Skip to content
Frontiers
Search

Original Research

Frontiers in Genetics ·

Volume 17 - 2026 | https://doi.org/10.3389/fgene.2026.1951476

The mutational and clinical spectrum of EYS -associated retinitis pigmentosa in an Eastern European and Northern Asian cohort: two recurrent founder alleles

  • Marianna Weener1,2*corresponding author
  • Igor Hatsenko3
  • Inna Zolnikova4
  • Natella Chincharauli5
  • Maria Shilova6
  • Anna Venger7
  • Olga Luneva7
  • Larisa Balashova8
  • Jean Salmasi8
  • Gennadiy Poryadin8
  1. 1Ocular Genomics Institute, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, United States
  2. 2Oftalmic Clinical Research Center, Moscow, Russia
  3. 3Morozovskaya Children’s City Clinical Hospital, Moscow, Russia
  4. 4Helmholtz National Medical Research Center of Eye Diseases, Moscow, Russia
  5. 5I.M. Sechenov First Moscow State Medical University, Moscow, Russia
  6. 6Ophthalmology Clinic of Dr. Shilova, Moscow, Russia
  7. 7EYS Patients Advocacy Group, Moscow, Russia
  8. 8Pirogov Russian National Research Medical University, Moscow, Russia
Article metrics0 viewsView details
PDFCiteMetrics

Abstract

Biallelic EYS variants are one of the frequent causes of autosomal recessive inherited retinal disease worldwide, yet the EYS mutational landscape of Eastern European and Northern Asian populations has not been systematically described. We characterized the molecular and clinical spectrum of EYS -associated retinitis pigmentosa (RP) in this population. Thirty-nine patients with confirmed biallelic EYS variants were selected from 500 patients enrolled in the prospective inherited retinal disease genotyping clinical trial (NCT03901391). All patients underwent whole exome sequencing with copy number/structural variant analysis and standardized ophthalmic phenotyping, including best corrected visual acuity (BCVA), slit lamp biomicroscopy, refractometry, perimetry, optical coherent tomography (OCT), fundus autofluorescence (FAF), ophthalmoscopy and electroretinogram (ERG). We identified 34 distinct EYS variants: 22 pathogenic, 8 likely pathogenic, and 4 variants of uncertain significance by American College of Medical Genetics (ACMG) criteria. Fifteen variants were novel, including eight structural deletions. Two recurrent alleles c.1155T>A (p.Cys385) in 16 (20.3%) alleles, and c.8648_8655del (p.Thr2883Lysfs4) in 15 (19.0%) alleles were the most frequent; together they accounted for 39.2% of alleles, with relatedness analysis supporting a shared founder origin. Median age of disease manifestation was 18 years and median BCVA 0.16 logMAR; worse acuity correlated with older age (rank correlation coefficient = 0.34, p = 0.035). This first description of the EYS spectrum in an Eastern European and Northern Asian cohort expands the allelic diversity of the gene, provides a genotype-phenotype description and defines two population-specific founder alleles amenable to targeted screening and future treatment.

Keywords

1 Introduction

Retinitis pigmentosa (RP) is the most common inherited retinal disease (IRD), affecting roughly 1 in 4,000 individuals and characterized by progressive rod-then-cone photoreceptor degeneration that manifests as nyctalopia, concentric visual field constriction, and eventual loss of central vision. Autosomal recessive RP (arRP) is genetically heterogeneous, with 79 causative genes. Among these, the EYS gene (Eyes shut homolog; RP25, OMIM 612424) is one of the most frequent causes of arRP (Abd El-Aziz et al., 2008; Collin et al., 2008; Verbakel et al., 2018).

EYS gene is located on chromosome 6q12, spans almost 2 Mb of genomic DNA and comprises 43 exons, reference transcript is NM_001142800.2 (ENST00000503581). It encodes a large secreted extracellular matrix protein expressed in the photoreceptor outer segments, where it is required for the maintenance of ciliary architecture and photoreceptor survival (Abd El-Aziz et al., 2008; Collin et al., 2008). Biallelic loss-of-function (LoF) variants in EYS cause photoreceptor disorganization and apoptosis, producing a progressive rod–cone dystrophy (Marques et al., 2025).

The reported contribution of EYS to arRP varies markedly by population, from approximately 5% in European and North-American cohorts to 18%–33% in East-Asian, and especially Japanese populations, where specific recurrent alleles reflect founder effects (Littink et al., 2010; Sun et al., 2020; Gao et al., 2022; Yang et al., 2020; Arai et al., 2015; Iwanami et al., 2019; Koyanagi et al., 2019; Barragán et al., 2010). Because EYS is large and structurally complex, its variant spectrum is enriched for copy number and structural variants (SVs), which are frequently missed by panel or exome sequencing that is not complemented by dedicated SV analysis. Characterizing the population-specific allelic frequency of EYS gene is relevant to diagnostic strategy and to the design of allele- and mutation-directed therapies (Iwanami et al., 2019; Zampaglione et al., 2020).

Population size of Eastern Europe and Northern Asia is more than 200 million people, and ethnic diversity of the populations encompass more than 190 recognized ethnic groups across the Russian Federation and neighboring states. Mutational spectrum of cone dystrophy and achromatopsia in this region was reported earlier (Ivanova et al., 2020; Zolnikova et al., 2017), but the rod-cone dystrophy mutational spectrum in this region has not been systematically evaluated. We therefore set out to define the molecular and clinical spectrum of EYS-associated RP in a cohort of 39 patients with confirmed molecular diagnosis, derived from a prospective genotyping study of 500 patients with RP (NCT03901391).

2 Materials and methods

2.1 Study design, participants, and ethics

This study was conducted within a prospective observational inherited retinal disorders (IRD) genotyping clinical trial (NCT03901391) carried out at the Oftalmic Clinical Research Center, Moscow. The study was approved by the Ethics Committee at UDP CKB, Moscow (approval number IRB#007, 26 June 2019) and adhered to the tenets of the Declaration of Helsinki. All participants provided written informed consent. 361/500 cases (72.2%) were molecularly solved and 39/361 (10.8%) patients were confirmed carrying biallelic EYS variants as a cause of RP diagnosis and were included in the analyses reported here (n = 39).

2.2 Clinical phenotyping

All participants underwent standardized ophthalmology examination including best corrected visual acuity (BCVA), slit lamp biomicroscopy, refractometry, intraocular pressure measurement, dilated fundus examination, automated perimetry, ERG, fundus autofluorescence, and optical coherence tomography (OCT). BCVA was measured monocularly (OD and OS) using a standard illuminated chart and recorded in decimal notation; for analysis, decimal acuities were converted to logMAR (logMAR = −log10[decimal]) and the mean of the two eyes was used. Objective refraction was obtained by autorefractometry; the spherical equivalent (SE) of each eye was calculated and averaged across eyes to yield a single representative value per participant. Automated perimetry (Humphrey Field Analyzer, Carl Zeiss Meditec) was used to estimate the size and shape of the visual field.

