Abstract
Hemifacial microsomia (HFM) is a rare congenital disease characterized by a spectrum of craniomaxillofacial malformations, including unilateral hypoplasia of the mandible and surrounding structures. Genetic predisposition for HFM is evident but the causative genes have not been fully understood. Thus, in the present study, we used whole-exome sequencing to screen 52 patients with HFM for rare germline mutations. We revealed 3,341 rare germline mutations in this patient cohort, including those in 13 genes previously shown to be associated with HFM. Among these HFM-related genes, NID2 was most frequently mutated (in 3/52 patients). PED4DIP, which has not been previously associated with HFM, exhibited rare variants most frequently (in 7/52 patients). Pathway enrichment analysis of genes that were mutated in >2 patients predicted the “laminin interactions” pathway to be most significantly disrupted, predominantly by mutations in ITGB4, NID2, or LAMA5. In summary, this study is the first to identify rare germline mutations in HFM. The likely disruptions in the signaling pathways due to the mutations reported here may be considered potential causes of HFM.
Introduction
Hemifacial microsomia (HFM), also known as craniofacial microsomia and oculo-auriculo-vertebral spectrum, is a rare congenital craniofacial malformation condition estimated to affect 1/3,000–1/5,000 live births (). Patients exhibit a broad spectrum of symptoms of varying severity, ranging from microtia to complex developmental defects of the face (e.g., maxillary and mandibular hypoplasia) and surrounding soft tissue. These can be further complicated by ipsilateral orbital anomalies, facial paralysis, transverse facial cleft, and other rare phenotypes (Tuin et al., 2015). HFM treatment is not only very painful and expensive but also challenging and predominantly symptomatic due to the complexity of induced defects.
The pathogenic mechanisms that underlie HFM remain unknown; however, HFM etiology is widely recognized as being multi-factorial, including both environmental and genetic factors (). Despite the use of advanced gene sequencing technologies to identify chromosomal anomalies and candidate gene mutations in patients with HFM, the genetic causes of HFM remain elusive (Terhal et al., 2006; ; Zhu et al., 2007; ; Ou et al., 2008; ; Rooryck et al., 2009; ; ; Rooryck et al., 2010; Su et al., 2012; ; Quintero-Rivera and Martinez-Agosto, 2013; Torti et al., 2013; Zielinski et al., 2014; ; ; ; ; Zhang et al., 2016; ; ; Spineli-Silva et al., 2018). Thus, in the present study, we analyzed rare germline mutations by using the whole-exome sequencing (WES) technology to detect potential genetic causes and novel therapeutic targets for HFM.
Materials and Methods
Patients
Although no common HFM diagnostic criteria exist, most patients with HFM exhibit underdevelopment of the mandible, maxilla, ear, orbit, soft tissue, and/or facial nerve. In this study, our minimal diagnostic criterion was the presence of unilateral mandibular hypoplasia diagnosed by using computed tomography scans and excluded patients with extracranial symptoms to minimize differences caused by the presentation of multiple phenotypes. The study thus enrolled a cohort of 52 patients with a mean age of 4.99 years (range, 0.5–20 years) (Figure 1), male:female ratio of 30:22, and a right:left-side-affected ratio of 26:26. All patients were further classified by using the OMENS+ classification system for HFM (Tuin et al., 2015; Table 1). All patients (or patient guardians) provided written informed consent prior to their participation in the study, which was approved by the Ethics Committee of Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine.
