Abstract
Adiposity is an important determinant of blood metabolites, but little is known about the variations of blood amino acids according to general and central adiposity status among Chinese population. This study included 187 females and 322 males who were cancer-free subjects randomly selected from two cohorts in Shanghai, China. Participants’ plasma concentrations of amino acids were measured by ultra-performance liquid chromatography coupled to tandem mass spectrometry. Linear regression models were used to examine the cross-sectional correlations between general and central adiposity and amino acid levels. A total of 35 amino acids in plasma were measured in this study. In females, alanine, aspartic acid and pyroglutamic acid were positively correlated with general adiposity. In males, glutamic acid, aspartic acid, valine and pyroglutamic acid showed positive correlations, and glutamine, serine and glycine showed negative correlations with both general and central adiposity; phenylalanine, isoleucine and leucine were positively correlated and N-phenylacetylglutamine was negatively correlated with general adiposity; asparagine was negatively correlated with central adiposity. In summary, general adiposity and central adiposity were correlated with the concentrations of specific plasma amino acids among cancer-free female and male adults in China. Adiposity–metabolite characteristics and relationships should be considered when studying blood biomarkers for adiposity-related health outcomes.
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Data will be available upon request pending application and approval by the scientific committee of the relevant institutes.
Abbreviations
- BCAA:
-
Branched-chain amino acid
- BMI:
-
Body mass index
- CI:
-
Confidence interval
- CV:
-
Coefficients of variation
- FFQ:
-
Food-frequency questionnaires
- MET:
-
Standard metabolic equivalents
- PAQ:
-
Physical activity questionnaires
- QC:
-
Quality control
- WC:
-
Waist circumference
References
Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, O’Brien WL, Bassett DR Jr, Schmitz KH, Emplaincourt PO, Jacobs DR Jr, Leon AS (2000) Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc 32(9 Suppl):S498-504. https://doi.org/10.1097/00005768-200009001-00009
Arnold M, Pandeya N, Byrnes G, Renehan PAG, Stevens GA, Ezzati PM, Ferlay J, Miranda JJ, Romieu I, Dikshit R, Forman D, Soerjomataram I (2015) Global burden of cancer attributable to high body-mass index in 2012: a population-based study. Lancet Oncol 16(1):36–46. https://doi.org/10.1016/s1470-2045(14)71123-4
Bamji-Stocke S, van Berkel V, Miller DM, Frieboes HB (2018) A review of metabolism-associated biomarkers in lung cancer diagnosis and treatment. Metabolomics 14(6):81. https://doi.org/10.1007/s11306-018-1376-2
Bao Y, Lu J, Wang C, Yang M, Li H, Zhang X, Zhu J, Lu H, Jia W, Xiang K (2008) Optimal waist circumference cutoffs for abdominal obesity in Chinese. Atherosclerosis 201(2):378–384. https://doi.org/10.1016/j.atherosclerosis.2008.03.001
Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol 57(1):289–300
Bi X, Tey SL, Loo YT, Henry CJ (2017) Central adiposity-induced plasma-free amino acid alterations are associated with increased insulin resistance in healthy Singaporean adults. Eur J Clin Nutr 71(9):1080–1087. https://doi.org/10.1038/ejcn.2017.34
Brennan AM, Tchernof A, Gerszten RE, Cowan TE, Ross R (2018) Depot-specific adipose tissue metabolite profiles and corresponding changes following aerobic exercise. Front Endocrinol (lausanne) 9:759. https://doi.org/10.3389/fendo.2018.00759
Chinese Nutrition Society (2021) Scientific research report on dietary guidelines for Chinese residents. https://www.cnsoc.org/bookpublica/422120200.html.