SD-OCT was performed under standardized conditions for high resolution macular imaging (Zeiss, CIRRUS 6000). Fundus imaging was performed using Topcon TRC-NW8 fundus camera. Ganzfeld (full-field) ERG was recorded according to the standards of the International Society for Clinical Electrophysiology of Vision (ISCEV). For each subject, a- and b-wave amplitudes and latency times were analyzed separately and averaged. Quantitative ERG was available for all 39 patients (36 with recordable responses and 3 non-recordable). Ultrawide-field (Optos) imaging was not available at the study site and was therefore not obtained.

2.3 DNA extraction, sequencing, and variant calling

Genomic DNA was extracted from peripheral blood using a Qiagen DNA kit. Whole exome sequencing was performed on an Illumina NovaSeq 6000 platform (2 × 100 bp) with target enrichment using the Agilent SureSelect Human All Exon V7 panel, to a mean on-target depth of 70–100×. Reads were aligned and variants called using an automated pipeline against the human reference genome hg38. The method did not reliably detect insertions/deletions longer than 10 bp or intronic variants (other than those adjacent to exons); such variants were addressed by dedicated copy number/structural variant analysis and multiplex ligation-dependent probe amplification (MLPA).

2.4 Structural variant detection and confirmation

Copy number and structural variants in EYS were identified from exome coverage data and confirmed by MLPA using a standardized protocol. Structural deletion breakpoints are reported in genomic coordinates hg38 (Table 1; Supplementary Table 1).

TABLE 1. The 34 distinct EYS variants identified in the cohort. Variants are ordered along the coding sequence (NM_001142800.2).

Nucleotide change (NM_001142800.2)Protein changeLocationVariant typeNgnomAD v4.1 MAFACMG classReferences
c.32dupTp.Met12Aspfs*14Exon 4Frameshift21.55 × 10−5LPSun et al. (2020)
c.105delAp.Gln34fsExon 2Deletion11.24 × 10−6P–
c.525_527delGGAp.Glu176delExon 4Frameshift15.95 × 10−5VUSBarragán et al. (2010)
c.600C>Ap.Cys200*Exon 4Nonsense1–PNovel
c.1057-1G>C–Intron 6Splicing2–PBarragán et al. (2010)
c.1155T>Ap.Cys385*Exon 7Nonsense162.98 × 10−4LPYang et al. (2020)
c.1641_1644delTCAGp.Ser547fsExon 11Frameshift1–PNovel
c.1956C>Ap.Cys652*Exon 12Nonsense2–PNovel
c.2259+1G>A–Intron 14Splicing45.83 × 10−5PYang et al. (2020)
c.2829T>Ap.Cys943*Exon 18Nonsense1–PWestin et al. (2021)
c.2989_2990insAA–Intron 19Splicing1–PNovel
c.3676G>Tp.Gly1226*Exon 24Nonsense46.7 × 10−7LPWoof et al. (2024)
c.4120C>Tp.Arg1374*Exon 26Nonsense21.09 × 10−5PWoof et al. (2024)
c.4350_4356delp.Ile1451Profs*3Exon 26Frameshift19.47 × 10−5LPMarques et al. (2025)
c.4815_4816delCAinsATAGp.Thr1606fsExon 26Frameshift2–PNovel
c.5084C>Gp.Ser1695*Exon 26Nonsense26.45 × 10−7PWoof et al. (2024)
c.5835+1G>A–Intron 27Splicing17.12 × 10−7PHeutinck et al. (2025)
c.6714delp.Ile2239Serfs*18Exon 33Frameshift45.22 × 10−5LPWestin et al. (2021)
c.7056-1G>A–Intron 35Splicing1–PNovel
c.7276T>Gp.Tyr2426AspExon 37Missense14.51 × 10−6VUS–
c.7394C>Gp.Thr2465SerExon 37Missense13.54 × 10−4VUSGao et al. (2022)
c.7550G>Ap.Gly2517AspExon 38Missense1–VUSNovel
c.8133_8137delCTTTCp.Phe2712fsExon 42Frameshift23.67 × 10−5LPDi et al. (2016)
c.8648_8655del​CAT​GCA​GAp.Thr2883Lysfs*4Exon 43Frameshift153.65 × 10−4LPDi et al. (2016)
c.8831dupp.Arg2946LysfsTer4Exon 43Frameshift1–PWoof et al. (2024)
c.9317_9336delp.Thr3106LysfsTer13Exon 43Frameshift14.52 × 10−5LPWestin et al. (2021)
chr6:63984236-63984906671bp deletionExon 35Deletion1–PNovel
chr6:65291239-652944493 kb deletionIntron 12Deletion1–PNovel
chr6:65297039-65131851165 kb deletionExon 11Deletion1–PNovel
chr6:65490945-654989768.1 kb deletionExon 3-4Deletion1–PNovel
chr6:65491560-65384458107 kb deletionExon 4-7Deletion1–PNovel
chr6:65497059-65352499145.4 kb deletionExon 6-8Deletion1–PNovel
chr6:65504108-6551549511.1 kb deletionIntron 2Deletion1–PNovel
chr6:65508505-65382463126.7 kb deletionExon 5-7Deletion1–PNovel

N = allele count in the cohort. MAF = minor allele frequency, gnomAD v4.1. ACMG classification of P, pathogenic; LP, likely pathogenic; VUS, variant of uncertain significance. The two founder alleles, c.1155T>A (p.Cys385) and c.8648_8655del (p.Thr2883Lysfs4), are the most frequent. Structural deletions are given as approximate hg38 coordinates with size.

2.5 Variant classification (ACMG/AMP)

Sequence variants were classified according to the American College of Medical Genetics (ACMG) and the Association for Molecular Pathology (AMP) standards and guidelines (Richards et al., 2015). Each variant was assigned a tier of pathogenic (P), likely pathogenic (LP), or variant of uncertain significance (VUS) and the specific ACMG/AMP criteria applied to each variant are listed in Supplementary Table 1. For previously reported variants, ClinVar and published classifications were considered as supporting evidence; for novel variants (which by definition have no ClinVar entry), classification was performed de novo from the criteria, and the basis of classification is recorded in a separate column.

2.6 Determination of variant novelty

A variant was considered novel if it was absent from gnomAD v4.1, ClinVar, the Human Gene Mutation Database (HGMD), and the peer-reviewed EYS literature at the time of analysis. Structural variants were additionally checked for absence from population structural variant resources: gnomAD-SV and Database of Genomic Variants (DGV). Population allele frequencies are reported from gnomAD v4.1 (Table 1; Supplementary Table 1).

