New developments in the genetics, pathogenesis, and therapy of IgA nephropathy

Recent years have brought notable progress in the field of IgA nephropathy. Here, we highlight important new directions and latest developments, including successful discovery of several genetic susceptibility loci, formulation of the multihit pathogenesis model, introduction of the Oxford pathology scoring system, and formalization of the Kidney Disease Improving Global Outcomes (KDIGO) consensus treatment guidelines. We focus on the latest genetic findings that confirm a strong contribution of inherited factors and explain some of the geoethnic disparities in disease susceptibility. Most IgA nephropathy susceptibility loci discovered to date encode genes involved in the maintenance of the intestinal epithelial barrier and response to mucosal pathogens. The concerted pattern of interpopulation allelic differentiation across all genetic loci parallels the disease prevalence and correlates with variation in local pathogens, suggesting that multilocus adaptation might have shaped the present-day landscape of IgA nephropathy. Importantly, the 'Intestinal Immune Network for IgA Production' emerged as one of the new targets for potential therapeutic intervention. We place these findings in the context of the multihit pathogenesis model and existing knowledge of IgA immunobiology. Lastly, we provide our perspective on the existing treatment options, discuss areas of clinical uncertainty, and outline ongoing clinical trials and translational studies.Kidney International advance online publication, 16 September 2015; doi:10.1038/ki.2015.252

Epidemiologic characteristics of amniotic band sequence with limb malformations without body wall defect: data from the Polish Registry of Congenital Malformations

Abstract Amniotic Band Sequence (ABS) is a rare disruptive condition, with a variable spectrum of congenital defects caused by fibrous bands emerging as a result of amniotic rupture in the first trimester of gestation. Several factors, such as young parental age, primigravidity, febrile maternal illness, and drug use in the first trimester, were postulated to have substantial influence on ABS prevalence rate. We aimed our study to determine the prevalence of ABS with limb defects, but no body wall affectation, in a Polish population. We also examined the influence of different parental, gestational and environmental factors on the ABS prevalence value, and assessed the rate of gestational complications associated with this disorder. Among 1 706 639 births surveilled between 1998 and 2005, 36 liveborn infants with ABS-L were reported to the Polish Registry of Congenital Malformations, giving a global prevalence for a Polish population of 1 per 47 619 livebirths. We found that young maternal age, young paternal age, and primigravidity significantly increase the risk of ABS-L, when their effect was analyzed independently. However, because of a close relationship of these variables, we analyzed their mutually adjusted effect using conditional logistic regression models, and found that young maternal age proved the strongest risk factor for ABS-L (p = 0.0508). The condition was also more prevalent in infants with low birthweight (OR = 5.71; p < 0.0001). Since gestational complications are often relevant to maternal age and birth order, we introduced an adjustment for these variables, and found that respiratory tract infections and vaginal bleeding/spotting convey approximately fourfold increased risk of ABS-L (OR = 3.72/p = 0.0058 and OR = 3.70/p = 0.0014 respectively)

A Panel of Serum Biomarkers Differentiates IgA Nephropathy from Other Renal Diseases

Background and Objectives: There is increasing evidence that galactose-deficient IgA1 (Gd-IgA1) and Gd-IgA1-containing immune complexes are important for the pathogenesis of IgA nephropathy (IgAN). In the present study, we assessed a novel noninvasive multi-biomarker approach in the diagnostic test for IgAN. Materials and Methods: We compared serum levels of IgA, IgG, Gd-IgA1, Gd-IgA1-specific IgG and Gd-IgA1-specific IgA in 135 IgAN patients, 79 patients with non-IgAN chronic kidney disease (CKD) controls and 106 healthy controls. Serum was collected at the time of kidney biopsy from all IgAN and CKD patients. Results: Each serum marker was significantly elevated in IgAN patients compared to CKD (P<0.001) and healthy controls (P<0.001). While 41% of IgAN patients had elevated serum Gd-IgA1 levels, 91% of these patients exhibited Gd-IgA1-specific IgG levels above the 90th percentile for healthy controls (sensitivity 89%, specificity 92%). Although up to 25% of CKD controls, particularly those with immune-mediated glomerular diseases including lupus nephritis, also had elevated serum levels of Gd-IgA1-specific IgG, most IgAN patients had elevated levels of Gd-IgA1-specific antibody of both isotypes. Serum levels of Gd-IgA1-specific IgG were associated with renal histological grading. Furthermore, there was a trend toward higher serum levels of Gd-IgA1-specific IgG in IgAN patients with at least moderate proteinuria (≥1.0 g/g), compared to patients with less proteinuria. Conclusions Serum levels of Gd-IgA1-specific antibodies are elevated in most IgAN patients, and their assessment, together with serum levels of Gd-IgA1, improves the specificity of the assays. Our observations suggest that a panel of serum biomarkers may be helpful in differentiating IgAN from other glomerular diseases

