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Abstract
The recent European Respiratory Society statement on familial pulmonary fibrosis supports the need for genetic testing in the care of patients and their relatives. However, no solution (i.e., a concrete test) was provided to implement genetic testing in daily practice. Herein, we tabulated and standardized the nomenclature of 128 genetic variants in 20 genes implicated in adult-onset pulmonary fibrosis. The objective was to develop a laboratory-developed test (LDT) on the basis of standard Sanger sequencing to capture all known familial pulmonary fibrosis–associated variants. Targeted DNA fragments were amplified using harmonized PCR conditions to perform the LDT in a single 96-well plate. The new genetic test was evaluated in 62 sporadic cases of idiopathic pulmonary fibrosis. As expected in this population, we observed a low yield of disease-causing mutations. More important, 100% of targeted variants by the LDT were successfully evaluated. Furthermore, four variants of uncertain significance with in silico–predicted deleterious scores were identified in three patients, suggesting novel pathogenic variants in genes known to cause idiopathic pulmonary fibrosis. Finally, the MUC5B promoter variant rs35705950 was strongly enriched in these patients with a minor allele frequency of 41.1% compared with 10.6% in a matched population-based cohort (n = 29,060), leading to an estimation that this variant may explain up to 35% of the population-attributable risk. This LDT provides a solution for rapid clinical translation. Technical laboratory details are provided so that specialized pulmonary centers can implement the LDT in house to expedite the clinical recommendations of expert panels.
Idiopathic pulmonary fibrosis (IPF) is a progressive, lethal lung disease characterized by fibrotic changes, scarring of the pulmonary interstitium, and thickening of the alveolar walls leading to respiratory insufficiency (1). In Europe and North America, the incidence of IPF is estimated at 3 to 9 cases per 100,000 person-years (2). Patients with IPF have a poor prognosis, with a median survival time of 2–4 years after diagnosis (3). For a long time, lung transplantation was the only treatment option, but now pharmacologic therapies (pirfenidone and nintedanib) that slow disease progression are available (4, 5). As its name suggests, the etiology of IPF is largely unknown. Repeated cycles of subclinical epithelial injury and aberrant lung repair (6) as well as the activation of development pathways (7) have been proposed to explain the pathogenesis. Recent advances in genomics and bioinformatics are starting to unlock its genetic component and, in turn, refine our molecular understanding of this disease (8).
During the past two decades, rare genetic variants in nearly 20 genes implicated in the familial forms of IPF have been identified. Most of them can be classified into two broad biologic pathways: genes related to telomere biology (TERT, TERC, RTEL1, DKC1, TINF2, PARN, NAF1, ZCCHC8, NOP10, NHP2, ACD, RPA1, and POT1) and those related to surfactant metabolism (SFTPC, SFTPA2, SFTPA1, ABCA3, NKX2.1). In addition to genes known to cause familial pulmonary fibrosis (FPF), many common polymorphisms have been associated with pulmonary fibrosis in genome-wide association studies (GWASs) (9–16). Together, these studies have reported 30 associated loci and implicated genes playing a role in airway clearance, cell–cell adhesion, tissue integrity, telomere maintenance, cell survival, host defense, and autoimmunity. Cumulatively, GWAS SNPs were shown to explain approximately one-third of the variability in the risk of developing IPF (10). Although the effect sizes of these GWAS SNPs are small and are unlikely to be of clinical relevance, at least when considered individually, there is one exception in the field of pulmonary fibrosis. The common promoter polymorphism rs35705950 in the MUC5B gene is associated with IPF, with increased risk of 6-fold for heterozygotes and 20-fold for homozygotes (17). Although still controversial, the MUC5B genotype status has been identified as an independent predictor of transplantation-free survival and may provide valuable information for clinical prognostication (18). Finally, a whole-exome sequencing (WES) study in a case–control series of patients with IPF has revealed an enrichment of rare deleterious variants in KIF15 that may, in turn, contribute to disease susceptibility by affecting the proliferative potential of epithelial cells (19).
