Allelic Heterogeneity Research Articles

Background. PMP22-related neuropathies comprise a spectrum of predominantly demyelinating disorders, most commonly Charcot–Marie–Tooth type 1A (CMT1A; 17p12 duplication) and hereditary neuropathy with liability to pressure palsies (HNPP; 17p12 deletion), with rarer phenotypes due to PMP22 sequence variants (CMT1E, Dejerine–Sottas syndrome [DSS]). Methods. We conducted a PRISMA-compliant systematic review (PROSPERO ID: 1139921) of PubMed and Scopus (January 2015–August 2025). Eligible studies reported genetically confirmed PMP22-related neuropathies with clinical and/or neurophysiological data. Owing to heterogeneous reporting, we synthesized pooled counts and proportions without meta-analysis, explicitly tracking missing denominators. Results. One hundred twenty-seven studies (n = 4493 patients) were included. Sex was available for 995 patients (males 53.8% [535/995]; females 46.2% [460/995]); mean age at onset was 23.7 years in males and 16.4 years in females. Phenotypic classification was reported for 4431/4493 (75.4% CMT1A, 20.9% HNPP, 2.6% CMT1E, 1.2% DSS). Across phenotypes, weakness/foot drop was the leading presenting symptom when considering only cohorts that explicitly reported it (e.g., 65.3% in CMT1A; 76.0% in HNPP); sensory complaints (numbness, paresthesia/dysesthesia) were variably documented. Neurophysiology consistently showed demyelinating patterns, with median and ulnar nerves most frequently abnormal among assessed nerves; in HNPP, deep peroneal and sural involvement were also common in evaluated subsets. Comorbidities clustered by phenotype: orthopedic/neuromuscular features (pes cavus/hammer toes, scoliosis/kyphosis, tremor) in CMT1A and DSS; broader metabolic/autoimmune and neurodevelopmental associations in HNPP; and higher syndromic/ocular/hearing involvement in CMT1E. Genetically, 75.6% (3241/4291) had 17p12 duplication, 19.6% (835/4291) 17p12 deletion, and 4.8% (215/4291) PMP22 sequence variants with marked allelic heterogeneity. Among 2571 cases with available methods, MLPA was most used (41.9%), followed by NGS (20.4%) and Sanger sequencing (17.8%). Main limitations include heterogeneous and incomplete reporting across studies (especially symptoms and nerve-specific data) and the absence of a formal risk-of-bias appraisal, which preclude meta-analysis and may skew phenotype proportions toward more frequently reported entities (e.g., CMT1A). Conclusions. Recent literature confirms that PMP22 copy-number variants account for the vast majority of cases, while sequence-level variants underpin a minority with distinct phenotypes (notably CMT1E/DSS). Routine MLPA, complemented by targeted/NGS, optimizes diagnostic yield. Standardized reporting of nerve-conduction parameters and symptom denominators is urgently needed to enable robust cross-study comparisons in both pediatric and adult populations.

