Renal function and genetic polymorphisms in pediatric heart transplant recipients

Cardiovascular health in pediatric heart transplant patients

BACKGROUND

Ideal "cardiovascular health" (CVH)-optimal diet, exercise, nonsmoking, BMI, BP, lipids, and glucose-is associated with healthy longevity in adults. Pediatric heart transplant (HT) patients may be at risk for suboptimal CVH.

METHODS

Single-center retrospective study of HT patients 2003-2014 who survived 1 year post-transplant. Five CVH metrics were collected at listing, 1, 3 and 5 years post-transplant (diet and exercise were unavailable). CVH was scored by summing individual metrics: ideal = 2, intermediate = 1, and poor = 0 points; total scores of 8-10 points were considered high (favorable). CVH was compared between HT patients and the US pediatric population (GP) utilizing NHANES 2007-2016. Logistic regression was performed to examine the association of CVH 1 year post-transplant with a composite adverse outcome (death, re-listing, coronary vasculopathy, or chronic kidney disease) 3 years post-transplant.

RESULTS

We included 110 HT patients (median age at HT: 6 years [range 0.1-21]) and 19,081 NHANES participants. CVH scores among HT patients were generally high at listing (75%), 1 (74%), 3 (87%) and 5 (76%) years post-transplant and similar to GP, but some metrics (e.g., glucose) were worse among HT patients. Among HT patients, CVH was poorer with older age and non-Caucasian race/ethnicity. Per 1-point higher CVH score, the demographic-adjusted OR for adverse outcomes was 0.95 (95% CI, 0.7-1.4).

CONCLUSIONS

HT patients had generally favorable CVH, but some metrics were unfavorable and CVH varied by age and race/ethnicity. No significant association was detected between CVH and adverse outcomes in this small sample, but study in a larger sample is warranted.

The Influence of Race and Common Genetic Variations on Outcomes After Pediatric Heart Transplantation

Significant racial disparity remains in the incidence of unfavorable outcomes following heart transplantation. We sought to determine which pediatric posttransplantation outcomes differ by race and whether these can be explained by recipient demographic, clinical, and genetic attributes. Data were collected for 80 black and 450 nonblack pediatric recipients transplanted at 1 of 6 centers between 1993 and 2008. Genotyping was performed for 20 candidate genes. Average follow-up was 6.25 years. Unadjusted 5-year rates for death (p = 0.001), graft loss (p = 0.015), acute rejection with severe hemodynamic compromise (p = 0.001), late rejection (p = 0.005), and late rejection with hemodynamic compromise (p = 0.004) were significantly higher among blacks compared with nonblacks. Black recipients were more likely to be older at the time of transplantation (p < 0.001), suffer from cardiomyopathy (p = 0.004), and have public insurance (p < 0.001), and were less likely to undergo induction therapy (p = 0.0039). In multivariate regression models adjusting for age, sex, cardiac diagnosis, insurance status, and genetic variations, black race remained a significant risk factor for all the above outcomes. These clinical and genetic variables explained only 8-19% of the excess risk observed for black recipients. We have confirmed racial differences in survival, graft loss, and several rejection outcomes following heart transplantation in children, which could not be fully explained by differences in recipient attributes.

Pharmacogenomics and heart failure in congenital heart disease

Congenital heart disease (CHD) constitutes a lifelong challenge in heart failure management. Current therapy is based mainly on physiologic principles extrapolated from the management of left ventricular failure in adult populations with either ischemic or nonischemic cardiomyopathy. However, there is good evidence of genomic variability in the origin and progression of CHD that suggests the need for a individualized approach to treatment. The developing science of pharmacogenomics presents an opportunity for CHD management broadly, and especially in the context of heart failure. There is growing evidence that individualizing drug therapy for these patients might be beneficial, and that prediction of response to therapy might be possible by incorporating genomic data into the treatment algorithm for individual patients.