Dataset Information

Fractal circuit sensors enable rapid quantification of biomarkers for donor lung assessment for transplantation.

ABSTRACT: Biomarker profiling is being rapidly incorporated in many areas of modern medical practice to improve the precision of clinical decision-making. This potential improvement, however, has not been transferred to the practice of organ assessment and transplantation because previously developed gene-profiling techniques require an extended period of time to perform, making them unsuitable in the time-sensitive organ assessment process. We sought to develop a novel class of chip-based sensors that would enable rapid analysis of tissue levels of preimplantation mRNA markers that correlate with the development of primary graft dysfunction (PGD) in recipients after transplant. Using fractal circuit sensors (FraCS), three-dimensional metal structures with large surface areas, we were able to rapidly (<20 min) and reproducibly quantify small differences in the expression of interleukin-6 (IL-6), IL-10, and ATP11B mRNA in donor lung biopsies. A proof-of-concept study using 52 human donor lungs was performed to develop a model that was used to predict, with excellent sensitivity (74%) and specificity (91%), the incidence of PGD for a donor lung. Thus, the FraCS-based approach delivers a key predictive value test that could be applied to enhance transplant patient outcomes. This work provides an important step toward bringing rapid diagnostic mRNA profiling to clinical application in lung transplantation.

SUBMITTER: Sage AT

PROVIDER: S-EPMC4643795 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

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Fractal circuit sensors enable rapid quantification of biomarkers for donor lung assessment for transplantation.

Sage Andrew T AT Besant Justin D JD Mahmoudian Laili L Poudineh Mahla M Bai Xiaohui X Zamel Ricardo R Hsin Michael M Sargent Edward H EH Cypel Marcelo M Liu Mingyao M Keshavjee Shaf S Kelley Shana O SO

Science advances 20150828 7

Biomarker profiling is being rapidly incorporated in many areas of modern medical practice to improve the precision of clinical decision-making. This potential improvement, however, has not been transferred to the practice of organ assessment and transplantation because previously developed gene-profiling techniques require an extended period of time to perform, making them unsuitable in the time-sensitive organ assessment process. We sought to develop a novel class of chip-based sensors that wo ...[more]

PMID: 26601233

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Project description:Several recipient biomarkers are reported to predict graft dysfunction, but these are not useful in decision making for the acceptance or allocation of deceased donor kidneys; thus, it is necessary to develop donor biomarkers predictive of graft dysfunction. To address this issue, we prospectively enrolled 94 deceased donors and their 109 recipients who underwent transplantation between 2010 and 2013 at 4 Korean transplantation centers. We investigated the predictive values of donor urinary neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), and L-type fatty acid binding protein (L-FABP) for reduced graft function (RGF). We also developed a prediction model of RGF using these donor biomarkers. RGF was defined as delayed or slow graft function. Multiple logistic regression analysis was used to generate a prediction model, which was internally validated using a bootstrapping method. Multiple linear regression analysis was used to assess the association of biomarkers with 1-year graft function. Notably, donor urinary NGAL levels were associated with donor AKI (P = 0.014), and donor urinary NGAL and L-FABP were predictive for RGF, with area under the receiver-operating characteristic curves (AUROC) of 0.758 and 0.704 for NGAL and L-FABP, respectively. The best-fit model including donor urinary NGAL, L-FABP, and serum creatinine conveyed a better predictive value for RGF than donor serum creatinine alone (P = 0.02). In addition, we generated a scoring method to predict RGF based on donor urinary NGAL, L-FABP, and serum creatinine levels. Diagnostic performance of the RGF prediction score (AUROC 0.808) was significantly better than that of the DGF calculator (AUROC 0.627) and the kidney donor profile index (AUROC 0.606). Donor urinary L-FABP levels were also predictive of 1-year graft function (P = 0.005). Collectively, these findings suggest donor urinary NGAL and L-FABP to be useful biomarkers for RGF, and support the use of a new scoring system based on donor biomarkers to facilitate decision-making in acceptance and allocation of deceased donor kidneys and contribute to maximal organ utilization.

Project description:Background: Donor age affects allograft quality and the prognosis of recipients after liver transplantation (LT). Clinicians have assessed the quality of grafts from older donors based on their appearance and texture, with no reliable quantitative evidence. Our study aimed to assess the quantitative impact of donor age on post-transplant outcomes and its safety threshold for LT, based on the published literature. Methods: Relevant studies were retrieved from the Embase, PubMed, and ISI Web of Science databases. Pooled dichotomous relative risks (RRs) were calculated using metan. Continuous RRs were calculated using a two-stage random-effects model. Results: Eleven studies including 30,691 LT cases were included for further analysis. For categorical comparison, the RR of death within the first post-transplant year was significantly higher among patients who received grafts from older donors. Similarly, the RR of graft failure (GF) was increased within the 3 years after transplantation. For continuous comparison, advanced donor age affected transplant outcomes in a linear manner (P > 0.05). A 10-year increment in donor age was associated with RRs 1.10, 1.12, 1.15, 1.10, and 1.08 for 90-day, 180-day, 1-year, 3-year, and 5-year patient mortality and 1.08, 1.06, 1.10, 1.11, and 1.12, for 90-day, 180-day, 1-year, 2-year, and 3-year GF, respectively (all P < 0.05). A spline model showed that transplants using grafts from donors <43 years old were not associated with age-related risks (P > 0.05). The risk of GF was increased in subgroups with fewer LT cases, longer cold ischemic time, fewer male donors, and recipients with viral hepatitis (P < 0.05). Conclusion: Donor age might affect post-LT outcomes in a dose-dependent manner. The safety threshold for donor age in terms of GF should be lowered to 43 years as an early warning for the guarantee of satisfactory outcomes. Clinicians should weigh the benefits against the risks carefully for patients receiving grafts from older donors. Further studies are warranted to investigate the mechanisms responsible for the relationship between donor age and graft quality.

Dataset Information

Fractal circuit sensors enable rapid quantification of biomarkers for donor lung assessment for transplantation.

Publications

Fractal circuit sensors enable rapid quantification of biomarkers for donor lung assessment for transplantation.

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