The Impact of Donor and Recipient Genetic Variation on Outcomes After Solid Organ Transplantation:a Scoping Review and Future Perspectives

At the outset of solid organ transplantation, genetic variation between donors and recipients was recognized as a major player in mechanisms such as allograft tolerance and rejection. Genome-wide association studies have been very successful in identifying novel variant-trait associations, but have been difficult to perform in the field of solid organ transplantation due to complex covariates, era effects, and poor statistical power for detecting donor-recipient interactions. To overcome a lack of statistical power, consortia such as the International Genetics and Translational Research in Transplantation Network have been established. Studies have focused on the consequences of genetic dissimilarities between donors and recipients and have reported associations between polymorphisms in candidate genes or their regulatory regions with transplantation outcomes. However, knowledge on the exact influence of genetic variation is limited due to a lack of comprehensive characterization and harmonization of recipients' or donors' phenotypes and validation using an experimental approach. Causal research in genetics has evolved from agnostic discovery in genome-wide association studies to functional annotation and clarification of underlying molecular mechanisms in translational studies. In this overview, we summarize how the recent advances and progresses in the field of genetics and genomics have improved the understanding of outcomes after solid organ transplantation

IBC CARe Microarray Allelic Population Prevalences in an American Indian Population

Background: The prevalence of variant alleles among single nucleotide polymorphisms (SNPs) is not well known for many minority populations. These population allele frequencies (PAFs) are necessary to guide genetic epidemiology studies and to understand the population specific contribution of these variants to disease risk. Large differences in PAF among certain functional groups of genes could also indicate possible selection pressure or founder effects of interest. The 50K SNP, custom genotyping microarray (CARe) was developed, focusing on about 2,000 candidate genes and pathways with demonstrated pathophysiologic influence on cardiovascular disease (CVD). Methods: The CARe microarray was used to genotype 216 unaffected controls in a study of pre-eclampsia among a Northern Plains, American Indian tribe. The allelic prevalences of 34,240 SNPs suitable for analysis, were determined and compared with corresponding HapMap prevalences for the Caucasian population. Further analysis was conducted to compare the frequency of statistically different prevalences among functionally related SNPs, as determined by the DAVID Bioinformatics Resource. Results: Of the SNPs with PAFs in both datasets, 9.8%,37.2% and 47.1% showed allele frequencies among the American Indian population greater than, less than and either greater or less than (respectively) the HapMap Caucasian population. The 2,547 genes were divided into 53 functional groups using the highest stringency criteria. While none of these groups reached the Bonferroni corrected p value of 0.00094, there were 7 of these 53 groups with significantly more or less differing PAFs, each with a probability of less than 0.05 and an overall probability of 0.0046. Conclusion: In comparison to the HapMap Caucasian population, there are substantial differences in the prevalence among an American Indian community of SNPs related to CVD. Certain functional groups of genes and related SNPs show possible evidence of selection pressure or founder effects

Gene-centric meta-analyses of 108,912 individuals confirm known body mass index loci and reveal three novel signals

Recent genetic association studies have made progress in uncovering components of the genetic architecture of body mass index (BMI). We used the ITMAT-Broad-CARe (IBC) array comprising up to 49,320 single nucleotide polymorphisms (SNPs) across ~2,100 metabolic and cardiovascular-related loci to genotype up to 108,912 individuals of European ancestry (EA), African Americans, Hispanics, and East Asians, from 46 studies, to provide additional insight into SNPs underpinning BMI. We used a five-phase study design: Phase I focused on meta-analysis of EA studies providing individual level genotype data; Phase II performed a replication of cohorts providing summary level EA data; Phase III meta-analyzed results from the first two phases; associated SNPs from Phase III were used for replication in Phase IV; finally in Phase V, a multi-ethnic meta-analysis of all samples from four ethnicities was performed. At an array-wide significance (P<2.40E-06), we identify novel BMI associations in loci TOMM40-APOE-APOC1 (rs2075650, P=2.95E-10), SREBF2 (a sterol regulatory element binding transcription factor gene, rs5996074, P=9.43E-07) and NTRK2 (a BDNF receptor, rs1211166, P=1.04E-06) in the Phase IV meta-analysis. Of ten loci with previous evidence for BMI association represented on IBC array, eight were replicated, with the remaining two showing nominal significance. Conditional analyses revealed two independent BMI associated signals in BDNF and MC4R regions. Of the 11 array-wide significant SNPs, three are associated with gene expression levels in both primary B-cells and monocytes; with rs4788099 in SH2B1 notably being associated with the expression of multiple genes in cis. These multi-ethnic meta-analyses expand our knowledge of BMI genetics

Harnessing publicly available genetic data to prioritize lipid modifying therapeutic targets for prevention of coronary heart disease based on dysglycemic risk

