Advantages of plasmatic CXCL-10 as a prognostic and diagnostic biomarker for the risk of rejection and subclinical rejection in kidney transplantation

Advancements in noninvasive techniques for transplant rejection: from biomarker detection to molecular imaging

Transplant rejection remains a significant barrier to the long-term success of organ transplantation. Biopsy, although considered the gold standard, is invasive, costly, and unsuitable for routine monitoring. Traditional biomarkers, such as creatinine and troponin, offer limited predictive value owing to their low specificity, and conventional imaging techniques often fail to detect early organ damage, increasing the risk of undiagnosed rejection episodes. Considering these limitations, emerging noninvasive biomarkers and molecular imaging techniques hold promise for the early and accurate detection of transplant rejection, enabling personalized management strategies. This review highlights noninvasive biomarkers that predict, diagnose, and assess transplant prognosis by reflecting graft injury, inflammation, and immune responses. For example, donor-derived cell-free DNA (dd-cfDNA) is highly sensitive in detecting early graft injury, whereas gene expression profiling effectively excludes moderate-to-severe acute rejection (AR). Additionally, microRNA (miRNA) profiling enhances the diagnostic specificity for precise AR detection. Advanced molecular imaging techniques further augment the monitoring of rejection. Fluorescence imaging provides a high spatiotemporal resolution for AR grading, ultrasound offers real-time and portable monitoring, and magnetic resonance delivers high tissue contrast for anatomical assessments. Nuclear imaging modalities such as single photon emission computed tomography and positron emission tomography, enable dynamic visualization of immune responses within transplanted organs. Notably, dd-cfDNA and nuclear medicine imaging have already been integrated into clinical practice, thereby demonstrating the translational potential of these techniques. Unlike previous reviews, this work uniquely synthesizes advancements in both noninvasive biomarkers and molecular imaging, emphasizing their complementary strengths. Biomarkers deliver molecular-level insights, whereas imaging provides spatial and temporal resolution. Together, they create a synergistic framework for comprehensive and precise transplant monitoring. By bridging these domains, this review underscores their individual contributions and collective potential to enhance diagnostic accuracy, improve patient outcomes, and guide future research and clinical applications in transplant medicine.

miRNAs, dd-cf-DNA, and Chemokines as Potential Noninvasive Biomarkers for the Assessment of Clinical Graft Evolution and Personalized Immunosuppression Requirement in Solid Organ Transplantation

ABSTRACT

The use of noninvasive biomarkers may reduce the need for biopsy and guide immunosuppression adjustments during transplantation. The scientific community in solid organ transplantation currently considers that chemokines, T- and B-cell immunophenotypes, and gene expression, among other molecular biomarkers, have great potential as diagnostic and predictive biomarkers for graft evolution; however, in clinical practice, few valid early biomarkers have emerged. This review focuses on the most relevant scientific advances in this field in the last 5 years regarding the role of 3 biomarkers: miRNAs, chemokines, and ddcf-DNA, in both adult and pediatric populations. An update was provided on the scores based on the combination of these biomarkers. The most-featured articles were identified through a literature search of the PubMed database. This review provides a comprehensive analysis of the potential clinical applications of these biomarkers in the diagnosis and prediction of graft outcomes and discusses the reasons why none have been implemented in clinical practice to date. Translating these biomarkers into routine clinical practice and combining them with pharmacogenetics and pharmacokinetic monitoring is challenging; however, it is the key to present/future individualized immunosuppressive therapies. It is essential that they be shown to be applicable and robust in real-life patient conditions and properly evaluate their added value when combined with the standard-of-care factor monitoring for graft clinical assessment. Partnership strategies among scientists, academic institutions, consortia, including expert working groups and scientific societies, and pharmaceutical and/or biotechnology companies should promote the development of prospective, randomized, multicenter intervention studies for adequate clinical validation of these biomarkers and their monitoring frequency, and their commercialization to make them available to transplant physicians.

An autophagy-associated diagnostic signature based on peripheral blood for antibody-mediated rejection in renal transplantation

BACKGROUND

Antibody-mediated rejection (ABMR) emerged as a major cause of graft loss in renal transplantation. Needle biopsy is the gold standard for diagnosis of ABMR in renal allografts. Thus, noninvasive diagnosis methods of ABMR with high accuracy are urgently needed to prevent unnecessary biopsies.

METHODS

We collected peripheral blood transcriptome data from two independent renal transplantation cohorts with patients with ABMR, stable well-functioning transplants (STA), and T-cell mediated rejection (TCMR). Differentially expressed genes (DEGs) were identified by comparing the ABMR group with the STA group. In addition, functional enrichment analysis and gene set enrichment analysis were performed to seek new key underlying mechanisms in ABMR. Subsequently, we utilized a Boruta algorithm and least absolute shrinkage and selection operator logistic algorithm to establish a diagnostic model which was then evaluated and validated in an independent cohort.

