Language
English
Publication Date
1-3-2025
Journal
Clinical Chemistry
DOI
10.1093/clinchem/hvae188
PMID
39749505
Abstract
Background: Disease-causing copy-number variants (CNVs) often encompass contiguous genes and can be detected using chromosomal microarray analysis (CMA). Conversely, CNVs affecting single disease-causing genes have historically been challenging to detect due to their small sizes.
Methods: A custom comprehensive CMA (Baylor College of Medicine - BCM v11.2) containing 400k probes and featuring exonic coverage for >4200 known or candidate disease-causing genes was utilized for the detection of CNVs at single-exon resolution. CMA results across a consecutive clinical cohort of more than 13 000 patients referred for genetic investigation at Baylor Genetics were examined. The genomic characteristics of CNVs impacting single protein-coding genes were investigated.
Results: Pathogenic or likely pathogenic (P/LP) CNVs (n = 190) affecting single protein-coding genes were detected in 188 patients, accounting for 9.9% (188/1894) of patients with P/LP CMA findings. The P/LP monogenic CNVs accounted for 9.2% (190/2058) of all P/LP nuclear CNVs detected by CMA. A total of 57.9% (110/190) of P/LP monogenic CNVs were smaller than 50 kb in size. Single exons were affected by 26.3% (50/190) of P/LP monogenic CNVs while 13.2% (25/190) affected 2 exons. CNVs were detected across 107 unique genes associated with predominantly autosomal dominant (AD) and X-linked (XL) conditions but also contributed to autosomal recessive (AR) conditions.
Conclusions: CMA with exon-targeted coverage of disease-associated genes facilitated the detection of small CNVs affecting single protein-coding genes, adding substantial clinical sensitivity to comprehensive CNV investigation. This approach resolved monogenic CNVs associated with autosomal and X-linked monogenic etiologies and yielded multiple significant findings. Monogenic CNVs represent an underrecognized subset of disease-causing alleles for Mendelian disorders.
Keywords
Humans, DNA Copy Number Variations, Exons, Oligonucleotide Array Sequence Analysis, Genome, Human
Published Open-Access
yes
Recommended Citation
Chau, Matthew Hoi Kin; Anderson, Stephanie A; Song, Rodger; et al., "Detection of Clinically Relevant Monogenic Copy-Number Variants by a Comprehensive Genome-Wide Microarray with Exonic Coverage" (2025). Faculty, Staff and Students Publications. 7108.
https://digitalcommons.library.tmc.edu/baylor_docs/7108