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  • 标题:Novel plasma biomarkers improve discrimination of metabolic health independent of weight
  • 本地全文:下载
  • 作者:Stephen Ellison ; Jawan W. Abdulrahim ; Lydia Coulter Kwee
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2020
  • 卷号:10
  • 期号:1
  • 页码:1-9
  • DOI:10.1038/s41598-020-78478-w
  • 出版社:Springer Nature
  • 摘要:We sought to determine if novel plasma biomarkers improve traditionally defined metabolic health (MH) in predicting risk of cardiovascular disease (CVD) events irrespective of weight. Poor MH was defined in CATHGEN biorepository participants (n > 9300), a follow-up cohort (> 5600 days) comprising participants undergoing evaluation for possible ischemic heart disease. Lipoprotein subparticles, lipoprotein-insulin resistance (LP-IR), and GlycA were measured using NMR spectroscopy (n = 8385), while acylcarnitines and amino acids were measured using flow-injection, tandem mass spectrometry (n = 3592). Multivariable Cox proportional hazards models determined association of poor MH and plasma biomarkers with time-to-all-cause mortality or incident myocardial infarction. Low-density lipoprotein particle size and high-density lipoprotein, small and medium particle size (HMSP), GlycA, LP-IR, short-chain dicarboxylacylcarnitines (SCDA), and branched-chain amino acid plasma biomarkers were independently associated with CVD events after adjustment for traditionally defined MH in the overall cohort (p = 3.3 × 10−4–3.6 × 10−123), as well as within most of the individual BMI categories (p = 8.1 × 10−3–1.4 × 10−49). LP-IR, GlycA, HMSP, and SCDA improved metrics of model fit analyses beyond that of traditionally defined MH. We found that LP-IR, GlycA, HMSP, and SCDA improve traditionally defined MH models in prediction of adverse CVD events irrespective of BMI.
  • 其他摘要:Abstract We sought to determine if novel plasma biomarkers improve traditionally defined metabolic health (MH) in predicting risk of cardiovascular disease (CVD) events irrespective of weight. Poor MH was defined in CATHGEN biorepository participants (n > 9300), a follow-up cohort (> 5600 days) comprising participants undergoing evaluation for possible ischemic heart disease. Lipoprotein subparticles, lipoprotein-insulin resistance (LP-IR), and GlycA were measured using NMR spectroscopy (n = 8385), while acylcarnitines and amino acids were measured using flow-injection, tandem mass spectrometry (n = 3592). Multivariable Cox proportional hazards models determined association of poor MH and plasma biomarkers with time-to-all-cause mortality or incident myocardial infarction. Low-density lipoprotein particle size and high-density lipoprotein, small and medium particle size (HMSP), GlycA, LP-IR, short-chain dicarboxylacylcarnitines (SCDA), and branched-chain amino acid plasma biomarkers were independently associated with CVD events after adjustment for traditionally defined MH in the overall cohort ( p  = 3.3 × 10 −4 –3.6 × 10 −123 ), as well as within most of the individual BMI categories ( p  = 8.1 × 10 −3 –1.4 × 10 −49 ). LP-IR, GlycA, HMSP, and SCDA improved metrics of model fit analyses beyond that of traditionally defined MH. We found that LP-IR, GlycA, HMSP, and SCDA improve traditionally defined MH models in prediction of adverse CVD events irrespective of BMI.
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