1 Introduction
Although it affects approximately 1 in 136 000 newborns [
1], Fanconi anemia (FA; OMIM: 227650) is a rare autosomal recessive or X-linked recessive bone marrow failure disorder with a carrier frequency of up to 0.3% [
2]. The disease exhibits both phenotypic and genotypic heterogeneity, characterized by progressive hemocytopenia, a tendency to malignancies, and numerous congenital deformities, including short stature, microcephaly, skin pigmentation abnormalities, and skeletal anomalies [
3]. FA is caused by mutations or deletions in germline genes, which lead to anomalies in several biological processes, such as the regulation of DNA damage repair and interstrand crosslink repair. Although different mutations or deletions can result in different subtypes and clinical manifestations, there is no obvious correlation between the clinical severity of FA and its subtypes, and even within a subtype, there can be significant variation in the clinical manifestations [
4]. FA has a rather high degree of clinical and genetic heterogeneity, and the absence of distinctive symptoms makes it easy to misdiagnose or underdiagnose, delaying the start of treatment.
Finger abnormalities are the most prevalent congenital malformations in the Chinese rare disease cohort, affecting approximately 1 in 4 patients with FA [
5]. When a FA family with a
FANCA mutation has a finger-deficient phenotype, it is tempting to attribute this digital deficiency phenotype to
FANCA mutations, overlooking the potential that a mix of other mutations may be present.
EHMT1 is a crucial histone methyltransferase in the human body, responsible for regulating the cell cycle. Mutations or deletions in the
EHMT1 gene can result in abnormalities during embryonic development [
6]. The
EHMT1 gene deletion or mutation leads to the absence of the functional euchromatic histone methyltransferase 1 enzyme. This absence disrupts the proper regulation of certain genes in various organs and tissues of the human body, causing developmental and functional abnormalities that are characteristic of Kleefstra syndrome [
7]. This study presents a report of a compound heterozygous
FANCA mutant pedigree that displays the phenotype of FA. Through pedigree analysis, it was determined that individuals carrying the
EHMT1 gene mutation exhibited the phenotype of ectrodactyly. Genetic and bioinformatic analyses confirmed that the phenotypes of these two individuals were caused by mutations in different genes.
2 Methods and materials
2.1 Research subjects
The research was carried out on a FA pedigree in China. The pedigree spanned three generations, and there were no marriages between close relatives within the pedigree (Fig. 1A). This study was carried out with the approval of the Ethics Committee of Fujian Provincial Hospital. Prior to the study, the family members who were recruited were duly informed and voluntarily signed the written informed consent form. The proband, a 9-year-old boy, exhibited pallor for over a month along with scattered petechiae and ecchymoses on the limbs. There were no signs of hematuria, hematochezia, rash, bone/joint/muscle pain, or any history of exposure to chemicals, toxins, or parasitic diseases. After admission, the patient’s height was measured at 130 cm and his weight at 24.5 kg. He exhibited pale palpebral conjunctiva, tachycardia, and no enlargement of the liver or spleen. There were no deformities observed in either upper limbs (Fig. 1B), but slight hyperpigmentation was present in both lower limbs (Fig. 1C). The development of the testes was normal on both sides. No other family members exhibited anemia or physical developmental abnormalities, except for the proband’s paternal relatives (II3 and II5), who had congenital finger defects in the upper limbs (Fig. 1D).
2.2 DNA extraction
The proband and participating family members provided 5 mL of peripheral blood samples, which were collected in ethylenediaminetetraacetic acid (EDTA)-anticoagulated tubes (Shanghai Solarbio Bioscience & Technology Co., Ltd., China). The DNA was then extracted using the QIAamp DNA Blood Mini Kit (QIAGEN, Germany). The concentration and purity of DNA were assessed using a Nanodrop 1000 spectrophotometer (Nanodrop Technologies, USA).
2.3 Candidate gene location and mutation-screening strategies
After quality assessment, whole-genome sequencing (WGS) was performed. Sequencing reads were aligned to the human hg19 reference genome using Burrows-Wheeler Aligner (BWA) tool, and variants (SNVs/indels) were called using SAMtools and GATK. Variants were annotated with ANNOVAR and filtered against dbSNP, gnomAD v4.1, 1000G, HGMD, and ESP6500. Pathogenicity was predicted using PolyPhen-2, SIFT, and MutationTaster, and classified following American College of Medical Genetics and Genomics (ACMG) guidelines.
2.4 Sanger sequencing verification
Candidate mutations were PCR-amplified using primers designed with Primer Premier 5.0 software (FANCA: NM_000135.4; EHMT1: NM_024757.5). The PCR products were purified using a commercial purification kit (Takara Bio Inc., Japan) and subjected to Sanger sequencing on an Applied Biosystems 3730XL DNA Analyzer. Primer sequences are listed as follows:
FANCA-F: 5′-TCGAACTCCTGACCCTGAGT-3′
FANCA-R: 5′-CCCGTGTGTGAATTGTGCTG-3′
EHMT1-F: 5′-ACTGTCTGGGAAGGACCTGT-3′
EHMT1-R: 5′-CCTCTCTGAAAGGCGGAGTC-3′
Detection of copy number variation (CNV) by quantitative real-time polymerase chain reaction (qPCR) using genomic DNA
Genomic DNA samples from participating family members were diluted to working concentrations. Target-specific primers (Table 1) were designed based on next-generation sequencing-identified deletion regions. qPCR was performed using a fluorescence quantitative PCR detection system (BORI Gene-9660A), with normal human DNA as reference. Copy numbers were calculated using the comparative threshold cycle (2−ΔΔCt) method (normal diploid copy number = 2), with the following thresholds: homozygous deletion (2−ΔΔCt < 0.1), heterozygous deletion (0.3–0.7), normal copy number (0.7–1.3), and copy number duplication (1.3–1.8).
2.5 Minigene splicing and RT-qPCR analysis
Total RNA was extracted from whole blood samples using TRIpure reagent (F. Hoffmann-La Roche Ltd., Switzerland). For minigene splicing analysis, cDNA was synthesized using the RevertAid First Strand cDNA Synthesis Kit (Thermo Fisher Scientific Inc., USA), followed by PCR amplification with gene-specific primers (EHMT1-F: 5′-GGACGGAATTGACCCCAACT-3′; EHMT1-R: 5′-CTTCCATCAACGGGGTCCTC-3′). The PCR products were analyzed by electrophoresis and Sanger sequencing. For RT-qPCR, gene-specific primers (Table 2) were used, and cDNA was amplified under standard cycling conditions (95 °C/10 min; 40 cycles of 95 °C/15 s, 60 °C/20 s, 72 °C/25 s; 72 °C/5 min) with melting curve analysis (65–95 °C).
2.6 Western blotting
Peripheral blood samples were collected from the proband’s father (II5) and healthy control using anticoagulated tubes. Total leukocytes were isolated via a red blood cell lysis method. The cell pellet was washed twice with PBS. Subsequently, the cells were lysed on ice using a lysis buffer containing protease inhibitors. After centrifugation, the supernatant was collected as the total protein extract. Protein concentration was determined using the BCA assay. Proteins were separated by SDS-PAGE and transferred onto a PVDF membrane via the wet transfer method. The membrane was blocked with 5% skim milk for 1 h at room temperature and then incubated overnight at 4 °C with the following primary antibodies: EHMT1 Rabbit pAb (Abclonal; Cat# A8513; 1:500), Histone H3K9me2 Antibody (Proteintech; Cat# 39754; 1:500), and Albumin Polyclonal Antibody (Proteintech; Cat# 16475-1-AP; 1:5000). Thereafter, the membrane was incubated with HRP-conjugated Goat anti-Rabbit IgG (H + L) Secondary Antibody (Thermo Fisher Scientific; Cat# 31460; 1:2000) for 2 h at room temperature. Protein bands were visualized using an ECL chemiluminescence detection system. Band intensity was quantified with ImageJ software, and data were visualized using GraphPad Prism 10.1.2.
