An estimation of the prevalence of genomic disorders using chromosomal microarray data

Abstract

Multiple genomic disorders result from recurrent deletions or duplications between low-copy repeat (LCR) clusters, mediated by nonallelic homologous recombination (NAHR). These copy number variants (CNVs) often exhibit variable expressivity and/or incomplete penetrance. However, the population prevalence of many genomic disorders has not been estimated accurately. A subset of genomic disorders similarly characterized by CNVs between LCRs have been studied epidemiologically, including Williams-Beuren syndrome (7q11.23), Smith-Magenis syndrome (17p11.2), Velocardiofacial syndrome (22q11.21), Prader-Willi/Angelman syndromes (15q11.2q12), 17q12 deletion syndrome, and Charcot-Marie-Tooth Neuropathy type 1 (CMT1A)/hereditary neuropathy with liability to pressure palsy (HNPP) (PMP22, 17q11.2). We have generated a method to estimate prevalence of highly penetrant genomic disorders by (1) leveraging epidemiological data for genomic disorders with previously reported prevalence estimates, (2) obtaining chromosomal microarray data on genomic disorders from a large medical genetics clinic; and (3) utilizing these in a linear regression model to determine the prevalence of this syndromic copy number change among the general population. Using our algorithm, the prevalence for five clinically relevant recurrent genomic disorders: 1q21.1 microdeletion (1/6,882 live births) and microduplication syndromes (1/6,309), 15q13.3 microdeletion syndrome (1/5,525), and 16p11.2 microdeletion (1/3,021) and microduplication syndromes (1/4,216), were determined. These findings will inform epidemiological strategies for evaluating those conditions, and our method may be useful to evaluate the prevalence of other highly penetrant genomic disorders.