As our knowledge of genetic factors underlying IPF is improving, genetic testing for FPF is progressively being integrated as part of routine clinical practice within interstitial lung disease (ILD) services. This has led to a recent statement by the European Respiratory Society on genetic testing, clinical management, and screening of patients with FPF and their relatives (20). After an extensive review of the literature, the experts recommend genetic testing for 1) any patient with ILD and one or more first- or second-degree family members with fibrotic ILD; 2) any patient with a relative carrying a pathogenic or likely pathogenic variant known to cause ILD; 3) any patient with suspected short telomere syndrome; and 4) any patient with an idiopathic fibrosing ILD before the age of 50 years.
These recommendations are in line with the recent American Pulmonary Fibrosis Foundation Genetic Testing Work Group proposal (21). Obviously, implementation in clinical practice requires a full understanding of genetic factors associated with FPF and a genetic test that captures all known causal and susceptibility variants. The American and European recommendations (20, 21) do not provide a specific solution (i.e., a concrete test) to perform genetic testing and provide only broad advice by indicating that multiple gene-sequencing technologies are available, including whole-genome sequencing, WES, and gene-panel testing. Consequently, developing a genetic test for FPF that captures all causal gene variants falls within the expertise of a genetic laboratory.
The goals of this study were threefold: first, to tabulate a list of causal and susceptibility variants of IPF from the literature and standardize their nomenclature; second, to develop a laboratory-developed test (LDT) capturing all these variants; and finally, to evaluate the performance of the new LDT in a cohort of sporadic cases of IPF.
Adults visiting the ILD clinic at Institut Universitaire de Cardiologie et de Pneumologie de Québec – Université Laval (IUCPQ-UL), with diagnoses of IPF were invited to participate in this study. Personal health information, demographic data, age at the time of diagnosis, medication use, and clinical test measurements were collected in a local electronic database. All participants signed the Biobank informed consent document, which was approved by the IUCPQ-UL ethics committee. At the Biobank, subjects were deidentified using a code number for confidentiality. Access to data was protected using the data management structure approved annually by the ethics committee. Medical history, clinical assessment, diagnosis, and inclusion and exclusion criteria are provided in the data supplement.
DNA was extracted from 200 μl of buffy coat using the QIAamp DNA Mini Kit (Qiagen). Table E1 in the data supplement provides the final pairs of primers used in the LDT. PCR and sequencing conditions are described in the data supplement. MUC5B genotype confirmation by restriction fragment length polymorphism is also provided in the data supplement.
In silico pathogenicity prediction of genetic variants was evaluated using PolyPhen-2 (http://genetics.bwh.harvard.edu/pph2/) scores (22) and the combined annotation-dependent depletion (CADD) framework (23) on the basis of the human genome build 38. Clinical interpretation was queried in ClinVar (24). Allele frequencies of identified variants were compared with publicly available databases, including the 1000 Genomes Project (25) and the variant browser Bravo from the National Heart, Lung, and Blood Institute’s TOPMed program (Freeze 10; https://bravo.sph.umich.edu).
All analyses were performed using R statistical software version 4.2.2. (https://www.R-project.org/). Quality control on allele and genotype frequencies was evaluated using Hardy-Weinberg test statistics implemented in PLINK (https://www.cog-genomics.org/plink/). MUC5B genotyping groups were compared using one-way ANOVA for continuous clinical variables and χ2 tests for categorical variables. The allele frequency of the MUC5B promoter variant rs35705950 observed in the Quebec City IPF cohort was compared with CARTaGENE, which is a population-based project of residents from the province of Quebec enrolled at 40–69 years of age (www.cartagene.qc.ca). All individuals with genotyping data were considered (n = 29,060). The population-attributable risk was calculated as 100% × P × (OR − 1)/[P × (OR − 1) + 1], where P is the frequency of the risk allele (T allele) associated with IPF in the control group, and OR is the odds ratio calculated in the case–control (Quebec City IPF-CARTaGENE) cohort. Access to CARTaGENE in this project was approved under data application number 890519.
