Visual Abstract
Abstract
Background Genetic variation in complement genes is a predisposing factor for atypical hemolytic uremic syndrome (aHUS), a life-threatening thrombotic microangiopathy, however interpreting the effects of genetic variants is challenging and often ambiguous.
Methods We analyzed 93 complement and coagulation genes in 400 patients with aHUS, using as controls 600 healthy individuals from Iowa and 63,345 non-Finnish European individuals from the Genome Aggregation Database. After adjusting for population stratification, we then applied the Fisher exact, modified Poisson exact, and optimal unified sequence kernel association tests to assess gene-based variant burden. We also applied a sliding-window analysis to define the frequency range over which variant burden was significant.
Results We found that patients with aHUS are enriched for ultrarare coding variants in the CFH, C3, CD46, CFI, DGKE, and VTN genes. The majority of the significance is contributed by variants with a minor allele frequency of <0.1%. Disease-related variants tend to occur in specific complement protein domains of FH, CD46, and C3. We observed no enrichment for multiple rare coding variants in gene-gene combinations.
Conclusions In known aHUS-associated genes, variants with a minor allele frequency >0.1% should not be considered pathogenic unless valid enrichment and/or functional evidence are available. VTN, which encodes vitronectin, an inhibitor of the terminal complement pathway, is implicated as a novel aHUS-associated gene. Patients with aHUS are not enriched for multiple rare variants in complement genes. In aggregate, these data may help in directing clinical management of aHUS.
Atypical hemolytic uremic syndrome (aHUS) defines a spectrum of thrombotic microangiopathies (TMAs) characterized by hemolytic anemia, thrombocytopenia, and acute renal injury not caused by Shiga toxin-producing Escherichia coli or ADAMTS13 deficiency.1,2 It is ultrarare, with an incidence of approximately 0.5 per million per year and until the introduction of eculizumab, a humanized mAb against C5 that blocks the terminal pathway of the complement cascade, it carried a very poor prognosis.3,4 As the quintessential complement-mediated disease, aHUS develops in people carrying predisposing genetic abnormalities in complement genes after exposure to a host of triggering/causal events that include infection, drugs, malignancy, transplantation, and pregnancy.2
Genetic studies in patients with a clinical diagnosis of aHUS identify mutations in alternative pathway-related genes in up to half of cases.5–9 The list of extensively reported aHUS genes includes CFH (implicated in approximately 25% of patients), CD46 (approximately 10%), C3 (approximately 6%), CFI (approximately 6%), CFB (approximately 2%), THBD (approximately 2%), and a noncomplement exception, DGKE (approximately 3%).2 Autoantibodies against factor H (FHAA) account for 5%–13% of cases and are associated with the absence of both copies of CFHR1.10 If a genetic variation is found, it is often considered a predisposing factor rather than a direct cause of aHUS. This distinction reflects the high variability in disease penetrance, with the notable exception being pathogenic variants in DGKE, which follow an autosomal recessive inheritance pattern.11–14
The term “primary aHUS” has been proposed by some clinicians to designate patients with aHUS who carry a genetic abnormality in complement genes; however, the distinction between primary and secondary aHUS is challenging for several reasons. First, significant complement variants are not identified in a large portion of the patients with aHUS who respond to terminal complement-blocking treatment.3 Second, in many persons who carry genetic variants in complement genes, the disease does not develop in the absence of triggering events. Third, aHUS shows variable penetrance, making it difficult to interpret the role many genetic variants play in disease. Fourth, crosstalk between the complement and coagulation pathways makes it challenging to provide an integrated interpretation of genetic results. Lastly, a TMA lesion is a component of many diseases, which confounds the diagnosis of aHUS.1,2,5
When genetic variants are identified in a patient with aHUS, it is critically important to determine their clinical significance, as it has a bearing on long-term anticomplement therapy. Purported disease variants are often defined as such because they are not detected in a few hundred healthy controls. This approach has been challenged by publications showing that ultrarare but benign variants are not uncommon.15 For example, Marinozzi et al.16 demonstrated experimentally that nine out of 15 reported CFB gene mutations were unrelated to aHUS pathogenesis. Novel variants have also been identified in CFH that may be unrelated to aHUS.17 Although these reports support the value of functional studies to assess variant impact, these studies are labor intensive and difficult, making functional assessment impractical in every instance.
