Researchers have identified a panel of genes which can help predict whether a transplanted kidney will later develop fibrosis, which can cause the organ to fail.
Researchers in the Genomics of Chronic Allograft Rejection (GoCAR) study obtained biopsy samples from transplanted kidneys three months and twelve months after transplantation. Using microarray, a method by which the expression levels of a large numbers of genes or proteins can be measured simultaneously, the researchers determined which genes were correlated with biopsy samples which had an increased Chronic Allograft Damage Index (CADI) score at the 12-month biopsy. The CADI score is a measure of the level of fibrosis in the transplanted kidney. The researchers then narrowed the genes down to a predictive gene set that identified patients at risk for decline in renal function and loss of the transplanted kidney beyond one year. The rate of correlation of the identified gene set with damage was greater than the clinico-pathological variables currently used in practice to identify kidney transplant recipients at risk of allograft damage and loss.
“This is the first finding of its kind,” said Barbara Murphy, system chair of medicine for the Mount Sinai Health System and Murray M Rosenberg professor of medicine (nephrology) at the Icahn School of Medicine at Mount Sinai, and the lead investigator on the study. “By helping us better understand the causes of damage to transplanted kidneys, this study has the potential to change how we monitor and manage all renal transplant patients.”
“The study offers the potential to identify renal transplant recipients at risk for a loss of the new organ prior to the development of irreversible damage,” said Murphy. “This would mean that doctors might eventually have the opportunity to change the therapeutic treatment approach in order to prevent fibrosis from progressing at all.”
Other institutions involved in the study include Westmead Hospital, Sydney, Australia; Northwestern University; Massachusetts General Hospital; Brigham and Women’s Hospital; University of Michigan; and University of Wisconsin.
Background: Chronic injury in kidney transplants remains a major cause of allograft loss. The aim of this study was to identify a gene set capable of predicting renal allografts at risk of progressive injury due to fibrosis.
Methods: This Genomics of Chronic Allograft Rejection (GoCAR) study is a prospective, multicentre study. We prospectively collected biopsies from renal allograft recipients (n=204) with stable renal function 3 months after transplantation. We used microarray analysis to investigate gene expression in 159 of these tissue samples. We aimed to identify genes that correlated with the Chronic Allograft Damage Index (CADI) score at 12 months, but not fibrosis at the time of the biopsy. We applied a penalised regression model in combination with permutation-based approach to derive an optimal gene set to predict allograft fibrosis.
Findings: We identified a set of 13 genes that was independently predictive for the development of fibrosis at 1 year (ie, CADI-12 ≥2). The gene set had high predictive capacity (area under the curve [AUC] 0•967), which was superior to that of baseline clinical variables (AUC 0•706) and clinical and pathological variables (AUC 0•806). Furthermore routine pathological variables were unable to identify which histologically normal allografts would progress to fibrosis (AUC 0•754), whereas the predictive gene set accurately discriminated between transplants at high and low risk of progression (AUC 0•916). The 13 genes also accurately predicted early allograft loss (AUC 0•842 at 2 years and 0•844 at 3 years). We validated the predictive value of this gene set in an independent cohort from the GoCAR study (n=45, AUC 0•866) and two independent, publically available expression datasets (n=282, AUC 0•831 and n=24, AUC 0•972).
Interpretation: Our results suggest that this set of 13 genes could be used to identify kidney transplant recipients at risk of allograft loss before the development of irreversible damage, thus allowing therapy to be modified to prevent progression to fibrosis.
Philip J O’Connell, Weijia Zhang, Madhav C Menon, Zhengzi Yi, Bernd Schröppel, Lorenzo Gallon, Yi Luan, Ivy A Rosales, Yongchao Ge, Bojan Losic, Caixia Xi, Christopher Woytovich, Karen L Keung, Chengguo Wei, Ilana Greene, Jessica Overbey, Emilia Bagiella, Nader Najafian, Milagros Samaniego, Arjang Djamali, Stephen I Alexander, Brian J Nankivell, Jeremy R Chapman, Rex Neal Smith, Robert Colvin, Barbara Murphy