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Biochemical and Hematological Correlates of Elevated Homocysteine in National Surveys and a Longitudinal Study of Urban Adults.

May A BeydounHind A BeydounPeter H MacIverSharmin HossainJose-Atilio CanasMichele K EvansAlan B Zonderman
Published in: Nutrients (2020)
Elevated blood homocysteine (Hcy) among middle-aged adults can increase age-related disease risk, possibly through other biochemical and hematological markers. We selected markers for hyperhomocysteinemia among middle-aged adults, studied time-dependent Hcy-marker associations and computed highly predictive indices of hyperhomocysteinemia, with cross-sectional and longitudinal validations. We used data from the National Health and Nutrition Examination Survey (NHANES III, phase 2, nmax = 4000), the NHANES 1999-2006 (nmax = 10,151) and pooled NHANES (cross-sectional validation). Longitudinal validation consisted of mixed-effects linear regression models (Hcy predicting markers' annual rates of change), applied to the Healthy Aging in Neighborhoods of Diversity Across the Life Span (HANDLS, n = 227-244 participants, k = 2.4 repeats/participant, Agebase: 30-65 years) data. Machine learning detected nine independent markers for Hcy > 14 µmol/L (NHANES III, phase 2): older age; lower folate and B-12 status; higher serum levels of creatinine, uric acid, alkaline phosphatase, and cotinine; mean cell hemoglobin and red cell distribution widths (RDW); results replicated in the 1999-2006 NHANES [AUC = 0.60-0.80]. Indices combining binary markers increased elevated Hcy odds by 6.9-7.5-fold. In HANDLS, first-visit Hcy predicted annual increase in creatinine, RDW and alkaline phosphatase, with third-visit index (2013-2018) directly predicting Hcy (2004-2009). We provide evidence of the internal and external validity of indices composed of several biomarkers that are strongly associated with elevated Hcy.
Keyphrases
  • cross sectional
  • uric acid
  • middle aged
  • machine learning
  • single cell
  • metabolic syndrome
  • cell therapy
  • magnetic resonance imaging
  • stem cells
  • mesenchymal stem cells
  • artificial intelligence