In:
Circulation, Ovid Technologies (Wolters Kluwer Health), Vol. 146, No. Suppl_1 ( 2022-11-08)
Abstract:
Introduction: Although exercise training is known to alter body composition, the molecular biomarkers and mechanisms related to these changes have not been fully elucidated. The purpose of this study was to examine the associations between plasma proteins and body composition traits before and after exercise training. Methods: Measurements were taken before and after 20 weeks of standardized, endurance training in self-identified Black and White adults of the HERITAGE Family Study (n=647). Plasma proteins were measured using an affinity-based platform (n=4979 aptamers). 11 body composition traits were measured using underwater weighing, CT scans, and anthropometry: BMI, body surface area, fat mass, fat free mass, %fat, waist circumference, waist-to-hip ratio, body weight, and abdominal visceral, subcutaneous, and total fat. Linear mixed models were used to test the association between plasma proteins and each trait at baseline and in response to training with full covariate adjustment ( Table 1 ). Significance was set to FDR 〈 0.05. Results: On average, subjects were [mean and (SD)] 35 (14) years old, 33% Black, 54% female, and had BMI 26.2 (5.2) kg/m 2 . The number of significant associations between proteins and traits at baseline and in response to exercise training ranged from 645-1714 and 0-42, respectively ( Table 1 ). While leptin was among the top associated proteins at both time points for almost all traits, our analysis revealed many novel associations between changes in proteins with changes in body composition. Changes in DLK-1 significantly associated with changes in 9 of 11 traits but was not associated with baseline measures. Conclusions: Numerous plasma proteins were associated with body composition traits at baseline, with fewer associated with trait responses to training. Notably, we identified a subset of proteins uniquely associated with exercise-induced changes in body composition traits.
Type of Medium:
Online Resource
ISSN:
0009-7322
,
1524-4539
DOI:
10.1161/circ.146.suppl_1.15316
Language:
English
Publisher:
Ovid Technologies (Wolters Kluwer Health)
Publication Date:
2022
detail.hit.zdb_id:
1466401-X
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