Identification of a Circulating Amino Acid Signature in Frail Older Persons with Type 2 Diabetes Mellitus: Results from the Metabofrail Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Population
2.2. Blood Collection and Determination of Serum Concentrations of Amino Acids and Derivatives
2.3. Statistical Analysis
2.4. Partial Least Squares-Discriminant Analysis and Double Cross-Validation Procedures
3. Results
3.1. Study Population
3.2. Identification of Circulating Amino Acid Profiles
4. Discussion
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Sinclair, A.; Dunning, T.; Rodriguez-Mañas, L. Diabetes in older people: New insights and remaining challenges. Lancet Diabetes Endocrinol. 2015, 3, 275–285. [Google Scholar] [CrossRef]
- Cho, N.H.; Shaw, J.E.; Karuranga, S.; Huang, Y.; da Rocha Fernandes, J.D.; Ohlrogge, A.W.; Malanda, B. IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes Res. Clin. Pract. 2018, 138, 271–281. [Google Scholar] [CrossRef] [PubMed]
- GBD 2017 Disease and Injury Incidence and Prevalence Collaborators; James, S.L.; Abate, D.; Abate, K.H.; Abay, S.M.; Abbafati, C.; Abbasi, N.; Abbastabar, H.; Abd-Allah, F.; Abdela, J.; et al. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018, 392, 1789–1858. [Google Scholar] [CrossRef] [Green Version]
- Kalyani, R.R.; Golden, S.H.; Cefalu, W.T. Diabetes and Aging: Unique Considerations and Goals of Care. Diabetes Care 2017, 40, 440–443. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Cesari, M.; Calvani, R.; Marzetti, E. Frailty in Older Persons. Clin. Geriatr. Med. 2017, 33, 293–303. [Google Scholar] [CrossRef] [PubMed]
- Clegg, A.; Young, J.; Iliffe, S.; Rikkert, M.O.; Rockwood, K. Frailty in elderly people. Lancet 2013, 381, 752–762. [Google Scholar] [CrossRef] [Green Version]
- El Assar, M.; Laosa, O.; Rodríguez Mañas, L. Diabetes and frailty. Curr. Opin. Clin. Nutr. Metab. Care 2019, 22, 52–57. [Google Scholar] [CrossRef]
- LeRoith, D.; Biessels, G.J.; Braithwaite, S.S.; Casanueva, F.F.; Draznin, B.; Halter, J.B.; Hirsch, I.B.; McDonnell, M.E.; Molitch, M.E.; Murad, M.H.; et al. Treatment of Diabetes in Older Adults: An Endocrine Society* Clinical Practice Guideline. J. Clin. Endocrinol. Metab. 2019, 104, 1520–1574. [Google Scholar] [CrossRef] [Green Version]
- Sinclair, A.J.; Rodriguez-Mañas, L. Diabetes and Frailty: Two Converging Conditions? Can. J. Diabetes 2016, 40, 77–83. [Google Scholar] [CrossRef] [Green Version]
- Larsson, L.; Degens, H.; Li, M.; Salviati, L.; Lee, Y., II; Thompson, W.; Kirkland, J.L.; Sandri, M. Sarcopenia: Aging-Related Loss of Muscle Mass and Function. Physiol. Rev. 2019, 99, 427–511. [Google Scholar] [CrossRef]
- Guerrero, N.; Bunout, D.; Hirsch, S.; Barrera, G.; Leiva, L.; Henríquez, S.; De la Maza, M.P. Premature loss of muscle mass and function in type 2 diabetes. Diabetes Res. Clin. Pract. 2016, 117, 32–38. [Google Scholar] [CrossRef] [PubMed]
