Monoallelic IFT140 pathogenic variants are an important cause of the autosomal dominant polycystic kidney-spectrum phenotype

Keywords: ADPKD, IFT140, ciliopathy, short rib thoracic dysplasia, polycystic kidney disease, monoallelic cystic disease, cilia, intraflagellar transport

Study participants and clinical analysis

Details of the study participants and their recruitment sites are summarized in Figure 1. Subjects were recruited from ADPKD clinical trials: HALT-PKD (n = 49),^{36 ,37} TAME-PKD (n = 83),³⁸ and DIPAK (n = 12);³⁹ observational ADPKD studies: Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) (n = 11),⁴⁰ Genkyst (n = 10),⁴¹ and DIPAK Observational Study (n = 137);⁴² genetic studies of ADPKD: ADKPD Modifier Study (n = 49), the Mayo PKD Center (n = 737), and the Irish Kidney Gene Project (IKGP; n = 35);⁴³ and from other academic centers studying ADPKD. The relevant institutional review boards or ethics committees approved all studies, and participants gave informed consent. Clinical and imaging data were obtained by review of clinical records. Hypertension was recorded as the age at which the individual started anti-hypertensive medications or had two or more consecutive readings of 140/90 or above. Kidney volumes were measured by stereology or automatedly⁴⁴ from the most recent abdominal CT or MRI and the Mayo Imaging Class (MIC) was determined.⁸ Kidney function was calculated as estimated glomerular filtration rate (eGFR; mL/min/1.73 m²) from clinical serum creatinine measurements with the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula.⁴⁵ Blood or buccal samples for standard DNA isolation were collected from the probands and all available family members.

Targeted next-generation sequencing (tNGS)

Screening was performed using either a 137 or 357 gene tNGS panel containing known and candidate PKD and ciliopathy genes,^{38 ,46} and for the 35 IKGP and 69 Brest/Genkyst individuals, as described, respectively, with IFT140 added to the French panel.^{17 ,43} As indicated in Figure 1, causative variants in PKD1 or PKD2 were not found in previous testing of 352 families, while 834 families had not been previously screened. Library preparation, sequencing, read-alignment, and variant calling were performed as previously described.^{12 ,46} Variant mining was performed with SNP and Variation Suite (v.8.9.0, Golden Helix; SVS) after employing the following filters: (1) variant-based read depth (DP ≥ ×ばつ) and genotype quality (GQ ≥ 20), (2) removal of variants with minor allele frequency (MAF) > 0.01 in gnomAD, and (3) removal of variants > 40 bp from target coding regions.

Whole-exome sequencing (WES)

Twenty-nine previously unresolved families were screened by WES at the Mayo Clinic. Genomic DNA (500 ng) was sheared by ultrasonication, and libraries were prepared on an Agilent Bravo system with the NEBNext UltraDNA Preparation Kit. Samples were pooled in groups of 12 prior to capture with the Agilent SureSelectXT Human All Exon V7 kit. Samples were sequenced by the Mayo Clinic Genome Analysis Core with 150 bp paired-end reads on an Illumina HiSeq4000 with one pool per lane. Read alignment and variant calling was performed with the same methodology as the tNGS panels. Variant mining was done in SVS with the following filters: (1) variant DP ≥ ×ばつ and GQ ≥ 10, (2) removal of variants with MAF > 0.001 in gnomAD, and (3) removal of variants > 40 bp from coding regions.

Sanger screening, copy number variant analysis, and variant assessment and confirmation

In samples where no causative variant was identified, PKD1 and PKD2 were further screened via exon-specific amplification and Sanger sequencing, with the duplicated region of PKD1 first amplified by previously described long-range PCR.⁴⁶ Large copy number variants (CNVs) were assessed from the NGS by calculating the log2 ratio of actual read-depth over the expected read-depth for a given locus, and suspected variants confirmed by multiplex ligation-dependent probe amplification (MLPA).⁴⁶ Exon specific PCR primers were designed for confirmation of variants identified in IFT140 (Table S1) and other genes of interest. Variants of interest in probands and any available family members were confirmed and segregated by amplifying 100 ng of gDNA and Sanger sequenced bi-directionally at GeneWiz. We analyzed Ab1 files by employing Mutation Surveyor (V5.1.1, SoftGenetics) to confirm the variant.