Therapeutic interventions that lower LDL-cholesterol effectively reduce the risk of coronary artery disease (CAD). However, statins, the most widely prescribed LDL-cholesterol lowering drugs, increase diabetes risk. We used genome-wide association study (GWAS) data in the public domain to investigate the relationship of LDL-C and diabetes and identify loci encoding potential drug targets for LDL-cholesterol modification without causing dysglycemia. We obtained summary-level GWAS data for LDL-C from GLGC, glycemic traits from MAGIC, diabetes from DIAGRAM and CAD from CARDIoGRAMplusC4D consortia. Mendelian randomization analyses identified a one standard deviation (SD) increase in LDL-C caused an increased risk of CAD (odds ratio [OR] 1.63 (95 % confidence interval [CI] 1.55, 1.71), which was not influenced by removing SNPs associated with diabetes. LDL-C/CAD-associated SNPs showed consistent effect directions (binomial P = 6.85 × 10−5). Conversely, a 1-SD increase in LDL-C was causally protective of diabetes (OR 0.86; 95 % CI 0.81, 0.91), however LDL-cholesterol/diabetes-associated SNPs did not show consistent effect directions (binomial P = 0.15). HMGCR, our positive control, associated with LDL-C, CAD and a glycemic composite (derived from GWAS meta-analysis of four glycemic traits and diabetes). In contrast, PCSK9, APOB, LPA, CETP, PLG, NPC1L1 and ALDH2 were identified as “druggable” loci that alter LDL-C and risk of CAD without displaying associations with dysglycemia. In conclusion, LDL-C increases the risk of CAD and the relationship is independent of any association of LDL-C with diabetes. Loci that encode targets of emerging LDL-C lowering drugs do not associate with dysglycemia, and this provides provisional evidence that new LDL-C lowering drugs (such as PCSK9 inhibitors) may not influence risk of diabetes

Identification of common genetic variation that modulates alternative splicing

Alternative splicing of genes is an efficient means of generating variation in protein function. Several disease states have been associated with rare genetic variants that affect splicing patterns. Conversely, splicing efficiency of some genes is known to vary between individuals without apparent ill effects. What is not clear is whether commonly observed phenotypic variation in splicing patterns, and hence potential variation in protein function, is to a significant extent determined by naturally occurring DNA sequence variation and in particular by single nucleotide polymorphisms (SNPs). In this study, we surveyed the splicing patterns of 250 exons in 22 individuals who had been previously genotyped by the International HapMap Project. We identified 70 simple cassette exon alternative splicing events in our experimental system; for six of these, we detected consistent differences in splicing pattern between individuals, with a highly significant association between splice phenotype and neighbouring SNPs. Remarkably, for five out of six of these events, the strongest correlation was found with the SNP closest to the intron-exon boundary, although the distance between these SNPs and the intron-exon boundary ranged from 2 bp to greater than 1,000 bp. Two of these SNPs were further investigated using a minigene splicing system, and in each case the SNPs were found to exert cis-acting effects on exon splicing efficiency in vitro. The functional consequences of these SNPs could not be predicted using bioinformatic algorithms. Our findings suggest that phenotypic variation in splicing patterns is determined by the presence of SNPs within flanking introns or exons. Effects on splicing may represent an important mechanism by which SNPs influence gene function

Two Variants of the C-Reactive Protein Gene Are Associated with Risk of Pre-Eclampsia in an American Indian Population

Background: The etiology of pre-eclampsia (PE) is unknown; but it is accepted that normal pregnancy represents a distinctive challenge to the maternal immune system. C-reactive protein is a prominent component of the innate immune system; and we previously reported an association between PE and the CRP polymorphism, rs1205. Our aim was to explore the effects of additional CRP variants. The IBC (Cardiochip) genotyping microarray focuses on candidate genes and pathways related to the pathophysiology of cardiovascular disease. Methods: This study recruited 140 cases of PE and 270 matched controls, of which 95 cases met criteria as severe PE, from an American Indian community. IBC array genotypes from 10 suitable CRP SNPs were analyzed. A replication sample of 178 cases and 427 controls of European ancestry was also genotyped. Results: A nominally significant difference (p value <0.05) was seen in the distribution of discordant matched pairs for rs3093068; and Bonferroni corrected differences (P<0.005) were seen for rs876538, rs2794521, and rs3091244. Univariate conditional logistic regression odds ratios (OR) were nominally significant for rs3093068 and rs876538 models only. Multivariate logistic models with adjustment for mother's age, nulliparity and BMI attenuated the effect (OR 1.58, P = 0.066, 95% CI 0.97–2.58) for rs876538 and (OR 2.59, P = 0.050, 95% CI 1.00–6.68) for rs3093068. An additive risk score of the above two risk genotypes shows a multivariate adjusted OR of 2.04 (P = 0.013, 95% CI 1.16–3.56). The replication sample also demonstrated significant association between PE and the rs876538 allele (OR = 1.55, P = 0.01, 95% CI 2.16–1.10). We also show putative functionality for the rs876538 and rs3093068 CRP variants. Conclusion: The CRP variants, rs876538 and rs3093068, previously associated with other cardiovascular disease phenotypes, show suggestive association with PE in this American Indian population, further supporting a possible role for CRP in PE