Simple SummaryInflammatory bowel disease (IBD), which includes Crohn’s disease and ulcerative colitis, is a long-term illness that causes inflammation in the gut. Scientists have found that IBD is not only a disease of the intestines but can also affect the brain, leading to problems such as depression, anxiety, and other neurological conditions. In this study, we examined genetic data from large international studies to identify genes that increase the risk of IBD. We then explored how these genes are expressed in both the gut and the brain. Our results showed that many of the same genes active in IBD are also active in specific brain regions and are involved in pathways that regulate immunity, stress response, and nerve function. This suggests that the genetic background of IBD may also influence brain health. By highlighting these shared pathways, our findings provide insights into why people with IBD are more likely to experience neurological or psychiatric problems. This knowledge could help guide new treatments, not only for IBD but also for related brain conditions and may eventually improve patient care by addressing the disease in a more holistic way.Inflammatory bowel disease (IBD), comprising Crohn’s disease (CD) and ulcerative colitis (UC), arises from complex genetic and environmental interactions. Here, we integrate genome-wide association study (GWAS) meta-analyses with tissue-specific expression data from GTEx to map the polygenic architecture of IBD and its systemic implications. We identified 69 genome-wide significant single-nucleotide polymorphisms (SNPs) across 26 genes shared by CD and UC, revealing an almost equal partition of subtype-specific (50.7%) and shared (49.3%) risk variants. IL23R exhibited the highest allelic heterogeneity—three UC-specific, one CD-specific, and three shared SNPs—while ATG16L1′s four CD-specific variants underscored autophagy’s pivotal role in CD. Chromosomal mapping revealed distinct regulatory hotspots: UC-only loci on chromosomes 1 and 6, CD-only loci on chromosomes 10 and 16, and shared loci on chromosomes 7 and 19. Pathway enrichment emphasized IL-23/IL-17, Th17 differentiation, NF-κB, and JAK–STAT signaling as central to IBD pathogenesis. GTEx analyses showed uniformly high expression of IBD genes in gastrointestinal tissues, but pronounced heterogeneity across brain regions, including the cerebellum, frontal cortex, and hippocampus. This neuro-expression, together with enrichment of neurotrophin and neurodegeneration pathways and a nearly two-fold gene overlap with autism spectrum disorder, schizophrenia, and depression (FDR < 0.05), provides integrative evidence for gut–brain axis involvement in IBD. These findings consolidate prior work while extending perspectives on systemic disease implications. This study consolidates and systematizes dispersed genetic and transcriptomic findings into a unified reference framework. Our results highlight recurrent immune-regulatory and neuro-inflammatory pathways shared between gut and brain, offering a resource to guide future mechanistic, clinical, and translational investigations in IBD and related disorders.

BackgroundGLI family zinc finger 3 (GLI3) is a transcription factor involved in limb development. GLI3 gene variants have been shown to be associated with several human congenital limb malformations, including Greig cephalopolysyndactyly, Pallister–Hall syndrome, non-syndromic postaxial polydactyly (PAP-A/B), and preaxial polydactyly type IV (PPD-IV). The aim of this study was to identify GLI3 gene variants in ten Chinese families with limb malformations.MethodsTen Chinese families with limb malformations were recruited. Variant screening in probands was then performed using NGS, with candidate pathogenic variants verified by polymerase chain reaction (PCR) combined with Sanger DNA sequencing. Variant pathogenicity was evaluated using bioinformatics, evolutionary conservation, and disease and mutant allele co-segregation approaches. The biological effects of missense variants were predicted by three-dimensional protein conformation analysis.ResultsTen GLI3 variants were identified: two missense variants c.1063G>A (p.Val355Ile) and c.1489C>A (p.Leu497Ile), four nonsense variants c.2374C>T (p.Arg792*), c.2008C>T (p.Gln670*), c.1096 C>T (p.Arg366*), and c.2029C>T (p.Gln677*); three frameshift variants c.600delC (p.Tyr200*), c.1880_1881del (p.His627Argfs*48), and c.811_812delCT (p.Leu271Serfs*5); a large fragment deletion of NC_000007.14: g.42061081_42069739. Seven of these ten variants have never been recorded in the Human Gene Variant Database.ConclusionTen GLI3 variants were successfully identified in families with different limb malformations, indicating significant clinical and allelic heterogeneity of GLI3-related limb malformations. The present study expands the spectra of pathogenic variants and clinical manifestation for GLI3-related morphological disorder and provides solid evidence for genetic counseling and prenatal gene diagnosis in the affected families.