Deurenberg P, Deurenberg-Yap M, Guricci S (2002) Asians are different from Caucasians and from each other in their body mass index/body fat per cent relationship. Obes Rev 3(3):141–146. https://doi.org/10.1046/j.1467-789x.2002.00065.x
Dunn WB, Lin W, Broadhurst D, Begley P, Brown M, Zelena E, Vaughan AA, Halsall A, Harding N, Knowles JD, Francis-McIntyre S, Tseng A, Ellis DI, O’Hagan S, Aarons G, Benjamin B, Chew-Graham S, Moseley C, Potter P, Winder CL, Potts C, Thornton P, McWhirter C, Zubair M, Pan M, Burns A, Cruickshank JK, Jayson GC, Purandare N, Wu FC, Finn JD, Haselden JN, Nicholls AW, Wilson ID, Goodacre R, Kell DB (2015) Molecular phenotyping of a UK population: defining the human serum metabolome. Metabolomics 11:9–26. https://doi.org/10.1007/s11306-014-0707-1
Elliott P, Posma JM, Chan Q, Garcia-Perez I, Wijeyesekera A, Bictash M, Ebbels TM, Ueshima H, Zhao L, van Horn L, Daviglus M, Stamler J, Holmes E, Nicholson JK (2015) Urinary metabolic signatures of human adiposity. Sci Transl Med. 7(285):285ra262. https://doi.org/10.1126/scitranslmed.aaa5680
Farrokhi Yekta R, Rezaie Tavirani M, Arefi Oskouie A, Mohajeri-Tehrani MR, Soroush AR (2017) The metabolomics and lipidomics window into thyroid cancer research. Biomarkers 22(7):595–603. https://doi.org/10.1080/1354750x.2016.1256429
Felig P, Owen OE, Wahren J, Cahill GF Jr (1969) Amino acid metabolism during prolonged starvation. J Clin Invest 48(3):584–594. https://doi.org/10.1172/jci106017
Gasmi A, Noor S, Menzel A, Dosa A, Pivina L, Bjorklund G (2021) Obesity and insulin resistance: associations with chronic inflammation, genetic and epigenetic factors. Curr Med Chem 28(4):800–826. https://doi.org/10.2174/0929867327666200824112056
Glynn EL, Piner LW, Huffman KM, Slentz CA, Elliot-Penry L, AbouAssi H, White PJ, Bain JR, Muehlbauer MJ, Ilkayeva OR, Stevens RD, Porter Starr KN, Bales CW, Volpi E, Brosnan MJ, Trimmer JK, Rolph TP, Newgard CB, Kraus WE (2015) Impact of combined resistance and aerobic exercise training on branched-chain amino acid turnover, glycine metabolism and insulin sensitivity in overweight humans. Diabetologia 58(10):2324–2335. https://doi.org/10.1007/s00125-015-3705-6
Gunther SH, Khoo CM, Sim X, Tai ES, van Dam RM (2020) Diet, physical activity and adiposity as determinants of circulating amino acid levels in a multiethnic asian population. Nutrients 12(9):2603. https://doi.org/10.3390/nu12092603
Jurj AL, Wen W, Xiang YB, Matthews CE, Liu D, Zheng W, Shu XO (2007) Reproducibility and validity of the Shanghai men’s health study physical activity questionnaire. Am J Epidemiol 165(10):1124–1133. https://doi.org/10.1093/aje/kwk119
Kim MJ, Kim JH, Kim MS, Yang HJ, Lee M, Kwon DY (2019) Metabolomics associated with genome-wide association study related to the basal metabolic rate in overweight/obese Korean women. J Med Food 22(5):499–507. https://doi.org/10.1089/jmf.2018.4310
Kliemann N, Viallon V, Murphy N, Beeken RJ, Rothwell JA, Rinaldi S, Assi N, van Roekel EH, Schmidt JA, Borch KB, Agnoli C, Rosendahl AH, Sartor H, Huerta JM, Tjønneland A, Halkjær J, Bueno-de-Mesquita B, Gicquiau A, Achaintre D, Aleksandrova K, Schulze MB, Heath AK, Tsilidis KK, Masala G, Panico S, Kaaks R, Fortner RT, Van Guelpen B, Dossus L, Scalbert A, Keun HC, Travis RC, Jenab M, Johansson M, Ferrari P, Gunter MJ (2021) Metabolic signatures of greater body size and their associations with risk of colorectal and endometrial cancers in the European prospective investigation into cancer and nutrition. BMC Med 19(1):101. https://doi.org/10.1186/s12916-021-01970-1
Kochhar S, Jacobs DM, Ramadan Z, Berruex F, Fuerholz A, Fay LB (2006) Probing gender-specific metabolism differences in humans by nuclear magnetic resonance-based metabonomics. Anal Biochem 352(2):274–281. https://doi.org/10.1016/j.ab.2006.02.033
