Development of a plasma-free amino acid-based risk score for the incidence of cardiovascular diseases in a general population: The Nagahama study

2018, Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017: a systematic analysis for the Global Burden of Disease Study 2017, Lancet, 392, 1736, 10.1016/S0140-6736(18)32203-7 2016, Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015, Lancet, 388, 1603, 10.1016/S0140-6736(16)31460-X Nomura, 2017, Population health and regional variations of disease burden in Japan, 1990–2015: a systematic subnational analysis for the Global Burden of Disease Study 2015, Lancet, 390, 1521, 10.1016/S0140-6736(17)31544-1 Magnusson, 2013, A diabetes-predictive amino acid score and future cardiovascular disease, Eur Heart J, 34, 1982, 10.1093/eurheartj/ehs424 Würtz, 2015, Metabolite pofiling and crdiovascular event risk, Circulation, 131, 774, 10.1161/CIRCULATIONAHA.114.013116 Delles, 2018, Nuclear magnetic resonance-based metabolomics identifies phenylalanine as a novel predictor of incident heart failure hospitalisation: results from PROSPER and FINRISK 1997, Eur J Heart Fail, 20, 663, 10.1002/ejhf.1076 Wang, 2011, Metabolite profiles and the risk of developing diabetes, Nat Med, 17, 448, 10.1038/nm.2307 Yamakado, 2015, Plasma free amino acid profiles predict four-year risk of developing diabetes, metabolic syndrome, dyslipidemia, and hypertension in Japanese population, Sci Rep, 5, 10.1038/srep11918 Noguchi, 2006, Network analysis of plasma and tissue amino acids and the generation of an amino index for potential diagnostic use, Am J Clin Nutr, 83, 513s, 10.1093/ajcn/83.2.513S Imaizumi, 2019, Genetic basis for plasma amino acid concentrations based on absolute quantification: a genome-wide association study in the Japanese population, Eur J Hum Genet, 27, 621, 10.1038/s41431-018-0296-y Schmidt, 2016, 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, 70, 306, 10.1038/ejcn.2015.144 Nishimura, 2014, Predicting coronary heart disease using risk factor categories for a Japanese urban population, and comparison with the Framingham risk score: the Suita study, J Atherosclerosis Thromb, 21, 784, 10.5551/jat.19356 Nakai, 2020, Development of a cardiovascular disease risk prediction model using the Suita study, a population-based prospective cohort study in Japan, J Atherosclerosis Thromb, 27, 1160, 10.5551/jat.48843 Ridker, 2007, Development and validation of improved algorithms for the assessment of global cardiovascular risk in women, JAMA, 297, 611, 10.1001/jama.297.6.611 Yoshida, 2015, Validation of an analytical method for human plasma free amino acids by high-performance liquid chromatography ionization mass spectrometry using automated precolumn derivatization, J Chromatogr B, 998, 88, 10.1016/j.jchromb.2015.05.029 Takehana, 2016, The effects of pre-analysis sample handling on human plasma amino acid concentrations, Clin Chim Acta, 455, 68, 10.1016/j.cca.2016.01.026 Umemura, 2019, The Japanese Society of Hypertension guidelines for the management of hypertension (JSH 2019), Hypertens Res, 42, 1235, 10.1038/s41440-019-0284-9 2022 Seino, 2010, Report of the Committee on the classification and diagnostic criteria of diabetes mellitus, J Diabetes Investig, 1, 212, 10.1111/j.2040-1124.2010.00074.x Harrell, 1996, Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors, Stat Med, 15, 361, 10.1002/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>3.0.CO;2-4 Bansal, 2007, Fasting compared with nonfasting triglycerides and risk of cardiovascular events in women, JAMA, 298, 309, 10.1001/jama.298.3.309 Brownstein, 2019, Tests of trend between disease outcomes and ordinal covariates discretized from underlying continuous variables: simulation studies and applications to NHANES 2007–2008, BMC Med Res Methodol, 19, 2, 10.1186/s12874-018-0630-7 Uno, 2013, A unified inference procedure for a class of measures to assess improvement in risk prediction systems with survival data, Stat Med, 32, 2430, 10.1002/sim.5647 2020 Ottestad, 2018, Reduced plasma concentration of branched-chain amino acids in sarcopenic older subjects: a cross-sectional study, Br J Nutr, 120, 445, 10.1017/S0007114518001307 Foroumandi, 2018, Age-dependent changes in plasma amino acids contribute to alterations in glycoxidation products, J Med Biochem, 37, 426 Anderson, 1987, Cholesterol and mortality. 