Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
Leiden Computational Biology Center, Leiden, The Netherlands.
FASEB J. 2022 Nov;36(11):e22578. doi: 10.1096/fj.202201037R.
The response to lifestyle intervention studies is often heterogeneous, especially in older adults. Subtle responses that may represent a health gain for individuals are not always detected by classical health variables, stressing the need for novel biomarkers that detect intermediate changes in metabolic, inflammatory, and immunity-related health. Here, our aim was to develop and validate a molecular multivariate biomarker maximally sensitive to the individual effect of a lifestyle intervention; the Personalized Lifestyle Intervention Status (PLIS). We used H-NMR fasting blood metabolite measurements from before and after the 13-week combined physical and nutritional Growing Old TOgether (GOTO) lifestyle intervention study in combination with a fivefold cross-validation and a bootstrapping method to train a separate PLIS score for men and women. The PLIS scores consisted of 14 and four metabolites for females and males, respectively. Performance of the PLIS score in tracking health gain was illustrated by association of the sex-specific PLIS scores with several classical metabolic health markers, such as BMI, trunk fat%, fasting HDL cholesterol, and fasting insulin, the primary outcome of the GOTO study. We also showed that the baseline PLIS score indicated which participants respond positively to the intervention. Finally, we explored PLIS in an independent physical activity lifestyle intervention study, showing similar, albeit remarkably weaker, associations of PLIS with classical metabolic health markers. To conclude, we found that the sex-specific PLIS score was able to track the individual short-term metabolic health gain of the GOTO lifestyle intervention study. The methodology used to train the PLIS score potentially provides a useful instrument to track personal responses and predict the participant's health benefit in lifestyle interventions similar to the GOTO study.
生活方式干预研究的反应往往是异质的，尤其是在老年人中。个体可能代表健康增益的微妙反应并不总是被经典的健康变量所检测到，这强调了需要新的生物标志物来检测与代谢、炎症和免疫相关的健康的中间变化。在这里，我们的目的是开发和验证一种对生活方式干预个体效应最敏感的分子多变量生物标志物；个人生活方式干预状态（PLIS）。我们使用了 H-NMR 空腹血液代谢物测量值，这些测量值来自于 13 周的综合身体和营养 Growing Old TOgether（GOTO）生活方式干预研究前后，并结合五倍交叉验证和自举方法，为男性和女性分别训练单独的 PLIS 评分。PLIS 评分由女性和男性的 14 和 4 种代谢物组成。PLIS 评分在跟踪健康收益方面的性能通过与几种经典代谢健康标志物的关联来说明，例如 BMI、躯干脂肪百分比、空腹 HDL 胆固醇和空腹胰岛素，这是 GOTO 研究的主要结果。我们还表明，基线 PLIS 评分表明哪些参与者对干预有积极的反应。最后，我们在一项独立的体育活动生活方式干预研究中探索了 PLIS，结果表明 PLIS 与经典代谢健康标志物的关联相似，尽管强度明显较弱。总之，我们发现特定于性别的 PLIS 评分能够跟踪 GOTO 生活方式干预研究中个体的短期代谢健康收益。用于训练 PLIS 评分的方法可能提供了一种有用的工具，可以跟踪个人反应并预测参与者在类似于 GOTO 研究的生活方式干预中的健康获益。