Lai HS, Lee JC, Lee PH, Wang ST, Chen WJ (2005) Plasma free amino acid profile in cancer patients. Semin Cancer Biol 15(4):267–276. https://doi.org/10.1016/j.semcancer.2005.04.003
Lauby-Secretan B, Scoccianti C, Loomis D, Grosse Y, Bianchini F, Straif K (2016) International agency for research on cancer handbook working g body fatness and cancer-viewpoint of the IARC working group. N Engl J Med 375(8):794–798. https://doi.org/10.1056/NEJMsr1606602
Lee SG, Yim YS, Lee YH, Lee BW, Kim HS, Kim KS, Lee YW, Kim JH (2018) Fasting serum amino acids concentration is associated with insulin resistance and pro-inflammatory cytokines. Diabetes Res Clin Pract 140:107–117. https://doi.org/10.1016/j.diabres.2018.03.028
Leichtle AB, Nuoffer JM, Ceglarek U, Kase J, Conrad T, Witzigmann H, Thiery J, Fiedler GM (2012) Serum amino acid profiles and their alterations in colorectal cancer. Metabolomics 8(4):643–653. https://doi.org/10.1007/s11306-011-0357-5
Lynch CJ, Adams SH (2014) Branched-chain amino acids in metabolic signalling and insulin resistance. Nat Rev Endocrinol 10(12):723–736. https://doi.org/10.1038/nrendo.2014.171
Ma RC, Chan JC (2013) Type 2 diabetes in East Asians: similarities and differences with populations in Europe and the United States. Ann N Y Acad Sci 1281:64–91. https://doi.org/10.1111/nyas.12098
Magkos F, Bradley D, Schweitzer GG, Finck BN, Eagon JC, Ilkayeva O, Newgard CB, Klein S (2013) Effect of Roux-en-Y gastric bypass and laparoscopic adjustable gastric banding on branched-chain amino acid metabolism. Diabetes 62(8):2757–2761. https://doi.org/10.2337/db13-0185
Matthews CE, Shu XO, Yang G, Jin F, Ainsworth BE, Liu D, Gao YT, Zheng W (2003) Reproducibility and validity of the Shanghai Women’s Health Study physical activity questionnaire. Am J Epidemiol 158(11):1114–1122. https://doi.org/10.1093/aje/kwg255
Miyagi Y, Higashiyama M, Gochi A, Akaike M, Ishikawa T, Miura T, Saruki N, Bando E, Kimura H, Imamura F, Moriyama M, Ikeda I, Chiba A, Oshita F, Imaizumi A, Yamamoto H, Miyano H, Horimoto K, Tochikubo O, Mitsushima T, Yamakado M, Okamoto N (2011) Plasma free amino acid profiling of five types of cancer patients and its application for early detection. PLoS ONE 6(9):e24143. https://doi.org/10.1371/journal.pone.0024143
Moore SC, Matthews CE, Sampson JN, Stolzenberg-Solomon RZ, Zheng W, Cai Q, Tan YT, Chow WH, Ji BT, Liu DK, Xiao Q, Boca SM, Leitzmann MF, Yang G, Xiang YB, Sinha R, Shu XO, Cross AJ (2014) Human metabolic correlates of body mass index. Metabolomics 10(2):259–269. https://doi.org/10.1007/s11306-013-0574-1
Nakamura H, Nishikata N, Kawai N, Imaizumi A, Miyano H, Mori M, Yamamoto H, Noguchi Y (2016) Plasma amino acid profiles in healthy East Asian subpopulations living in Japan. Am J Hum Biol 28(2):236–239. https://doi.org/10.1002/ajhb.22787
Nakayama K, Inaba Y (2019) Genetic variants influencing obesity-related traits in Japanese population. Ann Hum Biol 46(4):298–304. https://doi.org/10.1080/03014460.2019.1644373
Nie C, He T, Zhang W, Zhang G, Ma X (2018) Branched chain amino acids: beyond nutrition metabolism. Int J Mol Sci 19(4):954. https://doi.org/10.3390/ijms19040954
Okekunle AP, Li Y, Liu L, Du S, Wu X, Chen Y, Li Y, Qi J, Sun C, Feng R (2017) Abnormal circulating amino acid profiles in multiple metabolic disorders. Diabetes Res Clin Pract 132:45–58. https://doi.org/10.1016/j.diabres.2017.07.023
Park S, Sadanala KC, Kim EK (2015) A metabolomic approach to understanding the metabolic link between obesity and diabetes. Mol Cells 38(7):587–596. https://doi.org/10.14348/molcells.2015.0126
Shim K, Gulhar R, Jialal I (2019) Exploratory metabolomics of nascent metabolic syndrome. J Diabetes Complications 33(3):212–216. https://doi.org/10.1016/j.jdiacomp.2018.12.002