- Park, S.W.; Goodpaster, B.H.; Strotmeyer, E.S.; Kuller, L.H.; Broudeau, R.; Kammerer, C.; de Rekeneire, N.; Harris, T.B.; Schwartz, A.V.; Tylavsky, F.A.; et al. Accelerated Loss of Skeletal Muscle Strength in Older Adults With Type 2 Diabetes: The Health, Aging, and Body Composition Study. Diabetes Care 2007, 30, 1507–1512. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Landi, F.; Calvani, R.; Cesari, M.; Tosato, M.; Martone, A.M.; Bernabei, R.; Onder, G.; Marzetti, E. Sarcopenia as the Biological Substrate of Physical Frailty. Clin. Geriatr. Med. 2015, 31, 367–374. [Google Scholar] [CrossRef] [PubMed]
- Calvani, R.; Marini, F.; Cesari, M.; Tosato, M.; Anker, S.D.; von Haehling, S.; Miller, R.R.; Bernabei, R.; Landi, F.; Marzetti, E.; et al. Biomarkers for physical frailty and sarcopenia: State of the science and future developments. J. Cachexia. Sarcopenia Muscle 2015, 6, 278–286. [Google Scholar] [CrossRef] [PubMed]
- Picca, A.; Coelho-Junior, H.J.; Cesari, M.; Marini, F.; Miccheli, A.; Gervasoni, J.; Bossola, M.; Landi, F.; Bernabei, R.; Marzetti, E.; et al. The metabolomics side of frailty: Toward personalized medicine for the aged. Exp. Gerontol. 2019, 126, 110692. [Google Scholar] [CrossRef] [PubMed]
- Calvani, R.; Rodriguez-Mañas, L.; Picca, A.; Marini, F.; Biancolillo, A.; Laosa, O.; Pedraza, L.; Gervasoni, J.; Primiano, A.; Miccheli, A.; et al. The “Metabolic biomarkers of frailty in older people with type 2 diabetes mellitus” (MetaboFrail) study: Rationale, design and methods. Exp. Gerontol. 2020, 129, 110782. [Google Scholar] [CrossRef] [PubMed]
- Calvani, R.; Picca, A.; Marini, F.; Biancolillo, A.; Gervasoni, J.; Persichilli, S.; Primiano, A.; Coelho-Junior, H.; Bossola, M.; Urbani, A.; et al. A Distinct Pattern of Circulating Amino Acids Characterizes Older Persons with Physical Frailty and Sarcopenia: Results from the BIOSPHERE Study. Nutrients 2018, 10, 1691. [Google Scholar] [CrossRef] [Green Version]
- Pasini, E.; Corsetti, G.; Aquilani, R.; Romano, C.; Picca, A.; Calvani, R.; Dioguardi, F.S. Protein-Amino Acid Metabolism Disarrangements: The Hidden Enemy of Chronic Age-Related Conditions. Nutrients 2018, 10, 391. [Google Scholar] [CrossRef] [Green Version]
- Lu, Y.; Karagounis, L.G.; Ng, T.P.; Carre, C.; Narang, V.; Wong, G.; Tan, C.T.Y.; Zin Nyunt, M.S.; Gao, Q.; Abel, B.; et al. Systemic and Metabolic Signature of Sarcopenia in Community-Dwelling Older Adults. J. Gerontol. Ser. A 2019. [Google Scholar] [CrossRef]
- Neinast, M.; Murashige, D.; Arany, Z. Branched Chain Amino Acids. Annu. Rev. Physiol. 2019, 81, 139–164. [Google Scholar] [CrossRef]
- Zhenyukh, O.; Civantos, E.; Ruiz-Ortega, M.; Sánchez, M.S.; Vázquez, C.; Peiró, C.; Egido, J.; Mas, S. High concentration of branched-chain amino acids promotes oxidative stress, inflammation and migration of human peripheral blood mononuclear cells via mTORC1 activation. Free Radic. Biol. Med. 2017, 104, 165–177. [Google Scholar] [CrossRef] [PubMed]
