Faculty Bibliography

BACKGROUND:Acute cellular rejection (ACR) remains a common complication causing significant morbidity post-liver transplantation. Non-human leukocyte antigen (non-HLA) mismatches were associated with an increased risk of ACR in kidney transplantation. Therefore, we hypothesized that donor-recipient non-HLA genetic mismatch is associated with increased ACR incidence post-liver transplantation. METHODS:We conducted an international multicenter case-control genome-wide association study of donor-recipient liver transplant pairs in 3 independent cohorts, totaling 1846 pairs. To assess genetic mismatch burden, we calculated sum scores for single-nucleotide polymorphism (SNP) mismatch based on all non-HLA functional SNPs, specifically SNPs coding for transmembrane or secreted proteins as they more likely affect the immune system. We analyzed the association between the non-HLA mismatch scores and ACR in a multivariable Cox regression model per cohort, followed by a weighted meta-analysis. RESULTS:During the first year post-transplantation, 90 of 689 (13%), 161 of 720 (22%), and 48 of 437 (11%) recipients experienced ACR in cohorts 1-3, respectively. Weighted meta-analyses showed that higher mismatch in functional non-HLA SNPs was associated with an increased incidence of ACR (HR 5.99; 95% CI: 1.39-20.08; p=0.011). Moreover, we found a larger effect of mismatch in SNPs coding for transmembrane or secreted proteins on ACR (HR 7.54; 95% CI 1.95-28.79; p=0.003). Sensitivity analyses showed that imputed HLA mismatch did not affect the associations between both non-HLA mismatch scores and ACR. CONCLUSIONS:Donor-recipient mismatch of functional non-HLA SNPs overall and, especially, of SNPs encoding transmembrane or secreted proteins correlated with 1-year ACR post-liver transplantation. Identifying high-risk immunological burdens between pairs may prevent early graft rejection and aid in personalizing immunosuppressive therapy. Future studies are, however, needed to validate our findings using a genotyped HLA cohort.

BACKGROUND:The genetic architecture of chronic kidney disease (CKD) is complex, including monogenic and polygenic contributions. CKD progression to kidney failure is influenced by factors including male sex, baseline estimated glomerular filtration rate (eGFR), hypertension, diabetes, proteinuria, and the underlying kidney disease. These traits all have strong genetic components, which can be partially quantified using polygenic risk scores. This paper examines the association between polygenic risk scores for CKD-related traits and age at kidney failure development. METHODS:Genome-wide genotype data from 10,586 patients with kidney failure were compiled from 12 cohorts. Polygenic risk scores for hypertension, albuminuria, rapid decline in eGFR, decreased total kidney volume, and decreased eGFR were calculated using weights from published independent population-scale genome-wide association studies. The association between each polygenic risk score and age at kidney failure was investigated using logistic regression models. The association between polygenic risk score and age at kidney failure was also investigated separately for each primary kidney disease. RESULTS:Individuals in the highest 10% of polygenic risk score for decreased eGFR developed kidney failure 2 years earlier than those in the bottom 90% (49.9 years and 47.9 years, P = 5e-5). A standard deviation increase in decreased eGFR polygenic risk score was associated with increased odds of developing kidney failure before the age of 60 years (Odds ratio (OR) = 1.05; 95% CI 1.01-1.10; P = 0.01), as was high decreased eGFR polygenic risk score (OR = 1.26; 95% CI 1.08-1.46; P = 0.003). CONCLUSIONS:We conclude that decreased eGFR polygenic risk score explains a portion of the variation in age at development of kidney failure.

Kidney transplant outcomes are influenced by donor and recipient age, sex, HLA mismatch, donor type, anti-rejection medication adherence and disease recurrence, but variability in transplant outcomes remains unexplained. We hypothesise that donor and recipient polygenic burden for traits related to kidney function may also influence graft function. We assembled a cohort of 6,060 living and deceased kidney donor-recipient pairs. We calculated polygenic risk scores (PRSs) for kidney function-related traits in both donors and recipients. We investigated the association between these PRSs and recipient eGFR at 1- and 5-year post-transplant as well as graft failure. Donor: hypertension PRS (P < 0.001), eGFR PRS (P < 0.001), and intracranial aneurysm PRS (P = 0.01), along with recipient eGFR PRS (P = 0.001) were associated with eGFR at 1-year post-transplantation. Clinical factors explained 25% of the variation in eGFR at 1-year and 13% at 5-year, with PRSs cumulatively adding 1% in both cases. PRSs were not associated with long-term graft survival. We demonstrate a small, but statistically significant association between donor and recipient PRSs and recipient graft function at 1- and 5-year post-transplant. This effect is, at present, unlikely to have clinical application and further research is required to improve PRS performance.