Shu XO, Li H, Yang G, Gao J, Cai H, Takata Y, Zheng W, Xiang YB (2015) Cohort profile: the shanghai men’s health study. Int J Epidemiol 44(3):810–818. https://doi.org/10.1093/ije/dyv013
Shu XO, Yang G, Jin F, Liu D, Kushi L, Wen W, Gao YT, Zheng W (2004) Validity and reproducibility of the food frequency questionnaire used in the Shanghai women’s health study. Eur J Clin Nutr 58(1):17–23. https://doi.org/10.1038/sj.ejcn.1601738
Tian X, Wang H (2022) Projecting National-level prevalence of general obesity and abdominal obesity among Chinese adults with aging effects. Front Endocrinol (lausanne). 13:849392. https://doi.org/10.3389/fendo.2022.849392
Tobias DK, Hazra A, Lawler PR, Chandler PD, Chasman DI, Buring JE, Lee IM, Cheng S, Manson JE, Mora S (2020) Circulating branched-chain amino acids and long-term risk of obesity-related cancers in women. Sci Rep 10(1):16534. https://doi.org/10.1038/s41598-020-73499-x
Tore EC, Elshorbagy AK, Bakers FCH, Brouwers M, Dagnelie PC, Eussen S, Jansen JFA, Kooi ME, Kusters Y, Meex SJR, Olsen T, Refsum H, Retterstøl K, Schalkwijk CG, Stehouwer CDA, Vinknes KJ, van Greevenbroek MMJ (2022) Associations between plasma sulfur amino acids and specific fat depots in two independent cohorts: CODAM and the maastricht study. Eur J Nutr. https://doi.org/10.1007/s00394-022-03041-4
Trock BJ (2011) Application of metabolomics to prostate cancer. Urol Oncol 29(5):572–581. https://doi.org/10.1016/j.urolonc.2011.08.002
Villegas R, Yang G, Liu D, Xiang YB, Cai H, Zheng W, Shu XO (2007) Validity and reproducibility of the food-frequency questionnaire used in the Shanghai men’s health study. Br J Nutr 97(5):993–1000. https://doi.org/10.1017/s0007114507669189
Wang G, Shen ZP (1991) Chinese food composition tables. People’s Health Publishing House, Beijin
Wang H, Zhai F (2013) Programme and policy options for preventing obesity in China. Obes Rev 14(Suppl 2):134–140. https://doi.org/10.1111/obr.12106
Wang L, Zhou B, Zhao Z, Yang L, Zhang M, Jiang Y, Li Y, Zhou M, Wang L, Huang Z, Zhang X, Zhao L, Yu D, Li C, Ezzati M, Chen Z, Wu J, Ding G, Li X (2021) Body-mass index and obesity in urban and rural China: findings from consecutive nationally representative surveys during 2004–18. Lancet 398(10294):53–63. https://doi.org/10.1016/S0140-6736(21)00798-4
Wolfe RR (2006) The underappreciated role of muscle in health and disease. Am J Clin Nutr 84(3):475–482. https://doi.org/10.1093/ajcn/84.3.475
Xie B, Waters MJ, Schirra HJ (2012) Investigating potential mechanisms of obesity by metabolomics. J Biomed Biotechnol 2012:805683. https://doi.org/10.1155/2012/805683
Xie G, Wang L, Chen T, Zhou K, Zhang Z, Li J, Sun B, Guo Y, Wang X, Wang Y, Zhang H, Liu P, Nicholson JK, Ge W, Jia W (2021) A metabolite array technology for precision medicine. Anal Chem 93(14):5709–5717. https://doi.org/10.1021/acs.analchem.0c04686
Yamaguchi N, Mahbub MH, Takahashi H, Hase R, Ishimaru Y, Sunagawa H, Amano H, Kobayashi-Miura M, Kanda H, Fujita Y, Yamamoto H, Yamamoto M, Kikuchi S, Ikeda A, Takasu M, Kageyama N, Nakamura M, Tanabe T (2017) Plasma free amino acid profiles evaluate risk of metabolic syndrome, diabetes, dyslipidemia, and hypertension in a large Asian population. Environ Health Prev Med 22(1):35. https://doi.org/10.1186/s12199-017-0642-7
Yamakado M, Tanaka T, Nagao K, Ishizaka Y, Mitushima T, Tani M, Toda A, Toda E, Okada M, Miyano H, Yamamoto H (2012) Plasma amino acid profile is associated with visceral fat accumulation in obese Japanese subjects. Clin Obes 2(1–2):29–40. https://doi.org/10.1111/j.1758-8111.2012.00039.x
Yan-Do R, MacDonald PE (2017) Impaired “Glycine”-mia in type 2 diabetes and potential mechanisms contributing to glucose homeostasis. Endocrinology 158(5):1064–1073. https://doi.org/10.1210/en.2017-00148
