rs3780126

Liver transplantation (LT) is a life-saving treatment for end-stage liver disease, but long-term immunosuppression (IS) is associated with significant side effects. Achieving operational tolerance (OT), where the graft is accepted without IS, remains a critical goal. Biomarkers play a pivotal role in understanding the complex mechanisms of OT, enabling personalized treatment strategies and improving patient outcomes. Additionally, machine learning techniques offer powerful tools for identifying predictive biomarkers and optimizing IS withdrawal protocols. This multicenter trial aimed to investigate the longitudinal evolution of genetic biomarkers during IS withdrawal and validate their predictive value for OT in LT recipients. A prospective, multicenter IS withdrawal trial was conducted with 91 LT patients. Tolerant (TOL) and non-tolerant (non-TOL) patients were compared, and longitudinal blood and liver samples were collected to analyze biomarkers. Generalized Additive Mixed Models (GAMMs) and logistic algorithms were employed to assess biomarker associations and predict OT. Of the 45 patients who completed the trial, 17 (37.8%) achieved OT. Molecular biomarker analysis revealed significant differences between TOL and non-TOL groups. Non-TOL patients exhibited higher baseline methylation of the FOXP3 regulatory T cell-specific demethylated region (TSDR) in whole blood. Longitudinal analysis showed distinct patterns in FOXP3, SENP6, miR31, and miR95 expression between groups. Notably, FOXP3 expression followed a U-shaped trajectory in TOL patients, decreasing during IS withdrawal and increasing post-withdrawal. Machine learning identified several key predictive biomarkers for OT. This study confirms the association between FOXP3 TSDR methylation and OT in LT patients and identifies FEM1C, miR31 and TFRC as promising predictive biomarkers. These findings highlight the potential for personalized IS withdrawal strategies, though further validation in larger cohorts is needed before clinical application.

2025 · Gloria López-Díaz (), María Isabel Sánchez-Lorencio (), Mercedes Iñarrairaegui (), María Luisa González-Diéguez (), Valle Cadahía (), Alejandra Otero-Ferreiro (), María Ángeles Vázquez-Millán (), Mario Romero-Cristóbal (), Magdalena Salcedo (), Sara Lorente-Pérez (), Gloria Sánchez-Antolín (), Jesús de la Peña (), Pablo Ramírez (), María P. Pata (), Alberto Baroja-Mazo (), José I. Herrero (), José Antonio Pons ()

The aim of this research was to investigate the role of genetic and nutritional variation within the folate-mediated one-carbon network in relation to cardiovascular disease risk. The enzymes serine hydroxymethyltransferase 1 (gene name SHMT1) and methylenetetrahydrofolate reductase (gene name MTHFR) regulate key reactions in folate-mediated one-carbon metabolism. We investigated the effect of the SHMT1 rs1979277 SNP and the SHMT1 rs1979277 - MTHFR rs1801133 interaction in two epidemiologic cohorts. In the Nurses' Health Study, the MTHFR rs1801133 variant genotypes were associated with an increased CVD risk, and there was an interaction between SHMT1 and MTHFR such that the association of MTHFR rs1801133 CT genotype (vs. CC; the TT genotype could not be evaluated) was stronger in the presence of the SHMT1 rs1979277 TT genotype. In the Health Professionals FollowUp Study, the MTHFR rs1801133 genotype was not associated with CVD risk nor was there an interaction with SHMT1 rs1979277. Next, using data from the Normative Aging Study, 330 SNPs in 52 genes were studied in relation to cardiovascular disease biomarkers. Using a nominal significance threshold of P[LESS-THAN OR EQUAL TO]0.005, 20 SNPs were associated with homocysteine, 8 with Alu methylation, and 1 with LINE-1 methylation. Using a more stringent false discovery rate threshold, SNPs in FTCD, SLC19A1, and SLC19A3 genes were associated with plasma homocysteine, gene x vitamin B-6 interactions were identified for Alu and LINE-1 methylation, and epistatic interactions involving the MTHFR rs1801133 SNP were identified for the plasma homocysteine phenotype. Finally, the SNPs were prospectively evaluated for their association with cardiovascular disease in a U.S. population studied prior to mandatory folate fortification. Using a nominal significance threshold of P[LESS-THAN OR EQUAL TO]0.005, 8 SNPs were associated with CVD risk. Using a more stringent false discovery rate threshold, a polymorphism in the GGH gene was associated with reduced CVD risk. A gene x folate interaction was identified (MAT2B) and two gene x vitamin B-12 interactions were identified (BHMT and SLC25A32). Hypotheses related to SHMT1 were explored and significant gene x gene interactions were identified. Overall, genetic variation in folate-mediated one-carbon metabolism, other than the wellknown effects of the MTHFR 677 C[RIGHTWARDS ARROW]T rs1801133, is predictive of cardiovascular disease risk.

2011 · Susan M. Wernimont