All variants and genes known to cause familial forms of IPF are listed in Table 1. More details about the variants are provided in Table E2, which includes the legacy nomenclature. A total of 20 genes are included and are mapped on the 22 autosomal and sex chromosomes (Figure 1). A majority (13 of 20) are telomere-related genes, which harbor 76 disease-causing mutations. The largest number of reported mutations are in TERT and RTEL1, with 16 and 19 mutations, respectively. Five other genes implicated in surfactant homeostasis contained 35 mutations, including 13 in SFTPC, 5 in SFTPA2, 2 in SFTPA1, 6 in ABCA3, and 9 in NKX2.1. Together this group of genes harbors 27.6% of disease-causing mutations reported to date. Finally, KIF15, involved in cell proliferation, and MUC5B, encoding a mucin protein, a component of mucus secretion, completed the list of IPF genes carrying, respectively, 16 and 1 susceptibility variants. The exon-intron structure of the 20 IPF genes are illustrated in Figure 2, together with the position of the 128 genetic variants targeted by the LDT. All are either point mutations changing a single nucleotide with another, including 78 coding nonsynonymous, 5 noncoding, and 15 splice-site variants or indels, including 24 frameshift, 2 in-frame, and 4 splice-site variants (see Table E2).
| Gene | Mutations | PubMed ID |
|---|---|---|
| Surfactant metabolism | ||
| SFTPC | c.116T>C (p.V39A), c.211A>G (p.M71V), c.218T>C (p.I73T), c.298G>A (p.G100S), c.325-1G>A, c.424delC (p.H142Tfs*43), c.435G>C (p.Q145H), c.435 + 1G>A, c.435 + 2T>C, c.563T>A (p.L188Q), c.563T>C (p.L188P), c.566G>A (p.C189Y), c.581T>C (p.L194P) | 11207353, 11991887, 20656946, 21828032, 21248320, 19443464 |
| SFTPA2 | c.511A>T (p.N171Y), c.593T>C (p.F198S), c.629A>C (p.N210T), c.691G>A (p.G231R), c.692G>T (p.G231V) | 19100526, 26568241 |
| SFTPA1 | c.532G>A (p.V178M), c.631T>C (p.W211R) | 26792177, 30854216 |
| ABCA3 | c.839G>A (p.R280H), c.863G>A (p.R288K), c.875A>T (p.E292V), c.2891G>A (p.G964D), c.3081_3092delinsCG (p.S1028Vfs*103), c.3784A>G (p.S1262G) | 24730976, 24136335, 20656946 |
| NKX2.1 | c.175_176del (p.M59Gfs*379), c.267dup (p.H90Afs*349), c.344dup (p.G115Gfs*324), c.463 + 2T>C, c.572G>T (p.R191L), c.583C>T (p.R195W), c.714G>A (p.W238*), c.728G>A (p.R243H), c.876_877del (p.V292Vfs*146) | 28732825 |
| Telomere biology | ||
| TERT | c.97C>T (p.P33S), c.164T>A (p.L55Q), c.219 + 1C>T, c.336delC (p.P112Pfs*16), c.430G>A (p.V144M), c.1456C>T (p.R486C), c.1892G>A (p.R631Q), c.2240delT (p.V747Afs*20), c.2371G>A (p.V791I), c.2583-2T>G, c.2593C>T (p.R865C), c.2594G>A (p.R865H), c.2599G>A (p.V867M), c.2648T>G (p.F883C), c.3329C>T (p.T1110M), c.3346_3522del (p.E1116_Ter1133delext*12) | 17392301, 17460043, 21483807, 22853774 |
| TERC | r.37A>G, r.98G>A | 17392301, 17460043 |
| RTEL1 | c.146C>T (p.T49M), c.602delG (p.G201Efs*15), c.637C>T (p.R213W), c.958 + 2dupT, c.1451C>T (p.P484L), c.1482-1G>A, c.1546G>C (p.V516L), c.1549del35 (p.P517Vfs*2), c.1618T>G (p.S540A), c.1940C>T (p.P647L), c.2005C>T (p.Q669*), c.2219_2227del (p.H740_I742del), c.2413 + 1G>C, c.2890T>C (p.F964L), c.2920C>T (p.R974*), c.2957G>A (p.R986Q), c.3371A>C (p.H1124P), c.3493dupC (p.Q1165Pfs*22), c.3791G>A (p.R1264H) | 25607374, 25848748, 26022962 |