FIGURE 1
TABLE 1
| Patient number | Sample name | Sex | Age (years) | Symptom laterality | OMENS+ classification |
| 1 | B12815834 | M | 3 | L | O1M1E2N3S1 |
| 2 | B12816089 | M | 0.5 | R | O2M3E3N0S3 |
| 3 | WGC096878U | F | 1 | L | O1M3E3N1S2+C1 |
| 4 | WGC096879U | F | 7 | L | O0M2bE0N0S2+C1 |
| 5 | WGC096880U | F | 6 | R | O2M2aE2N2S1 |
| 6 | WGC096882U | M | 0.5 | L | O0M2aE0N0S1 |
| 7 | WGC098141U | M | 3 | R | O1M2bE3N3S1+C1 |
| 8 | ly4454 | M | 10 | R | O1M3E3N2S3 |
| 9 | ly4453 | M | 1 | L | O1M2aE2N3S1 |
| 10 | ly4693 | F | 2 | L | O1M1E0N0S1+C1 |
| 11 | ly4691 | F | 7 | R | O0M2aE3N0S2 |
| 12 | ly4692 | M | 11 | L | O1M2bE3N0S1 |
| 13 | ly4808 | F | 2 | R | O0M2bE0N0S1 |
| 14 | ly4809 | M | 4 | R | O0M2aE0N0S2+C1 |
| 15 | ly5117 | F | 17 | L | O0M2aE0N3S3 |
| 16 | ly5116 | M | 8 | R | O1M2aE0N0S1 |
| 17 | ly5115 | M | 18 | L | O1M2bE3N0S2 |
| 18 | ly5133 | F | 20 | L | O2M2aE0N0S1 |
| 19 | ly5112 | M | 7 | L | O3M2bE3N2S2 |
| 20 | ly5113 | M | 7 | R | O1M3E1N0S3 |
| 21 | ly5119 | M | 13 | R | O1M2bE3N1S2 |
| 22 | ly5172 | M | 7 | R | O1M2bE3N0S1 |
| 23 | ly5170 | M | 2 | R | O3M2bE3N2S1 |
| 24 | ly5171 | F | 2 | R | O3M2bE3N3S2 |
| 25 | ly5176 | M | 1 | R | O1M3E3N1S2+C1 |
| 26 | ly5178 | F | 4 | L | O0M1E0N0S1 |
| 27 | ly5174 | M | 2 | L | O1M1E3N0S1 |
| 28 | ly5173 | M | 1 | L | O0M3E3N3S2 |
| 29 | ly5175 | F | 1 | R | O0M2bE2N0S2+C1 |
| 30 | ly5268 | F | 2 | L | O1M2aE0N0S1 |
| 31 | ly5265 | M | 1 | L | O1M2bE0N0S1+C1 |
| 32 | ly5664 | M | 11 | R | O1M2bE0N0S2 |
| 33 | ly5758 | M | 6 | L | O3M2aE3N0S2 |
| 34 | ly5759 | F | 4 | R | O0M1E0N0S2+C1 |
| 35 | ly5830 | F | 3 | L | O3M2aE3N3S2 |
| 36 | ly5839 | F | 0.5 | L | O1M2bE1N0S2 |
| 37 | ly5838 | F | 4 | R | O2M2bE3N0S2 |
| 38 | ly5877 | M | 6 | L | O3M2bE3N2S3 |
| 39 | ly5900 | M | 8 | R | O2M2aE0N0S2 |
| 40 | ly6059 | F | 8 | R | O2M2bE3N0S2 |
| 41 | ly6058 | M | 7 | L | O2M2bE3N0S2 |
| 42 | ly6060 | F | 1.5 | L | O3M3E2N0S3+C1 |
| 43 | ly6070 | M | 5 | R | O0M2aE3N0S1 |
| 44 | ly6075 | M | 0.5 | R | O2M2bE3N0S1 |
| 45 | ly6077 | M | 5 | L | O1M2aE0N0S1 |
| 46 | ly6385 | M | 1.5 | R | O3M3E3N2S3+C1 |
| 47 | ly6278 | M | 1 | L | O1M2aE1N0S1+C1 |
| 48 | ly6676 | M | 0.5 | R | O3M3E0N0S2+C1 |
| 49 | ly6688 | F | 3 | L | O1M2aE0N0S2 |
| 50 | ly6694 | F | 8 | R | O0M2bE1N0S2+C1 |
| 51 | ly6711 | F | 0.5 | L | O1M3E3N2S2+C1 |
| 52 | ly6756 | F | 2.5 | R | O0M2bE3N0S2 |
Clinical information for the 52 analyzed patients with hemifacial microsomia.
M, male; F, female; L, left side affected; R, right side affected.