Phenotypic variability in presentation adds another layer of complexity. A recent collaborative, multi-institution study failed to find enrichment for rare genetic variants in the CFB, THBD, and PLG genes in patients with aHUS compared with controls from the Exome Aggregation Consortium database.18 That study, however, did not control for population stratification, which affects rare variant burden (Supplemental Figure 1). In addition, only a few genes were considered. Because the genetic landscape of aHUS is changing and other complement genes like C4BPA,19 C7,20 and CFHR2,21 and noncomplement genes like CBL, INF2,22–24 MMACHC,25–27 CLU,28 PLG,29 and F12,30 have been implicated in pathogenesis, we sought to analyze rare coding variant burden in a large aHUS cohort in which we control for population stratification, integrate two control cohorts, and study a large number of genes.
Methods
Participants
Patients referred to the Molecular Otolaryngology and Renal Research Laboratories at the University of Iowa (UI) for a genetic evaluation for TMAs were enrolled in this study. Atypical HUS was diagnosed by the referring physicians on the basis of the presence of hemolytic anemia, thrombocytopenia, and renal injury, absence of Shiga toxin-producing E. coli, and ADAMTS13 activity >10%. Patients were screened for variants in 93 TMA-related genes (Supplemental Table 1) using a targeted genomic enrichment panel known as CasCADE/GRP.29,31 The UI control group comprised 600 unrelated European Americans (300 males and 300 females) screened by the SeqCap EZ whole-exome panel plus custom targeted regions (v1/v2; Roche Sequencing, Pleasanton, CA).32 Both cases and UI controls are genetically of European descent, with other ethnicities removed to decrease population stratification (Supplemental Figures 2 and 3). Relatedness analysis was done to eliminate close relatives. A second control cohort of 63,345 individuals was accessed by utilizing the non-Finnish European (NFE) population extracted from the Genome Aggregation Database (gnomAD).15 The study was approved by the Institutional Review Board of Carver College of Medicine at UI (IRB ID# 201502804).
Sequencing and Bioinformatics
Genomic DNA was extracted from whole blood using the Gentra Puregene Kit (QIAGEN, Valencia, CA) or Chemagic 360 instrument (PerkinElmer Inc., Waltham, MA). Targeted genomic enrichment was automated using the customized SureSelect Target Enrichment System (Agilent Technologies Inc., Santa Clara, CA) and the Zephyr Workstation (PerkinElmer), as described.29,31 Enriched libraries were pooled and sequenced on HiSeq 2500 or MiSeq Sequencers (Illumina Inc., San Diego, CA). Using GATK best practices, the in-house workflow integrated multiple tools including Trimmomatic (v0.36) for adaptor sequence removal,33 BWA mem (v0.7.15) for alignment to the human reference genome GRCh37/hg19,34 Picard Tools (v2.7.1; www.broadinstitute.github.io/picard) MarkDuplicates for PCR duplication removal, GATK (v3.7) BaseRecalibrator for recalibration, HaplotypeCaller for single nucleotide variations (SNVs) and insertions/deletions (indels) calling, and GenotypeGVCFs for joint genotyping on gVCF files.35 FastQC (www.bioinformatics.babraham.ac.uk/projects/fastqc) and Picard CollectHsMetrics were used to assess sequencing quality. Variants were annotated using Variant Effect Predictor (v84).36 The Human Gene Mutation Database (HGMD, v2016r4)37 and ClinVar (v20170228)38 were used to query reported disease mutations. Variant frequency in populations was annotated using gnomAD. Other operations on BAM and VCF file were performed using SAMtools,39 BCFtools (v1.5),40 and in-house scripts.
Sequencing quality was controlled at the sample and variant levels. Low quality was defined as (1) coverage under 1 million reads, (2) mean depth <30×, (3) theoretical sensitivity of heterozygous SNP detection <95% (Supplemental Figure 4, Supplemental Material), or (4) significant drift in the ratio of alternative/reference allele depth (Supplemental Figure 5). Using Sanger sequencing data, low-quality SNVs were defined as any of QD (quality-by-depth)<4.5, FS (Fisher strand score)>60, SOR (strand odds ratio)>3, MQ (root mean square of the mapping quality)<39.5, MQRankSum<−28, and ReadPosRankSum<−5.0; low-quality small indels were defined as any of QD<4.5, FS>200, and ReadPosRankSum<−20.0. CR1, C2, CFHR1, CFHR3, and C4A/C4B were removed from analysis because of ambiguous read alignments caused by high sequence homology.
