Is IgA Nephropathy (IgAN) a Familial or Sporadic Disease?

From decades ago, genetic analysis in sporadic IgAN had been performed. Initially, the majority of them were case-control association studies by using classical techniques, such as restriction fragment length polymorphism (RFLP) to measure allele frequencies of one or a few genetic polymorphisms of functional candidate [20–26]. Although these studies may have contributed to our better understanding of the mechanisms of the initiation, as well as progression of the disease, not all the results had been confirmed by replication studies, and majority of them were not convincing enough to influence the clinical diagnosis and practice of this disease.

Recently, using microarray DNA analysis methods, genome-wide association studies (GWAS) of sporadic IgAN have been performed using large cohorts of more than thousands of cases with IgAN and controls. These studies have identified multiple susceptibility loci, providing an insight into the genetic architecture of this disease [27–29]. They demonstrated strong associations of the major histocompatibility (MHC) locus and four non-HLA loci, including chromosome 1q32, a common deletion of the complement factor H-related CFHR3 and CFHR1 genes (CFHR3,1–delta); 8p23, the α-defensin (DEFA) gene cluster; 17p23 (including TNFSF13); and 22q12 (including HORMAD2 and several other genes).

More recently, by international collaboration, the largest GWAS has been performed in 2,747 biopsy-confirmed cases and 3,952 controls as the discovery cohorts (stage I), and subsequently, top signals, defined by P < 5 × 10⁻⁵, were genotyped in an additional 4,911 cases and 9,002 controls (stage II), followed by meta-analysis to identify genome-wide significant signals across the combined cohorts of 20,612 individuals. This two-stage design was adequately powered to detect ORs as small as 1.15–1.25. This study has identified six novel genome-wide significant associations including genes as follows: four in ITGAM–ITGAX (encoding leukocyte-specific integrin αX, a component of complement receptor 4 (CR4)), VAV3 (encoding a guanine nucleotide exchange factor for Rho GTPases that is important for B and T lymphocyte development and antigen presentation), and CARD9 (encoding caspase recruitment domain-containing protein 9, an adapter protein that promotes activation of NF-κB in macrophages) and two new independent signals at HLA–DQB1 and DEFA, replicating the nine previously reported signals, including known SNPs in the HLA–DQB1 and DEFA loci (Table 3.2). The cumulative burden of risk alleles was strongly associated with age at disease onset. Interestingly, most loci are either directly associated with risk of inflammatory bowel disease (IBD) or maintenance of the intestinal epithelial barrier and response to mucosal pathogens. The geospatial distribution of risk alleles is highly suggestive of multi-locus adaptation, and genetic risk correlates strongly with variation in local pathogens, particularly helminth diversity, suggesting a possible role for host-intestinal pathogen interactions in shaping the genetic landscape of IgAN [8, 28, 30].

An additional GWAS of IgAN in Han Chinese, which was comprising 8,313 cases and 19,680 controls, has most recently been reported [31]. The authors identified novel associations at ST6GAL1 and ACCS, and their risk variants were strongly associated with mRNA expression levels in blood cells. Many studies described aberrant glycosylation of IgA1 in sporadic IgAN, and in also familial IgAN, that defect was reported to be inherited [32]. The associations of ST6GAL1 elucidated by GWAS might explain the genetic basis of defect of glycosylation in IgAN.

Indeed, it is obvious that recent genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits including IgAN and that these studies have provided valuable insights into their genetic architecture. However in general, most reported variants confer relatively small increments in risk and explain only a small proportion of familial clustering, leading many to question how the remaining, “missing” heritability can be explained. The underlying rationale for GWAS is the “common disease, common variant” hypothesis, positing that common diseases are attributable in part to allelic variants present in more than 1–5 % of the population. It has been suggested that low-frequency variants of intermediate effect might also contribute to explaining missing heritability that should be tractable through large meta-analyses and/or imputation of genome-wide association data to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment (Fig. 3.1) [33