WES
Whole-exome sequencing was conducted as previously described (). Briefly, DNA was extracted from patient blood samples by using a Qiagen DNeasy Blood & Tissue Kit (QIAGEN, GmbH, Germany). RNaseA (QIAGEN, GmBH, Germany) was used to prevent RNA contamination. The purity and quality of the extracted DNA were determined by electrophoresis in a 1% agarose gel and by using a NanoDrop spectrophotometer (Thermo Fisher Scientific, Waltham, MA, United States) and a Qubit fluorometer (Thermo Fisher Scientific, Waltham, MA, United States). The purified genomic DNA was then sheared, and the samples (500 ng) were subjected to further purification, end repair, 3’-end adenylation, indexed pair-end-adaptor ligation, ligation-product purification, and polymerase chain reaction (PCR) amplification. A WES library was constructed by using a SeqCap EZ capture kit (Roche) for exome capture and subjected to further PCR amplification, purification, validation, normalization, and pooling. An Illumina HiSeq Series Analyzer was used for library sequencing.
NGS (Next-Generation Sequencing) Data Processing
Next-generation sequencing data processing was conducted as previously described (), with minor changes. Briefly, BWA software () was used to map the generated sequencing reads to the human genome (hg19). VARSCAN2 software () was used to detect germline mutations in the BAM files (minimum coverage, 20; minimum variant frequency, 0.08; P-value, 0.05). The fpfilter module of VARSCAN was used to identify false-positive variations. The resulting high-quality mutations were annotated by using SNPEFF () and VEP () software.
Mutation Classification and Pathway Analysis
Annotated mutations were selected for further analysis if they exhibited an alternative allele depth ≥ 10 and a population alternative-allele frequency < 0.0005 and were predicted to incur a ‘‘High’’ or ‘‘Moderate’’ severity impact. Small insertions and deletions (INDELs) and single nucleotide variants (SNVs) not predicted to be ‘‘benign’’ and ‘‘tolerated’’ by POLYPHEN21 (), SIFT2 (), and CADD (cadd.gs.washington.edu) (Rentzsch et al., 2019) software tools, respectively, were used for following analysis as rare, potentially causative mutations.
Pathway analysis was performed by using ConsensusPathDB software3 () by entering the official names of the detected SNVs and INDELs and by using all known human genes included in the software database as controls. The Reactome database4 was used as a reference database to evaluate pathway enrichment.
Results
Novel Mutations in the Known HFM Genes
PubMed database mining identified a number of gene and chromosome regions that have been previously associated with HFM (Table 2). Next, rare, potentially causative mutations that were detected in the 52 patients in the present study were screened to identify novel mutations in the known HFM genes. This analysis revealed 13 novel mutations in HFM-associated NID2, PARD3B, CACNA1C, ERC1, IQSEC3, LZTR1, MED15, PLCD3, SALL4, SCR1B, SHROOM3, SLC6A13, and TCOF1, which collectively affected 14 (26.92%) of the analyzed patients (Figure 2A). Among these, mutations in NID2 affected the largest number of patients (3/52). The identified NID2 mutations, Asn202His, Asn658Lys, and Leu1136Arg, were each located in different protein domains (Figure 2B). The PARD3B mutations Pro630fs and Arg773Gln were also detected in more than one patient (Figure 2C).
