December 15, 2016

Not by Chance: Eight NEW Genetic Risk Factors Discovered for Multiple Myeloma

National Human Genome Research Institute, National Institutes of Health

National Human Genome Research Institute, National Institutes of Health

Dr. Gareth Morgan, professor and director of the Myeloma Center, Dr. Niels Weinhold, assistant professor and director of genetics at the Myeloma Center, and colleagues from Germany, the Netherlands, Sweden, Iceland, and the United Kingdom have identified eight additional gene variants that increase the risk of developing multiple myeloma. These results provide further evidence that multiple myeloma does not develop by chance, but is driven by inherited gene variants.

The risk of developing multiple myeloma is increased in the relatives of individuals with multiple myeloma. In an international collaboration, the UAMS Myeloma Center team investigated whether the cause for this increase may be found in the germline DNA* of patients. They analyzed characteristic changes in the genome of 9,866 patients and 239,188 healthy controls to identify inherited genetic variants that are seen more often in multiple myeloma patients. Methodologically, they conducted a meta-analysis** of genome-wide association studies (GWASs)*** and investigated variations of single base pairs, so-called single nucleotide polymorphisms (SNPs). This largest GWAS to date identified new risk loci that have relevance to myeloma biology. Locus (plural loci) refers to the specific location of SNPs.

While findings from the study provide evidence of inherited genetic susceptibility to myeloma, further studies are needed to understand the biology behind the risk variants. These studies, conducted in coordination with analyses of patients’ functional outcomes, are expected to lead to additional insights into myeloma biology that support the development of new therapeutic agents and personalized medicine approaches to treatment.

Genome-wide association study identifies multiple susceptibility loci for multiple myeloma
Nature Communications 7, Article number: 12050, published July 1, 2016

*Germline DNA: the DNA in germ cells (egg and sperm cells that join to form an embryo). Germline DNA is the source of DNA for all other cells in the body. Also called constitutional DNA.
NCI Dictionary of Cancer Terms

**Meta-analysis: a systematic method that takes data from a number of independent studies and integrates them using statistical analysis.
Dorland’s Medical Dictionary for Health Consumers

*** See pages 16-17
Genome-wide association study

Questions for Dr. Morgan and Dr. Weinhold

What is the primary significance of this study?
We are really starting to hone in on the genetic contributions to myeloma. Our findings have given us new insights into the early pathogenesis of multiple myeloma and are helping us develop new strategies to prevent myeloma.

How important was the magnitude of the study sample?
In contrast to the situation in other cancers, such as breast cancer where variants in BRCA1 and BRCA2 genes massively increase disease risk, genetic variants have only a small individual impact on multiple myeloma risk. Therefore, they can only be detected in data sets with several thousand cases and controls.

Were the samples representative of most patients who are diagnosed with myeloma?
Our samples came from a range of countries within Europe and from the United States and were representative of Caucasian patients. To investigate the impact of genetic variants on myeloma risk in patients of African descent, we recently started a collaboration with Dr. Wendy Cozen, professor of preventive medicine at the University of Southern California. Results of this study will be presented soon.

Is it important to expand the study sample?

Our calculations show that we have identified only a fraction of risk variants so far. Due to the small effect of these variants they are difficult to detect, but larger cohorts will significantly increase the power to identify them.

Could this type of study be effectively conducted at a single institution?
Definitely not!

Will follow-up studies that lead to further understanding of myeloma biology be conducted?
Yes, we will be studying risk variants in myeloma plasma cells and model systems to identify their impact on cell biology.

Do you expect to be involved in these follow-up studies?

Does the information from this study have the potential to move forward development of a myeloma cure?
Preventing myeloma is the ultimate goal. These findings are helping us develop appropriate strategies.

Should a relative of a myeloma patient consider genetic testing for myeloma risk variants?
While relatives have an increased risk of developing myeloma, their absolute risk is still very low. Thus, we do not recommend genetic testing for these variants.

Information about the Genome-wide Association Study
from the National Human Genome Research Institute, National Institutes of Health

What is a genome-wide association study?
A genome-wide association study is an approach that involves rapidly scanning markers across the complete sets of DNA, or genomes, of many people to find genetic variations associated with a particular disease. