Identifying regulatory variants in Indian Wilson’s disease patients with missing heritability

Wilson’s disease (WD) is a rare autosomal recessive copper metabolism disorder that primarily affects hepatic and neuronal tissues. The condition is caused by mutations in the ATP7B gene. Our group conducted extensive molecular genetic studies, identifying 13 clinically diagnosed Indian WD patients lacking the coding variant of ATP7B and 17 patients with a single mutated allele. We hypothesize that in these patients, unidentified mutations may reside in cis-regulatory elements of ATP7B or that a WD-like phenotype results from the cumulative effect of hypofunctional alleles of other key genes in the copper metabolism pathway. In this study, we employed an established bioinformatic pipeline to identify and screen cis-regulatory elements of ATP7B in WD patients with missing heritability through polymerase chain reaction sequencing. Although no pathogenic variants were identified, our analysis revealed two heterozygous single nucleotide polymorphisms (rs2181891 and rs747781) in two patients. Notably, rs2181891 showed strong regulatory potential with a RegulomeDB score of 1d. The genotype-specific expression profile for rs2181891 revealed it to be an expression quantitative trait locus for ATP7B in the cerebellum. In addition, the Genotype-Tissue Expression portal data suggest that the T allele of rs2181891 is associated with higher expression of ATP7B, making it unlikely to contribute to the WD phenotype. This novel study is the first to identify and screen ATP7B cis-regulatory elements in Indian WD patients with missing heritability.

Authors

Publication Details

Journal
Gene & Protein in Disease
Published
2025-03-13
DOI
https://doi.org/10.36922/gpd.7503
Primary Topic
Trace Elements in Health
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Identifying regulatory variants in Indian Wilson’s disease patients with missing heritability

Arpan Saha, Asif Iqbal, Debmalya Sengupta, Jharna Ray et al.
Gene & Protein in Disease
Trace Elements in Health
article

Identifying regulatory variants in Indian Wilson’s disease patients with missing heritability

Arpan Saha, Asif Iqbal, Debmalya Sengupta, Jharna Ray, Ashish Bavdekar, Kunal Ray, Sreyashi Bhattacharya, Mainak Sengupta, Sampurna Ghosh, Shubhrajit Roy, Shyamal Kumar Das, Prasanta Kumar Gangopadhyay
article en

Abstract

Wilson’s disease (WD) is a rare autosomal recessive copper metabolism disorder that primarily affects hepatic and neuronal tissues. The condition is caused by mutations in the ATP7B gene. Our group conducted extensive molecular genetic studies, identifying 13 clinically diagnosed Indian WD patients lacking the coding variant of ATP7B and 17 patients with a single mutated allele. We hypothesize that in these patients, unidentified mutations may reside in cis-regulatory elements of ATP7B or that a WD-like phenotype results from the cumulative effect of hypofunctional alleles of other key genes in the copper metabolism pathway. In this study, we employed an established bioinformatic pipeline to identify and screen cis-regulatory elements of ATP7B in WD patients with missing heritability through polymerase chain reaction sequencing. Although no pathogenic variants were identified, our analysis revealed two heterozygous single nucleotide polymorphisms (rs2181891 and rs747781) in two patients. Notably, rs2181891 showed strong regulatory potential with a RegulomeDB score of 1d. The genotype-specific expression profile for rs2181891 revealed it to be an expression quantitative trait locus for ATP7B in the cerebellum. In addition, the Genotype-Tissue Expression portal data suggest that the T allele of rs2181891 is associated with higher expression of ATP7B, making it unlikely to contribute to the WD phenotype. This novel study is the first to identify and screen ATP7B cis-regulatory elements in Indian WD patients with missing heritability.

Gene & Protein in DiseaseVol. 4(2)
Openalex Percentile: Top 94%
Trace Elements in Health
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.