TABLE 2
| Study | Mutated gene(s) symbol | Abnormal chromosomal region(s)/chromosome abnormality | Mutation type | Utilized analysis method |
| HMX-1, BAPX1, EYA1, PUF60, NRBP2, SCRIB, GATA3, ATR-16, NF1, PRKX, RAS2 | 4p16.1, 4p16.3p15.33, Xp22.33–p22.31, 22q11.21, 8q13.3, 8q24.3, 10q26.2q26.3, 10p13p14, 16p13.3, 16p13.11p12.3, 17q11.2, Xp22.33 | CNV (dup/del) | Karotyping with G-banding, CMA | |
| Spineli-Silva et al., 2018 | YPEL1, MAPK1, ERK2, GSC2 | 22q11.2 | CNV (del) | MLPA, CMA |
| MYT1 | 20q13.33 | SNV (c.323C>T, p.Ser108Leu) | SNP array | |
| MYT1 | 20q13.33 | SNV (c.314C > T, p.Ser105Leu) | WES, transient knockdown in zebrafish | |
| ZNF74, KLHL22, MED15, SNAP29, LZTR1 | 22q11.21 | CNV (del) | Genomic array analysis, MLPA | |
| Zhang et al., 2016 | ROBO1, GATA3, EPAS1, PARD3B, GBX2, SHROOM3, FRMD4A, FGF3, KLF12, EDNRB, NID2, SEMA7A, PLCD3 | 3p12.3, 10p14, 2p21, 2q33.3, 2q37.2, 4q21.1, 10p13, 11q13.3, 13q22.1, 13q22.3, 14q22.1, 15q24.1, 17q21.31 | UK | SNP, GWAS, GRAIL, DEPICT, qPCR, WGS |
| Not determined | 22q11 | CNV (dup/del) | aCGH | |
| ATP13A3, XXYLT1 | 3q29 | CNV (dup) | SNP array | |
| Zielinski et al., 2014 | OTX2 | 14q22.3 | CNV (dup) | WES, SNP array |
| Torti et al., 2013 | Not determined | 22q11.2 | CNV (dup/del) | aCGH, FISH |
| OTX2 | 14q23.1 | CNV (dup) | Linkage analysis in families with autosomal dominant inheritance, aCGH | |
| Quintero-Rivera and Martinez-Agosto, 2013 | Not determined | 22q11.1–q11.21 | CNV (tetrasomy) | FISH, aCGH |
| Su et al., 2012 | TCOF1 | 5q32–q33.1 | UK | PCR, direct sequencing |
| Rooryck et al., 2010 | IQSEC3, SLC6A12, SLC6A13, JARID1A, CCDC77, B4GALNT3, NINJ2, WNK1, HSN2, RAD52, ERC1, FBXL14, WNT5B, ADIPOR2, CACNA2D4, LRTM2, DCP1B, CACNA1C, SPRY2 | 12p13.33, 47, XXX, Yp–q11.221. Yq11.222–q12, t(9;18) (p23;q12,2), 13q13.1 | CNV (del/dup/trisomy/translocation) | aCGH, QMF-PCR |
| Not determined | inv(14) (p11.2q22.3) | CNV (inversion) | FISH | |
| BIR1C, OCLN | 5q13.2 | CNV (del) | Illumina HumanCNV370 Genotyping BeadChip, qPCR | |
| Rooryck et al., 2009 | WNT5B, CACNA1C | del(12) (pter/p13.33) | CNV (del) | aCGH, QMF-PCR |
| BAPX1, GSC, Hfm | 4p15.33, 14q32.13, 14q32 | UK | Review | |
| Not determined | 5p15.3–pter, 21q22.3–qter, 21q22.11q22.12. | CNV (del/dup) | FISH, aCGH | |
| Ou et al., 2008 | SIX1, SIX6, OTX2 | 14q22.3–q23.3; 13q21.31-q21.32 | CNV (del/dup) | Karotyping, FISH, aCGH |
| SALL1 | 16q12.1 | SNV (c.1256T > A, p.L419X) | PCR, direct sequencing | |
| Zhu et al., 2007 | ZIC3 | Xq26.3 | UK | Analysis of Zic3 null mice |
| Terhal et al., 2006 | SALL4 (exon 3) | 20q13.2 | UK | PCR, direct sequencing |
Summary of previous genetic studies of hemifacial microsomia.
aCGH, array-based comparative genomic hybridization; CMA, chromosomal microarray analysis; CNV, copy number variation; del, deletion; DEPICT, data-driven expression-prioritized integration for complex traits; dup, duplication; FISH, fluorescence in-situ hybridization; GRAIL, gene relationships across implicated loci; GWAS, genome-wide association study; MLPA, multiplex ligation-dependent probe amplification; PCR, polymerase chain reaction; QMF-PCR, quantitative multiplex fluorescence-PCR; qPCR, quantitative PCR; SNP, single nucleotide polymorphism; SNV, single nucleotide variant; UK, unknown; WES, whole-exome sequencing; WGS, whole-genome sequencing. XXX means XXX syndrome, also known as Triple X syndrome, and trisomy X, which is a rare and genetic disease. It is characterized by the presence of an extra X chromosome in each cell of a female.
