KiT-GENIE, the French genetic biobank of kidney transplantation

Abstract

KiT-GENIE is a monocentric DNA biobank set up to consolidate the very rich and homogeneous DIVAT French cohort of kidney donors and recipients (D/R) in order to explore the molecular factors involved in kidney transplantation outcomes. We collected DNA samples for kidney transplantations performed in Nantes, and we leveraged GWAS genotyping data for securing high-quality genetic data with deep SNP and HLA annotations through imputations and for inferring D/R genetic ancestry. Overall, the biobank included 4217 individuals (n = 1945 D + 2,272 R, including 1969 D/R pairs), 7.4 M SNPs and over 200 clinical variables. KiT-GENIE represents an accurate snapshot of kidney transplantation clinical practice in Nantes between 2002 and 2018, with an enrichment in living kidney donors (17%) and recipients with focal segmental glomerulosclerosis (4%). Recipients were predominantly male (63%), of European ancestry (93%), with a mean age of 51yo and 86% experienced their first graft over the study period. D/R pairs were 93% from European ancestry, and 95% pairs exhibited at least one HLA allelic mismatch. The mean follow-up time was 6.7 years with a hindsight up to 25 years. Recipients experienced biopsy-proven rejection and graft loss for 16.6% and 21.3%, respectively. KiT-GENIE constitutes one of the largest kidney transplantation genetic cohorts worldwide to date. It includes homogeneous high-quality clinical and genetic data for donors and recipients, hence offering a unique opportunity to investigate immunogenetic and genetic factors, as well as donor-recipient interactions and mismatches involved in rejection, graft survival, primary disease recurrence and other comorbidities.

Fig. 1. Building the KiT-GENIE DNA biocollection and GWAS SNP data.

A Establishment of the KiT-GENIE DNA biocollection. 5946 individuals were initially extracted from DIVAT Nantes for investigation of DNA samples. 1222 people were excluded due to missing or deteriorated DNA samples, and DNA was collected for 4723 individuals. Single deceased D for whom R DNA could not be retrieved (n = 147) were excluded from GWAS genotyping. As a result, 4577 individuals were genotyped, but 360 individuals were then excluded due to failed experiments or GWAS QC procedures. Finally, 4217 individuals with accurate genomic and clinical data were included in the KiT-GENIE biocollection. It is important to note that some recipients received multiple grafts and that some deceased donors have provided an organ to two different recipients, therefore impacting the number of pairs. B Analytical steps of GWAS genotyping data processing. The Axiom PMRA GWAS genotyping chip covers 902,506 SNPs. 831,213 SNPs passed the primary technological QC steps. Following the standard GWAS guidelines, 161,185 independent variants were used to run the PCA excluding SNPs on sexual chromosomes, from the highly polymorphic HLA region, or in high LD level. 374,743 frequent high-quality SNPs were included in the imputation pipeline to generate a total of 7,434,999 SNPs with high accuracy. C Common SNP enrichment through SNP imputation. Before imputation, we observed an enrichment in rare functional genetic variants (MAF < 1%) in accordance with the Axiom PMRA GWAS genotyping chip design. After imputation, we significantly increased the number of SNPs with a MAF > 1% available for subsequent association testing. QC quality control, PCA Principal component analysis, LD linkage disequilibrium, MAF minor allele frequency, HWE Hardy-Weinberg equilibrium, 1KGP 1000 Genomes Project.

Fig. 2. Distribution of KiT-GENIE recipients according to the year of graft.

KiT-GENIE patients were mostly transplanted between 2002 and 2018. Due to the enrichment in FSGS recipients (circles) and LKD (triangles), we have 8 patients transplanted between 1984 and 1999, whose native kidney disease was idiopathic FSGS and who underwent a subsequent transplant after the 2000s, and 23 patients transplanted after 2018 who received a graft from a LKD. Recipients without native FSGS kidney disease and who received a kidney from a deceased donor are depicted as “Other recipients” (square). In addition, the progressive transition from paper-based to electronic medical records in the early 2000s led to a low number of DNA samples retrieved in 2000–2001. FSGS Focal Segmental GlomeruloSclerosis, LKD Living Kidney Donor.

Fig. 3. PCA projection of KiT-GENIE individuals with the 1000 Genomes Project reference individuals.

A PCA projection of KiT-GENIE recipients (black stars) with 1KGP individuals from 5 large reference populations (colour-coded circles). The proportion of KiT-GENIE recipients projected in each large reference population is indicated in the bottom left corner. B PCA projection of KiT-GENIE donors (black stars) with 1KGP individuals from 5 large reference populations (colour-coded circles). The proportion of KiT-GENIE donors projected in each large reference population is indicated in the bottom left corner. PCA, principal component analysis; 1KGP 1000 Genomes Project, AFR African, AMR American, EAS East Asian, SAS South Asian, EUR European.

Fig. 4. Genetic ancestry matching between donors and recipients.

A Distribution of genetic ancestry within the D/R pairs. The EUR/EUR pairs are predominant (92.53%). B Genetic ancestry distance for all D/R pairs projected in the 3D space composed of the first three principal components. Each recipient (blue node) is connected to their donor (red node) to represent the D/R genetic distance within the first 3 PCs dimensions. C Focus on genetic ancestry distance for the EUR/EUR matching D/R pairs (n = 1822). D Genetic ancestry distances for D/R pairs composed of at least one non-EUR individuals (n = 147). AFR African, AMR American, EAS East Asian, SAS South Asian, EUR European.