2.7 Ethnicity and genetic ancestry

Ethnicity was first self-reported by participants on the basis of passport data and is provided to support future population-genetic and founder-mutation research in specific communities; we note that ethnicity is a fluid socio-political construct and that no single internationally recognised classification exists, so labels follow common regional usage and are standardised post hoc in line with Ethnonational Classification demographic recommendations (Ahmed et al., 2004). Self-reported ethnicity was then compared with genetically inferred ancestry from the whole exome sequencing (WES) data: individual germline variant profiles were projected against 1000 Genomes Project reference populations EUR, EAS, SAS, AFR, AMR–European, east Asian, south Asian, African and American respectively, and individual ancestry proportions were estimated by maximum-likelihood admixture analysis (ADMIXTURE and fastSTRUCTURE). We report self-reported ethnicity and genetically inferred ancestry as distinct categories and do not treat heterogeneous ethnic labels as equivalent taxonomic units in any analysis (Ahmed et al., 2004; Gusareva et al., 2025; Alexander et al., 2009; Raj et al., 2014).

2.8 Relatedness analysis

Because recurrent alleles suggest a possible founder effect, the exomes were analyzed for relatedness. Following joint calling through a single consistent pipeline (to reduce exome capture bias) and quality control, a filtered set of high quality SNPs (single nucleotide polymorphisms) in KING software version 2.3.2 on a filtered, high quality SNP set (12,300 SNPs per sample) on the hg38 build was used to estimate pairwise kinship (Manichaikul et al., 2010). Kinship coefficients were interpreted using standard KING thresholds (first-degree 0.177–0.354; second-degree 0.0884–0.177; third-degree 0.0442–0.0884; <0.0442 unrelated/more distant). The analyzed population was not considered small or endogamous, so background relatedness is not expected to inflate kinship estimates. The mean ± SD coefficient was 0.0092 ± 0.0034 and range of pairwise kinship coefficients among the founder allele carriers was from 0.0012 to 0.0531.

2.9 Segregation analysis

Segregation of all detected EYS variants was confirmed by PCR (polymerase chain reaction) amplification of the relevant targeted regions with gene-specific primers and Sanger sequencing (BigDye Terminator v3.1; ABI 3500 capillary sequencer), with bidirectional confirmation and manual review of chromatograms.

2.10 Statistical analysis

All statistical analyses were performed in R (v4.4). Continuous variables are summarised as median and interquartile range (IQR) with range; categorical variables - as counts and percentages. Because subgroup sizes were small and distributions non-normal, only non-parametric methods were used. Genotype-group comparisons (founder allele carriers vs. non-carriers) used the two-sided Wilcoxon rank-sum test with exact p-values; effect sizes were quantified with Cliff’s delta, which is a nonparametric effect-size measure that tells how strongly two groups differ, especially when the data are not normally distributed (with the conventional negligible/small/medium/large interpretation). To control the false-discovery rate across the four functional endpoints (age at onset, BCVA, visual field diameter, spherical equivalent), p-values were adjusted by the Benjamini–Hochberg (BH) procedure. Associations between age and visual function were assessed with Spearman’s rank correlation. Two-sided p < 0.05 was considered nominally significant; genotype-phenotype comparisons are reported as exploratory.

3 Results

3.1 Cohort and diagnostic context

Within this cohort EYS accounted for 39 of 361 (10.8%) molecularly solved cases, placing EYS among the most frequent arRP causative genes in this population. There were 22 women and 17 men. Self-reported ethnicity (from passport data) was predominantly East-Slavic but also included Tatar, Mari, Chechen, Cherkess, Kazakh, Tajik, Ukrainian, and Belarusian individuals, reflecting the ethnic diversity of Eastern Europe and Northern Asia. Genetic ancestry (from WES) was concordant with the self-reported origin (Section 2.7). Median age at disease manifestation was 18 years, interquartile range (IQR) 15–19; range 9–25, and median age at examination was 29 years (IQR 24.5–37.5; range 15–66).

3.2 The EYS mutational spectrum

The EYS gene mutation spectrum consisted of 10 frameshift variants (29.4%), nine deletions/SVs (26.5%), seven nonsense variants (20.6%), five splice-region variants (14.7%), and three missense variants (8.8%) (Figure 1a). All reported variants are shown in Figure 1b depicting in which domain of the EYS gene the exact variant was located. Fifteen of the 34 variants (44.1%) were novel (Figure 1c) absent from gnomAD v4.1, ClinVar, HGMD, and published EYS literature at the time of analysis (Section 2.6). Eight of these novel variants were structural deletions, underscoring the high structural variant burden of the EYS locus and the value of dedicated copy number/SV analysis alongside exome sequencing (Zampaglione et al., 2020; de Bruijn et al., 2023; Fabian-Morales et al., 2024).

Spectrum and classification of *EYS* variants in the cohort. **(a)** Distribution of the 34 unique disease-causing *EYS* variants by molecular consequence: frameshift 10 (29.4%), deletion (structural/copy number) 9 (26.5%), nonsense 7 (20.6%), splicing 5 (14.7%), and missense 3 (8.8%). **(b)** Positions of the identified variants along the *EYS* protein domain architecture (laminin G, EGF-like and Laminin A/G domains). **(c)** Variant composition of the unique set: novelty (15 novel, 44%; 19 previously reported, 56%) and ACMG/AMP classification (22 pathogenic, 8 likely pathogenic, 4 VUS).
Figure 1. Spectrum and classification of EYS variants in the cohort. (a) Distribution of the 34 unique disease-causing EYS variants by molecular consequence: frameshift 10 (29.4%), deletion (structural/copy number) 9 (26.5%), nonsense 7 (20.6%), splicing 5 (14.7%), and missense 3 (8.8%). (b) Positions of the identified variants along the EYS protein domain architecture (laminin G, EGF-like and Laminin A/G domains). (c) Variant composition of the unique set: novelty (15 novel, 44%; 19 previously reported, 56%) and ACMG/AMP classification (22 pathogenic, 8 likely pathogenic, 4 VUS).

Across 39 patients we identified 34 distinct EYS variants: 22 variants were pathogenic and 8 were likely pathogenic; the remaining 4 were classified as VUS (Figure 1c). Each of 38 patients had two variants, one in each allele, and patient P2 carried three alleles: one known pathogenic variant in EYS c.1057-1G>C and two VUS variants in the second allele confirmed by segregation analysis: c.7394C>G and c.525_527delGGA. They were classified as “hot” VUS with potentially damaging effect. As the available evidence did not allow reliable discrimination between these two VUSs, their individual contributions to the disease phenotype remain uncertain. This resulted in total of 79 alleles: 30 pathogenic, 45 likely-pathogenic, and 4 VUS alleles, classified by ACMG/AMP criteria (Richards et al., 2015). VUSs are reported separately with explicit caveats (Section 2.5), they were not used to support a molecular diagnosis. Following the hot/cold VUS classification, we regard VUS that occur in trans with an established null allele and carry additional supporting criteria as “hot” (leaning pathogenic and warranting functional follow-up), and isolated VUS without such support as “cold.”

3.3 Two recurrent founder alleles and relatedness

Two alleles recurred at high frequency (Table 1). The nonsense variant c.1155T>A (p.Cys385, exon 7) was carried by 16 of 39 patients (allele count 16/79; 20.3% of disease alleles), and the frameshift variant c.8648_8655del​CAT​GCA​GA (p.Thr2883Lysfs4, exon 43) was carried by 15 of 39 patients (allele count 15/79; 19.0%). Together these two alleles accounted for 31 of 79 disease alleles (39.2%). Twenty patients carried at least one of the two recurrent alleles, and nine patients carried both.

To test whether this recurrence reflects shared ancestry rather than independent mutational events, we performed relatedness analysis on the exomes of the cohort using KING version 2.3.2 on a filtered, high quality SNP set. Across all 741 pairwise comparisons, only two pairs showed above-background kinship P2–P3 (a known mother–daughter pair) and P16–P32 (fourth degree, known as second cousins); all remaining 739 pairs were unrelated (Figure 2; Supplementary Data Sheet 1). This confirms that the recurrent alleles reflect population-level founder effects rather than close familial clustering within the cohort (Manichaikul et al., 2010).

Genetic relatedness within the cohort. **(a)** Pairwise KING-software kinship coefficients for all 741 patient pairs (39 individuals); cells shaded by kinship (diagonal set to 0.5), with the two related pairs outlined. **(b)** Two related pairs against expected kinship with first- and fourth-degree relatives: P2–P3 (kinship 0.243, known mother–daughter pair) and P16–P32 (kinship 0.026, fourth degree; known second cousins). All remaining 739 pairs were unrelated.
Figure 2. Genetic relatedness within the cohort. (a) Pairwise KING-software kinship coefficients for all 741 patient pairs (39 individuals); cells shaded by kinship (diagonal set to 0.5), with the two related pairs outlined. (b) Two related pairs against expected kinship with first- and fourth-degree relatives: P2–P3 (kinship 0.243, known mother–daughter pair) and P16–P32 (kinship 0.026, fourth degree; known second cousins). All remaining 739 pairs were unrelated.

3.4 Genotype–phenotype associations

Because the two founder alleles were very frequent in the cohort, we asked whether carrying a founder allele was associated with a distinct clinical phenotype. We compared key clinical parameters between founder allele carriers (patients carrying at least one of c.1155T>A or c.8648_8655del; n = 20) and non-carriers (n = 19). Both founder alleles are loss-of-function (a nonsense and a frameshift), so this contrast also serves as a genotype-based severity comparison within the cohort and is presented in Table 2.

TABLE 2. Genotype–phenotype comparison: founder allele carriers vs. non-carriers.

EndpointFounder-carrier (n = 20), medianNon-carrier (n = 19), medianCliff’s delta δ95% confidence intervalp (Mann-Whitney)q (Benjamini–Hochberg)
Age at onset (y)18160.24[-0.15, 0.57]0.20.39
BCVA (logMAR)0.160.160.06[-0.29, 0.4]0.750.75
Visual field size (degrees)15100.31[-0.05, 0.6]0.0880.35
Spherical equivalent (Diopters)−2.5−1.5−0.2[-0.5, 0.16]0.290.39

Two-sided Mann–Whitney test with exact p-values; Cliff’s delta (δ) effect size with 95% CI (confidence interval); q = Benjamini–Hochberg-adjusted p across the four endpoints. Founder-carriers n = 20; non-carriers n = 19. No endpoint was significant after correction was observed (all q ≥ 0.35). logMAR: higher = worse acuity.

To assess potential differences between the two patient groups across the four clinical endpoints, we used non-parametric two-sided Wilcoxon rank-sum tests. This rank-based approach was chosen to ensure robust comparisons without assuming a normal distribution, preventing skewed data or extreme outliers from distorting the results. Statistically significant difference was not observed in these founder allele carriers (n = 20) and non-carriers (n = 19) groups.

To complement hypothesis testing with a direct measure of physical magnitude, we determined Cliff’s delta (δ) effect sizes for each outcome. This non-parametric coefficient ranges from −1 to +1 and quantifies the degree of overlap between the two group distributions, offering insight into any difference independent of sample size. Also, evaluating four distinct clinical endpoints simultaneously increases the risk of false-positive results. To address this, we applied the Benjamini–Hochberg procedure to adjust the p-values (q), effectively controlling the false discovery rate across all secondary comparisons.

Although age at onset was slightly higher in the carrier group, suggesting that founder alleles may be less severe, our study lacked sufficient statistical power to demonstrate statistical significance. Median of manifestation age was 18 vs. 16 years: p = 0.20, δ = 0.24; q = 0.39. Also, we observed that carriers exhibited a slightly higher refractive error, with mean spherical equivalent of −2.5 D compared to −1.5 D in non-carriers (p = 0.29, δ = −0.20; q = 0.39). However, BCVA was the same with mean 0.16 vs. 0.16 logMAR (p = 0.75, δ = 0.06; q = 0.75). Supporting hypothesis of founder alleles being less severe visual field diameter in founder allele carriers was slightly wider 15° degrees compared to non-carriers (10° degrees) with p = 0.088, δ = 0.31; q = 0.35. This comparison is exploratory and, given the modest subgroup sizes, is not powered to exclude small effects.

Clinical characteristics of the cohort in general is presented in Table 3 with details of carriers vs. non-carriers comparison in Figures 3a–d. Two patients who carried a missense allele in trans with a predicted loss-of-function allele: P4 (c.1155T>A nonsense + c.7276T>G missense) and P37 (c.1155T>A nonsense + c.7550G>A missense) were observed to present with less severe phenotype. Two patients carried the c.32dupT (p.Met12Aspfs14) allele in the heterozygous state (P1 and P7) with a defined second null allele, patient P1 with c.4350_4356del (p.Ile1451Profs3) and patient P7 with c.4815_4816delCAinsATAG (p.Thr1606fs) (Supplementary Table 1). We observed more cone involvement in these two patients primarily because severe, early truncating null allele abolishes protein function, and accelerates cone photoreceptor degeneration alongside typical rod loss.

TABLE 3. Cohort clinical characteristics (n = 39).

VariableValue
N39
Female22
Male17
Age at onset (years)median 18 (IQR 15–19; range 9–25; n = 39)
Age at exam (years)median 29 (IQR 24.5–37.5; range 15–66; n = 39)
BCVA (decimal)median 0.70 (IQR 0.40–0.80; range 0.15–1.00; n = 39)
BCVA (logMAR)median 0.16 (IQR 0.10–0.41; range −0.00-0.85; n = 39)
Visual field diameter (degrees)median 15.00 (IQR 10.00–17.50; range 5.00–20.00; n = 39)
Spherical equivalent (Diopters)median −2.50 (IQR -2.50--0.75; range −7.50-0.50; n = 39)
Macular complication n(%)12 (31%)
Cataract/pseudophakia n(%)13 (33%)

Values are median (IQR - interquartile range; range) for continuous variables and n (%) for categorical variables. BCVA, best corrected visual acuity; logMAR, logarithm of the minimum angle of resolution; D, diopters.