- Yoon, M.-S. The Emerging Role of Branched-Chain Amino Acids in Insulin Resistance and Metabolism. Nutrients 2016, 8, 405. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yang, Q.; Vijayakumar, A.; Kahn, B.B. Metabolites as regulators of insulin sensitivity and metabolism. Nat. Rev. Mol. Cell Biol. 2018, 19, 654–672. [Google Scholar] [CrossRef] [PubMed]
- Wang, T.J.; Larson, M.G.; Vasan, R.S.; Cheng, S.; Rhee, E.P.; McCabe, E.; Lewis, G.D.; Fox, C.S.; Jacques, P.F.; Fernandez, C.; et al. Metabolite profiles and the risk of developing diabetes. Nat. Med. 2011, 17, 448–453. [Google Scholar] [CrossRef] [PubMed]
- Wang-Sattler, R.; Yu, Z.; Herder, C.; Messias, A.C.; Floegel, A.; He, Y.; Heim, K.; Campillos, M.; Holzapfel, C.; Thorand, B.; et al. Novel biomarkers for pre-diabetes identified by metabolomics. Mol. Syst. Biol. 2012, 8, 615. [Google Scholar] [CrossRef] [PubMed]
- Floegel, A.; Stefan, N.; Yu, Z.; Mühlenbruch, K.; Drogan, D.; Joost, H.-G.; Fritsche, A.; Häring, H.-U.; Hrabě de Angelis, M.; Peters, A.; et al. Identification of serum metabolites associated with risk of type 2 diabetes using a targeted metabolomic approach. Diabetes 2013, 62, 639–648. [Google Scholar] [CrossRef] [Green Version]
- Chen, T.; Ni, Y.; Ma, X.; Bao, Y.; Liu, J.; Huang, F.; Hu, C.; Xie, G.; Zhao, A.; Jia, W.; et al. Branched-chain and aromatic amino acid profiles and diabetes risk in Chinese populations. Sci. Rep. 2016, 6, 20594. [Google Scholar] [CrossRef] [Green Version]
- Semba, R.D.; Gonzalez-Freire, M.; Moaddel, R.; Sun, K.; Fabbri, E.; Zhang, P.; Carlson, O.D.; Khadeer, M.; Chia, C.W.; Salem, N.; et al. Altered Plasma Amino Acids and Lipids Associated With Abnormal Glucose Metabolism and Insulin Resistance in Older Adults. J. Clin. Endocrinol. Metab. 2018, 103, 3331–3339. [Google Scholar] [CrossRef]
- Adachi, Y.; Ono, N.; Imaizumi, A.; Muramatsu, T.; Andou, T.; Shimodaira, Y.; Nagao, K.; Kageyama, Y.; Mori, M.; Noguchi, Y.; et al. Plasma Amino Acid Profile in Severely Frail Elderly Patients in Japan. Int. J. Gerontol. 2018, 12, 290–293. [Google Scholar] [CrossRef]
- Kochlik, B.; Stuetz, W.; Pérès, K.; Féart, C.; Tegner, J.; Rodriguez-Mañas, L.; Grune, T.; Weber, D. Associations of Plasma 3-Methylhistidine with Frailty Status in French Cohorts of the FRAILOMIC Initiative. J. Clin. Med. 2019, 8, 1010. [Google Scholar] [CrossRef] [Green Version]
- Lustgarten, M.S.; Price, L.L.; Chale, A.; Phillips, E.M.; Fielding, R.A. Branched chain amino acids are associated with muscle mass in functionally limited older adults. J. Gerontol. A Biol. Sci. Med. Sci. 2014, 69, 717–724. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Moaddel, R.; Fabbri, E.; Khadeer, M.A.; Carlson, O.D.; Gonzalez-Freire, M.; Zhang, P.; Semba, R.D.; Ferrucci, L. Plasma Biomarkers of Poor Muscle Quality in Older Men and Women from the Baltimore Longitudinal Study of Aging. J. Gerontol. A Biol. Sci. Med. Sci. 2016, 71, 1266–1272. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Rodríguez-Mañas, L.; Bayer, A.J.; Kelly, M.; Zeyfang, A.; Izquierdo, M.; Laosa, O.; Hardman, T.C.; Sinclair, A.J.; Moreira, S.; Cook, J.; et al. An evaluation of the effectiveness of a multi-modal intervention in frail and pre-frail older people with type 2 diabetes--the MID-Frail study: Study protocol for a randomised controlled trial. Trials 2014, 15, 34. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Rodriguez-Mañas, L.; Laosa, O.; Vellas, B.; Paolisso, G.; Topinkova, E.; Oliva-Moreno, J.; Bourdel-Marchasson, I.; Izquierdo, M.; Hood, K.; Zeyfang, A.; et al. Effectiveness of a multimodal intervention in functionally impaired older people with type 2 diabetes mellitus. J. Cachexia. Sarcopenia Muscle 2019. [Google Scholar] [CrossRef] [Green Version]
- Fried, L.P.; Tangen, C.M.; Walston, J.; Newman, A.B.; Hirsch, C.; Gottdiener, J.; Seeman, T.; Tracy, R.; Kop, W.J.; Burke, G.; et al. Frailty in older adults: Evidence for a phenotype. J. Gerontol. A Biol. Sci. Med. Sci. 2001, 56, M146–M156. [Google Scholar] [CrossRef] [PubMed]
- Folstein, M.F.; Folstein, S.E.; McHugh, P.R. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J. Psychiatr. Res. 1975, 12, 189–198. [Google Scholar] [CrossRef]
- Mahoney, F.I.; Barthel, D.W. Functional Evaluation: The barthel index. Md. State Med. J. 1965, 14, 61–65. [Google Scholar]
- Ståhle, L.; Wold, S. Partial least squares analysis with cross-validation for the two-class problem: A Monte Carlo study. J. Chemom. 1987, 1, 185–196. [Google Scholar] [CrossRef]
- Westerhuis, J.A.; Hoefsloot, H.C.J.; Smit, S.; Vis, D.J.; Smilde, A.K.; van Velzen, E.J.J.; van Duijnhoven, J.P.M.; van Dorsten, F.A. Assessment of PLSDA cross validation. Metabolomics 2008, 4, 81–89. [Google Scholar] [CrossRef] [Green Version]
- Smit, S.; van Breemen, M.J.; Hoefsloot, H.C.J.; Smilde, A.K.; Aerts, J.M.F.G.; de Koster, C.G. Assessing the statistical validity of proteomics based biomarkers. Anal. Chim. Acta 2007, 592, 210–217. [Google Scholar] [CrossRef]
- Marzetti, E.; Landi, F.; Marini, F.; Cesari, M.; Buford, T.W.; Manini, T.M.; Onder, G.; Pahor, M.; Bernabei, R.; Leeuwenburgh, C.; et al. Patterns of Circulating Inflammatory Biomarkers in Older Persons with Varying Levels of Physical Performance: A Partial Least Squares-Discriminant Analysis Approach. Front. Med. 2014, 1, 27. [Google Scholar] [CrossRef] [PubMed]
- Chen, R.; Snyder, M. Promise of Personalized Omics to Precision Medicine. Wiley Interdiscip. Rev. Syst. Biol. Med. 2013, 5, 73. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Loscalzo, J.; Barabasi, A.-L. Systems biology and the future of medicine. Wiley Interdiscip. Rev. Syst. Biol. Med. 2011, 3, 619–627. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Guijas, C.; Montenegro-Burke, J.R.; Warth, B.; Spilker, M.E.; Siuzdak, G. Metabolomics activity screening for identifying metabolites that modulate phenotype. Nat. Biotechnol. 2018, 36, 316–320. [Google Scholar] [CrossRef] [PubMed]
- Karczewski, K.J.; Snyder, M.P. Integrative omics for health and disease. Nat. Rev. Genet. 2018, 19, 299–310. [Google Scholar] [CrossRef] [PubMed]