| DKC1 | c.145A>T (p.T49S), c.194G>A (p.R65K), c.1213A>G (p.T405A), c.1226C>G (p.P409R) | 24284296, 23946118, 24504062 |
| TINF2 | c.605-7_612delttttcagAGTGCTCT, c.844C>T (p.R282C), c.851C>G (p.T284R), c.871-874delAGGA (p.R291Ifs*24) | 24072216, 24982060, 25539146, 29742735 |
| PARN | c.19A>C (p.N7H), c.168G>C (p.K56N), c.178-3C>T, c.246-2A>G, c.529C>T (p.Q177*), c.563dupT (p.I188Ifs*7), c.565G>T (p.E189*), c.620 + 5G>A, c.703-11_703-10delAT, c.751delA (p.R251Efs*14), c.887_888delCA (p.T296Sfs*14), c.1006-11G>A, c.1081 + 1G>A, c.1262A>G (p.K421R) | 25848748, 28414520 |
| NAF1 | c.956_957delAA (p.K319Rfs*21), c.984dup (p.S329Ifs*12) | 27510903 |
| ZCCHC8 | c.557C>T (p.P186L) | 31488579 |
| NOP10 | c.17A>G (p.Y6C), c.100C>T (p.R34W) | 32139460 |
| NHP2 | c.122G>A (p.R41H), c.182G>C (p.R61P), c.259C>T (p.P87S), c.289_290delAT (p.M97Vfs*2) | 31985013 |
| ACD | c.1-4C>A, c.250_252delAAG (p.K84del), c.250A>G (p.K84E) | 31515401 |
| RPA1 | c.680T>C (p.V227A), c.718G>A (p.E240K), c.808A>G (p.T270A), c.1735G>T (p.E579*) | 34767620 |
| POT1 | c.776T>C (p.L259S) | 35420632 |
| Impaired cell proliferation | ||
| KIF15 | c.94C>T (p.R32*), c.95G>A (p.R32Q), c.164C>T (p.S55F), c.247-1_248delaGG (p.E83fs), c.362-1G>A, c.409C>T (p.P137S), c.539_540delCT (p.S180Cfs*30), c.673G>A (p.A225T), c.1327G>T (p.E443*), c.1580_1581delTG (p.L527Qfs*26), c.1688-870T>C, c.2539delG (p.D847Ifs*5), c.3158_3159delCT (p.S1053*), c.3421-2A>G, c.3520delG (p.E1174Nfs*4), c.3940G>T (p.E1314*) | 35417304 |
| Mucin protein component of mucus secretions | ||
| MUC5B | g.1219991G>T | 21506741 |
Figure 1. The gene map of idiopathic pulmonary fibrosis (IPF). The map is an ideogram of the 22 autosomal and sex human chromosomes and shows the locations of causal genes reported in the literature. The map includes 18 genes in red known to cause monogenic forms of IPF as well as 2 genes in blue unveiled by GWASs carrying rare and common susceptibility variants. The alternating gray and white colors on the chromosomes distinguish cytogenic bands from the adjacent ones and do not correspond to the band colors observed on Giemsa-stained chromosomes. Information to construct the ideogram was obtained from the University of California, Santa Cruz, Genome Browser (hg19). GWAS = genome-wide association study; WES = whole-exome sequencing.
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Figure 2. Genetic variants in genes causing familial pulmonary fibrosis targeted by the laboratory-developed test (LDT) and identified in the Quebec City IPF cohort. Each subfigure presents one gene with its symbol on the top line. The lower part of each subfigure shows the exon–intron structure of the gene. The coding exons are shown in black, and the untranslated regions are shown in gray. The x-axis shows the localization of the gene and variants targeted by the LDT on the basis of the human genome build 38. Genetic variants are identified by rs numbers (if available) or standard gene mutation nomenclature (31), protein nomenclature, and minor allele frequency observed in the Quebec City IPF cohort. Targeted variants are illustrated in black, and those identified in the cohort are in blue. Polymorphisms (untargeted and unlikely to be causal) identified in the cohort are in gray. Other variants with in silico–predicted deleterious scores identified in the cohort are in red.