Genotype–phenotype relationships and retinal function. **(a)** Key clinical endpoints in founder allele carriers (n = 20) versus non-carriers (n = 19): age at onset (years), BCVA (logMAR), visual field size (degrees), and spherical-equivalent refraction (diopters). Boxes show median and interquartile range; points are individual patients; two-sided Wilcoxon p, BH-adjusted q, and Cliff’s delta (δ) are annotated. **(b)** Age at examination versus BCVA (logMAR) across all 39 patients, with linear trend and 95% band (Spearman rank correlation coefficient = 0.34, p = 0.035). **(c)** Full-field ERG maximal (dark-adapted) b-wave amplitude per patient, colored by founder-carrier status; 36 recordable (1.6–63.0 µV), 3 non-recordable (P5, P12, P24). **(d)** Macula status on ophthalmoscopic assessment: normal 27 (69.2%), cystoid macular oedema 11 (28.2%), macular hole 1 (2.6%).
Figure 3. Genotype–phenotype relationships and retinal function. (a) Key clinical endpoints in founder allele carriers (n = 20) versus non-carriers (n = 19): age at onset (years), BCVA (logMAR), visual field size (degrees), and spherical-equivalent refraction (diopters). Boxes show median and interquartile range; points are individual patients; two-sided Wilcoxon p, BH-adjusted q, and Cliff’s delta (δ) are annotated. (b) Age at examination versus BCVA (logMAR) across all 39 patients, with linear trend and 95% band (Spearman rank correlation coefficient = 0.34, p = 0.035). (c) Full-field ERG maximal (dark-adapted) b-wave amplitude per patient, colored by founder-carrier status; 36 recordable (1.6–63.0 µV), 3 non-recordable (P5, P12, P24). (d) Macula status on ophthalmoscopic assessment: normal 27 (69.2%), cystoid macular oedema 11 (28.2%), macular hole 1 (2.6%).

Considering the cohort as a whole, worse visual acuity was associated with older age at examination (Spearman rank correlation coefficient ρ = 0.34, p = 0.035; Figure 3b). Visual field diameter expectedly showed correlation with age (Spearman ρ = 0.013, p = 0.045), and age at onset was not correlated with visual acuity (Spearman ρ = −0.12, p = 0.47). These findings are consistent with the slowly progressive rod–cone dystrophy expected for EYS-associated disease.

3.5 Retinal imaging and electrophysiology

Fundus examination and full-field ERG were consistent with a progressive rod–cone dystrophy. Pale optic disc, attenuated retinal vessels, and bone-spicule pigmentation were universal (present in all 39 patients). Macular complications on fundus/ophthalmoscopic assessment, cystoid macular oedema and, in one patient, a macular hole (Figure 3d), were seen in 12 of 39 patients (31%), and cataract or pseudophakia was present in 13 of 39 (33%) (Table 3). Consistent with classic RP, rod function was affected earliest with later cone involvement, and central vision was comparatively preserved (Marques et al., 2023; Martins et al., 2024; Mucciolo et al., 2018).

Full-field ERG was available for the cohort (Figure 3c). Dark-adapted (maximal) responses were severely reduced across patients, in keeping with a rod–cone dystrophy: 36 patients had recordable maximal b-wave amplitudes (range 1.6–63.0 µV) and three had non-recordable ERG (P5, P12, P24). One founder-carrier retaining comparatively preserved retinal function (P4; a-wave 43 μV, b-wave 63 µV). These observations are descriptive; no formal statistical testing of ERG amplitudes was performed.

4 Discussion

This study provides the first systematic description of the EYS mutational and clinical spectrum in an Eastern European and Northern Asian cohort. In 39 patients we identified 34 distinct EYS variants, 15 of them novel (including eight novel structural deletions), and defined two recurrent alleles: c.1155T>A (p.Cys385) and c.8648_8655del (p.Thr2883Lysfs4), that together account for 39.2% of disease alleles and are consistent with a shared founder origin. These findings expand the known allelic diversity of EYS and identify population-specific targets for cost-effective first-tier screening in this region.

4.1 A high structural variant burden

Eight of the 15 novel variants were structural deletions, and large deletions/SVs constituted roughly a quarter of the entire variant spectrum. This high SV burden is characteristic of the EYS locus, which spans nearly 2 Mb, and reinforces that comprehensive EYS diagnostics require dedicated copy number and structural variant analysis (exome-based copy number variations (CNV) calling with MLPA confirmation) in addition to small-variant detection. Diagnostic pipelines that rely on small-variant calling alone will systematically under-ascertain EYS disease causality (de Bruijn et al., 2023; Fabian-Morales et al., 2024; Zeuli et al., 2024).

4.2 Founder alleles in EYS across populations

The distribution and frequency of EYS mutations vary substantially among ethnic groups. In Chinese (Sun et al., 2020; Gao et al., 2022), Japanese (Yang et al., 2020; Arai et al., 2015; Iwanami et al., 2019; Koyanagi et al., 2019), Korean (Park et al., 2025), Taiwanese (Chen et al., 2021), and Singapore (Teo et al., 2021) populations, pathogenic variants: c.4957dupA (p.Ser1653Lysfs2) and c.8805C>A (p.Tyr2935) are the most prevalent, accounting for a significant proportion of EYS-related RP cases. In India the most frequent variant in EYS is 2259+1G>A (Di et al., 2016) and in Iberia and Iran a ∼60.1 kb deletion of exons 13-14 c.(2023+1_2024-1)_(2259+1_2260-1)del is the most frequent variant (Heutinck et al., 2025). In European populations, recurrent variants including c.9253_9254delGA (p.Glu3085Ilefs*4) and c.6416G>A (p.Cys2139Tyr) are more commonly detected as we can see from the Dutch (Littink et al., 2010), Spanish (Barragán et al., 2010), Italian (Zeuli et al., 2024), Portuguese (Marques et al., 2023) and Swedish (Westin et al., 2021) reports. In the USA (Zampaglione et al., 2020), Mexico (Fabian-Morales et al., 2024) and Brazil (Martins et al., 2024), there is a greater diversity of RP causing EYS mutations. Data is scarce for Arab (Jaffal et al., 2021) and African (Habibi et al., 2016) countries. We examined whether the recurrent Russian alleles could share reported founder origins. Genetically inferred ancestry in our cohort was East and North Slavic and Central-Asian. Taken together, the Russian recurrent alleles represent independent, population-specific founder events (Figure 4).

