When a calorie is not just a calorie : Diet quality and timing as mediators of metabolism and healthy aging

Funding Information: We thank Dr. Yih-Woei Fridell of the National Institute on Aging for organizing the meeting, as well as the NIA Division of Aging Biology for their support. We thank Dr. Gino Cortopassi for his edits and suggestions. The figures were created with BioRender.com. The Mihaylova lab is supported in part by the NIA (R00AG054760), Office of the NIH Director (DP2CA271361), the American Federation for Aging Research, the V Foundation, Pew Biomedical Scholar award, and startup funds from the Ohio State University. The Delibegovic lab is funded by the British Heart Foundation, Diabetes UK, BBSRC, NHS Grampian, Tenovus Scotland, and the Development Trust (University of Aberdeen). J.J.R. is supported by NIA PO1AG062817, R21AG064290, and R21AG071156. Research support for J.B. was from NIH National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) grants R01DK127800, R01DK113011, R01DK090625, and R01DK050203 and the National Institute on Aging (NIA) grants R01AG065988 and P01AG011412, as well as the University of Chicago Diabetes Research and Training Center grant P30DK020595. This work was supported by NIH grants AG065992 to G.M. and AG068550 to G.M. and S.P. as well as UAB Startup funds 3123226 and 3123227 to G.M. R.S. is supported by NIH grants RF1AG043517, R01AG065985, R01DK123327, R56AG074568, and P01AG031782. Z.C. is primarily funded by The Welch Foundation (AU-1731-20190330) and NIH/NIA (R01AG065984, R56AG063746, RF1AG061901, and R56AG076144). A.C. is supported by NIA grant R01AG065993. W.W.J. is supported by the NIH (R01DC020031). M.S.-H. is supported by NIH R01 R35GM127049, R01 AG045842, and R21 NS122366. The research in the Dixit lab was supported in part by NIH grants AG031797, AG045712, P01AG051459, AR070811, AG076782, AG073969, and AG068863 and Cure Alzheimer's Fund (CAF). A.E.T.-M. is supported by the NIH/NIA (AG075059 and AG058630), NIAMS (AR071133), NHLBI (HL153460), pilot and feasibility funds from the NIDDK-funded UAB Nutrition Obesity Research Center (DK056336) and the NIA-funded UAB Nathan Shock Center (AG050886), and startup funds from UAB. J.A.M. is supported by the Intramural Research Program, NIA, NIH. The Panda lab is supported by the NIH (R01CA236352, R01CA258221, RF1AG068550, and P30CA014195), the Wu Tsai Human Performance Alliance, and the Joe and Clara Tsai Foundation. The Lamming lab is supported in part by the NIA (AG056771, AG062328, AG061635, and AG081482), the NIDDK (DK125859), startup funds from UW-Madison, and the U.S. Department of Veterans Affairs (I01-BX004031), and this work was supported using facilities and resources from the William S. Middleton Memorial Veterans Hospital. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. This work does not represent the views of the Department of Veterans Affairs or the United States Government. D.W.L. has received funding from, and is a scientific advisory board member of, Aeovian Pharmaceuticals, which seeks to develop novel, selective mTOR inhibitors for the treatment of various diseases. S.P. is the author of the books The Circadian Code and The Circadian Diabetes Code. Funding Information: We thank Dr. Yih-Woei Fridell of the National Institute on Aging for organizing the meeting, as well as the NIA Division of Aging Biology for their support. We thank Dr. Gino Cortopassi for his edits and suggestions. The figures were created with BioRender.com . The Mihaylova lab is supported in part by the NIA ( R00AG054760 ), Office of the NIH Director ( DP2CA271361 ), the American Federation for Aging Research , the V Foundation , Pew Biomedical Scholar award, and startup funds from the Ohio State University . The Delibegovic lab is funded by the British Heart Foundation , Diabetes UK , BBSRC , NHS Grampian , Tenovus Scotland , and the Development Trust ( University of Aberdeen ). J.J.R. is supported by NIA PO1AG062817 , R21AG064290 , and R21AG071156 . Research support for J.B. was from NIH National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) grants R01DK127800 , R01DK113011 , R01DK090625 , and R01DK050203 and the National Institute on Aging (NIA) grants R01AG065988 and P01AG011412 , as well as the University of Chicago Diabetes Research and Training Center grant P30DK020595 . This work was supported by NIH grants AG065992 to G.M. and AG068550 to G.M. and S.P., as well as UAB Startup funds 3123226 and 3123227 to G.M. R.S. is supported by NIH grants RF1AG043517 , R01AG065985 , R01DK123327 , R56AG074568 , and P01AG031782 . Z.C. is primarily funded by The Welch Foundation ( AU-1731-20190330 ) and NIH/NIA ( R01AG065984 , R56AG063746 , RF1AG061901 , and R56AG076144 ). A.C. is supported by NIA grant R01AG065993 . W.W.J. is supported by the NIH ( R01DC020031 ). M.S.-H. is supported by NIH R01 R35GM127049 , R01 AG045842 , and R21 NS122366 . The research in the Dixit lab was supported in part by NIH grants AG031797 , AG045712 , P01AG051459 , AR070811 , AG076782 , AG073969 , and AG068863 and Cure Alzheimer's Fund (CAF). A.E.T.-M. is supported by the NIH/NIA ( AG075059 and AG058630 ), NIAMS ( AR071133 ), NHLBI ( HL153460 ), pilot and feasibility funds from the NIDDK -funded UAB Nutrition Obesity Research Center ( DK056336 ) and the NIA -funded UAB Nathan Shock Center ( AG050886 ), and startup funds from UAB . J.A.M. is supported by the Intramural Research Program, NIA, NIH . The Panda lab is supported by the NIH ( R01CA236352 , R01CA258221 , RF1AG068550 , and P30CA014195 ), the Wu Tsai Human Performance Alliance , and the Joe and Clara Tsai Foundation . The Lamming lab is supported in part by the NIA ( AG056771 , AG062328 , AG061635 , and AG081482 ), the NIDDK ( DK125859 ), startup funds from UW-Madison , and the U.S. Department of Veterans Affairs ( I01-BX004031 ), and this work was supported using facilities and resources from the William S. Middleton Memorial Veterans Hospital. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. This work does not represent the views of the Department of Veterans Affairs or the United States Government.Peer reviewedPostprin