The possible significance of missense changes was assessed with the tools SIFT, PolyPhen-2, MutationTaster, MutationAssessor, PROVEAN, FATHMM, and CADD and more broadly as previously described.^{6 ,12 ,43} The pathogenicity of variants was assessed by the American College of Medical Genetic (ACMG) guidelines.⁴⁷ Splicing evaluation was performed with the Berkeley Drosophila Genome Project (BDGP) Splice Site Prediction by Neural Network and Genomnis Human Splice Finder (HSF) sites.^{48 ,49} Where possible, the phase of IFT140 and PKD1 variants was determined by segregation analysis in families.

Genomics England 100K project

All participants in the 100K Genomes Project (100kG) provided written consent to access their anonymized clinical and genomic data for research purposes. The project model and its informed consent process have been approved by the National Research Ethics Service, Research Ethics Committee for East of England (Cambridge South Research Ethics Committee). Whole-genome sequencing (WGS) was performed with the Illumina TruSeq DNA PCR-Free sample preparation kit (Illumina) and an Illumina HiSeq 2500 sequencer, generating a mean depth of ×ばつ (range from ×ばつ to ×ばつ) and greater than ×ばつ for at least 95% of the reference human genome. WGS reads were aligned to the Genome Reference Consortium human genome build 37 (GRCh37) with Isaac Genome Alignment Software (version 01.14; Illumina). Sequence data were analyzed with bcftools scripts designed to search vcf.gz files, and individual BAM files were viewed with IGV. Variant annotation was performed with Ensembl Variant Effect Predictor (VEP) with the following filter: canonical transcript (ENST00000426508.7) IFT140 gene and high impact (see results for details). Phenotypes of identified carriers were manually reviewed in Genomics England Participant Explorer. We reviewed exit questionnaires, filled in by the clinicians at the NHS Genomics Medical Centres (GMCs) for each closed case, to detect subjects solved for other genes. Those recruited under the "normalized specific disease" term cystic kidney disease, included 1,550 individuals from 1,291 families.

UK Biobank

UK Biobank is a large prospective study with over 500,000 participants aged 40–69 years when recruited in 2006–2010 and globally accessible to approved researchers who are undertaking health-related research that’s in the public interest.⁵⁰ Exome data on ∼200,000 individuals have been made available.⁵¹ Ethics approval for the UK Biobank study was obtained from the North West Centre for Research Ethics Committee (11/NW/0382). The exome data of 200,643 individuals were accessed for variants in IFT140 (GRCh38: chr16: 1,510,427–1,612,072) and filtered with Ensembl VEP for high or rare (gnomAD_AF ≤ 0.1%), low impact alleles (see results for details) predicted for the canonical transcript ENST00000426508.7. IMPACT predictions were a subjective classification of the severity of the variant consequence based on agreement with SNPEff (see also results). UK Biobank diagnoses and disease terms recorded in carriers of high and low impact variants were extracted, manually reviewed, and filtered for ICD-10 classifiers of kidney disease: Q61.x (cystic kidney disease), N28.1 (cyst of kidney), N18.x (chronic kidney disease), N17.x (acute renal failure), I12.x (hypertensive renal disease), and N20.0 (calculus of kidney); the term x indicates that all sub-classifications were taken into consideration (e.g., N18.x includes all stages of CKD corresponding to N18.1–N18.5 and N18.9 for unspecified CKD). A Fisher’s exact two-sided test was used for enrichment of diagnoses in high impact variant carriers, and p ≤ 0.05 was considered statistically significant.