3 Results
3.1 Clinical phenotypes
The proband exhibited childhood-onset pancytopenia with markedly reduced hemoglobin levels, mildly elevated bilirubin and liver enzymes levels, but normal coagulation function and renal function. Iron-deficiency anemia and megaloblastic anemia were ruled out, while hemoglobin electrophoresis suggested a possible diagnosis of thalassemia. Autoimmune antibodies, ANCA-associated, and hemolytic anemia antibodies were absent. Elevated CD3, CD8, and serum IgE were observed (Table 3), with no paroxysmal nocturnal hemoglobinuria (PNH) clone detected. Growth parameters, endocrine function, and abdominal/cardiac ultrasounds were normal (Fig. 1E). Bone marrow analysis revealed hypocellularity (15%), with decreased granulocytic (16%) and erythroid (0%) lineages, elevated lymphocytes (77%) and monocytes (5%), and absent extracellular/intracellular iron (Fig. 1F). Imprints showed reduced nucleated cells (granulocytic 16.0%, erythroid 25.5%), rare megakaryocytes, and increased non-hematopoietic cells (Fig. 1G). Blood smears demonstrated leukopenia, lymphocytosis, neutropenia, normocytic erythrocytes, and thrombocytopenia, with 25% NAP positivity (score 11/20) (Fig. 1H). The bone marrow biopsy showed marked hypocellularity (15%), with severe reduction in granulocytic and erythroid lineages. Most cells were post-progenitor stage, with rare megakaryocytes and relative increases in lymphocytes, plasma cells, and histiocytes. Myelofibrosis was graded as MF-0 to MF-1, and immunohistochemistry was negative for CD34, CD61, and TdT (Fig. 1I–1J). The bone marrow aspiration results confirmed that the proband had aplastic anemia. The proband’s paternal relatives (II3 and II5) exhibited congenital finger defects in their upper limbs, but their physical examinations, including routine blood tests, renal ultrasound, and cardiac ultrasound, were all normal.
3.2 Screening for mutations
We performed WGS analysis on the proband and his father, revealing two mutation sites in
FANCA. One of these mutations, NM_000135.4: c.154C>T in exon 2, led to a substitution of arginine at position 52 with a termination codon (p.Arg52Ter), resulting in the production of a truncated protein. Another mutation observed is a copy number heterozygous deletion mutation NC_000016.9: g.89865477_89895212del of approximately 29.7 kb in size in the q24.3 region of chromosome 16, and this mutation was identified through CNV testing, which affects the
FANCA gene (NM_000135.4: exon 1–10). The proband’s father was determined to have two mutation sites. One of them was a heterozygous mutation c.154C>T in the
FANCA gene (NM_000135.4). Unexpectedly, he did not have another deletion mutation in
FANCA but instead had a novel identified heterozygous intronic variant (c.2382 + 1750G>A) in the
EHMT1 gene (NM_024757.5). The pathogenicity of the identified variants was classified according to the ACMG guidelines [
8]. Both
FANCA variants, c.154C>T (p.Arg52Ter) and g.89865477_89895212del, were classified as Pathogenic (PVS1, PM2, PM3). The
EHMT1 c.2382 + 1750G>A variant was classified as a Variant of Uncertain Significance (PM2, PP3). Initially, we conducted Sanger validation on the proband and his parents. The proband confirmed that the base T at position 154 was identical to the homozygote mutation, as he possessed both the mutation c.154C>T and the fragment deletion mutation NM_000135.4: exon 1–10 (Fig. 2A). The proband’s father (II5) carried the heterozygous mutation c.154C>T (Fig. 2B), while the Sanger sequencing analysis of the proband’s mother (II6) indicated a wild-type sequence (Fig. 2C). This pattern suggested that the large deletion mutation (g.89865477_89895212del) was likely inherited from the mother, but this hypothesis required confirmation by quantitative genomic analysis. Subsequently, we conducted Sanger sequencing on the relatives of the proband’s father. Family members I2, II1, III1, III3, III6, and III7 all possessed the heterozygous mutation c.154C>T, while the other members II3, III2, III4, III5, and III9 exhibited the wild type.
EHMT1 Sanger sequencing identified the heterozygous c.2382 + 1750G>A variant exclusively in the proband’s father (II5) and uncle (II3) (Fig. 2D). The grandfather (I1), who exhibited congenital adactyly, was also predicted to carry this variant. All other family members, including the proband, showed wild-type sequences (Fig. 2E).
3.3 Genetic analysis of alternative limb malformation genes
To comprehensively evaluate alternative genetic causes for the ectrodactyly phenotype, we analyzed the sequencing data from the proband’s father (II5) for variants in genes with established associations to limb malformations. We identified several heterozygous variants in genes, including WDR35, DYNC2LI1, EVC2, and NEK1 (Table 4). However, the diseases linked to these genes are all inherited in an autosomal recessive manner, which is incompatible with the clear autosomal dominant inheritance pattern observed in this pedigree. Furthermore, the ACMG classifications of these variants were either “Benign”, “Likely benign”, or “Uncertain significance”. Therefore, these variants were considered unlikely to be causative for the dominant ectrodactyly trait in this family.