[More] [Minimize]We opted for conventional Sanger sequencing to develop the LDT given its affordability, availability, ease of analysis, and turnaround time and the small number of patients to screen periodically. Furthermore, the key success of the LDT is its ability to capture all 128 targeted variants into 59 amplicons distributed in a single 96-well plate and amplified using a single slow-down PCR amplification protocol. The plate layout is provided in Figure E1. This single 96-well plate of amplified DNA fragments is then transferred to a Sanger sequencing service provider together with the corresponding plate of sequencing primers. One plate is processed for each patient with IPF.
Variant calling is then performed by aligning targeted sequences to the reference sequences of the human genome build 38. Nucleotide changes detected on the sequencing chromatograms are visually inspected and included in the list of variants for further filtering and interpretation. Targeted variants (Table 1) are first prioritized to potentially explain the genetic cause. Subsequently, all untargeted variants identified for a patient are annotated using their rs numbers (if available), standard gene mutation nomenclature, and protein nomenclature. They are then prioritized on the basis of their frequency in the general population and in silico predictive pathogenicity tools. Finally, variants passing the priority filters are classified into five categories (pathogenic, likely pathogenic, uncertain significance, likely benign, and benign) in accordance with the recommendations defined in the American College of Medical Genetics and Genomics guidelines (26).
Demographics and clinical characteristics of patients are listed in Table 2. One hundred twenty-eight of 128 (100%) genetic variants targeted by the LDT were successfully evaluated. Other than the MUC5B variant, two mutations listed in Table 1 were identified in eight patients of the IPF cohort, including E292V (rs149989682, c.875A>T) in ABCA3 for one patient and rs74341405 in intron 14 of KIF15 for seven patients. The latter is a common susceptibility variant associated with IPF risk and is not considered the disease-causing variant. These results confirmed the relatively low yield of genetic testing in sporadic cases of IPF.
| Characteristic | All Patients (n = 62) | Men (n = 51) | Women (n = 11) |
|---|---|---|---|
| Age, yr | 70 ± 6.9 | 70.3 ± 6.5 | 68.6 ± 9.1 |
| Ethnicity, % White | 95.2 | 98.0 | 81.8 |
| Positive family history of pulmonary fibrosis | 12 (19.4) [28] | 8 (15.7) [21] | 4 (36.4) [7] |
| Smoking status | |||
| Smoker | 2 (3.2) | 1 (2) | 1 (9.1) |
| Ex-smoker | 44 (71) | 39 (76.5) | 5 (45.5) |
| Nonsmoker | 16 (25.8) | 11 (21.6) | 5 (45.5) |
| Lung function | |||
| FVC, L | 2.6 ± 0.9 [2] | 2.8 ± 0.8 [1] | 1.9 ± 0.6 [1] |
| FVC% predicted | 72.4 ± 18.8 [2] | 72 ± 19.7 [1] | 74.5 ± 14.7 [1] |
| DlCO% predicted | 50.5 ± 11.8 [5] | 48.2 ± 10.7 [3] | 62.6 ± 10.8 [2] |
| Chest CT patterns | |||
| UIP | 38 (61.3) | 31 (60.8) | 7 (63.6) |
| Probable UIP | 24 (38.7) | 20 (39.2) | 4 (36.4) |
| Biopsies | |||
| Open lung | 23 (37.1) [4] | 18 (35.3) [4] | 5 (45.5) |
| 6-min-walk test | |||
| Distance, m | 443 ± 100 [4] | 455 ± 95 [2] | 380 ± 104 [2] |
| Oxygen desaturation, delta resting − nadir | 8.4 ± 5.2 [3] | 7.9 ± 4.2 [1] | 11 ± 8.8 [2] |
| Therapy | |||
| Antifibrotic | 34 (54.8) [1] | 31 (60.8) [1] | 3 (27.3) |
| Supplemental oxygen | 17 (27.4) [1] | 11 (21.6) [1] | 6 (54.5) |
In total, we found 138 variants not targeted by the LDT (see Table E3). Interestingly, four of them were predicted as potentially damaging or probably damaging by PolyPhen-2 and as deleterious on the basis of a CADD score >20 (Table 3). These include D12H in NOP10 and E322D in NAF1, each identified in one patient, and F559I in RTEL1 and L59F in ACD, identified in the same patient. Note that T138N in SFTPC, identified in 25 patients, was also considered putatively damaging on the basis of pathogenicity scores (PolyPhen-2: possibly damaging; CADD score = 22.1). However, this is a common variant with a similar minor allele frequency (MAF) in the Quebec City IPF cohort (MAF = 22%) compared with the reference populations (MAF = 26% in the 1000 Genomes Project and MAF = 21% in TOPMed). The four putatively deleterious variants, in well-characterized genes known to cause IPF, suggest that we may have identified new pathogenic variants of IPF that might be specific to the French Canadian population.