- Wishart, D.S. Metabolomics for Investigating Physiological and Pathophysiological Processes. Physiol. Rev. 2019, 99, 1819–1875. [Google Scholar] [CrossRef] [PubMed]
- Johnson, P.; Perry, S.V. Biological activity and the 3-methylhistidine content of actin and myosin. Biochem. J. 1970, 119, 293–298. [Google Scholar] [CrossRef] [Green Version]
- Asatoor, A.M.; Armstrong, M.D. 3-methylhistidine, a component of actin. Biochem. Biophys. Res. Commun. 1967, 26, 168–174. [Google Scholar] [CrossRef]
- Sheffield-Moore, M.; Dillon, E.L.; Randolph, K.M.; Casperson, S.L.; White, G.R.; Jennings, K.; Rathmacher, J.; Schuette, S.; Janghorbani, M.; Urban, R.J.; et al. Isotopic decay of urinary or plasma 3-methylhistidine as a potential biomarker of pathologic skeletal muscle loss. J. Cachexia. Sarcopenia Muscle 2014, 5, 19–25. [Google Scholar] [CrossRef]
- Marchesini, G.; Forlani, G.; Zoli, M.; Vannini, P.; Pisi, E. Muscle protein breakdown in uncontrolled diabetes as assessed by urinary 3-methylhistidine excretion. Diabetologia 1982, 23, 456–458. [Google Scholar] [CrossRef] [Green Version]
- Wagenmakers, A.J. Protein and amino acid metabolism in human muscle. Adv. Exp. Med. Biol. 1998, 441, 307–319. [Google Scholar] [PubMed]
- Jang, C.; Hui, S.; Zeng, X.; Cowan, A.J.; Wang, L.; Chen, L.; Morscher, R.J.; Reyes, J.; Frezza, C.; Hwang, H.Y.; et al. Metabolite Exchange between Mammalian Organs Quantified in Pigs. Cell Metab. 2019, 30, 594–606.e3. [Google Scholar] [CrossRef] [PubMed]
- Gancheva, S.; Jelenik, T.; Álvarez-Hernández, E.; Roden, M. Interorgan Metabolic Crosstalk in Human Insulin Resistance. Physiol. Rev. 2018, 98, 1371–1415. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Jagoe, R.T.; Engelen, M.P.K.J. Muscle wasting and changes in muscle protein metabolism in chronic obstructive pulmonary disease. Eur. Respir. J. 2003, 22, 52s–63s. [Google Scholar] [CrossRef] [PubMed]
- Ilaiwy, A.; Quintana, M.T.; Bain, J.R.; Muehlbauer, M.J.; Brown, D.I.; Stansfield, W.E.; Willis, M.S. Cessation of biomechanical stretch model of C2C12 cells models myocyte atrophy and anaplerotic changes in metabolism using non-targeted metabolomics analysis. Int. J. Biochem. Cell Biol. 2016, 79, 80–92. [Google Scholar] [CrossRef] [Green Version]
- Lu, Y.; Wang, Y.; Liang, X.; Zou, L.; Ong, C.N.; Yuan, J.M.; Koh, W.P.; Pan, A. Serum amino acids in association with prevalent and incident type 2 diabetes in a Chinese population. Metabolites 2019, 9, 14. [Google Scholar] [CrossRef] [Green Version]
- Seibert, R.; Abbasi, F.; Hantash, F.M.; Caulfield, M.P.; Reaven, G.; Kim, S.H. Relationship between insulin resistance and amino acids in women and men. Physiol. Rep. 2015, 3, e12392. [Google Scholar] [CrossRef]
- Cheng, S.; Rhee, E.P.; Larson, M.G.; Lewis, G.D.; McCabe, E.L.; Shen, D.; Palma, M.J.; Roberts, L.D.; Dejam, A.; Souza, A.L.; et al. Metabolite profiling identifies pathways associated with metabolic risk in humans. Circulation 2012, 125, 2222–2231. [Google Scholar] [CrossRef] [Green Version]