RESULTS

According to functional enrichment analysis, autophagy was found to be the primary upregulated biological process in ABMR. Based on algorithms, three autophagy-associated genes, ubiquitin specific peptidase 33 (USP33), Ras homolog mTORC1 binding (RHEB), and ABL proto-oncogene 2 (ABL2), were selected to establish the diagnostic model in the training cohort. This autophagy-related gene model possessed good diagnostic value in distinguishing ABMR from STA blood samples in the training cohort (AUC = 0.907) and in the validation cohort (AUC = 0.972). In addition, this model also showed good discernibility in distinguishing ABMR from TCMR in the training and validation cohorts (AUCs = 0.908 and 0.833).

CONCLUSION

We identified and validated an autophagy-associated diagnostic model with high accuracy for renal transplant patients with ABMR. Our study provided a new potential test for the non-invasive diagnosis of ABMR in clinical practice and highlighted the importance of autophagy in ABMR.

Optimizing the approach to monitoring allograft inflammation using serial urinary CXCL10/creatinine testing in pediatric kidney transplant recipients

BACKGROUND

Urinary CXCL10/creatinine (uCXCL10/Cr) is proposed as an effective biomarker of subclinical rejection in pediatric kidney transplant recipients. This study objective was to model implementation in the clinical setting.

METHODS

Banked urine samples at a single center were tested for uCXCL10/Cr to validate published thresholds for rejection diagnosis (>80% specificity). The positive predictive value (PPV) for rejection diagnosis for uCXCL10/Cr-indicated biopsy was modeled with first-positive versus two-test-positive approaches, with accounting for changes associated with urinary tract infection (UTI), BK and CMV viremia, and subsequent recovery.

RESULTS

Seventy patients aged 10.5 ± 5.6 years at transplant (60% male) had n = 726 urine samples with n = 236 associated biopsies (no rejection = 167, borderline = 51, and Banff 1A = 18). A threshold of 12 ng/mmol was validated for Banff 1A versus no-rejection diagnosis (AUC = 0.74, 95% CI = 0.57-0.92). The first-positive test approach (n = 69) did not resolve a clinical diagnosis in 38 cases (55%), whereas the two-test approach resolved a clinical diagnosis in the majority as BK (n = 17/60, 28%), CMV (n = 4/60, 7%), UTI (n = 8/60, 13%), clinical rejection (n = 5/60, 8%), and transient elevation (n = 18, 30%). In those without a resolved clinical diagnosis, PPV from biopsy for subclinical rejection is 24% and 71% (p = .017), for first-test versus two-test models, respectively. After rejection treatment, uCXCL10/Cr level changes were all concordant with change in it-score. Sustained uCXCL10/Cr after CMV and BK viremia resolution was associated with later acute rejection.

CONCLUSIONS

Urinary CXCL10/Cr reliably identifies kidney allograft inflammation. These data support a two-test approach to reliably exclude other clinically identifiable sources of inflammation, for kidney biopsy indication to rule out subclinical rejection.

Molecular immune monitoring in kidney transplant rejection: a state-of-the-art review

Although current regimens of immunosuppressive drugs are effective in renal transplant recipients, long-term renal allograft outcomes remain suboptimal. For many years, the diagnosis of renal allograft rejection and of several causes of renal allograft dysfunction, such as chronic subclinical inflammation and infection, was mostly based on renal allograft biopsy, which is not only invasive but also possibly performed too late for proper management. In addition, certain allograft dysfunctions are difficult to differentiate from renal histology due to their similar pathogenesis and immune responses. As such, non-invasive assays and biomarkers may be more beneficial than conventional renal biopsy for enhancing graft survival and optimizing immunosuppressive drug regimens during long-term care. This paper discusses recent biomarker candidates, including donor-derived cell-free DNA, transcriptomics, microRNAs, exosomes (or other extracellular vesicles), urine chemokines, and nucleosomes, that show high potential for clinical use in determining the prognosis of long-term outcomes of kidney transplantation, along with their limitations.

A plasmatic score using a miRNA signature and CXCL-10 for accurate prediction and diagnosis of liver allograft rejection

Introduction

The use of noninvasive biomarkers may avoid the need for liver biopsy (LB) and could guide immunosuppression adjustment in liver transplantation (LT). The aims of this study were: to confirm the predictive and diagnostic capacity of plasmatic expression of miR-155-5p, miR-181a-5p, miR-122-5p and CXCL-10 for assessing T-cell mediated rejection (TCMR) risk; to develop a score based on a panel of noninvasive biomarkers to predict graft rejection risk and to validate this score in a separate cohort.

Methods

A prospective, observational study was conducted with a cohort of 79 patients followed during the first year after LT. Plasma samples were collected at predetermined time points for the analysis of miRNAs and the CXCL-10. Patients with LFTs abnormalities were submitted to a LB to rule out rejection, assessing previous and concurrent expression of the biomarkers to evaluate their predictive and diagnostic ability. Information from 86 patients included in a previous study was collected and used as a validation cohort.