Geographic distribution of patients and recurrent founder variants. Approximate residence localities of the 39 patients across Eastern Europe and Northern Asia on a political base map. Blue circles mark carriers of c.1155T>A (p.Cys385*) and orange squares mark carriers of c.8648_8655del (p.Thr2883Lysfs*4); grey diamonds mark the remaining patients. Carriers of both founder alleles concentrate in the Northwest (Saint Petersburg region) and in Tatarstan (Kazan region), supporting two independent regional founder origins; the Moscow region shows a mixture of variants. Marker positions are approximate, and where several patients share locality markers are offset for visibility.
Figure 4. Geographic distribution of patients and recurrent founder variants. Approximate residence localities of the 39 patients across Eastern Europe and Northern Asia on a political base map. Blue circles mark carriers of c.1155T>A (p.Cys385) and orange squares mark carriers of c.8648_8655del (p.Thr2883Lysfs4); grey diamonds mark the remaining patients. Carriers of both founder alleles concentrate in the Northwest (Saint Petersburg region) and in Tatarstan (Kazan region), supporting two independent regional founder origins; the Moscow region shows a mixture of variants. Marker positions are approximate, and where several patients share locality markers are offset for visibility.

4.3 Genotype–phenotype observations

The cohort presented a homogeneous, classic rod–cone dystrophy with relatively preserved central vision, in keeping with previous EYS published data (Marques et al., 2025). A formal comparison of founder allele carriers versus non-carriers showed no significant differences across the functional endpoints examined (all q ≥ 0.35), and the cohort is not powered to detect modest genotype effects. We nonetheless note, as a descriptive observation, that the two patients carrying a missense allele in trans with a null allele (P4 and P37) tended towards a milder course later onset, wider residual fields, more myopic refraction, and, in P4, a comparatively preserved maximal ERG b-wave consistent with the possibility that residual EYS function attenuates disease. This hypothesis warrants testing in larger, adequately powered cohorts (Soares et al., 2023).

Beyond the classic presentation, atypical EYS phenotypes including comparatively preserved or regionally atypical retinal findings are increasingly recognized, like macular-predominant degeneration, or unusually late/mild disease, with more high myopia-associated refraction, sector RP or regional retinal degeneration, unusual ERG pattern, disproportionate cone dysfunction or relatively preserved rod responses compared with classic EYS-RP (Pierrache et al., 2019). This atypical prevalence and mechanistic basis have been reviewed recently (Barthelemy et al., 2026). Systematic recognition of atypical presentations is important to avoid clinical under-diagnosis of EYS-associated disease.

4.4 Gene-based therapy

Establishing recurrent founder alleles has direct translational relevance. The predominance of a small number of alleles makes EYS an attractive candidate for mutation-directed approaches (for example, base or prime editing, or antisense oligonucleotide strategies) targeting the specific recurrent variants prevalent in this population. However, gene-supplementation for EYS remains constrained by the size of its coding sequence (∼10 kb), which exceeds the packaging capacity of a single adeno-associated virus vector, motivating dual-vector, non-viral, or gene-editing strategies. The two recurrent Russian alleles: a nonsense and a small deletion are in principle tractable to editing-based correction, and defining their frequency is a prerequisite for prioritising such approaches regionally.

4.5 Unsolved cases and non-coding variants

Comprehensive evaluation of the EYS locus requires interrogation beyond the coding exons, because a substantial number of possibly pathogenic alleles are deep-intronic or structural (Huang et al., 2025; Hayman et al., 2025). Within the cohort of 500 people with RP from the described program, six unsolved patients carried a single heterozygous pathogenic/likely-pathogenic EYS allele without an identified second variant: 1) c.8648_8655del​CAT​GCA​GA (p.Thr2883Lysfs*4), 2) c.9317_9336del (p.Thr3106LysfsTer13) 3) c.5053T>G (p.Ser1685Ala) 4) 93,5 Kb deletion of exons 4 – 7 with coordinates (hg38) chr6:65389883-65483419 5) c.6714del (p.Ile2239SerfsTer) and 6) c.3489T>A (p.Asn1163Lys). In these unsolved cases a second, non-coding or structural allele is likely and would require genome sequencing, long-read sequencing, and functional assays to resolve. If these unsolved cases will be confirmed with the second mutation in the second allele of EYS gene, that can increase diagnostic yield of EYS-causative RP in this cohort to up to 12.46%.

4.6 Strengths and limitations

Strengths of this study include a well-phenotyped, genetically confirmed cohort; comprehensive small-variant and structural variant analysis with MLPA confirmation; formal statistical treatment of genotype–phenotype relationships with acknowledgement of power in founder allele carriers versus non-carriers; and the first definition of EYS founder alleles in this population. Limitations include the cross-sectional design, which precludes direct measurement of progression rates and the small size of the subgroups, which limits genotype–phenotype inference.

5 Conclusion

In the first systematic analysis of EYS-associated RP in an Eastern European and Northern Asian cohort, we expand the EYS mutational spectrum with 15 novel variants (eight novel structural deletions) and define two population-specific founder alleles, c.1155T>A (p.Cys385) and c.8648_8655del (p.Thr2883Lysfs4), that together account for 39% of disease alleles. The cohort shows a homogeneous rod–cone dystrophy; founder allele carriers and non-carriers did not differ significantly in the examined clinical parameters. These findings support targeted first-tier screening for the recurrent alleles in this region and provide a genotype-phenotype foundation for future gene-based therapeutic development.

Generative AI statement

The author(s) declared that generative AI was used in the creation of this manuscript. During the preparation of this work, the authors used Claude AI for R programming support, visualizations and English language polish. The authors reviewed and edited the output as needed and take full responsibility for the content of the published article.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fgene.2026.1951476/full#supplementary-material

Supplementary material Supplementary material at the source

Supplementary material Supplementary material at the source

Footnotes

Edited by: Muhammad Jawad Hassan, Shifa International Hospital, Pakistan

Reviewed by: Tamar Ben-Yosef, Technion Israel Institute of Technology, Israel

Ansul Sharma, Medical College of Wisconsin, United States

Statements

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This research was partially funded by the Deaf-Blind Foundation “Connection” (grant number 19-2-010585).

Data availability

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.

Ethics approval

The studies involving humans were approved by Ethics Committee at UDP CKB, Moscow. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

Author contributions

MW: Conceptualization, Investigation, Writing – original draft, Writing – review and editing. IH: Investigation, Writing – review and editing. IZ: Investigation, Writing – review and editing. NC: Investigation, Writing – review and editing. MS: Investigation, Writing – review and editing. AV: Data curation, Writing – original draft, Writing – review and editing. OL: Data curation, Project administration, Resources, Validation, Writing – review and editing. LB: Formal Analysis, Project administration, Resources, Writing – review and editing. JS: Project administration, Resources, Supervision, Validation, Writing – review and editing. GP: Supervision, Writing – review and editing.

Acknowledgements

The authors sincerely thank all patients and their families who participated in this study, the Genetico laboratory team for NGS sequencing and bioinformatics support, the staff at the Oftalmic Clinical Research Center, and all referring ophthalmologists. Corresponding author is thankful to Eric Pierce and Kinga Bujakowska for mentorship and valuable advice during manuscript preparation.