INTRODUCTION: Hearing loss is the most common neurological disorder in humans. In its prelingual form, it occurs in one in every 1,000 live births. The most common type is isolated autosomal recessive hearing loss, caused mainly by pathogenic variants of the GJB2 gene. The most common of these in all populations is c.35delG, located in exon two, which encodes this gene. This mutation has been identified in heterozygosity in Cubans with hearing loss. Given its high allelic heterogeneity, Sanger sequencing is recommended to confirm the molecular diagnosis. OBJECTIVE: To characterise exon 2 of the GJB2 gene in a series of Cuban patients with autosomal recessive prelingual isolated hearing loss. MATERIAL AND METHOD: A descriptive, cross-sectional study was conducted. From 379 cases in which molecular study was performed by allele-specific PCR of the pathogenic variant c.35delG, 13 heterozygotes were selected in which deletions D13S1830 and D13S1854 of the GJB6 gene had previously been ruled out. Sanger sequencing of exon 2 was performed, for which four specific oligonucleotides were designed to amplify two overlapping fragments to ensure complete analysis of the coding region of the GJB2 gene. Given the characteristics of the c.35delG mutation, two additional primers were included to analyse the start of exon 2. Information on the identified variants was sought on the ClinVar website. The audiometric characteristics of the patients were observed. Throughout the research, the principles of human research ethics were followed. RESULTS The c.427C&gt;T variant was identified in three individuals, while the c.94C&gt;T mutation was found in another, and c.139G&gt;T in a fifth. The patients presented sensorineural hearing loss with severity levels exceeding 61 dB. CONCLUSION: Three pathogenic variants were identified in the coding region of the GJB2 gene, associated with severe to profound hearing loss.

Long-read sequencing (LRS) technologies have enhanced the ability to resolve complex genomic architecture and determine the 'phase' relationships of genetic variants over long distances. Although genome-wide association studies (GWAS) identify individual variants associated with complex traits, they do not typically account for whether multiple associated signals at a locus may act in cis or trans, or whether they reflect allelic heterogeneity. As a result, effects that arise specifically from phase relationships may remain hidden in analyses using short-read and microarray data. While the advent of LRS has enabled accurate measurement of phase in population cohorts, statistical methods that leverage phase in genetic association analysis remain underdeveloped. Here, we introduce the Regression on Phase (RoP) method, which directly models cis and trans phase effects between variants under a regression framework. In simulations, RoP outperforms genotype interaction tests that detect phase effects indirectly, and distinguishes in-cis from in-trans phase effects. We implemented RoP at two cystic fibrosis (CF) modifier loci discovered by GWAS. At the chromosome 7q35 trypsinogen locus, RoP confirmed that two variants contributed independently (allelic heterogeneity). At the SLC6A14 locus on chromosome X, phase analysis uncovered a coordinated regulatory mechanism in which a promoter variant modulates lung phenotypes in individuals with CF when acting in cis with a lung-specific enhancer (E2765449/enhD). This coordinated regulation was confirmed in functional studies. These findings highlight the potential of leveraging phase information from LRS in genetic association studies. Analyzing phase effects with RoP can provide deeper insights into the complex genetic architectures underlying disease phenotypes, ultimately guiding more informed functional investigations and potentially revealing new therapeutic targets.

Long-read sequencing (LRS) technologies have enhanced the ability to resolve complex genomic architecture and determine the ‘phase’ relationships of genetic variants over long distances. Although genome-wide association studies (GWAS) identify individual variants associated with complex traits, they do not typically account for whether multiple associated signals at a locus may act in cis or trans, or whether they reflect allelic heterogeneity. As a result, effects that arise specifically from phase relationships may remain hidden in analyses using short-read and microarray data. While the advent of LRS has enabled accurate measurement of phase in population cohorts, statistical methods that leverage phase in genetic association analysis remain underdeveloped. Here, we introduce the Regression on Phase (RoP) method, which directly models cis and trans phase effects between variants under a regression framework. In simulations, RoP outperforms genotype interaction tests that detect phase effects indirectly, and distinguishes in-cis from in-trans phase effects. We implemented RoP at two cystic fibrosis (CF) modifier loci discovered by GWAS. At the chromosome 7q35 trypsinogen locus, RoP confirmed that two variants contributed independently (allelic heterogeneity). At the SLC6A14 locus on chromosome X, phase analysis uncovered a coordinated regulatory mechanism in which a promoter variant modulates lung phenotypes in individuals with CF when acting in cis with a lung-specific enhancer (E2765449/enhD). This coordinated regulation was confirmed in functional studies. These findings highlight the potential of leveraging phase information from LRS in genetic association studies. Analyzing phase effects with RoP can provide deeper insights into the complex genetic architectures underlying disease phenotypes, ultimately guiding more informed functional investigations and potentially revealing new therapeutic targets.