Genetic variation in genes regulating skeletal muscle regeneration and tissue remodelling associated with weight loss in chronic obstructive pulmonary disease

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is the third leading cause of death globally. COPD patients with cachexia or weight loss have increased risk of death independent of body mass index (BMI) and lung function. We tested the hypothesis genetic variation is associated with weight loss in COPD using a genome-wide association study approach. METHODS: Participants with COPD (N = 4308) from three studies (COPDGene, ECLIPSE, and SPIROMICS) were analysed. Discovery analyses were performed in COPDGene with replication in SPIROMICS and ECLIPSE. In COPDGene, weight loss was defined as self-reported unintentional weight loss > 5% in the past year or low BMI (BMI < 20 kg/m2). In ECLIPSE and SPIROMICS, weight loss was calculated using available longitudinal visits. Stratified analyses were performed among African American (AA) and Non-Hispanic White (NHW) participants with COPD. Single variant and gene-based analyses were performed adjusting for confounders. Fine mapping was performed using a Bayesian approach integrating genetic association results with linkage disequilibrium and functional annotation. Significant gene networks were identified by integrating genetic regions associated with weight loss with skeletal muscle protein–protein interaction (PPI) data. RESULTS: At the single variant level, only the rs35368512 variant, intergenic to GRXCR1 and LINC02383, was associated with weight loss (odds ratio = 3.6, 95% confidence interval = 2.3–5.6, P = 3.2 × 10−8) among AA COPD participants in COPDGene. At the gene level in COPDGene, EFNA2 and BAIAP2 were significantly associated with weight loss in AA and NHW COPD participants, respectively. The EFNA2 association replicated among AA from SPIROMICS (P = 0.0014), whereas the BAIAP2 association replicated in NHW from ECLIPSE (P = 0.025). The EFNA2 gene encodes the membrane-bound protein ephrin-A2 involved in the regulation of developmental processes and adult tissue homeostasis such as skeletal muscle. The BAIAP2 gene encodes the insulin-responsive protein of mass 53 kD (IRSp53), a negative regulator of myogenic differentiation. Integration of the gene-based findings participants with PPI data revealed networks of genes involved in pathways such as Rho and synapse signalling. CONCLUSIONS: The EFNA2 and BAIAP2 genes were significantly associated with weight loss in COPD participants. Collectively, the integrative network analyses indicated genetic variation associated with weight loss in COPD may influence skeletal muscle regeneration and tissue remodelling

Power training and postmenopausal hormone therapy affect transcriptional control of specific co-regulated gene clusters in skeletal muscle

