Plasma Free Amino Acid Profiles Predict Four-Year Risk of Developing Diabetes, Metabolic Syndrome, Dyslipidemia, and Hypertension in Japanese Population View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-12

AUTHORS

Minoru Yamakado, Kenji Nagao, Akira Imaizumi, Mizuki Tani, Akiko Toda, Takayuki Tanaka, Hiroko Jinzu, Hiroshi Miyano, Hiroshi Yamamoto, Takashi Daimon, Katsuhisa Horimoto, Yuko Ishizaka

ABSTRACT

Plasma free amino acid (PFAA) profile is highlighted in its association with visceral obesity and hyperinsulinemia, and future diabetes. Indeed PFAA profiling potentially can evaluate individuals' future risks of developing lifestyle-related diseases, in addition to diabetes. However, few studies have been performed especially in Asian populations, about the optimal combination of PFAAs for evaluating health risks. We quantified PFAA levels in 3,701 Japanese subjects, and determined visceral fat area (VFA) and two-hour post-challenge insulin (Ins120 min) values in 865 and 1,160 subjects, respectively. Then, models between PFAA levels and the VFA or Ins120 min values were constructed by multiple linear regression analysis with variable selection. Finally, a cohort study of 2,984 subjects to examine capabilities of the obtained models for predicting four-year risk of developing new-onset lifestyle-related diseases was conducted. The correlation coefficients of the obtained PFAA models against VFA or Ins120 min were higher than single PFAA level. Our models work well for future risk prediction. Even after adjusting for commonly accepted multiple risk factors, these models can predict future development of diabetes, metabolic syndrome, and dyslipidemia. PFAA profiles confer independent and differing contributions to increasing the lifestyle-related disease risks in addition to the currently known factors in a general Japanese population. More... »

PAGES

11918

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/srep11918

DOI

http://dx.doi.org/10.1038/srep11918

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1021683268

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/26156880


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