Background: The causative role of alcohol consumption in renal disease is controversial, and its effect on renal graft and recipient survival has not been previously studied.
Methods: We analysed the association between pre-transplant [at the time of end-stage renal disease (ESRD) onset] alcohol dependency and renal graft and recipient survival. The United States Renal Data System (USRDS) records of kidney transplant recipients 18 years or older transplanted between 1 January 1995 and 31 December 2002 were examined. We used Kaplan-Meier analysis and Cox regression models adjusted for covariates to analyse the association between pre-transplant alcohol dependency and graft and recipient survival.
Results: In an entire study cohort of 60 523, we identified 425 patients with a history of alcohol dependency. Using Cox models, alcohol dependency was found to be associated with increased risk of death-censored graft failure [hazard ratio (HR) 1.38, P < 0.05] and increased risk of transplant recipient death (HR 1.56, P < 0.001). Subgroup analysis demonstrated an association of alcohol-dependency with recipient survival and death-censored graft survival in males (but not in females), and in both white and non-white racial subgroups.
Conclusions: We concluded that alcohol dependency at the time of ESRD onset is a risk factor for renal graft failure and recipient death.
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http://dx.doi.org/10.1093/ndt/gfl689 | DOI Listing |
Comput Biol Chem
December 2024
Guangdong Provincial Key Laboratory of Pharmaceutical Bioactive Substances, Guangdong Pharmaceutical University, Guangzhou 510006, PR China. Electronic address:
In the present study, we uncovered and validated potential biomarkers related to gout, characterized by the accumulation of sodium urate crystals in different joint and non-joint structures. The data set GSE160170 was obtained from the GEO database. We conducted differential gene expression analysis, GO enrichment assessment, and KEGG pathway analysis to understand the underlying processes.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Yale University, New Haven, CT, USA.
Background: Alcohol Use Disorder (AUD) affects over 15 million individuals in the United States, contributing to oxidative stress, neuroinflammation, and elevating the risk of neurodegeneration. Despite this, the connection between AUD and aging conditions, particularly Alzheimer's disease (AD), remains unclear. AD, with a heritability of 60-80%, is genetically linked, necessitating an exploration of the molecular implications of AUD and genetic susceptibility to AD.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Neurogenomics & Informatics Center, St. Louis, MO, USA.
Background: Clear sex differences exist in AD and PD. Several studies examined genetic regulations for AD phenotypes and gene expression data in a sex-specific manner, identifying some differences between males and females. In contrasts, although proteins are final effectors of most physiological pathways and important drug targets, sex-specific regulations for proteins remain vastly understudied.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Ontario Shores Centre for Mental Health Sciences, Whitby, ON, Canada.
Background: Previous literature has highlighted that excessive alcohol use (EAU) is directly linked with permanent neurological damage. Studies have also highlighted gradual improvements in heart rate variability (HRV) after cessation of alcohol use. Moreover, chronic alcohol consumption has also been correlated with reduced HRV and an increase in skin conductance (SC) among healthy adults, leading to a combined decline in cognitive performance.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
University of California, San Diego, La Jolla, CA, USA.
Background: Neurocognitive health is influenced by multiple modifiable and non-modifiable lifestyle factors. Machine learning tools offer a promising approach to better understand complex models of cognitive function. We used extreme gradient boosting (XG Boost), an algorithm of decision-tree modeling, to analyze the association between 15 late-life lifestyle and demographic factors with episodic memory performance.
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