The AstraZeneca PheWAS Portal is a repository of gene-phenotype associations for data derived from electronic health records, questionnaires, and continuous traits computed on exomes released by UK Biobank. Gene-level associations were tested with collapsing analyses comparing the proportion of cases with a qualifying variant with the proportion of controls with a qualifying variant in each gene. Twelve different sets of qualifying variant filters (models: ten dominant models, one recessive model, and one synonymous variant model) were applied to test the association between 18,762 genes and 18,780 phenotypes after extensive quality control filters.⁵² Here, we analyzed the gene associations with cystic kidney disease (ICD-10 code Q61) by using the collapsing model Ptv5pcnt (protein-truncating variants; PTVs, MAF ≤ 5% both within the cohort and gnomAD). PTVs were designated based on SnpEff annotations and defined as frameshifting, nonsense, typical splicing, copy number variant, and rare missense. Collapsing analysis p values were generated with a Fisher’s exact two-sided test. A study-wide significance threshold of p ≤ 2e⁻⁹ was defined on the basis of an empirical null distribution with the synonymous collapsing model and an n-of-1 permutation-based null distribution.

Study design

The design of this multinational collaborative study to identify genes harboring variants causative of an ADPKD-like phenotype is shown in Figure 1. Part 1 included screening individuals diagnosed with ADPKD or cystic kidneys, with the vast majority meeting the imaging criteria for ADPKD,^{53 ,54} by tNGS (n = 1,186) or WES (n = 29). Recruitment occurred from 12 different sites or studies and includes subjects for whom previous PKD1 and PKD2 sequencing did not identify a causative variant (n = 381) and unscreened populations (n = 834), with a total of 1,215 families screened (see Figure 1 for details). Part 2 of the study included analysis of large populations of individuals that were genetically characterized by WGS, the cystic kidney disease cohort from Genomics England 100K project (100kG; PKD), or WES, the UK Biobank ICD 10 code, Q61: cystic kidney disease (UK Biobank; Q61; Figure 1). One family detected in the 100kG (PKD) project where follow up was possible was analyzed in part 1 of the project.

IFT140 is an ADPKD-spectrum candidate gene

A gene with loss-of-function (LoF) variants identified in multiple ADPKD families from the tNGS analysis in part 1 of the study was IFT140 (MIM: 614620; Chr. 16p13.3). IFT140 has 29 exons and a coding region of 4,386 bp (GenBank: NM_014714.4) and encodes the IFT140 protein of 1462aa (GenBank: NP_055529.2). IFT140, is a principal component of the IFT-A core complex (along with IFT122 and WDR19 [IFT144]), while IFT43, WDR35 (IFT121), and TTC21B (IFT139) form a peripheral subcomplex.⁵⁵ The IFT-A proteins are responsible for dynein-associated retrograde trafficking of proteins from the ciliary tip back to the basal cell body.^{33 ,55 , 56 , 57} IFT140 bi-allelic pathogenic variants have been associated with the syndromic ciliopathy SRTD (SRTD9 [MIM: 266920]), also described as Jeune asphyxiating thoracic dystrophy or Sensenbrenner or Mainzer-Saldino syndromes.^{58 , 59 , 60} The SRTD9 phenotype includes retinal dystrophy, skeletal malformations (including small thorax, cone-shaped epiphyses, craniofacial abnormalities, and digit malformations), and chronic kidney disease (cysts and fibrosis).^{58 ,59} In addition, bi-allelic variants to IFT140 are associated with non-syndromic forms of retinal dystrophy (MIM: 617781), Leber congenital amaurosis, and retinitis pigmentosa.^{61 ,62} Conditional knockout of Ift140 in mouse kidney collecting ducts (HoxB7-Cre) demonstrated extensive cystic growth and fibrosis by P20 and short, stumpy cilia.⁶³ Therefore, IFT140 was a strong candidate as an ADPKD phenotype gene.