Definition of Variants
On the basis of sequence ontology, variant functional impact was defined as: (1) “high” for non-sense, canonical splice-site SNVs and frameshift indels; (2) “moderate” for missense SNVs and in-frame indels; (3) “low” for synonymous SNVs; and (4) “modifier” for noncoding variants (Supplemental Table 2).41 Rarity was on the basis of minor allele frequency (MAF) in the NFE population, with common, rare, and ultrarare variants defined by MAFs of ≥1%, <1%, and <0.01%, respectively. Rare coding variants with high or moderate function impact were included in subsequent analyses. Variant pathogenicity was determined by absence in public databases, enrichment in the patient cohort, and well studied functional impacts (described in detail in the Supplemental Material). Computational prediction of variant effect was not applied (Supplemental Figure 6).
Multiplex Ligation-Dependent Probe Amplification
Copy number variation in the CFH-CFHRs genomic region was evaluated by multiplex ligation-dependent probe amplification using the SALSA MLPA Reagent Kit (MRC-Holland, Amsterdam, The Netherlands), as described.29 Five normal and three positive controls were included in each run.
Detection of FHAA
FHAA were detected by ELISA, as described.42
Statistical Analyses
Statistical analyses were completed using R software (v3.3.2). Population stratification was evaluated using EIGENSOFT (v7.2.1).43 Relatedness analysis was performed using VCFtools (v0.1.14).44 The association between aHUS and rare coding variant burden by gene was tested using several complementary methods. One-sided variant burden comparisons between patients with aHUS and NEF controls were performed using the Fisher exact and modified Poisson exact tests. The Poisson test compared expected and observed ratios of summed variant allele numbers in cases to the summed number in both cases and NFE controls (Equation 1). The expected ratio was derived from all variants regardless of functional impact, whereas the observed ratio was derived from the subset of rare coding variants. This ratio is more robust to potential bias within datasets caused by inconsistencies in experimental and analytic workflows (Supplemental Figure 1).45 After adjusting for multiple testing, P<0.05 and P<0.001 were considered suggestive and significant, respectively.
Optimal unified sequence kernel association test (SKAT-O), which combines burden and variance-component analyses, was performed using the SKAT package (v1.3.0) to compare patients with aHUS and UI controls.46 Linear weighted kernel, missing cut-off of 0.9 and β-weights were used to calculate the permutation P-value, with adjustment of covariates including age, sex, and principal components of population stratification. P<0.05 was considered significant.
A sliding window was applied to identify MAF ranges over which variant enrichment occurs. A window size of 0.001 was moved from 0 to 0.01 along the MAF axis in a step of 1e−6. Variants within the window were collapsed and applied to burden tests during each step, generating a set of P-values that reflected enrichment within specific MAF ranges (see animated Supplemental Material). Significance was crossvalidated between NFE and UI control cohorts, as well as across the four burden tests.
Enrichment of gene-gene combinations for rare coding variants was tested by a permutation analysis under the null hypothesis that variant combination is random and independent. Genotypes were randomly shuffled among samples to generate the number of gene-gene combinations per permutation. Empirical P-values were calculated after 100,000 permutations. P<0.05 was considered significant.
Data Sharing
Rare variants identified in this patient cohort are publicly available in the Database of Complement Gene Variants (http://www.complement-db.org/home.php).
Results
Summary of Genetic Variation
Atypical HUS was diagnosed in 510 out of 623 referrals. In this group of 510 patients, there were seven sequencing quality control failures, 93 ethnic outliers, and ten related samples (Figure 1). One control was excluded because of low sequencing quality. Analyses were completed on 400 patients with aHUS (228 males and 182 females, median age of 21.6 years) and 599 UI controls (299 males and 300 females). Male patients showed lower median age than females (14.8 versus 27.3; P=0.01; Supplemental Figure 7).
A total of 400 patients and 599 in-house controls were included in this study on the basis of diagnosis and after filtering for quality, population stratification and relatedness. *Five patients carried rare coding variants in complement genes and a homozygous deletion in CFHR3-CFHR1, and one patient carried a variant in CFB, a homozygous deletion in CFHR3-CFHR1 and FHAAs. No other overlap among CFHR fusion genes, FHAAs and rare variants in complement genes was observed (het, heterozygous; LP, likely pathogenic; P, pathogenic; TTP, thrombotic thrombocytopenic purpura; VUS, variant with uncertain significance).
