Genome-Wide Detection of Copy Number Variation and Identification of Genes Associated with Risk of Multiple Myeloma
Authors: Lee Il-Kwon , Kim Nan Young , Kim Hee Nam , Kim Yeo-Kyeoung , Lee Je-Jung , Yang Deok-Hwan , Hwang Tai Ju , Kim Hyeoung Joon 
Published: October 2019

Abstract 4047

Background:

Despite increasing efforts to characterize the role of copy number variants (CNVs) in MM, the genetic contribution to multiple myleoma (MM) has not been fully elucidated. Recent studies showed that chromosomal aberrations are detectable in MM and can be associated with susceptibility to MM. To gain insight into the incidence of the chromosomal aberrations in MM, we examined Korean MM genomes using high-resolution single-nucleotide polymorphism (SNP) array-based analysis.

Patients and Methods:

As part of a larger cohort study, 14 cases analyzed had been diagnosed with MM (9 male, 5 female). Median age at diagnosis was 58 years (range, 40≂f74). Of these patients, five patients had Ig Kappa type, five with IgG Lambda, two with light chain Kappa and two with light chain Lambda. 1,140,419 CNV markers were considered on these samples using Illumina HumanOmni1-Quad v1 BeadChip. Genome-wide CNV, genotyping of markers including 32119 non-synonymous SNPs, loss of heterozygosity (LOH) analyses were performed using the GenomeStudio v2010.1. Linkage disequilibrium was analyzed by Haploview 4.2. The gene set enrichment analysis was performed using GO software, Panther.

Results:

The average call rates were 99.9 %. The average number of CNVs per genome in this study (353.9) is much higher than that of CNVs called in the recent studies using lower-resolution SNP- or CNV arrays. The median size of CNVs was 1,902 (range 39 ≂f 2,263,901 bp). When we analyzed the number of CNVs per genome, there was no significant difference between MM patients of different subgroups. Interestingly copy number losses were 36.7 times more frequent than copy number gains. We defined CNV regions (CNVRs) by merging overlapping CNVs (30% of overlap threshold) detected in two or more genomes. In total 1271 CNVRs identified. When all CNVRs identified in the study were compared with the CNVRs in the DGV, 149 common (more than 2 incidences) CNVRs were novel, not found in DGV database. Like CNVs, CNVRs-losses were more frequent than CNVR-gains. Defined CNVRs encompassing 29.2Mb accounted for ≂f1% of the human genome. Total of 1029 NM numbered transcripts were located near or within the 1271 CNVRs. Through gene ontology (GO) analysis, putative target genes within the commonly gained or deleted region were categorized. Gene functions significantly enriched in the identified CNVRs include receptors for signal transduction pathways, transcription factors with nucleic acid binding proteins, defense/immunity molecules and regulatory molecule related functions involved in developmental processes. Hierarchical clustering of pooled datasets clearly distinguished IgG Kappa from Lambda subtypes. Genotype distributions for 32,110 non-synonymous SNPs in MM were also examined and compared to two lab-specific as well as 90 Korean HapMap samples as control reference.

Conclusions:

Power of High-resolution single-nucleotide polymorphism (SNP) array-based analysis allowed us a high incidence of gains and losses in MM patients. Many of those detectable legions were previously unidentified cryptic chromosomal aberrations. Although results reveals high degrees of heterogeneity in the genomic alterations detectable in MM, genes of the signal transduction pathway and defense/immunity processes were the most frequently altered targets whose deregulation may play a role in the pathogenesis of MM. CNVs/CNVRs identified in the study will be solid resources for investigating chromosomal aberrations in MM and its potential association with MM.

Disclosures:

No relevant conflicts of interest to declare.