BackgroundEpidermolysis Bullosa (EB) is a rare genetic disorder that results in fragile skin and blistering and may lead to mucous membrane involvement. The disease manifests in several subtypes, among which the most serious conditions are dystrophic and junctional EB. This study intends to highlight the recurrent and novel genetic abnormalities that cause EB in the Western region of Saudi Arabia.MethodsTwelve Middle Eastern Arab families affected by Epidermolysis Bullosa (EB) were recruited from dermatology clinic from King Abdullah Medical Complex in Jeddah. Detailed clinical phenotyping was conducted for each patient to document EB-associated symptoms and to accurately determine the disease subtypes. Whole Exome Sequencing (WES) was performed to identify genetic variants associated with EB, and the resulting variants were classified by the guidelines of the American College of Medical Genetics and Genomics (ACMG). Additionally, multiple bioinformatics tools were employed to evaluate the pathogenicity of the detected variants. Variant segregation with disease phenotype was confirmed within the families using Sanger sequencing.ResultsWe identified 11 genetic variants, including three novel variants, in the COL7A1 (NM_000094.4), COL17A1 (NM_000494.4), and LAMB3 (NM_000228.3) genes across 12 EB families. The COL7A1 variants included frameshift variants (c.5924_5927del and c.6268_6269del), nonsense variants (c.1633C > T, c.1837C > T, c.2005C > T, and c.5888G > A), missense variants (c.4448G > A and c.8245G > A), and splice-site variants (c.6751-1G > A and c.8305-1G > A). Additionally, a splice-site variant was identified in COL17A1 (NM_000494.4; c.1394G > A) and another in LAMB3 (NM_000228.3; c.1977-1G > A). Bioinformatics analysis predicted these variants to be likely pathogenic because they disrupt collagen VII, XVII, and laminin 332, proteins essential for skin stability. Frameshift and nonsense variants introduce premature stop codons, leading to truncated or degraded transcripts. Splice-site variants likely cause aberrant splicing, disrupting the reading frame and impairing protein function.ConclusionWES is an effective first-line diagnostic tool for identifying EB-associated variants. This study reveals locus and allelic heterogeneity in EB cases from Saudi Arabia. The findings underscore the importance of early genetic screening for improving genetic counseling in high-consanguinity populations and emphasize the need for large-scale genetic studies in the country.

BackgroundHearing loss (HL) is a prevalent sensorineural disorder with a highly heterogeneous etiology. Next-generation sequencing (NGS) has revolutionized the genetic testing landscape for diseases characterized by high genetic and allelic heterogeneity, enabling the simultaneous screening of hundreds of genes.MethodsOne hundred and seventy-one unrelated patients with non-syndromic or syndromic HL were enrolled in this study. Exome sequencing (ES) was applied to explore molecular etiology in the cohort, and clinical reports were provided by geneticists and genetic counselors. Multidisciplinary team forums were conducted to ensure accurate diagnoses and improved patient management.ResultsThe molecular cause of HL was determined in 78 of 171 probands (45.6%): 54 with an autosomal recessive (AR) inheritance pattern, 23 with an autosomal dominant (AD) pattern, and 1 with both AR/AD inheritance patterns. Candidate variants in 33 genes were identified in the study cohort: 14 with an AR inheritance pattern, 18 with an AD pattern, and 1 with both AR/AD inheritance patterns. Twenty-eight of the variants identified in the study were novel.ConclusionExome sequencing facilitates genetic diagnosis and improves the management of patients with HL in clinical practice. Identifying the etiology of HL may improve patient care, refine genetic counseling, and facilitate the estimation of recurrence risk.