FIGURE 2
Genes With High-Frequency Rare, Potentially Causative Mutations in the HFM Patient Cohort
Genes with rare, potentially causative mutations that were detected in more than two patients were ranked by mutation frequency (Figure 3A). Of these, the most frequently mutated gene was PDE4DIP. Its mutations p.Ala141Thr, p.Lys154Arg, p.Cys19Gly, p.Asn1011Ser, p.Val120Ile, p.Gln535His, p.Pro2223Leu, and p.Gly2217Val affected the largest number of patients (7/52) (Figure 3B).
FIGURE 3
Pathway Analysis of Frequently Mutated Genes in the HFM Patient Cohort
Next, a pathway analysis was conducted for all genes detected to harbor mutations among the 52 analyzed patients. This analysis showed that the most enriched pathways in the list of mutated genes were “extracellular-matrix organization,” “collagen-chain trimerization,” and “collagen formation” (Supplementary Figure 1). Genes mutated in >2 patients were also subjected to the ConsensusPathDB enrichment analysis (Figure 4), which found that the “laminin-interaction” pathway most frequently affected (17/52, 32.69%), predominantly by mutations in ITGB4, LAMA5, or NID2 (Figure 5).
FIGURE 4
FIGURE 5
Discussion
To date, the molecular mechanisms that underlie HFM pathogenesis remain unclear; however, strong evidence suggests that these include genetic factors, as evidenced by the fact that several chromosomal abnormalities and gene mutations have been previously reported in patients with HFM (Table 2). The largest study conducted to date was a genome-wide association study (GWAS) that was performed in 2016 (Zhang et al., 2016). However, that study encompassed all immature derivatives of the first and second pharyngeal arches. Thus, its results may not be closely related to the mandibular malformation. Furthermore, it is worth noting that very few risk variants identified by GWASs to date have been located in functionally significant protein regions (e.g., in the exons or the 5’-untranslated region) (). Moreover, the GWAS method is generally considered insufficiently sensitive to detect rare variants for rare diseases (). Given these shortcomings, NGS technologies such as WES have become increasingly important tools for studies aiming to elucidate the pathogenesis of rare diseases (; ; ; ; ). Here, we have performed the first ever WES study of a large cohort of patients with HFM.
In the analyzed patient cohort comprising 52 individuals, we detected mutations in 13 genes that were previously associated with HFM, of which NID2, which encodes a member of the nidogen family of basement membrane proteins, was most frequently mutated. Previous studies have inferred a relationship between NID2 and osteogenic processes, consistent with the fact that the HFM phenotypic spectrum includes mandibular hypoplasia. For example, a previous study showed that NID2 was markedly upregulated in demineralized osseous surfaces compared to its levels in mineralized osseous surfaces, suggesting that NID2 may act as a temporal migration guide (Wischmann et al., 2018). Furthermore, NID2 has been implicated in osteoclastogenesis. TRAP5α, which is involved in osteoclast signaling and RANK signaling in osteoclasts, has been shown to interact with NID2 in cultured 3T3-L1 mouse pre-adipocytes (Patlaka et al., 2014). The fact that patients harboring NID2 mutations develop mandibular hypoplasia rather than mandibular agenesis is likely due to the fact that NID1 and NID2 are found in all vertebrates and exhibit partial functional redundancy. Consistent with this, genetic deletion of either gene alone induces only mild defects in the mouse ().
Among the genes with rare, potentially causative mutations detected in the present study, those in PDE4DIP were found to affect the greatest number of patients in the analyzed cohort. Mutations in PDE4DIP have been previously identified predominantly during sequencing of tumor samples, e.g., in prostate (), ovarian (), or lung cancer (), as well as in adult pineoblastoma (Snuderl et al., 2018). To date, however, to the best of our knowledge, there have been no published reports implicating PDE4DIP mutations in HFM or bone formation.