Zahed H, Johansson M, Ueland PM, Midttun Ø, Milne RL, Giles GG, Manjer J, Sandsveden M, Langhammer A, Sørgjerd EP, Grankvist K, Johansson M, Freedman ND, Huang WY, Chen C, Prentice R, Stevens VL, Wang Y, Le Marchand L, Wilkens LR, Weinstein SJ, Albanes D, Cai Q, Blot WJ, Arslan AA, Zeleniuch-Jacquotte A, Shu XO, Zheng W, Yuan JM, Koh WP, Visvanathan K, Sesso HD, Zhang X, Gaziano JM, Fanidi A, Muller D, Brennan P, Guida F, Robbins HA (2021) Epidemiology of 40 blood biomarkers of one-carbon metabolism, vitamin status, inflammation, and renal and endothelial function among cancer-free older adults. Sci Rep 11(1):13805. https://doi.org/10.1038/s41598-021-93214-8
Zhang A, Sun H, Yan G, Wang P, Han Y, Wang X (2014) Metabolomics in diagnosis and biomarker discovery of colorectal cancer. Cancer Lett 345(1):17–20. https://doi.org/10.1016/j.canlet.2013.11.011
Zheng W, Chow WH, Yang G, Jin F, Rothman N, Blair A, Li HL, Wen W, Ji BT, Li Q, Shu XO, Gao YT (2005) The Shanghai women’s health study: rationale, study design, and baseline characteristics. Am J Epidemiol 162(11):1123–1131. https://doi.org/10.1093/aje/kwi322
Zhou Y, Qiu L, Xiao Q, Wang Y, Meng X, Xu R, Wang S, Na R (2013) Obesity and diabetes related plasma amino acid alterations. Clin Biochem 46(15):1447–1452. https://doi.org/10.1016/j.clinbiochem.2013.05.045
Acknowledgements
We thank all participants and staff from the Shanghai Men’s and Women’s Health Studies for their contribution to this research.
Funding
This work was supported by the National Key Project of Research and Development Program of China [2021YFC2500404]; the parent cohorts were supported by a grant from the US National Institutes of Health [UM1 CA182910, UM1 CA173640]. All funders had no role in the design, analysis or writing of this article.
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Qiu-Ming Shen and Yong-Bing Xiang wrote the main manuscript text. Yong-Bing Xiang designed the research and obtained funding. Qiu-Ming Shen, Yu-Ting Tan, Jing Wang, Hong-Lan Li and Yong-Bing Xiang conducted research. Qiu-Ming Shen and Yong-Bing Xiang analyzed the data and interpreted the results. Yu-Ting Tan, Jing Wang, Jie Fang, Da-Ke Liu, Hong-Lan Li and Yong-Bing Xiang provided the database. Yong-Bing Xiang had primary responsibility for the final content. All authors read, reviewed and approved the final manuscript.
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Approval for the study was granted by the Renji Hospital Ethics Committee of Shanghai Jiao Tong University School of Medicine (No. KY2021-029). The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). Written informed consent was obtained from all study participants.
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Supplemental Table 1 Adjusted partial regression coefficients and 95% CIs of general adiposity and central adiposity for amino acids in females. Supplemental Table 2 Adjusted partial regression coefficients and 95% CIs of general adiposity and central adiposity for amino acids in males. Supplemental Table 3 Adjusted partial regression coefficients and 95% CIs of a 5-unit increase in BMI and 10-unit increase in WC for amino acids in females. Supplemental Table 4 Adjusted partial regression coefficients and 95% CIs of a 5-unit increase in BMI and 10-unit increase in WC for amino acids in males (DOCX 68 KB)
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Shen, QM., Tan, YT., Wang, J. et al. Cross-sectional relationships between general and central adiposity and plasma amino acids in Chinese adults. Amino Acids 55, 651–663 (2023). https://doi.org/10.1007/s00726-023-03258-5
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DOI: https://doi.org/10.1007/s00726-023-03258-5