Factor XI (FXI) deficiency, or hemophilia C, is a rare bleeding disorder resulting from reduced levels or dysfunctional FXI protein due to mutations in the F11 gene. This study investigated the correlation between FXI activity levels, F11 genotype, and bleeding phenotypes. Clinical and genetic characteristics of 93 individuals from southern Italy diagnosed with congenital FXI deficiency, including 39 index cases and their relatives, were evaluated. FXI:C plasma levels were measured. Sanger sequencing of F11 was performed, and the pathogenicity of variants identified was assessed using in silico tools. FXI activity levels ranged widely (1–69%), with most cases being heterozygous and showing moderate deficiency. Only 12 individuals had severe FXI deficiency, typically associated with homozygosity or compound heterozygosity. Bleeding symptoms varied from mild to severe and occurred in 31% of subjects, though only a minority of those with severe deficiency experienced spontaneous or surgery-related bleeding. Sanger sequencing revealed 24 distinct F11 gene variants, predominantly missense mutations, with three novel variants (p.Val89*, p.Leu306Pro, and p.Trp515Gly). Common mutations included p.Glu135* and p.Glu315Lys. Variants were distributed across the gene, with no domain-specific clustering. No clear genotype–phenotype correlation was observed. FXI levels alone did not reliably predict bleeding risk, highlighting the influence of additional factors such as age, gender, and clinical history. This study reinforces the allelic and clinical heterogeneity of FXI deficiency and the limited utility of FXI:C levels alone for predicting bleeding severity. Further research is needed to clarify the complex genotype–phenotype relationships in FXI deficiency.

Drosophila Col4a1 Glycine mutations highlight allelic heterogeneity and mechanistic pleiotropy.

Identification of 13 novel pathogenic SLC25A13 variants and comparison of the genetic spectrum among different geographic regions: Molecular characterization of a large cohort of citrin deficiency in China.

Identification of a pathogenic variant in NF1 is diagnostic for neurofibromatosis, but is often impossible at the moment of variant detection due to many factors including allelic heterogeneity, sequence homology, and the lack of functional assays. Computational tools may aid in interpretation but are not established for NF1. Here, we optimized our random forest-based predictor RENOVO for NF1 variant interpretation. RENOVO was developed using an approach of “database archaeology”: by comparing versions of ClinVar over the years, we defined “stable” variants that maintained the same pathogenic/likely pathogenic/benign/likely benign (P/LP/B/LB) classification over time (n = 3579, the training set), and “unstable” variants that were initially classified as Variants of Unknown Significance (VUS) but were subsequently reclassified as P/LP/B/LB (n = 57, the test set). This approach allows to retrospectively measure accuracy on prediction with insufficient information, reproducing the scenario of maximal clinical utility. We further validated performance on: (i) validation set 1: 100 NF1 variants classified as VUS at the time of RENOVO development and subsequently reclassified as P/LP/B/LB in ClinVar; (ii) validation set 2: 15 de novo variants discovered in a prospective clinical cohort and subsequently reclassified per ACMG criteria. RENOVO obtained consistently high accuracy on all datasets: 98.6% on the training test, 96.5% in the test set, 82% in validation set 1 (but 96.2% for missense variants) and 93.7% on validation set 2. In conclusion, RENOVO-NF1 accurately interprets NF1 variants for which information at the time of detection is insufficient for ACMG classification and may overcome diagnostic challenges in neurofibromatosis.Supplementary InformationThe online version contains supplementary material available at 10.1186/s40246-025-00803-z.

Detection Rate of Cataract-Related Gene Variants in Sporadic Childhood Cataract Patients in Southern China.

Testing inferred haplotype genealogies for association with phenotypes has been a longstanding goal in human genetics given their potential to detect association signals driven by allelic heterogeneity - when multiple causal variants modulate a phenotype - in both coding and noncoding regions. Recent scalable methods for inferring locus-specific genealogical trees along the genome, or representations thereof, have made substantial progress towards this goal; however, the problem of testing these trees for association with phenotypes has remained unsolved due to the growth in the number of clades with increasing sample size. To address this issue, we introduce several practical improvements to the kalis ancestry inference engine, including a general optimal checkpointing algorithm for decoding hidden Markov models, thereby enabling efficient genome-wide analyses. We then propose LOCATER, a powerful new procedure based on the recently proposed Stable Distillation framework, to test local tree representations for trait association. Although LOCATER is demonstrated here in conjunction with kalis, it may be used for testing output from any ancestry inference engine, regardless of whether such engines return discrete tree structures, relatedness matrices, or some combination of the two at each locus. Using simulated quantitative phenotypes, our results indicate that LOCATER achieves substantial power gains over traditional single marker testing, ARG-Needle, and window-based testing in cases of allelic heterogeneity, while also improving causal region localization. These findings suggest that genealogy-based association testing will be a fruitful approach for gene discovery, especially for signals driven by multiple ultra-rare variants.

