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Page 121 Waller et al. J Transl Genet Genom 2021;5:112-23 I http://dx.doi.org/10.20517/jtgg.2021.09

As in all family-based genetic studies, our results could be sensitive to inaccurate pedigree structures.
However, relationship and ethnicity checks are standard protocols and mitigate the possibility of error.
Another limitation to this study is the observational nature. Additional functional studies will be required
to describe causation and characterize the mechanisms involved in these loci and myeloma risk.

We have identified several novel loci that segregate in at least two myeloma HRPs. These loci are likely to
harbor genes and rare risk variants for MM and are compelling new targets for inherited risk to MM.

In conclusion, we developed a novel strategy for gene mapping in complex traits that uses multiple large
high-risk pedigrees. The approach is robust to heterogeneity both within and between pedigrees and
formally corrects for multiple testing to allow for statistically rigorous discovery. We applied this strategy to
MM, a complex cancer of plasma cells, and identified one novel genome-wide significant locus at 18q21.33
and 13 suggestive loci. Our study offers a new technique for gene mapping and demonstrates its utility to
narrow the search for risk variants in complex traits.

DECLARATIONS
Acknowledgments
We thank the participants and their families who make this research possible. Data collection was made
possible, in part, by the Utah Population Database and the Utah Cancer Registry. Computations were
supported by the University of Utah’s Center for High-Performance Computing.

Authors’ contributions
Designed the study and wrote the manuscript: Waller RG, Camp NJ
Contributed to the duo-SGS method development: Waller RG, Madsen MJ, Gardner J, Camp NJ
Provided analysis support and edited the manuscript: Madsen MJ, Gardner J
Provided clinical support and reviewed the manuscript: Sborov DW
Generated figures and tables: Waller RG

Availability of data and materials
The Shared Genome Segment (SGS) analysis software is freely available and can be accessed online: https://
uofuhealth.utah.edu/huntsman/labs/camp/analysis-tool/shared-genomic-segment.php. Data used in the
duo-SGS analysis includes pedigree structures, myeloma diagnoses, and genome-wide SNP genotypes.
Pedigree structures necessary for these analyses were acquired from the Utah Population Database (UPDB).
These are considered potentially identifiable by the Resource for Genetic and Epidemiologic Research
(RGE) - the ethical oversight committee for the UPDB. As a result, access to these data requires review by
the RGE committee (contact Jahn Barlow, jahn.barlow@utah.edu). Upon RGE approval, we will provide the
genotypes and pedigree structure in a format ready to be used by the SGS software.

Financial support and sponsorship
Research reported in this publication was supported by the National Cancer Institute of the National
Institutes of Health under Award Number F99CA234943 and K00CA234943. The content is solely the
responsibility of the authors and does not necessarily represent the official views of the National Institutes
of Health. Methodological development of the duo-SGS method was supported by the University of Utah’s
Center for Genomic Medicine. This research was supported by the Utah Cancer Registry, which is funded
by the National Cancer Institute’s SEER Program, Contract No. HHSN261201800016I, the US Center
for Disease Control and Prevention’s National Program of Cancer Registries, Cooperative Agreement
No. NU58DP0063200, with additional support from the University of Utah and the Huntsman Cancer
Foundation. Partial support for all datasets within the Utah Population Database is provided by the
University of Utah, Huntsman Cancer Institute, and the Huntsman Cancer Institute Cancer Center Support