Prospective association between an obesogenic dietary pattern in early adolescence and metabolomics derived and traditional cardiometabolic risk scores in adolescents and young adults from the ALSPAC cohort.

IF 3.9 2区 医学 Q2 NUTRITION & DIETETICS
Eduard Martínez Solsona, Laura Johnson, Kate Northstone, Genevieve Buckland
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引用次数: 0

Abstract

Background: Dietary intake during early life may be a modifying factor for cardiometabolic risk (CMR). Metabolomic profiling may enable more precise identification of CMR in adolescence than traditional CMR scores. We aim to assess and compare the prospective associations between an obesogenic dietary pattern (DP) score at age 13 years with a novel vs. traditional CMR score in adolescence and young adulthood in the Avon Longitudinal Study of Parents and Children (ALSPAC).

Methods: Study participants were ALSPAC children with diet diary data at age 13. The obesogenic DP z-score, characterized by high energy-density, high % of energy from total fat and free sugars, and low fibre density, was previously derived using reduced rank regression. CMR scores were calculated by combining novel metabolites or traditional risk factors (fat mass index, insulin resistance, mean arterial blood pressure, triacylglycerol, HDL and LDL cholesterol) at age 15 (n = 1808), 17 (n = 1629), and 24 years (n = 1760). Multivariable linear regression models estimated associations of DP z-score with log-transformed CMR z-scores.

Results: Compared to the lowest tertile, the highest DP z-score tertile at age 13 was associated with an increase in the metabolomics CMR z-score at age 15 (β = 0.20, 95% CI 0.09, 0.32, p trend < 0.001) and at age 17 (β = 0.22, 95% CI 0.10, 0.34, p trend < 0.001), and with the traditional CMR z-score at age 15 (β = 0.15, 95% CI 0.05, 0.24, p trend 0.020). There was no evidence of an association at age 17 for the traditional CMR z-score (β = 0.07, 95% CI -0.03, 0.16, p trend 0.137) or for both scores at age 24.

Conclusions: An obesogenic DP was associated with greater CMR in adolescents. Stronger associations were observed with a novel metabolite CMR score compared to traditional risk factors. There may be benefits from modifying diet during adolescence for CMR health, which should be prioritized for further research in trials.

Abstract Image

Abstract Image

青少年早期致胖饮食模式与ALSPAC队列中青少年和年轻人的代谢组学衍生和传统心脏代谢风险评分之间的前瞻性关联
背景:生命早期的饮食摄入可能是心血管代谢风险(CMR)的一个调节因素。代谢组学分析可以比传统的CMR评分更准确地识别青少年的CMR。我们的目的是评估和比较13岁时的致肥性饮食模式(DP)评分与青少年和青年期的新型CMR评分与传统CMR评分之间的前瞻性关联。方法:研究对象为13岁时有饮食日记资料的ALSPAC儿童。致肥性DP z-score的特征是高能量密度,总脂肪和游离糖的能量百分比高,纤维密度低,先前使用降秩回归得出。CMR评分是通过结合15岁(n = 1808)、17岁(n = 1629)和24岁(n = 1760)时的新代谢物或传统危险因素(脂肪质量指数、胰岛素抵抗、平均动脉血压、甘油三酯、高密度脂蛋白和低密度脂蛋白胆固醇)来计算的。多变量线性回归模型估计DP z-score与log-transform CMR z-score的关联。结果:与最低分位数相比,13岁时DP z评分最高的分位数与15岁时代谢组学CMR z评分的增加相关(β = 0.20, 95% CI 0.09, 0.32, p趋势)。结论:肥胖性DP与青少年较高的CMR相关。与传统的危险因素相比,新的代谢物CMR评分观察到更强的相关性。在青春期调整饮食可能对CMR健康有好处,这应该优先用于进一步的试验研究。
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来源期刊
Nutrition & Metabolism
Nutrition & Metabolism 医学-营养学
CiteScore
8.40
自引率
0.00%
发文量
78
审稿时长
4-8 weeks
期刊介绍: Nutrition & Metabolism publishes studies with a clear focus on nutrition and metabolism with applications ranging from nutrition needs, exercise physiology, clinical and population studies, as well as the underlying mechanisms in these aspects. The areas of interest for Nutrition & Metabolism encompass studies in molecular nutrition in the context of obesity, diabetes, lipedemias, metabolic syndrome and exercise physiology. Manuscripts related to molecular, cellular and human metabolism, nutrient sensing and nutrient–gene interactions are also in interest, as are submissions that have employed new and innovative strategies like metabolomics/lipidomics or other omic-based biomarkers to predict nutritional status and metabolic diseases. Key areas we wish to encourage submissions from include: -how diet and specific nutrients interact with genes, proteins or metabolites to influence metabolic phenotypes and disease outcomes; -the role of epigenetic factors and the microbiome in the pathogenesis of metabolic diseases and their influence on metabolic responses to diet and food components; -how diet and other environmental factors affect epigenetics and microbiota; the extent to which genetic and nongenetic factors modify personal metabolic responses to diet and food compositions and the mechanisms involved; -how specific biologic networks and nutrient sensing mechanisms attribute to metabolic variability.
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