References

  1. Abd El-Aziz M. M., Barragan I., O'Driscoll C. A., Goodstadt L., Prigmore E., Borrego S. (2008). EYS, encoding an ortholog of drosophila spacemaker, is mutated in autosomal recessive retinitis pigmentosa. Nat. Genet. 40 (11), 1285 – 1287. doi:10.1038/ng.241
  2. Ahmed P., Feliciano C., Emigh R. J. (2004). Ethnonational Classification in Eastern Europe, California Center for Population Research. Available online at: (Accessed July 17, 2026).
  3. Alexander D. H., Novembre J., Lange K. (2009). Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 19 (9), 1655 – 1664. doi:10.1101/gr.094052.109
  4. Arai Y., Maeda A., Hirami Y., Ishigami C., Kosugi S., Mandai M. (2015). Retinitis pigmentosa with EYS mutations is the most prevalent inherited retinal dystrophy in Japanese population. J. Ophthalmol. 2015, 819760. doi:10.1155/2015/819760
  5. Barragán I., Borrego S., Pieras J. I., González-del Pozo M., Santoyo J., Ayuso C. (2010). Mutation spectrum of EYS in Spanish patients with autosomal recessive retinitis pigmentosa. Hum. Mutat. 31 (11), E1772 – E1800. doi:10.1002/humu.21334
  6. Barthelemy N., Barrett S., Lee W., Sengillo J. D. (2026). Atypical retinitis pigmentosa associated with EYS variants. Am. J. Ophthalmol. Case Rep. 42, 102580. doi:10.1016/j.ajoc.2026.102580
  7. Chen T. C., Huang D. S., Lin C. W., Yang C. H., Yang C. M., Wang V. Y. (2021). Genetic characteristics and epidemiology of inherited retinal degeneration in Taiwan. NPJ Genom Med. 6 (1), 16. doi:10.1038/s41525-021-00180-1
  8. Collin R. W., Littink K. W., Klevering B. J., van den Born L. I., Koenekoop R. K., Zonneveld M. N. (2008). Identification of a 2 Mb human ortholog of drosophila eyes shut/spacemaker that is mutated in patients with retinitis pigmentosa. Am. J. Hum. Genet. 83 (5), 594 – 603. doi:10.1016/j.ajhg.2008.10.014
  9. de Bruijn S. E., Rodenburg K., Corominas J., Ben-Yosef T., Reurink J., Kremer H. (2023). Optical genome mapping and revisiting short-read genome sequencing data reveal previously overlooked structural variants disrupting retinal disease-associated genes. Genet. Med. 25 (3), 100345. doi:10.1016/j.gim.2022.11.013
  10. Di Y., Huang L., Sundaresan P., Li S., Kim R., Ballav S. B. (2016). Whole exome sequencing analysis identifies mutations in the EYS gene in Retinitis Pigmentosa in the Indian population. Sci. Rep. 6, 19432. doi:10.1038/srep19432
  11. Fabian-Morales G. E., Ordoñez-Labastida V., Garcia-Martínez F., Montes-Almanza L., Zenteno J. C. (2024). Identification of pathogenic copy number variants in Mexican patients with inherited retinal dystrophies applying an exome sequencing data-based read-depth approach. Mol. Genet. Genomic Med. 12 (10), e70019. doi:10.1002/mgg3.70019
  12. Gao F. J., Wang D. D., Hu F. Y., Xu P., Chang Q., Li J. K. (2022). Genotypic spectrum and phenotype correlations of EYS -associated disease in a Chinese cohort. Eye (Lond). 36 (11), 2122 – 2129. doi:10.1038/s41433-021-01794-6
  13. Gusareva E. S., Ghosh A. G., Kharkov V. N., Khor S. S., Zarubin A., Moshkov N. (2025). From North Asia to South America: tracing the longest human migration through genomic sequencing. Science 388 (6748), eadk5081. doi:10.1126/science.adk5081
  14. Habibi I., Chebil A., Falfoul Y., Allaman-Pillet N., Kort F., Schorderet D. F. (2016). Identifying mutations in Tunisian families with retinal dystrophy. Sci. Rep. 6, 37455. doi:10.1038/srep37455
  15. Hayman T., Ovadia S., Krishnan J., Bouckaert M., Panneman D. M., English M. (2025). Non-coding single-nucleotide and structural variants affecting the EYS putative promoter cause autosomal recessive retinitis pigmentosa. Genet. Med. 27 (7), 101427. doi:10.1016/j.gim.2025.101427
  16. Heutinck P. A. T., Iglesias A. I., Farhud D. D., Zarif-Yeganeh M., Kia S. K., Ghanbari M. (2025). Diagnostic whole exome sequencing in presumably autosomal recessive inherited retinal dystrophies in an Iranian population. Sci. Rep. 15 (1), 23745. doi:10.1038/s41598-025-08272-z
  17. Huang Y. S., Lu W. T., Chiu I. H., Chien P. M., Chen Y. A., Lin C. Y. (2025). Hidden splicing variants in inherited retinal degeneration: discovery and functional insight. Invest Ophthalmol. Vis. Sci. 66 (13), 12. doi:10.1167/iovs.66.13.12
  18. Ivanova M. E., Zolnikova I. V., Khatsenko I. E., Strelnikov V. V., Konovalov F. A., Lozier E. R. (2020). Epidemiologic, clinical and pathogenesis features of achromatopsia in the Russian population. Russ. Ophthalmol. J. 13 (1), 12 – 22. doi:10.21516/2072-0076-2020-13-1-12-22
  19. Iwanami M., Oishi A., Ogino K., Seko Y., Nishida-Shimizu T., Yoshimura N. (2019). Five major sequence variants and copy number variants in the EYS gene account for one-third of Japanese patients with autosomal recessive and simplex retinitis pigmentosa. Mol. Vis. 25, 766 – 779.
  20. Jaffal L., Joumaa H., Mrad Z., Zeitz C., Audo I., El Shamieh S. (2021). The genetics of rod-cone dystrophy in Arab countries: a systematic review. Eur. J. Hum. Genet. 29 (6), 897 – 910. doi:10.1038/s41431-020-00754-0
  21. Koyanagi Y., Akiyama M., Nishiguchi K. M., Momozawa Y., Kamatani Y., Takata S. (2019). Genetic characteristics of retinitis pigmentosa in 1204 Japanese patients. J. Med. Genet. 56 (10), 662 – 670. doi:10.1136/jmedgenet-2018-105691
  22. Littink K. W., van den Born L. I., Koenekoop R. K., Collin R. W., Zonneveld M. N., Blokland E. A. (2010). Mutations in the EYS gene account for approximately 5% of autosomal recessive retinitis pigmentosa and cause a fairly homogeneous phenotype. Ophthalmology 117 (10), e1 – e7. doi:10.1016/j.ophtha.2010.01.040
  23. Manichaikul A., Mychaleckyj J. C., Rich S. S., Daly K., Sale M., Chen W. M. (2010). Robust relationship inference in genome-wide association studies - KING. Bioinformatics 26 (22), 2867 – 2873. doi:10.1093/bioinformatics/btq559
  24. Marques J. P., Machado Soares R., Simão S., Abuzaitoun R., Andrews C., Alves C. H. (2023). Self-reported visual function and psychosocial impact of visual loss in EYS -associated retinal degeneration in a Portuguese population. Ophthalmic Genet. 44 (4), 334 – 340. doi:10.1080/13816810.2023.2191708
  25. Marques J. P., Santos Sousa I., Patrício D., Simões B. F., Chukwunalu O., Zeitz C. (2025). Eyes shut homolog (EYS): connecting molecule to disease. Prog. Retin Eye Res. 108, 101391. doi:10.1016/j.preteyeres.2025.101391
  26. Martins EADS, Rodrigues G. D., Ivama K. J., Pereira M. C., Texeira C. H. M., Amaral R. A. S. (2024). Multimodal imaging in retinitis pigmentosa related to the EYS gene. Arq. Bras. Oftalmol. 88 (3), e2024-0104. doi:10.5935/0004-2749.2024-0104
  27. Mucciolo D. P., Sodi A., Passerini I., Murro V., Cipollini F., Borg I. (2018). Fundus phenotype in retinitis pigmentosa associated with EYS mutations. Ophthalmic Genet. 39 (5), 589 – 602. doi:10.1080/13816810.2018.1509351
  28. Park H. S., Kim K., Lee D., Lee J. Y., Choi J. N., Kim J. H. (2025). Clinical exome-based redefinition and reclassification of retinitis pigmentosa. J. Korean Med. Sci. 40 (16), e54. doi:10.3346/jkms.2025.40.e54
  29. Pierrache L. H. M. M. M., Thiadens AAHJ, Haer-Wigman L., de Jong-Hesse Y., van Zelst-Stams W. A. G., Collin R. W. J. (2019). Extending the spectrum of EYS -associated retinal disease to macular dystrophy. Invest Ophthalmol. Vis. Sci. 60 (6), 2049 – 2063. doi:10.1167/iovs.18-25531
  30. Raj A., Stephens M., Pritchard J. K. (2014). fastSTRUCTURE: variational inference of population structure in large SNP data sets. Genetics 197 (2), 573 – 589. doi:10.1534/genetics.114.164350
  31. Richards S., Aziz N., Bale S., Bick D., Das S., Gastier-Foster J. (2015). Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American college of medical genetics and genomics and the association for molecular pathology. Genet. Med. 17 (5), 405 – 424. doi:10.1038/gim.2015.30
  32. Soares R. M., Carvalho A. L., Simão S., Soares C. A., Raimundo M., Alves C. H. (2023). Eyes shut homolog-associated retinal degeneration: natural history, genetic landscape, and phenotypic spectrum. Ophthalmol. Retina 7 (7), 628 – 638. doi:10.1016/j.oret.2023.02.001
  33. Sun Y., Li J. K., He W., Wang Z. S., Bai J. Y., Xu L. (2020). Genetic and clinical analysis in Chinese patients with retinitis pigmentosa caused by EYS mutations. Mol. Genet. Genomic Med. 8 (3), e1117. doi:10.1002/mgg3.1117
  34. Teo C. L., Cheung N., Poh S., Thakur S., Rim T. H., Cheng C. Y. (2021). Prevalence of retinitis pigmentosa in Singapore: the Singapore epidemiology of eye diseases study. Acta Ophthalmol. Feb 99 (1), e134 – e135. doi:10.1111/aos.14483
  35. Verbakel S. K., van Huet R. A. C., Boon C. J. F., den Hollander A. I., Collin R. W. J., Klaver C. C. W. (2018). Non-syndromic retinitis pigmentosa. Prog. Retin Eye Res. 66, 157 – 186. doi:10.1016/j.preteyeres.2018.03.005
  36. Westin I. M., Jonsson F., Österman L., Holmberg M., Burstedt M., Golovleva I. (2021). EYS mutations and implementation of minigene assay for variant classification in EYS -associated retinitis pigmentosa in northern Sweden. Sci. Rep. 11 (1), 7696. doi:10.1038/s41598-021-87224-9
  37. Woof W. A., de Guimarães T. A. C., Al-Khuzaei S., Daich Varela M., Sen S., Bagga P. (2024). Quantification of fundus autofluorescence features in a molecularly characterized cohort of >3500 patients with inherited retinal disease from the United Kingdom. Ophthalmol. Sci. 5 (2), 100652. doi:10.1016/j.xops.2024.100652
  38. Yang L., Fujinami K., Ueno S., Kuniyoshi K., Hayashi T., Kondo M. (2020). Genetic spectrum of EYS -associated retinal disease in a large Japanese cohort: identification of disease-associated variants with relatively high allele frequency. Sci. Rep. 10 (1), 5497. doi:10.1038/s41598-020-62119-3
  39. Zampaglione E., Kinde B., Place E. M., Navarro-Gomez D., Maher M., Jamshidi F. (2020). Copy number variation contributes 9% of pathogenicity in the inherited retinal degenerations. Genet. Med. 22 (6), 1079 – 1087. doi:10.1038/s41436-020-0759-8
  40. Zeuli R., Karali M., de Bruijn S. E., Rodenburg K., Scarpato M., Capasso D. (2024). Whole genome sequencing identifies elusive variants in genetically unsolved Italian inherited retinal disease patients. HGG Adv. 5 (3), 100314. doi:10.1016/j.xhgg.2024.100314
  41. Zolnikova I. V., Strelnikov V. V., Skvortsova N. A., Tanas A. S., Barh D., Rogatina E. V. (2017). Stargardt disease-associated mutation spectrum of a Russian Federation cohort. Eur. J. Med. Genet. 60 (2), 140 – 147. doi:10.1016/j.ejmg.2016.12.002