BIGKnock: fine-mapping gene-based associations via knockoff analysis of biobank-scale data

We propose BIGKnock (BIobank-scale Gene-based association test via Knockoffs), a computationally efficient gene-based testing approach for biobank-scale data, that leverages long-range chromatin interaction data, and performs conditional genome-wide testing via knockoffs. BIGKnock can prioritize causal genes over proxy associations at a locus. We apply BIGKnock to the UK Biobank data with 405,296 participants for multiple binary and quantitative traits, and show that relative to conventional gene-based tests, BIGKnock produces smaller sets of significant genes that contain the causal gene(s) with high probability. We further illustrate its ability to pinpoint potential causal genes at $$\sim 80\%$$ ∼ 80 % of the associated loci

Cystatin C is associated with adverse COVID-19 outcomes in diverse populations

COVID-19 has highly variable clinical courses. The search for prognostic host factors for COVID-19 outcome is a priority. We performed logistic regression for ICU admission against a polygenic score (PGS) for Cystatin C (CyC) production in patients with COVID-19. We analyzed the predictive value of longitudinal plasma CyC levels in an independent cohort of patients hospitalized with COVID-19. In four cohorts spanning European and African ancestry populations, we identified a significant association between CyC-production PGS and odds of critical illness (n cases=2,319), with the strongest association captured in the UKB cohort (OR 2.13, 95% CI 1.58-2.87, p=7.12e-7). Plasma proteomics from an independent cohort of hospitalized COVID-19 patients ( n cases = 131) demonstrated that CyC production was associated with COVID-specific mortality (p=0.0007). Our findings suggest that CyC may be useful for stratification of patients and it has functional role in the host response to COVID-19.Peer reviewe

Predicting Progression of IgA Nephropathy: New Clinical Progression Risk Score

IgA nephropathy (IgAN) is a common cause of end-stage renal disease (ESRD) in Asia. In this study, based on a large cohort of Chinese patients with IgAN, we aim to identify independent predictive factors associated with disease progression to ESRD. We collected retrospective clinical data and renal outcomes on 619 biopsy-diagnosed IgAN patients with a mean follow-up time of 41.3 months. In total, 67 individuals reached the study endpoint defined by occurrence of ESRD necessitating renal replacement therapy. In the fully adjusted Cox proportional hazards model, there were four baseline variables with a significant independent effect on the risk of ESRD. These included: eGFR [HR = 0.96(0.95–0.97)], serum albumin [HR = 0.47(0.32–0.68)], hemoglobin [HR = 0.79(0.72–0.88)], and SBP [HR = 1.02(1.00–1.03)]. Based on these observations, we developed a 4-variable equation of a clinical risk score for disease progression. Our risk score explained nearly 22% of the total variance in the primary outcome. Survival ROC curves revealed that the risk score provided improved prediction of ESRD at 24th, 60th and 120th month of follow-up compared to the three previously proposed risk scores. In summary, our data indicate that IgAN patients with higher systolic blood pressure, lower eGFR, hemoglobin, and albumin levels at baseline are at a greatest risk of progression to ESRD. The new progression risk score calculated based on these four baseline variables offers a simple clinical tool for risk stratification

Identification of a shared genetic risk locus for Kawasaki disease and immunoglobulin A vasculitis by a cross-phenotype meta-analysis.

