Whole Genome Sequencing Reveals Lower Apobec-Mutational Activity in Multiple Myeloma Patients with African Ancestry Compared with Those Having European Ancestry
Authors: Maclachlan Kylee H , Papadimitriou Marios , Blaney Patrick , Shekarkhand Tala , Chu Timothy R. , Poos Alexandra Maria , Brown Elizabeth , Hoering Antje , Diamond Benjamin , Ziccheddu Bachisio , Raab Marc S. , Weinhold Niels , Landgren Ola , Davies Faith E , Lesokhin Alexander M. , Usmani Saad Z. , Maura Francesco , Morgan Gareth 
Published: December 2024

INTRODUCTION: Improving outcomes for patients with African ancestry (AA) is a key healthcare aim, but it's unknown whether disparities arise primarily from differences in socioeconomic environment or tumor biology. In multiple myeloma (MM), studies have suggested that precursor conditions develop at a higher rate and earlier age in AA, with an excess of t(11;14) and fewer TP53 mutations. We established a whole-genome sequencing (WGS) series of 340 samples of MM and precursor patients that is enriched for self-declared AA and diverse background.
METHODS: In collaboration with the NYGC and Polyethnic-1000 consortium, we sequenced paired tumor (60-80x) and normal (30-40x) samples, employing a bioinformatics pipeline with consensus somatic variant calling (https://github.com/pblaney/mgp1000). Admixture estimated ancestral lineage using continentally distinct references (1000 Genomes Project). New data was compared with the CoMMpass trial, and an independent European-dominant dataset (GMMG-HD6). We calculated polygenic risk scores (PRS) and assessed genomic classification according to our recent individualized prognostic model (Maura JCO 2024). We assessed germline SNPs affecting APOBEC activity, calculated mutational signature contribution (mmsig), molecular timing estimates (mol_time) and kataegis events (katdetectr).
RESULTS: Using admixture estimations, we identified 5 clusters with single dominant ancestries (median proportion &gt;50% assignment to a reference population), and 1 cluster containing highly admixed individuals (median proportion &lt;50% from any population). Our cohort comprises 53.0% European dominant (EUR), 26.5% African (AFR), 8.6% American (AMR), 2.0% East Asian (EAS) and South-East Asian (SAS), respectively, and 7.9% highly admixed.
Stratifying by cluster, there were no significant differences observed in the prevalence of hyperdiploidy, IgH translocations, or TP53 mutations. While several features contributing to the individualized prediction model were significant at a univariate level, few retained significance after FDR correction, (AFR: less frequent gains in chr 3 / chr 18, more frequent del21p11.2 / del10p15.3). The genomic classification overall showed the ‘Simple’ genomic group to be enriched in AFR (p&lt;0.001).
Mutational signatures on tumor samples demonstrated a lower contribution from APOBEC activity (SBS2/SBS13) in AFR (clonal, 46%; subclonal 13%) compared with EUR (clonal, 69%; subclonal 7%, p=0.02918). This finding was validated by the EUR GMMG-HD6 cohort which are of EUR ancestry, and with the CoMMpass WES also demonstrating hyper-APOBEC activity to be lower in AFR (6%) vs EUR (11%). EUR also had more kataegis foci associated with APOBEC and AID activity (SBS84/SBS85) compared to AFR patients (p &lt; 0.01).
In germline samples, calculated PRS were higher in AFR than EUR, (median 3.8 vs 3.4, p&lt;0.01). Considering the somatic difference in APOBEC activity, we also examined germline SNPs specific to APOBEC activity. Though 17/23 PRS genes were different between AFR and EUR (p &lt; 0.05), only 2 of those were associated with increased APOBEC activity. APOBEC germline SNPs were not associated with higher APOBEC activity.
Considering the reported younger age in AA patients, we performed molecular timing analysis. Utilizing the clock-like SBS1/SBS5, there was no difference in estimated timing of cancer initiation in AFR vs EUR. However, pre-chromosomal-gain SBS9, reflecting early germinal center poly-eta activity, was higher in EUR than AFR. Post-gain and sub-clonal SBS9 activity were the same between AFR and EUR.
CONCLUSIONS: Here we leverage a large series of diverse patients with WGS and with a comprehensive approach integrate somatic data with germline ancestry. We demonstrate that most biological features are the same between admixture-based patient groups. However, while AFR patients have a higher polygenic risk score, EUR patients have less ‘Simple’ genomic classification, higher pre-gain SBS9, more APOBEC activity and more kataegis foci associated with APOBEC / AID. This data suggests that EUR patients may have a more intense germinal center interaction, leading to a more complex MM than AFR.