Leptin – A new marker for development of post-transplant diabetes mellitus?

Dedinská, Ivana; Macková, N; Kantárová, Daniela; Kováčiková, Lea; Graňák, Karol; Laca, Ľ; Miklušica, Juraj; Skálová, Petra; Galajda, Péter; Mokáň, Marián

doi:10.1016/j.jdiacomp.2018.07.002

Cited by 14 publications

(9 citation statements)

References 21 publications

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“…and PGE2 production ( 74 ). Most importantly, and relevant to our current study, high concentrations of Leptin in serum constitute an independent risk factor for the development of AR in kidney transplants ( 75 ).…”

Section: Discussionmentioning

confidence: 61%

The Effects of Tacrolimus on Tissue-Specific, Protein-Level Inflammatory Networks in Vascularized Composite Allotransplantation

et al. 2021

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Systems-level insights into inflammatory events after vascularized composite allotransplantation (VCA) are critical to the success of immunomodulatory strategies of these complex procedures. To date, the effects of tacrolimus (TAC) immunosuppression on inflammatory networks in VCA, such as in acute rejection (AR), have not been investigated. We used a systems biology approach to elucidate the effects of tacrolimus on dynamic networks and principal drivers of systemic inflammation in the context of dynamic tissue-specific immune responses following VCA. Lewis (LEW) rat recipients received orthotopic hind limb VCA from fully major histocompatibility complex-mismatched Brown Norway (BN) donors or matched LEW donors. Group 1 (syngeneic controls) received LEW limbs without TAC, and Group 2 (treatment group) received BN limbs with TAC. Time-dependent changes in 27 inflammatory mediators were analyzed in skin, muscle, and peripheral blood using Principal Component Analysis (PCA), Dynamic Bayesian Network (DyBN) inference, and Dynamic Network Analysis (DyNA) to define principal characteristics, central nodes, and putative feedback structures of systemic inflammation. Analyses were repeated on skin + muscle data to construct a “Virtual VCA”, and in skin + muscle + peripheral blood data to construct a “Virtual Animal.” PCA, DyBN, and DyNA results from individual tissues suggested important roles for leptin, VEGF, various chemokines, the NLRP3 inflammasome (IL-1β, IL-18), and IL-6 after TAC treatment. The chemokines MCP-1, MIP-1α; and IP-10 were associated with AR in controls. Statistical analysis suggested that 24/27 inflammatory mediators were altered significantly between control and TAC-treated rats in peripheral blood, skin, and/or muscle over time. “Virtual VCA” and “Virtual Animal” analyses implicated the skin as a key control point of dynamic inflammatory networks, whose connectivity/complexity over time exhibited a U-shaped trajectory and was mirrored in the systemic circulation. Our study defines the effects of TAC on complex spatiotemporal evolution of dynamic inflammation networks in VCA. We also demonstrate the potential utility of computational analyses to elucidate nonlinear, cross-tissue interactions. These approaches may help define precision medicine approaches to better personalize TAC immunosuppression in VCA recipients.

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Section: Discussionmentioning

confidence: 61%

The Effects of Tacrolimus on Tissue-Specific, Protein-Level Inflammatory Networks in Vascularized Composite Allotransplantation

et al. 2021

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“…We could substantially extend the seed sub-network with more genes, which (i) connected between many seed genes and (ii) had a significant weight after the propagation. The largest module was enriched with pathways related to leptin , which has been linked to diabetes before ( 65–67 ), as well as some IGF ( Insulin Like Growth Factor ) related pathways. These pathways included both genes that were already associated with the disease, as well as some novel candidates.…”

Section: Discussionmentioning

confidence: 99%

NetCore: a network propagation approach using node coreness

Barel

Herwig

2020

Nucleic Acids Research

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We present NetCore, a novel network propagation approach based on node coreness, for phenotype–genotype associations and module identification. NetCore addresses the node degree bias in PPI networks by using node coreness in the random walk with restart procedure, and achieves improved re-ranking of genes after propagation. Furthermore, NetCore implements a semi-supervised approach to identify phenotype-associated network modules, which anchors the identification of novel candidate genes at known genes associated with the phenotype. We evaluated NetCore on gene sets from 11 different GWAS traits and showed improved performance compared to the standard degree-based network propagation using cross-validation. Furthermore, we applied NetCore to identify disease genes and modules for Schizophrenia GWAS data and pan-cancer mutation data. We compared the novel approach to existing network propagation approaches and showed the benefits of using NetCore in comparison to those. We provide an easy-to-use implementation, together with a high confidence PPI network extracted from ConsensusPathDB, which can be applied to various types of genomics data in order to obtain a re-ranking of genes and functionally relevant network modules.

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“…Only two research groups have previously studied this association with rejection using leptin measures at different times, although with conflicting results. Thus, Dedinska et al [28] reported that high serum leptin concentrations before the transplant were associated with increased risk of acute rejection. In contrast, Fonseca et al [29] could not find such association when measurements were performed in the first week after grafting.…”

Section: P R E P R I N Tmentioning

confidence: 99%

Effect of leptin concentrations and leptin receptor gene polymorphisms on the outcome of renal transplantation

García-Pino¹,

Luna

Mota-Zamorano

et al. 2021

Arch Med Sci

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IntroductionLeptin is a pro-inflammatory adipocytokine implicated in cardiovascular disease, insulin resistance, obesity and chronic kidney disease.Material and methodsIn a cohort of 236 renal transplant recipients, we aimed to determine whether circulating leptin concentrations and/or three polymorphisms in the leptin receptor (LEPR) gene, namely rs1137100, rs1137101 and rs1805094, were related to clinical outcomes in renal transplantation. Plasma leptin concentrations were measured by ELISA. Genetic variants were determined by conventional real-time PCR assays and statistical associations with clinical outcomes were obtained by logistic regression modelling.ResultsPatients with elevated leptin levels were at higher risk of acute rejection [OR=1.03 (1.01–1.05), p=0.03] and displayed worse renal clearance (p=0.001) than patients with lower levels. Leptin levels were not significantly affected by any of the three LEPR SNPs. The rs1137101 G variant showed an inverse association with the risk of delayed graft function (DGF) [OR=0.42 (0.22-0.81), p=0.009], whilst the homozygous rs1805094 CC genotype was associated with increased risk of acute rejection [OR=11.38 (2.15-60.16), p=0.004]. A statistically significant association was also observed between the rs1137100 GG genotype and better renal function [mean difference vs. AA/AG =20.20 (4.91-35.49) ml/min, p=0.010].ConclusionsOur results show that both leptin plasma concentrations and polymorphisms in the LEPR gene may affect clinical outcomes in renal transplant recipients, suggesting that the determination of these parameters could be useful in predicting post-transplant adverse events.

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Leptin – A new marker for development of post-transplant diabetes mellitus?

Cited by 14 publications

References 21 publications

The Effects of Tacrolimus on Tissue-Specific, Protein-Level Inflammatory Networks in Vascularized Composite Allotransplantation

The Effects of Tacrolimus on Tissue-Specific, Protein-Level Inflammatory Networks in Vascularized Composite Allotransplantation

NetCore: a network propagation approach using node coreness

Effect of leptin concentrations and leptin receptor gene polymorphisms on the outcome of renal transplantation

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