生物体寿命研究和人类流行病学研究的数据。我们建议的研究不仅本身有价值，而且可以为许多关于人体减肥和实验模型热量限制的研究增加价值，从而增加美国国立卫生研究院S对此类研究的大量持续投资。