Families with monoallelic IFT140-truncating variants

To determine whether IFT140 variants are causing cystic disease in a monogenic fashion, it was important to demonstrate segregation in families. From our screening, 12 multiplex families with two or more members with IFT140 pathogenic variants and a cystic kidney phenotype were identified, and there was a total of 40 affected individuals. Clinical details of these families are summarized in Tables 1 and S2 and details of the pathogenic IFT140 variants are shown in Table 2.

Singleton individuals with monoallelic IFT140-truncating variants

In addition to the multiplex families, 26 families with a single genetically and clinically confirmed case with an IFT140 pathogenic variant were identified (see Tables 1, 2, and S2 and Figures S1–S3 for details). The majority of these families did not have a known family history, but in seven families, an affected relative was known or suspected, but a sample to test segregation and detailed clinical data was not available (Table S2). In pedigree F392, two relatives had the familial IFT140 variant but had negative ultrasounds at 53 years and 40 years, and in M241, the son had the family variant, but no clinical information was available. The phenotype in the singleton subjects was consistent with the familial cases; the kidney disease was generally bilateral with variable numbers of large cysts present and few liver cysts (Figures S1–S3). Unlike the multiplex families where all variants were truncating, four singleton cases had non-truncating variants. Two were larger inframe deletions that scored as likely pathogenic by ACMG guidelines (Figures S3G and S3I), and two were missense changes that have previously been scored as likely pathogenic changes associated with SRTD9; including c.634G>A (p.Gly212?), which is a likely splicing variant (Figures S3B, S3C, and S3E; Table 2).

IFT140 pathogenic variants are strongly enriched in cystic kidney families

Our analysis identified 38 families with IFT140 pathogenic variants, 36 from tNGS, one from WES, and one from WGS (Figure 1). None of these families had an LoF PKD1 or PKD2 (or other ADPKD-like gene) variant. Of the previously unscreened families, 16/834 (1.9%) had an IFT140 pathogenic variant. This compared to 21/381 (5.5%) families for whom no PKD1 and PKD2 pathogenic variant had been identified through previous testing (Figure 1).

Genomics England 100K Genomes Project analysis

To determine the burden of likely pathogenic IFT140 variants more broadly, we analyzed genetic and clinical data from the 100K Genomes Project that includes National Health Service (NHS) subjects affected by a rare disease or cancer and relatives. IFT140 variants were extracted from WGS of 64,185 subjects and after annotation 26 distinct strongly predicted pathogenic variants (stop gain, start loss, and canonical splice acceptor and donor variants) were identified in a total of 152 individuals (89 probands and 63 relatives) from 111 different families. Among these 152 individuals, kidney cyst(s) were described in 40 individuals (26.3%), including 31/89 probands (34.8%); 27 of these probands were recruited to the 100kG under the "cystic kidney disease" (100kG; PKD) group. Analysis of the 100kG; PKD group showed that 27/1,291 (2.1%) probands had IFT140 likely pathogenic variants, but these variants were much rarer in probands in other rare disease groups (62/33,127; 0.19%; p < 0.0001) or probands with primary neurological diagnoses (18/8,162; 0.22%; p < 0.0001). Twenty-five IFT140-positive probands in the 100kG; PKD group were considered unsolved by the Genomics England analysis; two carried monoallelic VUSs in PKD1 (see Tables 3 and S3). Three families showed segregation of the IFT140 variant with the cystic phenotype in 3, 2, or 1 family member (Table S3).

