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鉴定生物标志物以评估器官质量并预测移植后的结果。

Identification of biomarkers to assess organ quality and predict posttransplantation outcomes.

机构信息

Division of Transplantation, Department of Surgery, University of Virginia School of Medicine, Charlottesville, VA 22908-0679, USA.

出版信息

Transplantation. 2012 Oct 27;94(8):851-8. doi: 10.1097/TP.0b013e318263702b.

DOI:10.1097/TP.0b013e318263702b
PMID:22992769
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3927314/
Abstract

UNLABELLED

The increased disparity between organ supply and need has led to the use of extended criteria donors and donation after cardiac death donors with other comorbidities.

METHODS

We have examined the preimplantation transcriptome of 112 kidney transplant recipient samples from 100 deceased-donor kidneys by microarray profiling. Subject groups were segregated based on estimated glomerular filtration rate (eGFR) at 1 month after transplantation: the GFR-high group (n=74) included patients with eGFR 45 mL/min per 1.73 m(2), whereas the GFR-low group (n=35) included patients with eGFR 45 mL/min or less per 1.73 m(2).

RESULTS

Gene expression profiling identified higher expression of 160 probe sets (140 genes) in the GFR-low group, whereas expression of 37 probe sets (33 genes) was higher in the GFR-high group (P<0.01, false discovery rate <0.2). Four genes (CCL5, CXCR4, ITGB2, and EGF) were selected based on fold change and P value and further validated using an independent set of samples. A random forest analysis identified three of these genes (CCL5, CXCR4, and ITGB2) as important predictors of graft function after transplantation.

CONCLUSIONS

Inclusion of pretransplantation molecular gene expression profiles in donor quality assessment systems may provide the necessary information for better donor organ selection and function prediction. These biomarkers would further allow a more objective and complete assessment of procured renal allografts at pretransplantation time.

摘要

目的

通过微阵列分析,研究了 100 例死亡供体 112 例肾移植受者样本的植入前转录组。根据移植后 1 个月时的肾小球滤过率(estimated glomerular filtration rate,eGFR)将受者分为两组:GFR-高组(n=74)包括 eGFR 45 mL/min/1.73 m 2 的患者,GFR-低组(n=35)包括 eGFR 45 mL/min/1.73 m 2 或更低的患者。

方法

我们通过微阵列分析,研究了 100 例死亡供体的 112 例肾移植受者样本的植入前转录组。根据移植后 1 个月时的肾小球滤过率(estimated glomerular filtration rate,eGFR)将受者分为两组:GFR-高组(n=74)包括 eGFR 45 mL/min/1.73 m 2 的患者,GFR-低组(n=35)包括 eGFR 45 mL/min/1.73 m 2 或更低的患者。

结果

基因表达谱分析发现,GFR-低组有 160 个探针集(140 个基因)的表达较高,而 GFR-高组有 37 个探针集(33 个基因)的表达较高(P<0.01,假发现率<0.2)。根据 fold change 和 P 值选择了 4 个基因(CCL5、CXCR4、ITGB2 和 EGF),并使用独立样本进行了进一步验证。随机森林分析确定了这 3 个基因(CCL5、CXCR4 和 ITGB2)是移植后移植物功能的重要预测因子。

结论

将移植前分子基因表达谱纳入供体质量评估系统,可能为更好的供体器官选择和功能预测提供必要的信息。这些生物标志物将进一步允许在移植前时间对获取的肾同种异体移植物进行更客观和完整的评估。

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A comprehensive risk quantification score for deceased donor kidneys: the kidney donor risk index.deceased donor kidneys 供体已死亡的肾脏,即供体肾脏来自已死亡的供体,而非活体供体。在医学领域,供体肾脏的获取对于肾脏移植手术至关重要,而 deceased donor kidneys 是常见的肾脏来源之一。与之相对的是 living donor kidneys,即活体供体的肾脏。 deceased donor kidneys 可以为众多终末期肾病患者带来肾脏移植的希望,提高他们的生活质量,延长生存期。然而,使用 deceased donor kidneys 进行移植也面临一些挑战和风险评估。例如,需要对供体的身体状况、病史等进行全面评估,以确保移植肾脏的质量和安全性。同时,对于受体而言,术后也需要密切监测和免疫抑制治疗,以防止排斥反应等并发症的发生。 在临床实践中,医生会综合考虑各种因素,权衡 deceased donor kidneys 的利弊,为患者制定最适合的治疗方案。 以下是根据你提供的英文内容“A comprehensive risk quantification score for deceased donor kidneys: the kidney donor risk index.”的译文: deceased donor kidneys 供体已死亡的肾脏,即供体肾脏来自已死亡的供体,而非活体供体。在医学领域,供体肾脏的获取对于肾脏移植手术至关重要,而 deceased donor kidneys 是常见的肾脏来源之一。与之相对的是 living donor kidneys,即活体供体的肾脏。 deceased donor kidneys 可以为众多终末期肾病患者带来肾脏移植的希望,提高他们的生活质量,延长生存期。然而,使用 deceased donor kidneys 进行移植也面临一些挑战和风险评估。例如,需要对供体的身体状况、病史等进行全面评估,以确保移植肾脏的质量和安全性。同时,对于受体而言,术后也需要密切监测和免疫抑制治疗,以防止排斥反应等并发症的发生。 在临床实践中,医生会综合考虑各种因素,权衡 deceased donor kidneys 的利弊,为患者制定最适合的治疗方案。 针对 deceased donor kidneys 的综合风险量化评分:肾脏供体风险指数
Transplantation. 2009 Jul 27;88(2):231-6. doi: 10.1097/TP.0b013e3181ac620b.