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Page 113 Waller et al. J Transl Genet Genom 2021;5:112-23 I http://dx.doi.org/10.20517/jtgg.2021.09

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Results: We identified one genome-wide significant region at 18q21.33 (0.85 Mb, P = 7.3 × 10 ) which contains
one gene, CDH20. Thirteen regions were genome-wide suggestive: 1q42.2, 2p16.1, 3p25.2, 5q21.3, 5q31.1, 6q16.1,
6q26, 7q11.23, 12q24.31, 13q13.3, 18p11.22, 18q22.3 and 19p13.12.

Conclusion: Our results provide novel risk loci with segregating evidence from multiple HRPs and offer compelling
targets and specific segment carriers to focus a future search for functional variants involved in inherited risk
formyeloma.

Keywords: High-risk pedigrees, gene mapping, multiple myeloma, disease susceptibility

INTRODUCTION
Multiple myeloma (MM) is the second most common adult-onset lymphoid neoplasm and has the
[2]
[1]
worst 5-year survival . Inherited germline susceptibility for MM is consistently supported : excess MM
[3,4]
risk among relatives has been observed in family aggregation , epidemiologic case-control [5-9] , and
registry-based [10,11] studies. Disease rarity, short survival, clinical and locus heterogeneity challenge study
[12]
ascertainment and genetic discovery . Genome-wide association studies have identified 23 loci harboring
common-risk single nucleotide polymorphisms (SNPs) for MM [13-19] . Family-based studies have identified
rare germline variants in ARID1A and USP45 , KDM1A , and DIS3 in exome sequencing. However,
[22]
[21]
[20]
considerable missing heritability remains. Additional approaches are needed to aid the detection of the
remaining risk loci and genes.
We recently described a novel strategy to map genes involved in complex disease risk using extremely large
[20]
high-risk pedigrees and allowing for intra-familial heterogeneity, called Shared Genomic Segment (SGS) .
Cases sharing genomic segments from a common ancestor through 15 meioses or more are unexpected at a
[23]
genome-wide level , and hence a single large high-risk pedigree (HRP) can provide the power to identify
novel loci with genome-wide significance . Our resource of eleven large myeloma pedigrees included
[24]
[20]
several with 3-4 cases and meioses in the 8-14 range . While these remain extremely large families, they
may lack sufficient power individually for genome-wide significance. Also, a multi-pedigree strategy is
attractive. Evidence for the same risk locus in two extended pedigrees adds confidence to the locus and
can build on the power of both. The remaining challenge for any multi-pedigree approach, however, is to
[25]
adequately address heterogeneity between pedigrees .

Here, we expand the SGS method based on combining evidence from pairs of HRPs, while still allowing
for intra-familial heterogeneity within each pedigree. In our approach, duo-SGS, we fix one pedigree and
optimize over all pedigree pairs to balance discovery with multiple testing. Both pedigrees must have
a segregating genomic segment at the same risk locus. The method is robust to allelic heterogeneity as
different alleles at the same locus may be shared within each pedigree. We apply the duo-SGS approach to
eleven MM HRPs to identify novel loci involved in myeloma risk.

METHODS
Duo-SGS method
An overview of the duo-SGS approach can be found in Figure 1. After identifying HRPs and genotyping
cases, the observed shared genomic segments in single pedigrees are established and compared between
pedigrees, and genome-wide thresholds are determined.

Observed duo-SGS sharing
The single pedigree SGS approach has been described previously . Briefly, the single SGS approach
[20]
identifies shared observed genomic segments by defining consecutive runs of SNPs that are identity-by-