Dissecting Missing Heritability in Rare Inherited Macular Dystrophies

Background/Objectives: To describe the genetic resolution rate, molecular findings, and genotype–phenotype correlations of non-ABCA4 and non-BEST1 inherited macular dystrophies (IMDs) within an Irish inherited retinal disease (IRD) registry. Methods: Retrospective review of individuals with a clinical diagnosis of macular or cone dystrophy. Comprehensive phenotyping (dilated ocular biomicroscopy, multimodal retinal imaging, visual electrophysiology) and genetic testing (panel-based next-generation sequencing, single-gene testing, whole exome/genome sequencing, WES/WGS). Variants were interpreted using ACMG AMP criteria, and genotype-phenotype match was confirmed through multidisciplinary review. Results: 232 patients with macular/cone dystrophies were identified. ABCA4 and BEST1 accounted for most molecular diagnoses (47.4%). Removing ABCA4 and BEST1, 59.0% of IMDs were genetically unresolved, higher than the rate in general IRD cohorts. Deep phenotyping enabled diagnostic reclassification in 13/72 (18.1%), namely achromatopsia, congenital stationary night blindness, and oculocutaneous albinism. Further genetic testing resolved 35/72 (48.6%) of those unresolved on first-line testing, with PRPH2 being most prevalent (n = 12), followed by GUCY2D, CRB1, PROM1, and CRX. Characteristic phenotypic signatures—such as CRB1-associated retinal thickening and retinoschisis or PROM1-associated Stargardt-like changes—supported known genotype–phenotype correlations. Conclusions: Genetic resolution rates for rare IMDs remain lower than pan-retinal IRD phenotypes. Beyond ABCA4 and BEST1, IMDs exhibit substantial genetic and phenotypic heterogeneity (24 genotypes in this cohort), with low molecular diagnostic rates despite comprehensive sequencing approaches. Detailed multimodal phenotyping (i.e., structural, functional and extra-ocular) is essential to refine diagnosis, guide genetic testing and interpret candidate variants. Genetic testing is challenging when the retinal phenotype is advanced (i.e., atrophy) or lacks pathognomonic features. Meticulous phenotyping (functional, structural and systemic) and broader genomic strategies (e.g., WES/WGS) may further increase diagnostic yield, though gene panel content is constantly improving. Consistently improving molecular diagnostic rates will ensure equitable access to emerging gene-specific therapies.

Authors

Institutions

Publication Details

Journal
Genes
Published
2026-08-20
DOI
https://doi.org/10.3390/genes17080979
Primary Topic
Retinal Development and Disorders
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dissecting Missing Heritability in Rare Inherited Macular Dystrophies

Julia Zhu, James J. O’Byrne, Adrian Dockery, Ian Flitcroft et al.
Genes
Retinal Development and Disorders
article

Dissecting Missing Heritability in Rare Inherited Macular Dystrophies

Julia Zhu, James J. O’Byrne, Adrian Dockery, Ian Flitcroft, Kirk Stephenson, Bridget Moran, Jacqueline Turner, G. Jane Farrar, Tomás Burke, Deirdre Harford, David J. Keegan, Marcus Conway
article en

Abstract

Background/Objectives: To describe the genetic resolution rate, molecular findings, and genotype–phenotype correlations of non-ABCA4 and non-BEST1 inherited macular dystrophies (IMDs) within an Irish inherited retinal disease (IRD) registry. Methods: Retrospective review of individuals with a clinical diagnosis of macular or cone dystrophy. Comprehensive phenotyping (dilated ocular biomicroscopy, multimodal retinal imaging, visual electrophysiology) and genetic testing (panel-based next-generation sequencing, single-gene testing, whole exome/genome sequencing, WES/WGS). Variants were interpreted using ACMG AMP criteria, and genotype-phenotype match was confirmed through multidisciplinary review. Results: 232 patients with macular/cone dystrophies were identified. ABCA4 and BEST1 accounted for most molecular diagnoses (47.4%). Removing ABCA4 and BEST1, 59.0% of IMDs were genetically unresolved, higher than the rate in general IRD cohorts. Deep phenotyping enabled diagnostic reclassification in 13/72 (18.1%), namely achromatopsia, congenital stationary night blindness, and oculocutaneous albinism. Further genetic testing resolved 35/72 (48.6%) of those unresolved on first-line testing, with PRPH2 being most prevalent (n = 12), followed by GUCY2D, CRB1, PROM1, and CRX. Characteristic phenotypic signatures—such as CRB1-associated retinal thickening and retinoschisis or PROM1-associated Stargardt-like changes—supported known genotype–phenotype correlations. Conclusions: Genetic resolution rates for rare IMDs remain lower than pan-retinal IRD phenotypes. Beyond ABCA4 and BEST1, IMDs exhibit substantial genetic and phenotypic heterogeneity (24 genotypes in this cohort), with low molecular diagnostic rates despite comprehensive sequencing approaches. Detailed multimodal phenotyping (i.e., structural, functional and extra-ocular) is essential to refine diagnosis, guide genetic testing and interpret candidate variants. Genetic testing is challenging when the retinal phenotype is advanced (i.e., atrophy) or lacks pathognomonic features. Meticulous phenotyping (functional, structural and systemic) and broader genomic strategies (e.g., WES/WGS) may further increase diagnostic yield, though gene panel content is constantly improving. Consistently improving molecular diagnostic rates will ensure equitable access to emerging gene-specific therapies.

GenesVol. 17(8)
Trinity College Dublin (IE), Mater Misericordiae University Hospital (IE), Children's Health Ireland at Crumlin (IE), Temple Street Children's University Hospital (IE)
Health Research Board, Health Research Charities Ireland, Science Foundation Ireland
Openalex Percentile: Top 16%
Retinal Development and Disorders
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.