- Wu, G.; Morris, S.M. Arginine metabolism: Nitric oxide and beyond. Biochem. J. 1998, 336, 1–17. [Google Scholar] [CrossRef]
- Mangoni, A.A.; Rodionov, R.N.; Mcevoy, M.; Zinellu, A.; Carru, C.; Sotgia, S. New horizons in arginine metabolism, ageing and chronic disease states. Age Ageing 2019, 48, 776–782. [Google Scholar] [CrossRef]
- Cao, Y.-F.; Li, J.; Zhang, Z.; Liu, J.; Sun, X.-Y.; Feng, X.-F.; Luo, H.-H.; Yang, W.; Li, S.-N.; Yang, X.; et al. Plasma Levels of Amino Acids Related to Urea Cycle and Risk of Type 2 Diabetes Mellitus in Chinese Adults. Front. Endocrinol. 2019, 10, 50. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ducker, G.S.; Rabinowitz, J.D. One-Carbon Metabolism in Health and Disease. Cell Metab. 2017, 25, 27–42. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Koutros, S.; Meyer, T.E.; Fox, S.D.; Issaq, H.J.; Veenstra, T.D.; Huang, W.Y.; Yu, K.; Albanes, D.; Chu, L.W.; Andriole, G.; et al. Prospective evaluation of serum sarcosine and risk of prostate cancer in the prostate, lung, colorectal and ovarian cancer screening trial. Carcinogenesis 2013, 34, 2281–2285. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- De Vogel, S.; Ulvik, A.; Meyer, K.; Ueland, P.M.; Nygård, O.; Vollset, S.E.; Tell, G.S.; Gregory, J.F.; Tretli, S.; Bjørge, T. Sarcosine and other metabolites along the choline oxidation pathway in relation to prostate cancer—A large nested case-control study within the JANUS cohort in Norway. Int. J. Cancer 2014, 134, 197–206. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hasokawa, M.; Shinohara, M.; Tsugawa, H.; Bamba, T.; Fukusaki, E.; Nishiumi, S.; Nishimura, K.; Yoshida, M.; Ishida, T.; Hirata, K.; et al. Identification of biomarkers of stent restenosis with serum metabolomic profiling using gas chromatography/mass spectrometry. Circ. J. 2012, 76, 1864–1873. [Google Scholar] [CrossRef] [Green Version]
- Tsai, C.H.; Huang, H.C.; Liu, B.L.; Li, C.I.; Lu, M.K.; Chen, X.; Tsai, M.C.; Yang, Y.W.; Lane, H.Y. Activation of N-methyl-D-aspartate receptor glycine site temporally ameliorates neuropsychiatric symptoms of Parkinson’s disease with dementia. Psychiatry Clin. Neurosci. 2014, 68, 692–700. [Google Scholar] [CrossRef] [Green Version]
- Walters, R.O.; Arias, E.; Diaz, A.; Burgos, E.S.; Guan, F.; Tiano, S.; Mao, K.; Green, C.L.; Qiu, Y.; Shah, H.; et al. Sarcosine Is Uniquely Modulated by Aging and Dietary Restriction in Rodents and Humans. Cell Rep. 2018, 25, 663–676. [Google Scholar] [CrossRef] [Green Version]
- Svingen, G.F.T.; Schartum-Hansen, H.; Pedersen, E.R.; Ueland, P.M.; Tell, G.S.; Mellgren, G.; Njølstad, P.R.; Seifert, R.; Strand, E.; Karlsson, T.; et al. Prospective associations of systemic and urinary choline metabolites with incident type 2 diabetes. Clin. Chem. 2016, 62, 755–765. [Google Scholar] [CrossRef] [Green Version]