Objectives: Combining of genomic data of different pathologies as a single phenotype has emerged as a useful strategy to identify genetic risk loci shared among immune-mediated diseases. Our study aimed to increase our knowledge of the genetic contribution to Kawasaki disease (KD) and IgA vasculitis (IgAV) by performing the first comprehensive large-scale analysis on the genetic overlap between them. Methods: A total of 1190 vasculitis patients and 11 302 healthy controls were analysed. First, in the discovery phase, genome-wide data of 405 KD patients and 6252 controls and 215 IgAV patients and 1324 controls, all of European origin, were combined using an inverse variance meta-analysis. Second, the top associated polymorphisms were selected for replication in additional independent cohorts (570 cases and 3726 controls). Polymorphisms with P-values ¿5 × 10-8 in the global IgAV-KD meta-analysis were considered as shared genetic risk loci. Results: A genetic variant, rs3743841, located in an intron of the NAGPA gene, reached genome-wide significance in the cross-disease meta-analysis (P = 8.06 × 10-10). Additionally, when IgAV was individually analysed, a strong association between rs3743841 and this vasculitis was also evident [P = 1.25 × 10-7; odds ratio = 1.47 (95% CI 1.27, 1.69)]. In silico functional annotation showed that this polymorphism acts as a regulatory variant modulating the expression levels of the NAGPA and SEC14L5 genes. Conclusion: We identified a new risk locus with pleiotropic effects on the two childhood vasculitides analysed. This locus represents the strongest non-HLA signal described for IgAV to date.This work was supported by the Cooperative Research Thematic Network programme (RD16/0012/0013 and RD16/0012/0009) from the Instituto de Salud Carlos III (ISCIII, Spanish Ministry of Economy, Industry and Competitiveness). A.M. is a recipient of a Miguel Servet fellowship (CP17/00008) from the ISCIII (Spanish Ministry of Economy, Industry and Competitiveness). R.L.M. is a recipient of a Miguel Servet type I programme fellowship from ISCIII (Spanish Ministry of Economy, Industry and Competitiveness), co-funded by European Social Fund (ESF) (‘Investing in your future’) (grant CP16/00033)

Novel EDGE encoding method enhances ability to identify genetic interactions

Assumptions are made about the genetic model of single nucleotide polymorphisms (SNPs) when choosing a traditional genetic encoding: additive, dominant, and recessive. Furthermore, SNPs across the genome are unlikely to demonstrate identical genetic models. However, running SNP-SNP interaction analyses with every combination of encodings raises the multiple testing burden. Here, we present a novel and flexible encoding for genetic interactions, the elastic data-driven genetic encoding (EDGE), in which SNPs are assigned a heterozygous value based on the genetic model they demonstrate in a dataset prior to interaction testing. We assessed the power of EDGE to detect genetic interactions using 29 combinations of simulated genetic models and found it outperformed the traditional encoding methods across 10%, 30%, and 50% minor allele frequencies (MAFs). Further, EDGE maintained a low false-positive rate, while additive and dominant encodings demonstrated inflation. We evaluated EDGE and the traditional encodings with genetic data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes: age-related macular degeneration (AMD), age-related cataract, glaucoma, type 2 diabetes (T2D), and resistant hypertension. A multi-encoding genome-wide association study (GWAS) for each phenotype was performed using the traditional encodings, and the top results of the multi-encoding GWAS were considered for SNP-SNP interaction using the traditional encodings and EDGE. EDGE identified a novel SNP-SNP interaction for age-related cataract that no other method identified: rs7787286 (MAF: 0.041;intergenic region of chromosome 7)-rs4695885 (MAF: 0.34;intergenic region of chromosome 4) with a Bonferroni LRT p of 0.018. A SNP-SNP interaction was found in data from the UK Biobank within 25 kb of these SNPs using the recessive encoding: rs60374751 (MAF: 0.030) and rs6843594 (MAF: 0.34) (Bonferroni LRT p: 0.026). We recommend using EDGE to flexibly detect interactions between SNPs exhibiting diverse action. Author summary Although traditional genetic encodings are widely implemented in genetics research, including in genome-wide association studies (GWAS) and epistasis, each method makes assumptions that may not reflect the underlying etiology. Here, we introduce a novel encoding method that estimates and assigns an individualized data-driven encoding for each single nucleotide polymorphism (SNP): the elastic data-driven genetic encoding (EDGE). With simulations, we demonstrate that this novel method is more accurate and robust than traditional encoding methods in estimating heterozygous genotype values, reducing the type I error, and detecting SNP-SNP interactions. We further applied the traditional encodings and EDGE to biomedical data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes, and EDGE identified a novel interaction for age-related cataract not detected by traditional methods, which replicated in data from the UK Biobank. EDGE provides an alternative approach to understanding and modeling diverse SNP models and is recommended for studying complex genetics in common human phenotypes