| Gene | Variant | Chr | Position hg38 | Exon | mRNA | Protein | MAF | Pathogenicity | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| IPF Cohort | 1000G | TOPMed | PolyPhen-2 | CADD Score | ACMGG | |||||||
| RTEL1 | rs747497376 | 20 | 63,688,339 | 20 | c.1675T>A | F559I | 0.008 | 0 | 9.9 × 10−6 | 1.0 | 26.1 | VUS |
| ACD | rs368387402 | 16 | 67,659,970 | 2 | c.175C>T | L59F | 0.008 | 0 | 6.6 × 10−6 | 0.969 | 25 | VUS |
| NAF1 | rs146474502 | 14 | 163,133,221 | 7 | c.966A>C | E322D | 0.008 | 0 | 0.00051 | 0.906 | 24.2 | VUS |
| NOP10 | rs146261631 | 15 | 34,343,040 | 1 | c.34G>C | D12H | 0.008 | 0.007 | 0.00586 | 0.629 | 27.3 | VUS |
The promoter polymorphism rs35705950 in MUC5B was identified in 43 heterozygote and 4 homozygote individuals. The MAF is 41.1% and 75.8% of patients carried the risk allele. The genotype distribution deviated from that expected by Hardy-Weinberg equilibrium (P = 0.0013). We thus confirmed genotyping calls using an orthogonal approach (see Figure E2). Clinical data from patients with IPF stratified by MUC5B genotypes and by minor T allele carriers versus noncarriers are presented in Tables E4 and E5. Age at diagnosis was not different in carriers of the minor T allele. However, these individuals were characterized by better lung function. In CARTaGENE, a population-based reference of 29,060 individuals, the frequency of the minor T allele was 10.4%, including 5,454 heterozygote and 294 homozygote individuals. This clearly demonstrates an enrichment of the T allele in the Quebec City IPF cohort. The population-attributable risk for rs35705950 was estimated at 34.7%.
IPF is a lung-scarring disorder rising in incidence and associated with a high rate of mortality. Genetic studies are starting to elucidate rare and common variants explaining heritable cases in families as well as sporadic cases. However, for most patients, the genetic etiology remains unknown. In this study, we have built a comprehensive LDT interrogating all known genes and genetic variants associated with FPF. The goal was to translate the current genomic knowledge underpinning IPF into a convenient genetic test to expedite the clinical recommendations of recent expert panels (20, 21). Obviously, the proposed LDT will require constant upgrades, as genetic knowledge will continue to evolve with time. Accordingly, the current LDT can be considered the first version of the genetic test on nonsyndromic IPF.
The current version of the LDT tested a total of 128 genetic variants in 20 genes. This includes all 18 genes associated with ILD listed in the European Respiratory Society statement (20). In addition, we included two IPF genes (KIF15 and MUC5B) unveiled by GWASs and WES studies. Note that the American and European consensuses do not recommend genetic testing for common variants associated with IPF. However, having the genotype status of these variants as part of a multigene panel may still be useful in cases in which a monogenic disease-causing mutation is not identified. In this study, the estimated population-attributable risk indicates that ∼35% of cases in our population could be attributed to the MUC5B promoter variant. We would thus be in favor of its integration as part of genetic testing. Evidences are also building that this variant is associated with better survival and may improve prognosis discrimination (18, 27).