Monogenic forms of inflammatory bowel disease (IBD) are driven by variants in genes critical to pathways in intestinal homeostasis and immunity. We investigated gene- and variant-level effects of these genes with IBD and phenome-wide association, leveraging large-scale whole exome sequencing data across 4 diverse cohorts: BioMe Biobank (Regeneron and Sema4), Penn Med Biobank, and UK Biobank. Predicted loss- and gain-of function variants were extracted from 102 monogenic genes. Gene- and variant-level association tests for binary traits were performed across 4 cohorts grouped based on genetic similarity in European, African, and Admixed American populations. From 11 546 variants extracted, over two-thirds were predicted as loss-of-function (LOF), with 93% classified as ultra-rare and 1172 Goldilocks variants (not ultra-rare) enriched at least 10-fold in African populations. Gene-level IBD association testing demonstrated numerous replicated associations in European cohorts, reflecting well-powered independent cohorts. Twenty monogenic genes overlap with genome-wide IBD loci, fifteen of which displayed gene-level association trends. Heterozygous carriage of African-predominant LOF alleles in NPC1 (intracellular cholesterol transport) and ADA/ADA2 (purine metabolism), were associated with IBD. These variants also showed replicated associations with phenotypes related to cardiac conduction, infection, and lipid metabolism. We define overlap between monogenic and genome-wide IBD loci and reveal population-specific allelic heterogeneity of IBD risk genes. We uncover novel phenotype associations suggesting pleiotropic effects of monogenic IBD genes. African-predominant variants revealed allelic associations absent in European cohorts, and of potential clinical significance, underscoring the importance of increasing diversity in genetic studies.

Alcohol use disorder (AUD) is a leading cause of death and disability worldwide. There has been substantial progress in identifying genetic variants that underlie AUD. However, whole-exome sequencing studies of AUD have been hampered by the lack of available samples. We analyzed whole-exome sequencing data of 4530 samples from the Yale-Penn cohort and 469,835 samples from the UK Biobank, which represent an unprecedented resource for exploring the contribution of coding variants in AUD. After quality control, 1750 African-ancestry (1142 cases) and 2039 European-ancestry (1420 cases) samples from the Yale-Penn and 6142 African-ancestry (130 cases), 415,617 European-ancestry (12,861‬ cases), and 4607 South Asian (130 cases) samples from the UK Biobank cohorts were included in the analyses. We confirmed the well-known functional variant rs1229984 in ADH1B (p = 4.88 × 10-31) and several other variants in ADH1C. Gene-based collapsing tests that considered the high allelic heterogeneity revealed the previously unreported genes CNST (p = 1.19 × 10-6), attributable to rare variants with allele frequency < 0.001, and IFIT5 (p = 3.74 × 10-6), driven by the burden of both common and rare loss-of-function and missense variants. This study extends our understanding of the genetic architecture of AUD by providing insights into the contribution of rare coding variants, separately and convergently with common variants in AUD.

Nonsyndromic orofacial clefts (NSOFCs) are the most common human craniofacial defects. Genetic factors play a critical role in the pathogenesis of NSOFCs. However, known causal genes only explain a minority of the estimated heritability. To unveil the underlying genetic architecture, exome sequencing is performed on 214 sporadic patients with NSOFCs. The findings substantiate the genetic and allelic heterogeneity of NSOFCs and underscore the crucial role of dysregulation of OFC‐related signaling pathways in the occurrence of NSOFCs. Besides, the candidate variants discovered provide a fruitful resource for further genetic studies. Particularly, three BOC missense variants (p.R407W, p.G436S, and p.D1018N) are identified in three unrelated cases with cleft palate. In parallel, a BOC nonsense variant (p.R681X), co‐segregating with a GLI2 missense variant (p.A543G), is identified in a multiplex family with microform cleft lip. Functional studies demonstrate while the four BOC variants are hypomorphic alleles, the GLI2 variant is a hypermorphic allele. The counteraction between BOC p.R681X allele and GLI2 p.A543G allele accounts for the mild phenotype in the multiplex family. Thus, this study establishes BOC as a novel causal gene and implicates a two‐locus model of inheritance via the epistatic antagonism of two SHH pathway variants in NSOFCs.