- van der Veen, J.N.; Kennelly, J.P.; Wan, S.; Vance, J.E.; Vance, D.E.; Jacobs, R.L. The critical role of phosphatidylcholine and phosphatidylethanolamine metabolism in health and disease. Biochim. Biophys. Acta Biomembr. 2017, 1859, 1558–1572. [Google Scholar] [CrossRef]
- Funai, K.; Lodhi, I.J.; Spears, L.D.; Yin, L.; Song, H.; Klein, S.; Semenkovich, C.F. Skeletal muscle phospholipid metabolism regulates insulin sensitivity and contractile function. Diabetes 2016, 65, 358–370. [Google Scholar] [CrossRef] [Green Version]
- Rockenfeller, P.; Koska, M.; Pietrocola, F.; Minois, N.; Knittelfelder, O.; Sica, V.; Franz, J.; Carmona-Gutierrez, D.; Kroemer, G.; Madeo, F. Phosphatidylethanolamine positively regulates autophagy and longevity. Cell Death Differ. 2015, 22, 499–508. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Le Floc’h, N.; Otten, W.; Merlot, E. Tryptophan metabolism, from nutrition to potential therapeutic applications. Amino Acids 2011, 41, 1195–1205. [Google Scholar] [CrossRef] [PubMed]
- Marcos-Pérez, D.; Sánchez-Flores, M.; Maseda, A.; Lorenzo-López, L.; Millán-Calenti, J.C.; Strasser, B.; Gostner, J.M.; Fuchs, D.; Pásaro, E.; Valdiglesias, V.; et al. Frailty Status in Older Adults Is Related to Alterations in Indoleamine 2,3-Dioxygenase 1 and Guanosine Triphosphate Cyclohydrolase I Enzymatic Pathways. J. Am. Med. Dir. Assoc. 2017, 18, 1049–1057. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chen, T.; Zheng, X.; Ma, X.; Bao, Y.; Ni, Y.; Hu, C.; Rajani, C.; Huang, F.; Zhao, A.; Jiia, W.; et al. Tryptophan Predicts the Risk for Future Type 2 Diabetes. PLoS ONE 2016, 11, e0162192. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yu, E.; Papandreou, C.; Ruiz-Canela, M.; Guasch-Ferre, M.; Clish, C.B.; Dennis, C.; Liang, L.; Corella, D.; Fitó, M.; Razquin, C.; et al. Association of tryptophan metabolites with incident type 2 diabetes in the PREDIMED trial: A case–cohort study. Clin. Chem. 2018, 64, 1211–1220. [Google Scholar] [CrossRef]
- Huxtable, R.J. Physiological actions of taurine. Physiol. Rev. 1992, 72, 101–163. [Google Scholar] [CrossRef] [Green Version]
- Lambert, I.H.; Kristensen, D.M.; Holm, J.B.; Mortensen, O.H. Physiological role of taurine—From organism to organelle. Acta Physiol. 2015, 213, 191–212. [Google Scholar] [CrossRef]
- De Luca, G.; Calpona, P.R.; Caponetti, A.; Romano, G.; Di Benedetto, A.; Cucinotta, D.; Di Giorgio, R.M. Taurine and osmoregulation: Platelet taurine content, uptake, and release in type 2 diabetic patients. Metabolism 2001, 50, 60–64. [Google Scholar] [CrossRef]
- Franconi, F.A.; Bennardini, F.R.; Giuseppe, A.; Miceli, S.M.; Ciuti, M.; Mian, M. Plasma and platelet taurine are reduced in subjects with mellitus: Effects of taurine. Am. J. Clin. Nutr. 1995, 61, 1115–1119. [Google Scholar] [CrossRef] [Green Version]
- Ito, T.; Schaffer, S.W.; Azuma, J. The potential usefulness of taurine on diabetes mellitus and its complications. Amino Acids 2012, 42, 1529–1539. [Google Scholar] [CrossRef] [Green Version]
