# Whole-Exome Sequencing-Based Linkage Analysis of Multiple Myeloma (MM) and Monoclonal Gammopathy of Undetermined Significance (MGUS) Pedigrees

## TL;DR

This study finds a region on chromosome 6 linked to multiple myeloma and its precursor, highlighting new genes that may explain inherited risk.

## Contribution

The study identifies a chromosome 6 region and rare variants linked to MM/MGUS using family-based whole-exome sequencing linkage analysis.

## Key findings

- Significant linkage was found on chromosome 6q22.33–q24.2 for MM/MGUS risk.
- Fourteen rare variants in this region were identified, nine of which affect immune-regulatory areas.
- These findings suggest new genes and pathways involved in inherited risk for MM and MGUS.

## Abstract

People with relatives who have multiple myeloma or its early condition, monoclonal gammopathy of undetermined significance, face higher risk. Most research has focused on common DNA changes, but these do not explain all inherited risk. We studied 79 families with two or more affected relatives and examined their protein-coding DNA to find regions that are passed down together with disease. We found strong evidence that a stretch of chromosome 6 (q22.33–q24.2) is linked to risk. Within this region, we highlighted 14 rare variants predicted to affect gene function; nine reside in areas that regulate immune cells. This work shows that family-based DNA linkage can uncover risk regions missed by previous approaches and points to new genes and pathways that may help explain—and ultimately predict—risk for multiple myeloma and its precursor.

Background/Objectives: Family history is a known risk factor for multiple myeloma (MM) and its precursor condition, monoclonal gammopathy of undetermined significance (MGUS). Previous genome-wide association studies (GWASs) have identified 35 common loci associated with MM risk and 21 associated with MGUS. The objective of this study was to identify less common and rare genetic loci predisposing to MM/MGUS through whole-exome sequencing (WES)-based linkage analysis. Methods:Multipoint linkage analysis was conducted using the Multipoint Engine for Rapid Likelihood Inference (MERLIN) with the Lander–Green algorithm on germline WES data from 79 pedigrees with 2 or more affected relatives (120 MM, 86 MGUS, and 21 unaffected). Genome-wide linkage was evaluated using 12,946 independent single-nucleotide variants (linkage disequilibrium r2 < 0.05). Results: Significant linkage was observed at chromosome 6q22.33–q24.2 by the non-parametric model (logarithm-of-odds (LOD) = 3.3) and suggestive linkage by the dominant parametric model (heterogeneity LOD (HLOD) = 2.5). Fourteen rare variants within this region were prioritized using family-specific partial LOD scores and in silico functional prediction tools. Nine of these variants, REPS1, THEMIS, TAAR6, AHI1, VNN1, VNN3, MTFR2/FAM54A, LAMA2, and PHACTR2, overlapped immune-regulatory regions in blood cell lines and were not previously identified in GWASs. Conclusions: This study demonstrates the utility of applying a linkage analysis framework to familial WES data for identifying genomic regions and candidate genes that may contribute to MM/MGUS predisposition. These findings provide new insight into the inherited risk and etiology of familial MM and MGUS.