3.4 qPCR results of the exon of the FANCA gene
Since the father (II5) did not carry the FANCA deletion mutation as confirmed by WGS, we focused on maternal lineage for further validation of the deletion origin. To further confirm that the deletion mutation NC_000016.9: g.89865477_89895212del originated from the proband’s mother, we subjected the proband and his mother to qPCR of exons 2, 5, and 11 of the FANCA gene. The qPCR experiments showed that the 2-ΔΔCt values for exons 2, 5, and 11 of the proband’s FANCA gene were 0.13, 0.09, and 0.54, respectively. Therefore, the proband was found to have a homozygous deletion of exon 5 and a heterozygous deletion of exon 11, based on the reference range (Fig. 3A–3C). The proband’s mother exhibited a heterozygous deletion in exons 2 and 5, as well as a normal exon 11 of the FANCA gene. Based on our analysis, we predict the deletion mutation g.89865477_89895212del in the proband was inherited from his mother. Afterwards, we implemented qPCR analysis for relatives of the proband’s mother. We identified heterozygous deletions in exons 2 and 5 of individuals I3, II10, III9, III12, and III13, while exon 11 showed no abnormalities and were mutation g.89865477_89895212del carriers. Exons 2, 5, and 11 of the FANCA gene in I4, II8 are unaffected and classified as the wild type.
3.5 Prediction and analysis of bioinformatics
Both identified mutations in the FANCA gene result in the production of shortened proteins, and both are classified as pathogenic. To verify this hypothesis, we employed SWISS-MODEL to forecast the three-dimensional configurations of the wild-type proteins and FANCA mutants. Subsequently, we utilized Pymol to display the three-dimensional picture of the FANCA wild-type structure (Fig. 4A). The p.Arg52Ter mutation leads to a substantial loss of protein sequence (Fig. 4B), while the g.89865477_89895212del mutation results in the absence of portions of exons 1–10 of the FANCA protein (Fig. 4C).
3.6 Splicing and expression analysis of the EHMT1 c.2382 + 1750G>A variant
Minigene splicing assays demonstrated that the
EHMT1 (NM_024757.5): c.2382 + 1750G>A variant did not cause aberrant splicing (Fig. 5A and 5B). However, qPCR analysis revealed significantly reduced
EHMT1 mRNA expression in peripheral blood samples from the proband’s paternal relatives (II3 and II5) carrying this variant compared to healthy controls and the proband (Fig. 5C and 5D). To further investigate the functional consequence of the EHMT1 variant at the protein level, we performed Western blot analysis on peripheral blood mononuclear cells (PBMCs) from the proband’s father (II5) and a healthy control. We assessed the protein levels of EHMT1 and its catalytic product, histone H3 lysine 9 dimethylation (H3K9me2) [
9]. A protein band of approximately 100 kDa, detected by the EHMT1 antibody, showed markedly reduced intensity in the II5 compared to the control (Fig. 5E). It is noteworthy that while the canonical EHMT1 isoform is reported at ~141 kDa, a ~100 kDa isoform has been documented in the literature [
10], though its specific expression in PBMCs remains uncharacterized. Critically, and in support of EHMT1 functional deficiency, we observed a clear reduction in the global level of H3K9me2 in the proband’s father (Fig. 5E). Ensembl analysis confirmed the variant does not disrupt known transcriptional regulatory elements (Fig. S1). Notably, UCSC Genome Browser predicted this intronic variant may alter binding sites for multiple transcription factors, including SOX4, TCF7, TFAP2C, and others (Fig. 5F), suggesting a putative mechanism for the observed mRNA downregulation via potentially disrupted transcriptional regulation.
