Evidence map›Paper›PMID 42687888›Full record

ArticleResearch square2026

In Silico Prioritization of Variants of Uncertain Significance in ABCA4 Reveals Conserved Functional Motifs.

Jazzlyn S Jones, Barry Bodt, Subhasis B Biswas, Esther E Biswas-Fiss

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In one paragraph

Article in Research square, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jazzlyn S JonesUniversity of Delaware.
Barry BodtUniversity of Delaware.
Subhasis B BiswasUniversity of Delaware.
Esther E Biswas-FissUniversity of Delaware.

Funding

Understanding ABCA4 Variants of Unknown Significance Through Computational and Functional ApproachesR01EY036065 · NEI · UNIVERSITY OF DELAWARE · PI ESTHER Elissa BISWAS-FISS · 2024 to 2026
$1.4M
NEI NIH HHS R01 EY036065
6 · The paper itself

Abstract

Background: ABCA4 variants are the primary cause of Stargardt disease and also contribute to other inherited retinal disorders. Despite this central role, nearly half of all ABCA4 missense variants remain classified as variants of uncertain significance (VUS), limiting genetic diagnosis for many patients. The extracytoplasmic domain 2 (ECD2) harbors a disproportionate share of these unresolved variants yet remains poorly characterized. Methods: We analyzed 244 ECD2 missense variants using a consensus variant effect predictor (VEP) framework integrating PolyPhen-2, SIFT, and MutationTaster. Variants predicted pathogenic by all three tools were designated PAAT (pathogenic across all tools) and prioritized for further evaluation. PAAT variants were assessed using thermodynamic stability modeling ΔΔG and structural analysis, and alignment across ABCA family members was used to identify conserved regions, termed critical conserved motifs (CCMs). Results: PAAT variants were enriched in the central region of ECD2 (Pearson chi-square test, p = 0.0309) and showed a significantly higher frequency of destabilizing ΔΔG values than other variant categories (Cochran-Armitage trend test, p < 0.0001). PAAT variants had 2.2-fold higher odds of occurring within the four identified CCMs (95%: 1.29-3.81), directly linking predicted pathogenicity to sequence conservation. Structural modeling of select variants revealed specific disruptive mechanisms, including steric clashes and altered hydrogen bonding near the retinoid-binding interface. Conclusions: This integrative computational framework identifies four conserved motifs likely critical to ECD2 and ABCA4 function, and yields a prioritized, mechanistically grounded list of ECD2 variants for targeted experimental validation. These findings offer a practical path toward reclassifying ABCA4 VUS and improving genetic diagnosis for patients with Stargardt disease and related inherited retinal disorders.

Indexed as

ABCA4Extracytoplasmic domain 2 (ECD2)Stargardt diseaseVariant effect predictor (VEP)

Identifiers

PMID42687888
PMCPMC13532725

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.