30 years of follow-up from the Framingham study, JAMA, 257, 2176, 10.1001/jama.1987.03390160062027 Kannel, 1997, Blood pressure and cardiovascular morbidity and mortality rates in the elderly, Am Heart J, 134, 758, 10.1016/S0002-8703(97)70061-9 Bell, 2014, Risk stratification in very old adults: how to best gauge risk as the basis of management choices for patients aged over 80, Prog Cardiovasc Dis, 57, 197, 10.1016/j.pcad.2014.08.001 Kugimiya, 2022, Development of a one-step analysis method for several amino acids using a microfluidic paper-based analytical device, Sci Rep, 12, 3427, 10.1038/s41598-022-07408-9 Tatsumi, 2019, Development of a rapid and simple glycine analysis method using a stable glycine oxidase mutant, Anal Biochem, 587, 10.1016/j.ab.2019.113447 Hobbs, 2010, Barriers to cardiovascular disease risk scoring and primary prevention in Europe, QJM, 103, 727, 10.1093/qjmed/hcq122 Tochikubo, 2016, Weight loss is associated with plasma free amino acid alterations in subjects with metabolic syndrome, Nutr Diabetes, 6, e197, 10.1038/nutd.2016.5 Zheng, 2016, Weight-loss diets and 2-y changes in circulating amino acids in 2 randomized intervention trials, Am J Clin Nutr, 103, 505, 10.3945/ajcn.115.117689 Hilden, 2014, A note on the evaluation of novel biomarkers: do not rely on integrated discrimination improvement and net reclassification index, Stat Med, 33, 3405, 10.1002/sim.5804 Pepe, 2015, The net reclassification index (NRI): a misleading measure of prediction improvement even with independent test data sets, Stat Biosci, 7, 282, 10.1007/s12561-014-9118-0 Ding, 2016, Plasma glycine and risk of acute myocardial infarction in patients with suspected stable angina pectoris, J Am Heart Assoc, 5 Rizza, 2014, Metabolomics signature improves the prediction of cardiovascular events in elderly subjects, Atherosclerosis, 232, 260, 10.1016/j.atherosclerosis.2013.10.029 Dietrich, 2016, Identification of serum metabolites associated with incident hypertension in the European prospective investigation into cancer and nutrition–potsdam study, Hypertension, 68, 471, 10.1161/HYPERTENSIONAHA.116.07292 Floegel, 2013, Identification of serum metabolites associated with risk of type 2 diabetes using a targeted metabolomic approach, Diabetes, 62, 639, 10.2337/db12-0495 Kume, 2014, Predictive properties of plasma amino acid profile for cardiovascular disease in patients with type 2 diabetes, PLoS One, 9, 10.1371/journal.pone.0101219 Gunther, 2020, Diet, physical activity and adiposity as determinants of circulating amino acid levels in a multiethnic asian population, Nutrients, 12, 2603, 10.3390/nu12092603 Iguacel, 2021, Associations between dietary amino acid intakes and blood concentration levels, Clin Nutr, 40, 3772, 10.1016/j.clnu.2021.04.036 Ignarro, 2007, Nutrition, physical activity, and cardiovascular disease: an update, Cardiovasc Res, 73, 326, 10.1016/j.cardiores.2006.06.030 Nishioka, 2013, The overnight effect of dietary energy balance on postprandial plasma free amino acid (PFAA) profiles in Japanese adult men, PLoS One, 8, 10.1371/journal.pone.0062929 Ruiz-Canela, 2017, Comprehensive metabolomic profiling and incident cardiovascular disease: a systematic review, J Am Heart Assoc, 6 Altman, 2000, What do we mean by validating a prognostic model?, Stat Med, 19, 453, 10.1002/(SICI)1097-0258(20000229)19:4<453::AID-SIM350>3.0.CO;2-5