Results

Twenty-four rejection episodes were diagnosed in 22 patients. Plasmatic CXCL-10 concentration and the expression of the three miRNAs were significantly elevated prior to and at the moment of the diagnosis of rejection. We developed a logistic model for rejection prediction and diagnosis, which included CXCL-10, miR-155-5p and miR-181a-5p. The area under the ROC curve (AUROC) for rejection prediction was 0.975 (79.6% sensitivity, 99.1% specificity, 90,7% PPV; 97.7% NPV; 97.1% correctly classified) and 0.99 for diagnosis (87.5% sensitivity, 99.5% specificity, 91.3% PPV; 99.3% NPV; 98.9% correctly classified). In the validation cohort (n=86; 14 rejections), the same cut-off points were used obtaining AUROCs for rejection prediction and diagnosis of 0.89 and 0.92 respectively. In patients with graft dysfunction in both cohorts the score could discriminate those with rejection regarding other causes with an AUROC of 0.98 (97.3% sensitivity, 94.1%specificity).

Conclusion

These results suggest that the clinical implementation of the monitoring of this noninvasive plasmatic score may allow the prediction and diagnosis of rejection and identify patients with graft dysfunction due to rejection, helping with a more efficient guide for immunosuppressive therapy adjustment. This finding warrants the development of prospective biomarker-guided clinical trials.

Toward a new taxonomy of obstetrical disease: improved performance of maternal blood biomarkers for the great obstetrical syndromes when classified according to placental pathology

BACKGROUND

The major challenge for obstetrics is the prediction and prevention of the great obstetrical syndromes. We propose that defining obstetrical diseases by the combination of clinical presentation and disease mechanisms as inferred by placental pathology will aid in the discovery of biomarkers and add specificity to those already known.

OBJECTIVE

To describe the longitudinal profile of placental growth factor (PlGF), soluble fms-like tyrosine kinase-1 (sFlt-1), and the PlGF/sFlt-1 ratio throughout gestation, and to determine whether the association between abnormal biomarker profiles and obstetrical syndromes is strengthened by information derived from placental examination, eg, the presence or absence of placental lesions of maternal vascular malperfusion.

STUDY DESIGN

This retrospective case cohort study was based on a parent cohort of 4006 pregnant women enrolled prospectively. The case cohort of 1499 pregnant women included 1000 randomly selected patients from the parent cohort and all additional patients with obstetrical syndromes from the parent cohort. Pregnant women were classified into six groups: 1) term delivery without pregnancy complications (n=540; control); 2) preterm labor and delivery (n=203); 3) preterm premature rupture of the membranes (n=112); 4) preeclampsia (n=230); 5) small-for-gestational-age neonate (n=334); and 6) other pregnancy complications (n=182). Maternal plasma concentrations of PlGF and sFlt-1 were determined by enzyme-linked immunosorbent assays in 7560 longitudinal samples. Placental pathologists, masked to clinical outcomes, diagnosed the presence or absence of placental lesions of maternal vascular malperfusion. Comparisons between mean biomarker concentrations in cases and controls were performed by utilizing longitudinal generalized additive models. Comparisons were made between controls and each obstetrical syndrome with and without subclassifying cases according to the presence or absence of placental lesions of maternal vascular malperfusion.

RESULTS

1) When obstetrical syndromes are classified based on the presence or absence of placental lesions of maternal vascular malperfusion, significant differences in the mean plasma concentrations of PlGF, sFlt-1, and the PlGF/sFlt-1 ratio between cases and controls emerge earlier in gestation; 2) the strength of association between an abnormal PlGF/sFlt-1 ratio and the occurrence of obstetrical syndromes increases when placental lesions of maternal vascular malperfusion are present (adjusted odds ratio [aOR], 13.6 vs 6.7 for preeclampsia; aOR, 8.1 vs 4.4 for small-for-gestational-age neonates; aOR, 5.5 vs 2.1 for preterm premature rupture of the membranes; and aOR, 3.3 vs 2.1 for preterm labor (all P<0.05); and 3) the PlGF/sFlt-1 ratio at 28 to 32 weeks of gestation is abnormal in patients who subsequently delivered due to preterm labor with intact membranes and in those with preterm premature rupture of the membranes if both groups have placental lesions of maternal vascular malperfusion. Such association is not significant in patients with these obstetrical syndromes who do not have placental lesions.

CONCLUSION

Classification of obstetrical syndromes according to the presence or absence of placental lesions of maternal vascular malperfusion allows biomarkers to be informative earlier in gestation and enhances the strength of association between biomarkers and clinical outcomes. We propose that a new taxonomy of obstetrical disorders informed by placental pathology will facilitate the discovery and implementation of biomarkers as well as the prediction and prevention of such disorders.