- Scicchitano, B.M.; Sica, G. The Beneficial Effects of Taurine to Counteract Sarcopenia. Curr. Protein Pept. Sci. 2018, 19, 673–680. [Google Scholar] [CrossRef] [PubMed]
- Schmidt, J.A.; Rinaldi, S.; Scalbert, A.; Ferrari, P.; Achaintre, D.; Gunter, M.J.; Appleby, P.N.; Key, T.J.; Travis, R.C. Plasma concentrations and intakes of amino acids in male meat-eaters, fish-eaters, vegetarians and vegans: A cross-sectional analysis in the EPIC-Oxford cohort. Eur. J. Clin. Nutr. 2016, 70, 306–312. [Google Scholar] [CrossRef] [PubMed] [Green Version]
F-T2DM (n = 66) | Controls (n = 30) | p | |
---|---|---|---|
Age, years (mean ± SD) | 76.5 ± 14.5 | 74.6 ± 4.3 | 0.46 |
Sex (female), n (%) | 32 (48) | 16 (53) | 0.82 |
BMI, kg/m2 (mean ± SD) | 29.2 ± 4.9 | 26.7 ± 2.4 | 0.01 |
SPPB score (mean ± SD) | 8.6 ± 2.9 | 11.3 ± 0.9 | <0.0001 |
Number of diseases (mean ± SD) § | 2.8 ± 1.0 | 2.9 ± 2.0 | 0.86 |
Analytes | F-T2DM (n = 66) | Controls (n = 30) |
---|---|---|
3-methylhistidine | 7.8 ± 4.2 | 5.2 ± 2.5 |
Alanine | 542.3 ± 165.8 | 384.3 ± 98.3 |
Arginine | 168.3 ± 91.2 | 103.7 ± 31.2 |
Ethanolamine | 11.5 ± 3.4 | 9.0 ± 2.2 |
Glutamic acid | 130.0 ± 66.8 | 54.3 ± 21.3 |
Ornithine | 103.2 ± 37.6 | 109.4 ± 25.0 |
Sarcosine | 2.5 ± 0.9 | 1.6 ± 0.6 |
Taurine | 100.4 ± 49.0 | 189.5 ± 47.2 |
Tryptophan | 66.2 ± 23.4 | 62.0 ± 13.1 |
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Calvani, R.; Rodriguez-Mañas, L.; Picca, A.; Marini, F.; Biancolillo, A.; Laosa, O.; Pedraza, L.; Gervasoni, J.; Primiano, A.; Conta, G.; et al. Identification of a Circulating Amino Acid Signature in Frail Older Persons with Type 2 Diabetes Mellitus: Results from the Metabofrail Study. Nutrients 2020, 12, 199. https://doi.org/10.3390/nu12010199
Calvani R, Rodriguez-Mañas L, Picca A, Marini F, Biancolillo A, Laosa O, Pedraza L, Gervasoni J, Primiano A, Conta G, et al. Identification of a Circulating Amino Acid Signature in Frail Older Persons with Type 2 Diabetes Mellitus: Results from the Metabofrail Study. Nutrients. 2020; 12(1):199. https://doi.org/10.3390/nu12010199
Chicago/Turabian StyleCalvani, Riccardo, Leocadio Rodriguez-Mañas, Anna Picca, Federico Marini, Alessandra Biancolillo, Olga Laosa, Laura Pedraza, Jacopo Gervasoni, Aniello Primiano, Giorgia Conta, and et al. 2020. "Identification of a Circulating Amino Acid Signature in Frail Older Persons with Type 2 Diabetes Mellitus: Results from the Metabofrail Study" Nutrients 12, no. 1: 199. https://doi.org/10.3390/nu12010199
APA StyleCalvani, R., Rodriguez-Mañas, L., Picca, A., Marini, F., Biancolillo, A., Laosa, O., Pedraza, L., Gervasoni, J., Primiano, A., Conta, G., Bourdel-Marchasson, I., Regueme, S. C., Bernabei, R., Marzetti, E., Sinclair, A. J., & Gambassi, G., on behalf of the European MID-Frail Consortium. (2020). Identification of a Circulating Amino Acid Signature in Frail Older Persons with Type 2 Diabetes Mellitus: Results from the Metabofrail Study. Nutrients, 12(1), 199. https://doi.org/10.3390/nu12010199