Citation

Weener, M., et al. (2026). The mutational and clinical spectrum of EYS -associated retinitis pigmentosa in an Eastern European and Northern Asian cohort: two recurrent founder alleles. Frontiers in Genetics, Volume 17. https://doi.org/
Received
Accepted
Published
Volume
17 - 2026

Copyright

Copyright © 2026 Weener, Hatsenko, Zolnikova, Chincharauli, Shilova, Venger, Luneva, Balashova, Salmasi and Poryadin.

License: https://creativecommons.org/licenses/by/4.0/

*Correspondence: Marianna Weener

Article metrics

Views
0
Downloads
0
Citations
0
Shares
0

Related articles

Systematic ReviewGlobal trends and hotspots of genetic research on non-syndromic cleft lip with or without cleft palate: a bibliometric and bioinformatics analysisYuxuan Shang, Mingjian Zhao, Shuangshuang Gao, Shikang Gao, Mengru ZhuHypothesis and TheoryEconomic impact of biomarker-based aging interventions on healthcare costs and individual valueFederico FelizziMethodsA modular verification and validation framework for hybrid-capture next-generation sequencing HLA typing in clinical histocompatibility laboratoriesAlice Scarpa, Diego Ferrarese, Samantha Guidotti, Veronica Scaglia, Angela Rossi