A total of 2183 variants were identified and passed quality control filtering in the aHUS cohort (Table 1). Included in this number were 637 rare and 95 novel coding variants. There were 672 rare and 98 novel coding variants in UI controls. Several common variants in the F5, CFH, CFHR2, CD46, and MASP1 genes were significantly associated with aHUS (Supplemental Table 3).
Variants identified in patients with aHUS (n=400) and UI controls (n=599)
A total of 93 variants with MAF<0.1% were identified on 127 alleles in 105 patients in the known aHUS complement genes (CFH, CD46, C3, CFI, and CFB). CFH carried the highest number of variants (36 patients), followed by CD46 (24 patients), C3 (18 patients), CFI (nine patients), and CFB (six patients); 12 patients (11.4%) carried variants in more than one gene. Of the remaining 295 patients, four were homozygous or compound heterozygous for mutations in DGKE, six carried variants in PLG, and two carried variants in THBD. Homozygous deletion of CFHR3-CFHR1 or CFHR1 alone was found in 31 patients; 11 of these patients had FHAAs. FHAAs were also detected in five other patients. Fifteen different FHR fusion genes were identified (Supplemental Table 4). With the exception of six patients who carried variants in complement aHUS genes and were homozygous-deleted of CFHR3-CFHR1, there was no overlap across patient groups.
Rare Variant Burden by Fixed MAFs
Rare variant burden was examined across genes. Because of platform bias on indel calling, only SNVs were analyzed. Significant enrichment was confirmed in patients for rare coding variants in CFH, CD46, C3, and CFI genes across multiple burden tests (Table 2). CFB and PLG were significant only with MAF<0.01 as the threshold (Table 2). Significant enrichment in DGKE was confirmed by three tests, with the exception being the SKAT-O test with adjustment for population principle components, which may reflect subpopulation stratification in the DGKE group. Patients were not enriched for rare coding variants in CFHR5 and THBD, nor in the purported aHUS genes C4BPA, C7, MMACHC, CLU, CFHR2, and F12. Of other tested genes, only VTN was enriched for rare coding variants, nine of which were identified in 400 patients (2.25%; MAF<0.1%), compared with three variants in 599 UI controls (0.5%), and 619 variants in 63,345 NFE controls (0.97%). These differences for VTN were significant when the patient cohort was compared with UI controls and suggestive when compared with NEF controls after adjusting for multiple testing.
Comparison of rare coding SNV burden in patients with aHUS, UI controls, and NFE controls
Burden Analysis with MAF Sliding Windows
Sliding-window analysis defined MAF enrichment boundaries (Figure 2). Ultrarare/novel coding variants in the CFH, CD46, C3, CFI, and DGKE genes predominantly contributed to the significance burden. In the CFB and PLG genes, significance peaks were contributed by rs45484591 (CFB: p.Glu566Ala, aHUS MAF=3%, NFE MAF=0.99%, UI MAF=1%) and rs4252128 (PLG: p.Ala494Val, aHUS MAF=1.75%, NFE MAF=0.39%, UI MAF=0.33%). Significance burden in VTN was contributed predominantly by eight variants (nine alleles) with MAF<0.022%. On the basis of these data, variants predisposing to aHUS had an MAF<0.1%, with few exceptions.
Sliding windows analysis indicates significant enrichment for novel/ultrarare coding variants in CFH, CD46, C3, CFI, DGKE and VTN in patients with aHUS. A window size of 0.001 was moved from 0 to 0.01 in steps of 1e-6. Variants within each window were tested in patients with aHUS and the two control cohorts using four algorithms. Four sets of P-values are shown: black curve, SKAT-O test adjusting for population stratification in UI controls; yellow curve, SKAT-O test without this adjustment; red curve, Fisher exact test in NEF controls; blue curve, modified Poisson exact test in NEF controls; dashed horizontal lines, P=0.05 and P=0.001.
