Wei Chen1,2, Jessica Fitzpatrick3, Stephen M Sozio4,5, Bernard G Jaar4,5,6, Michelle M Estrella7,8, Dario F Riascos-Bernal1,9, Tong Tong Wu10, Yunping Qiu11, Irwin J Kurland1,11, Ruth F Dubin12, Yabing Chen13, Rulan S Parekh3,5, David A Bushinsky2, Nicholas E S Sibinga1,9. 1. Department of Medicine, Albert Einstein College of Medicine, Bronx, New York. 2. Department of Medicine, School of Medicine and Dentistry, University of Rochester, Rochester, New York. 3. Department of Medicine and Pediatrics, Hospital for Sick Children and University Health Network, University of Toronto, Toronto, Ontario, Canada. 4. Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland. 5. Department of Epidemiology, Bloomberg School of Public Health, Baltimore, Maryland. 6. Nephrology Center of Maryland, Fallston, Maryland. 7. Kidney Health Research Collaborative, Department of Medicine, University of California San Francisco, San Francisco, California. 8. San Francisco Veterans Affairs Health Care System, San Francisco, California. 9. Department of Developmental and Molecular Biology, Albert Einstein College of Medicine, Bronx, New York. 10. Department of Biostatistics and Computational Biology, School of Medicine and Dentistry, University of Rochester, Rochester, New York. 11. Einstein-Mount Sinai Diabetes Research Center, Albert Einstein College of Medicine, Bronx, New York. 12. Department of Medicine, University of California San Francisco, San Francisco, California. 13. Department of Pathology, University of Alabama at Birmingham and Birmingham Veterans Affairs Medical Center, Birmingham, Alabama.
Abstract
BACKGROUND: A better understanding of the pathophysiology involving coronary artery calcification (CAC) in patients on hemodialysis (HD) will help to develop new therapies. We sought to identify the differences in metabolomics profiles between patients on HD with and without CAC. METHODS: In this case-control study, nested within a cohort of 568 incident patients on HD, the cases were patients without diabetes with a CAC score >100 (n=51), and controls were patients without diabetes with a CAC score of zero (n=48). We measured 452 serum metabolites in each participant. Metabolites and pathway scores were compared using Mann-Whitney U tests, partial least squares-discriminant analyses, and pathway enrichment analyses. RESULTS: Compared with controls, cases were older (64±13 versus 42±12 years) and were less likely to be Black (51% versus 94%). We identified three metabolites in bile-acid synthesis (chenodeoxycholic, deoxycholic, and glycolithocholic acids) and one pathway (arginine/proline metabolism). After adjusting for demographics, higher levels of chenodeoxycholic, deoxycholic, and glycolithocholic acids were associated with higher odds of having CAC; comparing the third with the first tertile of each bile acid, the OR was 6.34 (95% CI, 1.12 to 36.06), 6.73 (95% CI, 1.20 to 37.82), and 8.53 (95% CI, 1.50 to 48.49), respectively. These associations were no longer significant after further adjustment for coronary artery disease and medication use. Per 1 unit higher in the first principal component score, arginine/proline metabolism was associated with CAC after adjusting for demographics (OR, 1.83; 95% CI, 1.06 to 3.15), and the association remained significant with additional adjustments for statin use (OR, 1.84; 95% CI, 1.04 to 3.27). CONCLUSIONS: Among patients on HD without diabetes mellitus, chenodeoxycholic, deoxycholic, and glycolithocholic acids may be potential biomarkers for CAC, and arginine/proline metabolism is a plausible mechanism to study for CAC. These findings need to be confirmed in future studies.
BACKGROUND: A better understanding of the pathophysiology involving coronary artery calcification (CAC) in patients on hemodialysis (HD) will help to develop new therapies. We sought to identify the differences in metabolomics profiles between patients on HD with and without CAC. METHODS: In this case-control study, nested within a cohort of 568 incident patients on HD, the cases were patients without diabetes with a CAC score >100 (n=51), and controls were patients without diabetes with a CAC score of zero (n=48). We measured 452 serum metabolites in each participant. Metabolites and pathway scores were compared using Mann-Whitney U tests, partial least squares-discriminant analyses, and pathway enrichment analyses. RESULTS: Compared with controls, cases were older (64±13 versus 42±12 years) and were less likely to be Black (51% versus 94%). We identified three metabolites in bile-acid synthesis (chenodeoxycholic, deoxycholic, and glycolithocholic acids) and one pathway (arginine/proline metabolism). After adjusting for demographics, higher levels of chenodeoxycholic, deoxycholic, and glycolithocholic acids were associated with higher odds of having CAC; comparing the third with the first tertile of each bile acid, the OR was 6.34 (95% CI, 1.12 to 36.06), 6.73 (95% CI, 1.20 to 37.82), and 8.53 (95% CI, 1.50 to 48.49), respectively. These associations were no longer significant after further adjustment for coronary artery disease and medication use. Per 1 unit higher in the first principal component score, arginine/proline metabolism was associated with CAC after adjusting for demographics (OR, 1.83; 95% CI, 1.06 to 3.15), and the association remained significant with additional adjustments for statin use (OR, 1.84; 95% CI, 1.04 to 3.27). CONCLUSIONS: Among patients on HD without diabetes mellitus, chenodeoxycholic, deoxycholic, and glycolithocholic acids may be potential biomarkers for CAC, and arginine/proline metabolism is a plausible mechanism to study for CAC. These findings need to be confirmed in future studies.
Authors: Edward R Smith; Martin L Ford; Laurie A Tomlinson; Emma Bodenham; Lawrence P McMahon; Stefan Farese; Chakravarthi Rajkumar; Stephen G Holt; Andreas Pasch Journal: J Am Soc Nephrol Date: 2013-10-31 Impact factor: 10.121
Authors: Guoyao Wu; Fuller W Bazer; Teresa A Davis; Sung Woo Kim; Peng Li; J Marc Rhoads; M Carey Satterfield; Stephen B Smith; Thomas E Spencer; Yulong Yin Journal: Amino Acids Date: 2008-11-23 Impact factor: 3.520
Authors: Wei Chen; Jessica Fitzpatrick; Jose M Monroy-Trujillo; Stephen M Sozio; Bernard G Jaar; Michelle M Estrella; Tong Tong Wu; Michal L Melamed; Rulan S Parekh; David A Bushinsky Journal: Kidney Int Rep Date: 2019-03-13