ABSTRACTTo elucidate the genetic etiology of hearing impairment (HI) in South Africa, 45 nonsyndromic HI (NSHI) and syndromic HI (SHI) families with ≥ 2 affected members were analyzed. Exome and sanger sequencing were used to identify causal genes. For NSHI, 14 of 24 families segregated variants in NSHI genes, that is, CDH23, GJB2, MITF, MYO7A, MYO15A, PCDH15, POU3F4, REST, SLC26A4, TMPRSS3, and WFS1. For the 21 SHI families, 14 have Waardenburg syndrome, two Branchio‐Oto‐Renal syndromes, and one each with Bartter, Chudley‐McCullough, Deafness‐Albinism, MYH9‐related disorder, and Pendred syndromes. The cause of SHI was determined for 14 families, with EDN3, EDNRB, GPSM2, MITF, MYH9, SLC12A1, and SLC26A4 underlying the syndrome in a single family, EYA1 in two families, and PAX3 in five families. For the NSHI and SHI genes, 52.9% and 35.7% of the variants, respectively, have not been reported in disease etiology. Additionally, two Waardenburg families segregated variants in NSHI genes, BDP1 and MYO6, but these findings need to be validated. This study enhances the understanding of the genetic landscape of HI in South Africa, revealing a high level of locus and allelic heterogeneity. Studying diverse populations provides new insights into HI etiology that, in turn, can improve genetic diagnosis and personalized management.

The MC1R gene, which is responsible for most cases of red hair, affects other hair and skin colours and contributes to differences in pain sensitivity and consists of a single exon with a very high level of allelic heterogeneity. In this research, we show that the Oxford Nanopore Technology (ONT) offers a good alternative to study the MC1R sequence variation. MinION was used to sequence the 1590bp MC1R exon and minimal promoter in a cohort of 126 subjects, including 65 red-haired individuals, using the FLO-MIN106 (R9.4) chemistry. Assigned DNA variants were validated using Ion Torrent technology provided with Ion Xpress Plus Fragment Library Kit and the Personal Genome MachineTM (PGMTM). We show that the use of the latest sequencing kit V14 together with the FLO-MIN114 (R10.4.1) flow cell has eliminated the systematic errors observed with the previous chemistry and allowed reliable detection of short indels important for phenotypic inference. Importantly, the use of the algorithm implemented in the EPI2ME software enabled convenient and accurate read-based phase determination which can be useful in data interpretation.

Vascular Ehlers Danlos Syndrome (vEDS) is a connective tissue disorder caused by COL3A1 mutations for which there are no treatments due to a limited understanding of underlying mechanisms. We aimed to identify the molecular insults of mutations, focusing on collagen folding, to establish if targeting protein folding represents a potential therapeutic approach. Analysis of two novel COL3A1 glycine mutations, G189S and G906R, in primary patient fibroblast cultures revealed secretion of misfolded collagen III and intracellular collagen retention leading to lower extracellular collagen levels. This was associated with matrix defects, endoplasmic reticulum (ER) stress, reduced cell proliferation and apoptosis. The ER stress was mediated by activation of IRE1 and PERK signalling arms with evidence of allelic heterogeneity. To establish if promoting ER protein folding capacity or protein degradation represents novel therapeutic avenues, we investigated the efficacy of FDA-approved small molecules. The chemical chaperone 4-phenylbutyric acid (PBA) rescued the ER stress and thermostability of secreted collagen leading to reduced apoptosis and matrix defects, and its efficacy was influenced by duration, dosage and allelic heterogeneity. Targeting protein degradation with carbamazepine (CBZ), or PBA-CBZ in combination did not increase treatment efficacy. These data establish that ER stress is a molecular mechanism in vEDS that can be influenced by the position of COL3A1 mutation. It combines with matrix defects due to reduced collagen III levels and/or mutant protein secretion to vEDS pathogenesis. Targeting protein folding using FDA-approved chemical chaperones represents a putative mechanism-based therapeutic approach for vEDS that can rescue intra- and extracellular defects.