UK Biobank analysis

Recently IFT140, or the recurrent IFT140 LoF variant c.2399+1G>T, was suggested to be associated with kidney cyst phenotypes in the UK Biobank population and the TOPMed Program.^{52 ,64} UK Biobank subjects were typically between 50 and 75 years old, and the study was not enriched for monogenic disease. A total of 240,037 individuals with WES data were available for study.⁵² Genes were screened for enrichment of protein-truncating variants (including nonsense, canonical splice, or frameshifts) in the ICD-10 code Q61 (cystic kidney disease; n = 521) group compared to controls (without Q61; n = 239,516). Individuals with monoallelic IFT140-truncating variants represented 2.69% of Q61 cases compared to 0.21% of controls (p = 1.62e⁻¹¹; Figure 4A). Carriers of truncating variants to PKD1, 8.45% cases versus 0.015% controls, and PKD2, 5.57% cases versus 0.004% controls, were also, as expected, highly enriched in the PKD group (p = 3.04e⁻⁹⁶ and 1.63e⁻⁶⁹, respectively). ALG9-truncating variant carriers, 0.77% cases and 0.032% controls, were the next highest but not significantly enriched (p = 0.00003; significance threshold p = 1.0e^−8.7).

In a separate analysis of the UK Biobank population, the prevalence of high (likely pathogenic: frameshifting, nonsense, or canonical splicing) versus low impact variants (likely benign: synonymous, non-canonical intronic) with a gnomAD MAF ≤ 0.1% were compared for various ICD-10 kidney disease codes (Figure 4B). For this analysis, out of a total population of 200,643 subjects with WES data, 481 individuals were monoallelic for high and 5,888 had low impact IFT140 variants. ICD-10 codes for cyst of kidney (N28.1), cystic kidney disease (Q61), and CKD stages 4 and 5 (N18.4 and N18.5) were more common in individuals carrying high compared to low impact IFT140 variants: 2.7% versus 0.5% (p = 1.3e⁻⁵, OR = 5.3; 95 CI: 2.7–10.1); 1.0% versus 0.07% (p = 2.4e⁻⁴, OR = 15.4; 95 CI 4.7–50.5); and 1.0% versus 0.3% (p = 0.02, OR = 3.9; 95 CI 1.5–10.3), respectively, whereas other kidney phenotypes were not significant (Figure 4B).

The monoallelic IFT140 phenotype

IFT140 subjects from part 1 of the study typically had conserved renal function, but 32 had an eGFR < 60, and one with a single kidney due to nephrectomy following infantile Wilms tumor had ESKD at 64 years (Tables 1 and S2). A plot of eGFR versus age showed an overall milder disease course than for PKD2 but a lower eGFR than seen in normal individuals (Figure 5A).⁶⁵ IFT140 individuals were diagnosed at a mean age of 52.7 years (±13.2 years), compared to 29.9 years (±11.9 years) for the ADPKD individuals in the TAME study,⁶⁶ and the diagnosis was often made incidentally. Hypertension was diagnosed in 66.1% of individuals (where the information was available), with an average age at onset of 56.9 years (the precise age at onset was not present in 14 individuals, and the mean eliminating those was 53.6 years); only one affected individual was hypertensive before 40 years. Therefore, hypertension was less frequent and diagnosed approximately 20 years later than in ADPKD overall.⁶⁷ Six IFT140-affected individuals had a vascular phenotype, including intracranial or aortic aneurysm, and some of these individuals had additional PKD gene variants (Table 3), but further study will be required to see whether there is an association as found in ADPKD overall.^{4 ,5} The htTKV was often enlarged in the monoallelic IFTI40 subjects but asymmetry was common with a small number of cysts accounting for most of the cystic disease (and increased TKV), hence, 27 individuals were classified as having an atypical (2A) MIC.⁸ Plotting the htTKV data shows a wide spread of values both for those with a typical and atypical MIC (Figure 5B). Liver cysts were rare, found in only nine subjects and, when present, were usually small (Table 1).