4 Discussion
FA is caused by changes or losses in germline genes that disrupt key biological processes, such as how DNA is repaired after damage and how crosslinks between DNA strands are fixed [
11]. Currently, a total of 22 genes have been identified, each located on distinct chromosomes [
12]. The most often occurring mutations are found in the
FANCA gene (65% of cases), followed by
FANCC (15%),
FANCG (10%),
FANCE and
FANCF (8%), and various other types of mutations accounting for less than 1% [
13]. With a highly complicated mutational spectrum, the
FANCA gene is the most polymorphic and largest member of the FA gene family. The extensive occurrence of repeated regions within the gene is primarily responsible for its high mutability [
14]. In contrast to other genes, the most frequent type of mutation in
FANCA is a substantial deletion, which makes up 20%–40% of all mutations and may span 1 to 31 exons [
15]. It has also been reported that deletions covering the whole
FANCA gene have occurred [
16]. Apart from a few common types of mutations, the majority of
FANCA variants are regarded as “private mutations” since patients with the same or homozygous mutations are rarely in the clinic [
17]. In addition, as of the current date (2025-07-12), the ClinVar database has documented 744 deletion mutations. It is noteworthy that over 75% of these deletion mutations are classified as pathogenic or likely pathogenic according to the database (https://www.ncbi.nlm.nih.gov/clinvar). Both
FANCA mutations observed in this investigation were characterized by segmental deletions, resulting in the loss of substantial portions of the segment. One of them, mutation c.154C>T (p.Arg52Ter), has been discovered to be compound heterozygous for the mutation and to also carry the mutation site c.2852G>A (p.Arg951Gln) in a 9-year-old boy with FA, according to exon testing [
18]. Therefore, the mutation p.Arg52Ter results in the production of shortened proteins that lack normal function and hence should be classified as a pathogenic mutation. The g.89865477_89895212del is a novel deletion mutation that has not been previously documented. ClinVar has also identified two other pathogenic mutations, g.(?_89874692)_(89881031_?)del and g.(?_89871678)_(89877489_?)del, within the deletion of this new mutation. Furthermore, the
FANCA exon 6–7 region is clinically significant, and deletions in this region are likely to be pathogenic [
19]. Through the application of bioinformatics, we utilized predictive methods to determine the three-dimensional structure of the protein for the g.89865477_89895212del mutant, and the mutation resulted in numerous missing fragments and alterations in the protein’s structure. While this
in silico structural prediction strongly suggests a deleterious effect [
20], definitive experimental validation of the protein conformational changes using techniques like cryo-EM [
21], remains an important avenue for future investigation, although it is beyond the scope of this clinical genetics report.
Most patients with FA have normal or nearly normal blood cells at birth. Between the ages of 5 and 10 years, they often experience hematopenia [
22], which is frequently accompanied by anemia, hemorrhage, and infections. Acute myeloid leukemia and progressive bone marrow failure are common causes of death in FA patients [
23]. Laboratory tests for FA include hematological, bone marrow, and cytogenetic assays. The bone marrow shows hypoproliferative hypoplasia, hematopoiesis, and a rise in non-hematopoietic cells, comparable to acquired aplastic anemia [
4]. Therefore, FA is the predominant genetic factor responsible for aplastic anemia [
24]. The proband had the onset of aplastic anemia during childhood, without any anomalies in the endocrine system or congenital deformities. Surprisingly, his father had congenital finger abnormalities, and we initially suspected that a mutation in the
FANCA gene was responsible. Eighty of the 107 infants in the research had congenital abnormalities; the most prevalent congenital malformations among children with FA were dwarfism, polydactyly, thumb deformity, and café-au-lait spots [
13]. According to a review, approximately 35% of FA patients have upper limb skeletal anomalies, while overall congenital malformations are present in ~75% of cases [
3]. FA-related genes are involved in DNA damage repair pathway. Upon detection of DNA interstrand crosslinks, the FA core complex is activated to monoubiquitinate FANCD2 and FANCI, which then interact with BRCA2 to mediate interstrand crosslink repair [
25]. The apical ectodermal ridge of the limb bud, the reproductive organs, and the hematopoietic tissue of the embryo all exhibit high levels of FA gene expression [
26]. Limb malformations are prevalent in patients with FA, which can be explained by this embryonic expression.
Unexpectedly, the proband’s father was heterozygous for the
FANCA mutation, indicating that the malformation in his fingers was not likely the result of a covert inheritance of FA. Functional analyses revealed that while the intronic
EHMT1 variant (c.2382 + 1750G>A) did not alter mRNA splicing, it was associated with significantly reduced
EHMT1 expression in peripheral blood. Critically, this variant co-segregated with the ectrodactyly phenotype, as the affected individuals of the proband’s paternal lineage who carried the mutation exhibited ectrodactyly. Currently, only Kleefstra syndrome, an autosomal dominant disorder, has been linked to
EHMT1 mutations.