Circular RNAs (circRNAs) have emerged as crucial cardiovascular regulators through gene expression modulation, microRNA sponging, and protein interactions. Their covalently closed structure confers exceptional stability, making them detectable in blood and tissues as potential biomarkers. This review explores current research examining circRNAs across cardiovascular diseases, including atherosclerosis, myocardial infarction, and heart failure. We highlight the control that circRNA exerts over endothelial function, smooth muscle switching, inflammatory recruitment, and cardiomyocyte survival. Key findings distinguish frequently disease-promoting circRNAs (circANRIL, circHIPK3) from context-dependent regulators (circFOXO3). Compartment-specific controllers include endothelial stabilizers (circGNAQ), smooth muscle modulators (circLRP6, circROBO2), and macrophage regulators (circZNF609), functioning as tunable rheostats across vascular compartments. Overall, the literature suggests that circRNAs represent promising tools in two translational avenues: (i) blood-based multimarker panels for precision diagnosis and (ii) targeted modulation of pathogenic circuits. Clinical translation will require precise cell-type targeting, efficient delivery to cardiovascular tissues, and rigorous mitigation of off-target effects.

Human leukocyte antigen-level matching in US kidney allocation has been deemphasized due to its role in elevating racial disparities. Molecular matching based on eplets might improve risk stratification compared to antigen matching, but the magnitude of racial disparities in molecular matching is not known. To assign eplets unambiguously, we utilized a cohort of 5193 individuals with high-resolution allele-level human leukocyte antigen genotypes from the National Kidney Registry. Using repeated random sampling to simulate donor-recipient genotype pairings based on the ethnic composition of the historical US deceased-donor pool, we profiled the percentage of well-matched donors available for candidates by ethnicity. The prevalence of well-matched donors with 0-DR/DQ eplet mismatch was 3-fold less racially disparate for Black and Asian candidates and 2-fold less for Latino candidates compared to 0-ABDR antigen mismatches. Compared to 0-DR antigen mismatch, 0-DR eplet mismatch was 1.33-fold more racially disparate for Asian and 1.28-fold more for Latino, with similar disparity for Black candidates, whereas 0-DQ eplet mismatch reduced disparities, showing 1.26-fold less disparity for Black, 1.14-fold less for Latino, but 1.26-fold higher for Asian candidates. The prevalence of well-matched donors for candidates of different ethnicities varied according to which molecules were chosen to define a low-risk match.

The advent of more affordable genomic analytical pipelines has facilitated the expansion of genetic studies in kidney transplantation. Advances in genetic sequencing have allowed for a greater understanding of the genetic basis of chronic kidney disease, which has helped to guide transplant management and address issues related to living donation in specific disease settings. Recent efforts have shown significant effects of genetic ancestry and donor APOL1 risk genotypes in determining worse allograft outcomes and increased donation risks. Genetic studies in kidney transplantation outcomes have started to assess the effects of donor and recipient genetics in primary disease recurrence and transplant-related comorbidities, while genome-wide donor-recipient genetic incompatibilities have been shown to represent an important determinant of alloimmunity. Future large-scale comprehensive studies will shed light on the clinical utility of integrative genomics in the kidney transplantation setting.

Tacrolimus metabolism is heavily influenced by the CYP3A5 genotype, which varies widely among African Americans (AA). We aimed to assess the performance of a published genotype-informed tacrolimus dosing model in an independent set of adult AA kidney transplant (KTx) recipients. CYP3A5 genotypes were obtained for all AA KTx recipients (n = 232) from 2010 to 2019 who met inclusion criteria at a single transplant center in Philadelphia, Pennsylvania, USA. Medical record data were used to calculate predicted tacrolimus clearance using the published AA KTx dosing equation and two modified iterations. Observed and model-predicted trough levels were compared at 3 days, 3 months, and 6 months post-transplant. The mean prediction error at day 3 post-transplant was 3.05 ng/mL, indicating that the model tended to overpredict the tacrolimus trough. This bias improved over time to 1.36 and 0.78 ng/mL at 3 and 6 months post-transplant, respectively. Mean absolute prediction error-a marker of model precision-improved with time to 2.33 ng/mL at 6 months. Limiting genotype data in the model decreased bias and improved precision. The bias and precision of the published model improved over time and were comparable to studies in previous cohorts. The overprediction observed by the published model may represent overfitting to the initial cohort, possibly limiting generalizability.

African American (AA) kidney recipients have a higher risk of allograft rejection and failure compared to non-AAs, but to what extent these outcomes are due to genetic versus environmental effects is currently unknown. Herein, we tested the effects of recipient self-reported race versus genetic proportion of African ancestry (pAFR), and neighborhood socioeconomic status (SES) on kidney allograft outcomes in multiethnic kidney transplant recipients from Columbia University (N = 1083) and the University of Pennsylvania (N = 738). All participants were genotyped with SNP arrays to estimate genetic admixture proportions. US census tract variables were used to analyze the effect of neighborhood factors. In both cohorts, self-reported recipient AA race and pAFR were individually associated with increased risk of rejection and failure after adjustment for known clinical risk factors and neighborhood SES factors. Joint analysis confirmed that self-reported recipient AA race and pAFR were both associated with a higher risk of allograft rejection (AA: HR 1.61 (1.31-1.96), P = 4.05E-06; pAFR: HR 1.90 (1.46-2.48), P = 2.40E-06) and allograft failure (AA: HR 1.52 (1.18-1.97), P = .001; pAFR: HR 1.70 (1.22-2.35), P = .002). Further research is needed to disentangle the role of genetics versus environmental, social, and structural factors contributing to poor transplantation outcomes in kidney recipients of African ancestry.