Volume 15 Issue 4
Jul.  2024
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Xu Yuan, Hou Shuang, Chen Qian, et al. Correlation between metabolic markers and blood lipid levels in kidney transplant recipients[J]. ORGAN TRANSPLANTATION, 2024, 15(4): 599-606. doi: 10.3969/j.issn.1674-7445.2024014
Citation: Xu Yuan, Hou Shuang, Chen Qian, et al. Correlation between metabolic markers and blood lipid levels in kidney transplant recipients[J]. ORGAN TRANSPLANTATION, 2024, 15(4): 599-606. doi: 10.3969/j.issn.1674-7445.2024014
shu

Correlation between metabolic markers and blood lipid levels in kidney transplant recipients

doi: 10.3969/j.issn.1674-7445.2024014
  • 1.

    Department of Organ Transplantation, the Affiliated Hospital of Guizhou Medical University, Guiyang 550004, China

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    Abstract
  •   Objective   To analyze the co-expressed genes in blood lipid metabolism, hyperlipidemia and tacrolimus metabolism and their correlation with blood lipid levels in kidney transplant recipients.   Methods  Co-expressed genes were screened from Comparative Toxicogenomic Database (CTD). Baseline data of 25 kidney transplant recipients were collected. The expression levels of ATP binding cassette subfamily A member 1(ABCA1), peroxisome proliferator activated receptor γ (PPAR-γ) and glycosylphosphatidylinositol anchored high density lipoprotein binding protein 1 (GPIHBP1) were measured. All recipients were followed up. The concentrations of fasting blood glucose, glycosylated hemoglobin, triglyceride, total protein, albumin, globulin, cholesterol, high-density lipoprotein, low-density lipoprotein and tacrolimus blood concentration were collected at postoperative 1, 3, 6 and 12 months, and the incidence of hyperlipidemia in the recipients was analyzed. The correlation between ABCA1, GPIHBP1, PPAR-γ and clinical indexes was assessed. The diagnostic efficiency of related indexes for hyperlipidemia after kidney transplantation was evaluated.   Results  Three co-expressed genes including ABCA1, PPAR-γ and GPIHBP1 were screened. ABCA1 was positively correlated with cholesterol level at postoperative 6 months and tacrolimus blood concentration at postoperative 3 months, whereas negatively correlated with fasting blood glucose level at postoperative 3 months (all P<0.05). GPIHBP1 was negatively correlated with preoperative cholesterol and triglyceride levels, whereas positively correlated with tacrolimus blood concentration at postoperative 3 months (all P<0.05). PPAR-γ was negatively correlated with preoperative globulin and low-density lipoprotein levels (both P<0.05). ABCA1, GPIHBP1 and PPAR-γ combined with preoperative globulin and blood glucose level at postoperative 1 and 6 months after operation yielded high diagnostic efficiency for hypertriglyceridemia after kidney transplantation (AUC=0.900). ABCA1, GPIHBP1 and PPAR-γ combined with tacrolimus blood concentrations at postoperative 1 and 6 months and blood glucose level at postoperative 6 months had high diagnostic efficiency for hypercholesterolemia after kidney transplantation (AUC=0.931).   Conclusions  ABCA1, GPIHBP1 and PPAR-γ are correlated with blood lipid level and tacrolimus blood concentration after kidney transplantation to different degrees. No definite evidence has been supported for predicting hyperlipidemia after kidney transplantation. Immunity improvement and rational blood glucose management may be beneficial factors for hyperlipidemia control.

     

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