Cardiovascular disease (CVD) remains the major cause of death in patients with end-stage renal disease (ESRD). Traditional risk factors do not explain the high prevalence of CVD in this population, and other non-traditional cardiovascular (CV) risk markers have now been described. Therefore, the potential relationship between CVD and phenotypic and genotypic risk markers was investigated prospectively in incident dialysis patients cohort. The 279 patients (244 on hemodialysis, 35 on peritoneal dialysis) within the Diamant Alpin Dialysis Cohort Study were investigated. Phenotypic and genotypic parameters were determined at dialysis initiation, patients monitored over a 2-year period, and CV events (morbidity and mortality) recorded. Globally, 82 CV events occurred and 26 patients (9.3%) died from CVD, whereas 28 (10%) died from non-CV causes. Previous CV events were strongly predictive of CV events occurrence, whatever patients had had one (hazard ratio (HR) 2, 95% confidence intervals (CI) 1.1-3.5) or more (HR 3.9, 95% CI 2.1-7.1) CV accidents before starting dialysis. Both lipoprotein(a) (HR 1.67, 95% CI 1-2.5) and total plasma homocysteine at cutoff 30 micromol/l (HR 1.7, 95% CI 1.1-2.8) were independent predictors of CV events outcome. In the subgroup of patients with homocysteine < 30 micromol/l, methylenetetrahydrofolate reductase (MTHFR) TT was the sole biological parameter predictive of CV event outcome (HR 2.5, 95% CI 1.1-10, P = 0.03). ESRD patients who enter chronic dialysis with a previous CV event, high total homocysteinemia levels, or MTHFR 677TT genotype must be considered at high risk of incident CV events.
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Clin Exp Med
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Department of Thoracic Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China.
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Department of Microbiology, Faculty of Science, Kasetsart University, Chatuchak, Bangkok, 10900, Thailand.
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University of North Carolina at Chapel Hill, CHAPEL HILL, North Carolina, United States.
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Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Richards Building B304, 3700 Hamilton Walk, Philadelphia, PA, 19104, USA.
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January 2025
Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA.
Background: The mechanistic pathways that give rise to the extreme symptoms exhibited by rare disease patients are complex, heterogeneous, and difficult to discern. Understanding these mechanisms is critical for developing treatments that address the underlying causes of diseases rather than merely the presenting symptoms. Moreover, the same dysfunctional series of interrelated symptoms implicated in rare recessive diseases may also lead to milder and potentially preventable symptoms in carriers in the general population.
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