Genome-Wide Study Updates in the International Genetics and Translational Research in Transplantation Network (iGeneTRAiN)

The prevalence of end-stage renal disease (ESRD) and the number of kidney transplants performed continues to rise every year, straining the procurement of deceased and living kidney allografts and health systems. Genome-wide genotyping and sequencing of diseased populations have uncovered genetic contributors in substantial proportions of ESRD patients. A number of these discoveries are beginning to be utilized in risk stratification and clinical management of patients. Specifically, genetics can provide insight into the primary cause of chronic kidney disease (CKD), the risk of progression to ESRD, and post-transplant outcomes, including various forms of allograft rejection. The International Genetics & Translational Research in Transplantation Network (iGeneTRAiN), is a multi-site consortium that encompasses >45 genetic studies with genome-wide genotyping from over 51,000 transplant samples, including genome-wide data from >30 kidney transplant cohorts (n = 28,015). iGeneTRAiN is statistically powered to capture both rare and common genetic contributions to ESRD and post-transplant outcomes. The primary cause of ESRD is often difficult to ascertain, especially where formal biopsy diagnosis is not performed, and is unavailable in ∼2% to >20% of kidney transplant recipients in iGeneTRAiN studies. We overview our current copy number variant (CNV) screening approaches from genome-wide genotyping datasets in iGeneTRAiN, in attempts to discover and validate genetic contributors to CKD and ESRD. Greater aggregation and analyses of well phenotyped patients with genome-wide datasets will undoubtedly yield insights into the underlying pathophysiological mechanisms of CKD, leading the way to improved diagnostic precision in nephrology

The genetic architecture of membranous nephropathy and its potential to improve non-invasive diagnosis

Membranous Nephropathy (MN) is a rare autoimmune cause of kidney failure. Here we report a genome-wide association study (GWAS) for primary MN in 3,782 cases and 9,038 controls of East Asian and European ancestries. We discover two previously unreported loci, NFKB1 (rs230540, OR = 1.25, P = 3.4 × 10−12) and IRF4 (rs9405192, OR = 1.29, P = 1.4 × 10−14), fine-map the PLA2R1 locus (rs17831251, OR = 2.25, P = 4.7 × 10−103) and report ancestry-specific effects of three classical HLA alleles: DRB1*1501 in East Asians (OR = 3.81, P = 2.0 × 10−49), DQA1*0501 in Europeans (OR = 2.88, P = 5.7 × 10−93), and DRB1*0301 in both ethnicities (OR = 3.50, P = 9.2 × 10−23 and OR = 3.39, P = 5.2 × 10−82, respectively). GWAS loci explain 32% of disease risk in East Asians and 25% in Europeans, and correctly re-classify 20–37% of the cases in validation cohorts that are antibody-negative by the serum anti-PLA2R ELISA diagnostic test. Our findings highlight an unusual genetic architecture of MN, with four loci and their interactions accounting for nearly one-third of the disease risk