Reclassification of Reported Disease Mutations
Of 329 pathogenic aHUS variants listed by HGMD, 61 were replicated in this study. However, we downgraded ten (3.04%) variants in CFH, C3, CD46, and CFI reported as pathogenic to likely benign, on the basis of high MAF in the NFE group and other populations and absence of enrichment in patients with aHUS (Table 3).
aHUS variants reclassified from pathogenic to likely benign on the basis of MAF and lack of differential enrichment in patients
Enrichment of Disease Variants in Featured Domains
Disease variants reported in HGMD and identified in this study showed a distinct pattern of distribution across specific complement protein domains compared with variants in NFE controls. Significant enrichment for aHUS-related variants was found in short consensus repeat (SCR) 19 (Fisher exact P=0.004; odds ratio [OR], 2.71 with 95% confident interval [95% CI] 1.34 to 5.25) and SCR 20 (P=3.91e-12; OR, 7.53; 95% CI, 4.16 to 13.57) of FH, the thioester-containing domain of C3 (P=1.86e-5; OR, 3.66; 95% CI, 2.00 to 6.58), and the vWf type A in FB (P=0.002; OR, 4.58; 95% CI, 1.56 to 14.30) (Figure 3). In the CD46 protein, aHUS-related variants localized mainly to the extracellular SCR domains (P=0.001; OR, 5.84; 95% CI, 1.73 to 30.69). Several other protein domains, such as SCR10 in FH (P=0.11; OR, 1.98; 95% CI, 0.83 to 4.36) and macroglobulin 6a in C3 (P=0.21; OR, 2.08; 95% CI, 0.39 to 7.30), were possibly enriched for aHUS-associated variants but further confirmation is required.
Rare coding variants (MAF<0.1%) associated with aHUS show specific distribution patterns across protein domains in complement genes. Reported aHUS mutations from HGMD and coding variants from the current aHUS cohort have been mapped to their corresponding protein domain in each complement gene. As compared with the NFE cohort from the gnomAD database, aHUS-related variants accumulate in the last two SCRs of FH, four SCRs of CD46, the TED of C3, and the vWf type A domain of FB. Density curves (red for HGMD and variants identified in this study; blue for NFE variants) were approximated using Gaussian kernel density estimation.
No Enrichment for Multiple Rare Coding Variants in Patients with aHUS
Enrichment for multiple rare coding variants was tested in CFH, CD46, CFI, C3, and CFB (Table 4). Of 105 patients carrying variants in complement aHUS genes, 12 patients (11.43%) carried variants in gene pairs. A permutation test gives 14.20 as the expected total variant combinations (P=0.92). In all gene pairs (the CFH-CD46 gene pair was most frequently observed, n=6), the observed variant combinations did not differ from the expected variant combinations (Table 4).
aHUS gene-gene pairs carrying rare coding variants
Discussion
In this study, we sequenced 93 complement and coagulation genes to test the hypothesis that patients with aHUS are enriched for rare coding variants in specific genes after correcting for population stratification. We used two control cohorts, a small UI cohort and a large NFE cohort. The UI cohort enabled us to test for noncausal variants and variant effects in different directions (i.e., protective versus risk) using the SKAT-O test. The NFE cohort provided power to uncover small genetic effects in the same direction (i.e., all risk) using the Fisher and Poisson exact tests.
Results from both comparisons agreed that CFH, C3, CD46, CFI, and DGKE are enriched for rare coding variants in patients with aHUS (Figure 2). However, in other reported aHUS-related genes, there was no enrichment, and for two genes, CFB and PLG, the significance was driven by two associated variants. These results are consistent with the recently reported collaborative study looking at 3128 patients with aHUS from six centers.18 In that study, CFB, THBD, CFHR5, and PLG showed insignificant burden for ultrarare variants compared with Exome Aggregation Consortium controls, suggesting that if these genes make any contribution to aHUS, it is small. In the absence of segregation and functional data, pathogenic mutations in CFB, THBD, CFHR5, and PLG should be reported with caution.
In CFH, CD46, and DGKE, it is the extremely rare coding variants that contribute to the aHUS-associated enrichment we observed. These variants show unique distribution patterns across protein domains compared with the distribution of all rare variants from NFE controls (Figure 2). The affected domains include SCRs 19 and 20 in FH, the thioester-containing domain in C3, vWf type A in FB, and all SCRs in CD46 (Figure 2). Variant enrichment in the SCRs of CD46 is likely due to dynamic alternative splicing in exons coding C-terminal domains, which increases the tolerance of this region of the gene to truncating variations.47,48 Examples of ultrarare replicable variants in our aHUS cohort include CFH c.3644G>A p.R1215Q (six patients), C3 c.188C>T p.P63L (three patients), and CD46 c.725T>G p.F242C (three patients), none of which was present in >138,000 gnomAD controls. Variants with an MAF>0.1% are unlikely to be disease related.
