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

Background & aims: Levels of circulating amino acids (AAs) have been suggested to be associated with cardiovascular diseases (CVDs). This study aimed to develop a plasma-free amino acid (PFAA)-based CVD risk-prediction model in a general population. Methods: The study participants consisted of 9220 community residents (mean age, 53.2 years; standard deviation, 13.3 years). Circulating levels of 19 PFAAs were measured via high-performance liquid chromatography/electrospray ionization mass spectrometry. The incidence of CVDs was determined by reviewing participants' clinical records. The prediction model was developed using the Cox proportional hazards model with the brute force variable selection and then cross-validated. Results: During the 8.5-year follow-up, 220 CVD events were observed. Six AAs (alanine, citrulline, glycine, histidine, serine, and tyrosine) were identified as components of the prediction model, of which the C-index was 0.72. The association between the fourth quartile of the risk score calculated using the prediction model and the CVD events was independent of conventional risk factors (adjusted hazard ratio [HR], 1.9; 95 % confidence interval, 1.1-3.3). When examining crude relationships between conventional risk factors and the PFAA-based risk score by subgroup analyses, the association was significant for most subpopulations, men [crude HR = 6.4 (2.0-20.2)] and women [crude HR = 4.9 (2.6-9.3)], and individuals with [crude HR = 4.7 (2.5-8.9)] and without [crude HR = 7.2 (2.7-18.9)] lifestyle-related diseases, but not for older (>= 70 years) participants [crude HR = 3.3 (0.8-13.5)]. The risk score successfully identified at-risk individuals [HR = 2.1 (1.2-3.5)] from participants who were classified as low risk by a conventional CVD risk score. Conclusions: The PFAA-based risk score predicted CVD events independently of conventional risk factors. (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).