Most previous studies investigating HFM pathogenesis have focused on a single gene mutation or mutations identified in a single patient; however, this approach is problematic given that the etiology of HFM is thought to be highly heterogeneous and dependent on genetic, epigenetic, and environmental factors. Thus, instead of focusing on single genes, in the present study, we conducted a pathway-based association analysis of generated WES data to identify common biological pathways that are likely to be affected in multiple (unrelated) patients with HFM. We suggest that this type of pathway analysis, which combines genomic and functional data and assesses the effect of multiple gene mutations, may be a better method to investigate the pathogenesis of rare diseases. Thus, we explored the distribution of signaling pathways known to be associated with genes that were mutated in >2 sporadic HFM cases. The “laminin-interaction” signaling pathway was predicted to be most frequently disrupted in the present cohort of patients with HFM, predominantly by mutations in ITGB4, NID2, or LAMA5. This is consistent with the fact that previous reports have demonstrated a close relationship (either positive or negative) between laminin interaction and bone formation during both osteogenesis and osteoclastogenesis (; Susek et al., 2018).
The limitations of the present study are that candidate genes and pathways were not confirmed; further functional experiments are needed to confirm the candidate genes and pathways. Furthermore, it should be noted that the diverse phenotypic spectrum of HFM is thought to be the result of gene-environment interactions and etiologic heterogeneity, which collectively cause incomplete penetrance and variable expression (). Heterozygous mutations in reference alleles causing organ specificity in HFM may be affected by environmental and other factors. Many additional studies, such as RNA sequencing or whole-genome methylation studies, are needed to provide further information regarding this issue. In addition, we unfortunately failed to collect biological samples from the parents of the individuals involved. This was because the majority of patients came to our department with only one parent, and some of them refused to provide biological samples.
Conclusion
In summary, this was the first study of rare germline mutations in a cohort of individuals with HFM. The likely disruptions in the signaling pathways due to the described mutations may be considered potential pathogenic causes of HFM and therefore, may serve as promising therapeutic targets.
Statements
Data availability statement
The data presented in this study are deposited in NCBI online repositories. The BioProject ID is PRJNA626382. The SRA accession numbers for these isolates are from SAMN14639160 to 14639211.
Ethics statement
The studies involving human participants were reviewed and approved by Ethics Committee of Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin. Written informed consent was obtained from the minor(s)’ legal guardian/next of kin for the publication of any potentially identifiable images or data included in this article.
Author contributions
XC, FL, YZ, and GC contributed to conception and design of the study. XC and ZM collected the clinical data and samples. FL performed the bioinformatics analysis. XC wrote the first draft of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.
Funding
This study was funded by Shanghai Municipal Key Clinical Specialty-shslczdzk00901 (ZWJCB18), Science and Technology Commission of Shanghai Municipality (19441912300 and 18DZ2201900), and Clinical Research Program of the 9th People’s Hospital, Shanghai Jiao Tong University School of Medicine (JYLJ031).
Acknowledgments
We would like to thank Editage (www.editage.com) for English language editing.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fgene.2021.580761/full#supplementary-material
Supplementary Table 1Detailed information about all the mutations mentioned in the manuscript.
Footnotes
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Summary
Keywords
hemifacial microsomia, whole-exome sequencing, rare germline mutations, pathway enrichment analysis, mandibular hypoplasia
Citation
Chen X, Liu F, Mar Aung Z, Zhang Y and Chai G (2021) Whole-Exome Sequencing Reveals Rare Germline Mutations in Patients With Hemifacial Microsomia. Front. Genet. 12:580761. doi: 10.3389/fgene.2021.580761
Received
07 July 2020
Accepted
06 April 2021
Published
17 May 2021
Volume
12 - 2021
Edited by
Loredana Bury, University of Perugia, Italy
Reviewed by
Leslie Matalonga, National Center for Genomic Analysis, Center for Genomic Regulation (CRG), Spain; Nelson L. S. Tang, The Chinese University of Hong Kong, China
Updates
Copyright
© 2021 Chen, Liu, Mar Aung, Zhang and Chai.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Gang Chai, chaig1081@sh9hospital.org.cnYan Zhang, zhangy1330@sh9hospital.org.cn
This article was submitted to Genetics of Common and Rare Diseases, a section of the journal Frontiers in Genetics
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