Implementing this LDT is key to identify patients harboring genetic variants known to cause the disease. Finding causal mutations is important to improve diagnosis in families at greater risk and opens new avenues for detection of early disease and the implementation of more aggressive prevention strategies. This includes counseling on the risks of tobacco use, lifestyle and/or occupational modification, and earlier treatment initiation to prevent lung disease progression. Once the causal mutations are identified in a family, clinicians can efficiently screen relatives of probands in cascade screening to initiate lifestyle modification. Note that cascade screening does not require the full LDT developed herein but simply subsetting the Sanger sequencing assay for the mutation of interest. This highlights the versatility of the LDT that can be readily adapted in house on the basis of the knowledge of known mutations in families or the presence of the most common mutations in some geographical regions.
It is well established that a negative result is the most common outcome of genetic testing for IPF (8). Approximately 10–25% of patients with IPF report family histories of ILD and may thus benefit from the LDT (28). It is believed that ∼25–30% of FPF cases and 10–15% of sporadic IPF cases are explained by pathogenic variants targeted by the LDT (8, 29, 30). The diagnostic yield was lower in our French Canadian cohort of patients with sporadic IPF. Only two targeted variants were identified among the 62 sporadic cases, and one of them is a common susceptibility variant (not disease causing) in KIF15. Although caution is warranted considering the limited sample size, our results may suggest a lower prevalence of known pathogenic variants of IPF in our population. Finding variants of unknown significance is also common and part of the challenge associated with genetic testing. Here we found four untargeted variants with in silico–predicted deleterious score in genes previously known to cause IPF. These variants will require further investigations, including testing multiple affected family members (if possible) to demonstrate cosegregation with disease. Altogether, our results support the recommendation of not applying genetic testing in sporadic cases as well as to conduct larger scale discovery studies to find the missing genetic determinants of IPF.
Not all FPF cases are expected to be monogenic in nature. In recent years, GWASs have unveiled ∼30 loci associated with IPF susceptibility (9–16). With this progress, we foresee a second version of the LDT including common genetic variants identified by GWASs to assess the polygenic contribution of risk alleles. As the number of IPF variants increases, the choice of sequencing technology is likely to evolve into next-generation sequencing. In this study, we decided to develop the LDT using Sanger sequencing, as it was the optimal approach for our clinical setting considering the cost and turnaround time as well as the relatively small number of patients to screen periodically. We believe that our approach offers the right degree of throughput for most ILD services and will facilitate widespread implementation.
Herein described, the LDT developed in this study is for research use only and may require additional validation and standardization on the basis of regulations specific to each jurisdiction. The LDT does not cover the full coding regions of the 20 genes of interest (see Table E6) but was designed to capture variants reported in the literature and summarized by expert panels. In addition, targeted variants were selected on the basis of the interpretation of the authors in the original articles. Evidence supporting some variants is relatively modest and may eventually be classified as benign. Caution in interpretation is warranted, and genetic counseling is recommended before genetic testing. It must also be emphasized that our genetic test does not exclude next-generation sequencing testing (including gene panel, WES, and whole-genome sequencing) as a first or second step of investigation in areas where clinicians have the resources as well as the bioinformatics, medical, and genetic counseling expertise to analyze and filter the large resulting number of genetic variants that will be found using these approaches.
In this study, we developed a comprehensive genetic test to identify patients with IPF harboring causal and/or susceptibility variants associated with the disease. Importantly, offering this new genetic test in a clinical or research setting will expedite the clinical recommendations of expert panels and has the potential to have a direct impact on the care of patients and their relatives.
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Supported by Fondation de l‘Institut Universitaire de Cardiologie et de Pneumologie de Québec.
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Originally Published in Press as DOI: 10.1165/rcmb.2024-0009MA on February 16, 2024
Author disclosures are available with the text of this article at www.atsjournals.org.
