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The amino acid profile of young adults is modified by sex, body mass index (BMI) and insulin resistance (IR). However, we do not know if age or the presence of specific polymorphisms in the genes of BCAT2 and BCKDH contribute to changes in the amino acid profile, especially in subjects with obesity. Therefore, we have evaluated the effect of age, the presence of IR and the polymorphisms of BCAT2 rs11548193 and BCKDH rs45500792 on the concentration of amino acids in subjects with obesity. This was a cross-sectional study conducted with 487 subjects with obesity. Participants underwent a physical examination in which their clinical history was obtained and a blood sample was taken for biochemical, hormonal, and DNA analysis. Adults <30 years old with obesity had higher levels of alanine, arginine, aspartate, histidine, leucine, lysine, methionine, phenylalanine, proline, serine and valine than adults ≥30 years old. Interestingly, regardless of age, we found that arginine, aspartate, serine decreased, while proline and tyrosine increased in the presence of IR; tyrosine and sum of branched-chain amino acids (∑BCAA) were the amino acids that increased in the presence of BCAT2 rs11548193 and BCKDH rs45500792 polymorphisms. We found that the amino acid profiles of subjects with obesity are differentially modified by age, the presence of IR, and the presence of the BCAT2 rs11548193 and BCKDH rs45500792 polymorphisms. [ABSTRACT FROM AUTHOR]

Summary Background & aims Accurate predictive equations of resting energy expenditure (REE) are crucial in devising nutritional strategies to manage overweight/obesity, especially in countries where these are highly prevalent. REE is the most common measurement used to estimate energy requirements in the nutritional context; the most accurate method of measuring REE is indirect calorimetry (IC). However, this method is costly and often rarely feasible in many clinical settings. The objective of the present study was to develop and validate a new equation for predicting REE in adults with overweight and obesity. Methods This was a cross-sectional study including 410 men and women with overweight and obesity (20–60 y). Participants were randomly assigned; the development group included 200 subjects and the validation group 210 subjects. The new predictive equation was derived using stepwise multiple linear regression analysis. The accuracy of the new equation was compared to several existing predictive equations (PEs). The accuracy rate was calculated as the percentage of subjects whose REE-PE was within ±10% of the REE-IC. REE was measured by IC and anthropometric measurements. Results One predictive equation was developed (NEQ) in which weight was the strongest predictor of REE. Compared with others predicted equations already using, the new designed equation showed the less mean bias (Kj/day): NEQ: 25.7, Valencia:129, WHO/FAO/United Nations University: 270, Mifflin-St Jeor: 308, Owen: −808, Carrasco: −1097, Korth: −36.4, Johnstone: −375, Livingstone: −315, De Lorenzo: −28.3, Lazzer: −123, Muller: −145, Huang: −399 and Bernstein: −1335. Conclusions The present equation had the highest predictive accuracy in subjects with overweight or obesity compared with the previous equations derived from different populations. Thus, these new equation can be used to assist the nutritional management of these subjects. [ABSTRACT FROM AUTHOR]