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      Associations Between Dietary Protein Sources, Plasma BCAA and Short-Chain Acylcarnitine Levels in Adults

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          Abstract

          Elevated plasma branched-chain amino acids (BCAA) and C3 and C5 acylcarnitines (AC) levels observed in individuals with insulin resistance (IR) might be influenced by dietary protein intakes. This study explores the associations between dietary protein sources, plasma BCAA levels and C3 and C5 ACs in normal weight (NW) or overweight (OW) individuals with or without metabolic syndrome (MS). Data from 199 men and women aged 18–55 years with complete metabolite profile were analyzed. Associations between metabolic parameters, protein sources, plasma BCAA and AC levels were tested. OW/MS+ consumed significantly more animal protein ( p = 0.0388) and had higher plasma BCAA levels ( p < 0.0001) than OW/MS− or NW/MS− individuals. Plasma BCAA levels were not associated with BCAA intakes in the whole cohort, while there was a trend for an association between plasma BCAA levels and red meat or with animal protein in OW/MS+. These associations were of weak magnitude. In NW/MS− individuals, the protein sources associated with BCAA levels varied greatly with adjustment for confounders. Plasma C3 and C5 ACs were associated with plasma BCAA levels in the whole cohort ( p < 0.0001) and in subgroups based on OW and MS status. These results suggest a modest association of meat or animal protein intakes and an association of C3 and C5 ACs with plasma BCAA levels, obesity and MS.

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          Dietary factors and low-grade inflammation in relation to overweight and obesity.

          Low-grade inflammation is a characteristic of the obese state, and adipose tissue releases many inflammatory mediators. The source of these mediators within adipose tissue is not clear, but infiltrating macrophages seem to be especially important, although adipocytes themselves play a role. Obese people have higher circulating concentrations of many inflammatory markers than lean people do, and these are believed to play a role in causing insulin resistance and other metabolic disturbances. Blood concentrations of inflammatory markers are lowered following weight loss. In the hours following the consumption of a meal, there is an elevation in the concentrations of inflammatory mediators in the bloodstream, which is exaggerated in obese subjects and in type 2 diabetics. Both high-glucose and high-fat meals may induce postprandial inflammation, and this is exaggerated by a high meal content of advanced glycation end products (AGE) and partly ablated by inclusion of certain antioxidants or antioxidant-containing foods within the meal. Healthy eating patterns are associated with lower circulating concentrations of inflammatory markers. Among the components of a healthy diet, whole grains, vegetables and fruits, and fish are all associated with lower inflammation. AGE are associated with enhanced oxidative stress and inflammation. SFA and trans-MUFA are pro-inflammatory, while PUFA, especially long-chain n-3 PUFA, are anti-inflammatory. Hyperglycaemia induces both postprandial and chronic low-grade inflammation. Vitamin C, vitamin E and carotenoids decrease the circulating concentrations of inflammatory markers. Potential mechanisms are described and research gaps, which limit our understanding of the interaction between diet and postprandial and chronic low-grade inflammation, are identified.
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            Amino acid signalling upstream of mTOR.

            Mammalian target of rapamycin (mTOR) is a conserved Ser/Thr kinase that is part of mTOR complex 1 (mTORC1), a master regulator that couples amino acid availability to cell growth and autophagy. Multiple cues modulate mTORC1 activity, such as growth factors, stress, energy status and amino acids. Although amino acids are key environmental stimuli, exactly how they are sensed and how they activate mTORC1 is not fully understood. Recently, a model has emerged whereby mTORC1 activation occurs at the lysosome and is mediated through an amino acid sensing cascade involving RAG GTPases, Ragulator and vacuolar H(+)-ATPase (v-ATPase).
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              Red meat consumption and risk of type 2 diabetes: 3 cohorts of US adults and an updated meta-analysis.

              The relation between consumption of different types of red meats and risk of type 2 diabetes (T2D) remains uncertain. We evaluated the association between unprocessed and processed red meat consumption and incident T2D in US adults. We followed 37,083 men in the Health Professionals Follow-Up Study (1986-2006), 79,570 women in the Nurses' Health Study I (1980-2008), and 87,504 women in the Nurses' Health Study II (1991-2005). Diet was assessed by validated food-frequency questionnaires, and data were updated every 4 y. Incident T2D was confirmed by a validated supplementary questionnaire. During 4,033,322 person-years of follow-up, we documented 13,759 incident T2D cases. After adjustment for age, BMI, and other lifestyle and dietary risk factors, both unprocessed and processed red meat intakes were positively associated with T2D risk in each cohort (all P-trend <0.001). The pooled HRs (95% CIs) for a one serving/d increase in unprocessed, processed, and total red meat consumption were 1.12 (1.08, 1.16), 1.32 (1.25, 1.40), and 1.14 (1.10, 1.18), respectively. The results were confirmed by a meta-analysis (442,101 participants and 28,228 diabetes cases): the RRs (95% CIs) were 1.19 (1.04, 1.37) and 1.51 (1.25, 1.83) for 100 g unprocessed red meat/d and for 50 g processed red meat/d, respectively. We estimated that substitutions of one serving of nuts, low-fat dairy, and whole grains per day for one serving of red meat per day were associated with a 16-35% lower risk of T2D. Our results suggest that red meat consumption, particularly processed red meat, is associated with an increased risk of T2D.
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                Author and article information

                Journal
                Nutrients
                Nutrients
                nutrients
                Nutrients
                MDPI
                2072-6643
                15 January 2019
                January 2019
                : 11
                : 1
                : 173
                Affiliations
                [1 ]Institute of Nutrition and Functional Foods (INAF), Laval University, Quebec City, QC G1V 0A6, Canada; michele.rousseau.1@ 123456ulaval.ca (M.R.); frederic.guenard@ 123456fsaa.ulaval.ca (F.G.); veronique.garneau@ 123456fsaa.ulaval.ca (V.G.); benedicte.allam-ndoul@ 123456criucpq.ulaval.ca (B.A.-N.); simone.lemieux@ 123456fsaa.ulaval.ca (S.L.); louis.perusse@ 123456kin.ulaval.ca (L.P.)
                [2 ]School of Nutrition, Laval University, Quebec City, QC G1V 0A6, Canada
                [3 ]Department of Kinesiology, Laval University, Quebec City, QC G1V 0A6, Canada
                Author notes
                [* ]Correspondence: marie-claude.vohl@ 123456fsaa.ulaval.ca ; Tel.: +1-418-656-2131 (ext. 4676)
                Author information
                https://orcid.org/0000-0002-0565-2337
                https://orcid.org/0000-0001-5734-3811
                https://orcid.org/0000-0002-7017-5848
                Article
                nutrients-11-00173
                10.3390/nu11010173
                6356602
                30650556
                792139f7-f94a-472f-a20e-b6772a8c8fa1
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 27 November 2018
                : 11 January 2019
                Categories
                Article

                Nutrition & Dietetics
                branched-chain amino acids,acylcarnitines,dietary protein sources,meat,metabolic syndrome,metabolite profiling,diet

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