The Genomic Landscape of Wilson Disease in a Pan India Disease Cohort and Population-Scale Data

Abstract

Background: Wilson's disease (WD) results from pathogenic ATP7B gene variations, causing copper accumulation mainly in the liver, brain, and kidneys.

Objectives: In India, despite studies on ATP7B variants, WD often goes undiagnosed, with the prevalence, carrier rate, and mutation spectrum remaining unknown.

Methods: A multicenter study examined genetic variations in WD among individuals of Indian origin via whole exome sequencing. The study used the InDelible structural variants calling pipeline and conducted molecular dynamic simulations on variants of uncertain significance (VUS) in ATP7B AlphaFold protein structures. Additionally, a high-throughput gene screening panel for WD was developed.

Results: This study examined 128 clinically diagnosed cases of WD, revealing 74 genetically confirmed cases, 22 with ATP7B variants, and 32 without. Twenty-two novel ATP7B gene variants were identified, including a 322 bp deletion classified as a structural variant. Molecular dynamics simulations highlighted the potential deleterious effects of 11 ATP7B VUS. Gene burden analysis suggested associations with ANO8, LGR4, and CDC7. ATP7B gene hotspots for pathogenic variants were identified. Prevalence and carrier rates were determined as one in 18,678 and one in 67, respectively. A multiplex sequencing panel showed promise for accurate WD diagnosis.

Conclusions: This study offers crucial insights into WD's genetic variations and prevalence in India, addressing its underdiagnosis. It highlights the novel genetic variants in the ATP7B gene, the involvement of other genes, a scalable, cost-effective multiplex sequencing panel for WD diagnosis and management and promising advancements in WD care.

Keywords: ATP7B; gene burden analysis; molecular dynamic simulation; structural variants; variant; whole exome sequencing.

FIG. 1

All genetic variations depicted on the ATP7B gene, RNA and protein observed in the Indian Wilson's disease patients of the Collaborative Research Consortium on Wilson Disease (iCROWD). The size of the circle in the figure belongs to the number of cases (the visualization was performed using ProteinPaint).

FIG. 2

Depiction of the presence of all the ATP7B variations spectrum in Wilson's disease (WD) cases. Figure legends include, Hom_P(42); 42 cases have pathogenic homozygous variants, Hom_LP(8); eight cases have homozygous likely pathogenic variants, Comp_Het_P(16); 16 cases have compound heterozygous pathogenic variants, Comp_Het_P_LP(8); eight cases have compound heterozygous pathogenic with likely pathogenic variants, Het_P(11)/Het_LP(11); 11 cases have heterozygous pathogenic/likely pathogenic variant with Het_VUS(11); 11 variant of uncertain significance, Only_P(4); four patients have only pathogenic, Only_LP(2); two cases have only likely pathogenic, Only_VUS(4); four patients have only variant of uncertain significance, Likely_Ben(35); 35 cases additionally have benign variant, No_variant(32); 32 patients without any pathogenic/likely pathogenic variant in ATP7B.

FIG. 3

(A) Polymerase chain reaction ‐based amplification of targeted regions showing heterozygous variant in ATP7B gene compared with control sample. (B) An IGV snapshot shows marked split reads. (C) Results from Sanger's sequencing. (D) Deletion range at the genetic level.

FIG. 4

(A) Different variants systems generated using wild‐type ATP7B AlphaFold predicted structure. (B) Root‐mean‐square deviation (RMSD) in molecular dynamic simulation compared with simulated wild‐type ATP7B protein.

FIG. 5

Variants of uncertain significance variants fluctuations compared with wild‐type ATP7B protein, indicating the relative root‐mean‐square fluctuation (RMSF).