EHMT1 encodes a euchromatin histone methyltransferase that methylates histone H3 at lysine 9 (H3K9) in promoter regions, repressing gene transcription [
27]. Thus, our data are compatible with a model in which c.2382 + 1750G>A might disrupt transcriptional regulation, potentially via altered binding of key factors (e.g., SOX4, TCF7, TFAP2C), which would provide a plausible mechanism for the observed mRNA downregulation. Complementing this model, established mechanisms of mRNA decay suggest that the intronic variant could alternatively compromise pre-mRNA stability by perturbing RNA processing pathways [
28,
29], providing a parallel explanation for reduced transcript abundance. Our Western blot analysis provided further, multi-level support for the functional impact of this variant. The observed reduction in H3K9me2 offers compelling functional evidence for EHMT1 impairment, a finding consistent with the decreased H3K9me2 levels observed in fibroblasts from a patient with a pathogenic EHMT1 frameshift deletion [
30]. The concomitant reduction of a ~100 kDa protein band recognized by the EHMT1 antibody, potentially corresponding to a documented shorter isoform [
10], aligns with this trend, although definitive identification in PBMCs warrants future investigation.
EHMT1 dysfunction causes embryonic developmental anomalies [
31], which may underlie the ectrodactyly observed here.
The presentation of isolated ectrodactyly in our study, in the absence of the classic neurodevelopmental features of Kleefstra syndrome, aligns with the well-established framework of
EHMT1-related disorders. In our genetic analysis, we considered all plausible candidate variants that could explain the ectrodactyly phenotype. Key among our filtering criteria were the mode of inheritance and ACMG pathogenicity classification. Variants in genes such as
WDR35,
DYNC2LI1,
EVC2, and
NEK1 were deemed low priority because they are associated with autosomal recessive disorders, and their heterozygous state is not sufficient to cause disease. This is in stark contrast to the
EHMT1 variant, which resides in a gene linked to autosomal dominant conditions and perfectly co-segregates with the phenotype in a dominant manner. First, Kleefstra
et al. conclusively demonstrate that haploinsufficiency of
EHMT1 is the core disease mechanism, with no genotype-phenotype correlations observed among patients carrying various mutations, including large deletions, nonsense, splice-site, or missense variants, all of whom presented a similarly severe and variable classic syndrome [
7,
32]. Our finding of significantly reduced
EHMT1 mRNA expression, coupled with the observed decrease in H3K9me2 levels and the reduction of the putative EHMT1 protein, provides multi-level confirmation that the c.2382 + 1750G>A variant operates via this haploinsufficiency mechanism. Second, the phenotypic spectrum of
EHMT1 haploinsufficiency includes highly attenuated forms. Willemsen
et al. reported somatic mosaics with large deletions in
EHMT1 exhibiting only mild features, such as learning difficulties and subtle dysmorphisms [
33], proving that
EHMT1 gene partial deficiency can yield incomplete penetrance. This is exemplified in our study by the proband’s father, who exhibited isolated ectrodactyly rather than classic Kleefstra syndrome features; such phenotypic variability may arise from genetic modifiers, environmental factors, or tissue-specific disruption in gene regulation. Direct experimental confirmation of altered transcription factor binding (e.g., via EMSA or ChIP assays) would provide valuable mechanistic validation of the proposed transcriptional dysregulation hypothesis; these approaches represent a logical and important direction for future research to build upon our current findings.
An important limitation of this study is that it is based on a single pedigree. While pedigree studies are highly informative for identifying and characterizing rare variants, comparing the frequency of the observed FANCA deletion and assessing the association of the EHMT1 variant with ectrodactyly in larger, independent cohorts would significantly strengthen the pathogenicity assessment. In addition, it is important to acknowledge the limitations of our functional evidence regarding the EHMT1 variant. While the observed co-segregation within this pedigree strongly suggests a linkage between this genetic locus and the ectrodactyly phenotype, it does not constitute definitive proof of pathogenicity for the c.2382 + 1750G>A variant itself. The reduction in mRNA expression, although significant, could be correlative rather than causative. Although our in silico analysis predicts alterations in transcription factor binding sites, this remains a prediction requiring experimental validation to confirm a direct functional impact on transcriptional regulation. Therefore, we cannot exclude the possibility that other variants in linkage disequilibrium with c.2382 + 1750G>A could be responsible for the phenotype, or that this intronic variant acts in combination with other genetic or environmental factors.
5 Conclusions
Genetic sequencing remains the gold standard for diagnosing FA. In this study, we identified a novel FANCA deletion (g.89865477_89895212del) that expands the known mutational spectrum of FA. In addition, we identified an intronic EHMT1 variant (c.2382 + 1750G>A) that co-segregated with ectrodactyly in the pedigree and was accompanied by significantly reduced EHMT1 mRNA expression.
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