At the moment, there is no clear molecular explanation for the steeper decline in muscle performance after menopause or the mechanisms of counteractive treatments. The goal of this genome-wide study was to identify the genes and gene clusters through which power training (PT) comprising jumping activities or estrogen containing hormone replacement therapy (HRT) may affect skeletal muscle properties after menopause. We used musculus vastus lateralis samples from early stage postmenopausal (50–57 years old) women participating in a yearlong randomized double-blind placebo-controlled trial with PT and HRT interventions. Using microarray platform with over 24,000 probes, we identified 665 differentially expressed genes. The hierarchical clustering method was used to assort the genes. Additionally, enrichment analysis of gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways was carried out to clarify whether assorted gene clusters are enriched with particular functional categories. The analysis revealed transcriptional regulation of 49 GO/KEGG categories. PT upregulated transcription in “response to contraction”—category revealing novel candidate genes for contraction-related regulation of muscle function while HRT upregulated gene expression related to functionality of mitochondria. Moreover, several functional categories tightly related to muscle energy metabolism, development, and function were affected regardless of the treatment. Our results emphasize that during the early stages of the postmenopause, muscle properties are under transcriptional modulation, which both PT and HRT partially counteract leading to preservation of muscle power and potentially reducing the risk for aging-related muscle weakness. More specifically, PT and HRT may function through improving energy metabolism, response to contraction as well as by preserving functionality of the mitochondria

EFSA Panel on Dietetic Products, Nutrition and Allergies (NDA); Scientific Opinion on Dietary Reference Values for protein

This opinion of the EFSA Panel on Dietetic Products, Nutrition and Allergies (NDA) deals with the setting of Dietary Reference Values (DRVs) for protein. The Panel concludes that a Population Reference Intake (PRI) can be derived from nitrogen balance studies. Several health outcomes possibly associated with protein intake were also considered but data were found to be insufficient to establish DRVs. For healthy adults of both sexes, the average requirement (AR) is 0.66 g protein/kg body weight per day based on nitrogen balance data. Considering the 97.5th percentile of the distribution of the requirement and assuming an efficiency of utilisation of dietary protein for maintenance of 47 %, the PRI for adults of all ages was estimated to be 0.83 g protein/kg body weight per day and is applicable both to high quality protein and to protein in mixed diets. For children from six months onwards, age-dependent requirements for growth estimated from average daily rates of protein deposition and adjusted by a protein efficiency for growth of 58 % were added to the requirement for maintenance of 0.66 g/kg body weight per day. The PRI was estimated based on the average requirement plus 1.96 SD using a combined SD for growth and maintenance.For pregnancy, an intake of 1, 9 and 28 g/d in the first, second and third trimesters, respectively, is proposed in addition to the PRI for non-pregnant women. For lactation, a protein intake of 19 g/d during the first six months, and of 13 g/d after six months, is proposed in addition to the PRI for non-lactating women. Data are insufficient to establish a Tolerable Upper Intake Level (UL) for protein. Intakes up to twice the PRI are regularly consumed from mixed diets by some physically active and healthy adults in Europe and are considered safe

Genetic variation and exercise-induced muscle damage: implications for athletic performance, injury and ageing.

Prolonged unaccustomed exercise involving muscle lengthening (eccentric) actions can result in ultrastructural muscle disruption, impaired excitation-contraction coupling, inflammation and muscle protein degradation. This process is associated with delayed onset muscle soreness and is referred to as exercise-induced muscle damage. Although a certain amount of muscle damage may be necessary for adaptation to occur, excessive damage or inadequate recovery from exercise-induced muscle damage can increase injury risk, particularly in older individuals, who experience more damage and require longer to recover from muscle damaging exercise than younger adults. Furthermore, it is apparent that inter-individual variation exists in the response to exercise-induced muscle damage, and there is evidence that genetic variability may play a key role. Although this area of research is in its infancy, certain gene variations, or polymorphisms have been associated with exercise-induced muscle damage (i.e. individuals with certain genotypes experience greater muscle damage, and require longer recovery, following strenuous exercise). These polymorphisms include ACTN3 (R577X, rs1815739), TNF (-308 G>A, rs1800629), IL6 (-174 G>C, rs1800795), and IGF2 (ApaI, 17200 G>A, rs680). Knowing how someone is likely to respond to a particular type of exercise could help coaches/practitioners individualise the exercise training of their athletes/patients, thus maximising recovery and adaptation, while reducing overload-associated injury risk. The purpose of this review is to provide a critical analysis of the literature concerning gene polymorphisms associated with exercise-induced muscle damage, both in young and older individuals, and to highlight the potential mechanisms underpinning these associations, thus providing a better understanding of exercise-induced muscle damage