Rare variants in CFH, C3, CD46, CFI, and CFB were identified in 105 patients (26.3%), which is lower than the anticipated rate based on other reports.6,7,18 This difference reflects the inclusion of “secondary” aHUS, the implementation of relatedness analysis, and the use of a lower MAF (<0.1%). In a study by Osborne et al., 39% of patients with aHUS harbored variants with an MAF<1.0%.18 Applying this MAF to our cohort increases the rare variant carrier rate to 36% (144 patients), suggesting that lowering the MAF had a major impact. We recommend reviewing archived data and applying an MAF of 0.1% to refine the genetic diagnosis of aHUS.
More than one rare coding variant was identified in 11.43% of patients (expected rate, 13.5%), with lower rates reported by both Bresin et al. (7.14%)6 and Noris et al. (7.92%, only CFH, CD46, and CFI considered),11 meaning that patients with aHUS are not enriched for multiple rare variants in complement genes (Table 4).5–9,11 In addition, of the 329 variants previously implicated in aHUS, ten variants above an MAF of 0.1% showed no enrichment in patients compared with controls, and are likely benign (Table 3).
By screening all complement and coagulation genes, we identified significant enrichment for rare coding variants in VTN. VTN encodes vitronectin, a multifunctional protein abundant in serum and the extracellular matrix that plays a wide role in regulating complement activation, coagulation, fibrinolysis, wound healing, and cell adhesion.49,50 It inhibits the terminal complement cascade by blocking the formation of membrane attack complex and has been reported in immune-complex GN.51–53 We identified nine alleles carrying eight rare missense variants in eight patients; all variants had MAFs<0.025% (Table 5). Of these eight patients, one also carried FHAAs and another carried a fusion protein.
Rare coding variants in VTN identified in patients with aHUS
An intuitive hypothesis in the pathophysiology of aHUS is that variants in vitronectin impair its function and thereby compromise negative regulation of the terminal complement pathway and increase the risk of aHUS. VTN variants identified in controls included 35 non-sense and 587 missense variants (one non-sense and two missense variants in the UI controls, and 34 non-sense and 585 missense variants in the 63,345 NFE controls), consistent with tolerance to inferred loss of function (from Exome Aggregation Consortium, pLI (loss-of-function intolerance)=0.00).15 The mouse homozygous for the targeted deletion of vitronectin appears phenotypically normal,54 but minor changes are seen in thrombi stabilization, delay of vessel occlusion, and platelet aggregation.55 The vitronectin variants from our aHUS cohort distributed across multiple domains, which interact with many serum proteins.49 As such, it is possible that VTN variation increases the risk of aHUS rather than directly causing the disease, and that the association with aHUS may underlie a mechanism that is more complex than merely enhancing complement dysregulation.
In conclusion, after adjusting for population stratification in patients and controls, we demonstrate domain-specific enrichment for ultrarare coding variants in the CFH, C3, CD46, CFI, and DGKE genes. As a guide to variant classification, we show that pathogenicity is unlikely when variants have an MAF>0.1%. The impact of more common variants should be interpreted with caution. We also show that patients with aHUS are not enriched for rare variants in multiple complement genes. Lastly, our results identify VTN as another gene associated with aHUS. In aggregate, these data should help to refine the long-term clinical management of patients with aHUS.
Disclosures
None.
Acknowledgments
We are grateful to the many clinicians who have entrusted us with genetic and complement function testing of their patients.
F.B. and R.J.H.S. conceived the study and wrote the manuscript. F.B., N.G.B., M.B.J., A.O.T., E.T., and K.F. performed sequencing-related experiments. Y.Z. and N.C.M. performed functional assays. F.B. performed statistical analysis, with contributions by K.W. R.J.H.S., C.N., and C.P.T. performed clinical and genetic diagnoses, with contributions by F.B., Y.Z., and N.G.B.
This study was supported in part by the Foundation for Children with Atypical HUS and an unrestricted award by the Navikas Family Renal Research Fund.
Footnotes
Published online ahead of print. Publication date available at www.jasn.org.
This article contains supplemental material online at http://jasn.asnjournals.org/lookup/suppl/doi:10.1681/ASN.2018070759/-/DCSupplemental.
- Copyright © 2018 by the American Society of Nephrology
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