Retinal degeneration is a phenotype associated with bi-allelic IFT140 pathogenic variants and there was some anecdotal analysis of eye disease in monoallelic individuals. In M199, III-1 had age-related macular degeneration (AMD) and early-stage retinal pigment epithelium (RPE) detachment, while in M1374, R3376 had AMD and atrophy of the RPE (Table S2; Figure S4). In addition, in P1505, Ox5262 had congenital aniridia and blindness (see also below). However, only a limited number of eye exams were available and analyses in these individuals by an optometrist revealed no systematic eye phenotype. In addition, several individuals had a diagnosis of cancer, including five with colorectal cancer but further analysis will be required to determine whether there is any association. Of note in the 100kG data, nine high impact IFT140 variant carriers had diaphragmatic (or umbilical) hernias, seven of whom also had kidney cysts, while in the UK Biobank data, ICD-10 K40.9 (unilateral or unspecified inguinal hernia, without obstruction or gangrene) was enriched in high impact carriers (p = 0.016).

Genetic variants in other genes

IFT140 lies in chromosome region 16p13.3 (Chr16: 1,560,428–1,662,111; hg19) less than 0.5 Mb distal to PKD1 (Chr16: 2,138,711–2,185,899; hg19). Consequently by linkage analysis, IFT140 pathogenic variants can be linked to PKD1 variants in family and sometimes population analyses. For instance, three families with IFT140: c.2399+1G>T also had the PKD1 variant c.11017−3C>T; these variants co-segregated with the disease in M132 (Figure 2A, Table 3). This PKD1 noncanonical splicing change has been described as pathogenic but is not predicted to significantly alter splicing and is found 298 times in gnomAD.⁶⁸ As another example, PKD1: c.2990C>T (p.Thr997Met), a somewhat conservative substitution at a residue well conserved in PKD1 orthologs, but not in the PKD repeat domain, and found twice in gnomAD, was considered pathogenic from clinical testing because it segregated in three affected individuals in M1629, but IFT140: c.2400−2A>T also segregates in this family (Figure 3A). Variants of possible significance in other PKD genes were also found in IFT140 families. For instance, M1266 has the PKHD1 frameshifting variant c.3549delT (p.His1184fs^∗36), as well as IFT140: c.223delG, both segregating in the two affected sisters and perhaps associated with the liver cysts. Families P1504 and F662 had an LoF variant in another IFT-A encoding gene, IFT43 (MIM: 614068) or TTC21B (MIM: 612014), respectively, and R1403 (M241) had a single LoF to the SRTD gene, WDR60 (MIM: 615462). LoF variants in three other ciliopathy genes were found in three other families (Table 3), but some variants, BBS2 (MIM: 606151): c. 823C>T (p.Arg275^∗) (M1320; Figure 2L) and DYNC2H1 (MIM: 603297): c.3054delC (p.Phe1018fs^∗3) (M199; Figure 2G), did not fully segregate with the disease. P1505 had the OFD1 (MIM: 300171) canonical splicing variant c.936−2A>G, but which is present 24 times in gnomAD and the significance is uncertain. The eye phenotype in this family could be associated with the IFT140 and/or OFD1 variants.

Declaration of interests

M.M. reports grants and consulting fees outside the submitted work from Otsuka Pharmaceuticals, Sanofi, Chinook, Goldilocks, Natera, and Palladio. R.D.P. reports clinical trial support from Reata, Kadmon, Sanofi-Genzyme, US Department of Defense; consultant/advisory fees from Otsuka and Sanofi-Genzyme; and is section editor Renal Cystic Disease: UpToDate. J.A.S. has received honorarium from consulting positions from Otsuka Pharmaceuticals, Sanofi, and Takeda. V.E.T. reports grants and/or other fees from Mironid, Blueprint Medicines, Otsuka Pharmaceuticals, Palladio Biosciences, Sanofi Genzyme, Reata, and Regulus Therapeutics, all outside the submitted work.

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Supplementary Materials

Data Availability Statement

Primary data from the 100,000 Genomes Project, which are held in a secure research environment, are available to registered users. UK Biobank association statistics are publicly available through the AstraZeneca Centre for Genomics Research (CGR) PheWAS Portal. UK Biobank whole-exome sequencing data described in this paper are publicly available to registered researchers through the UKB data access protocol.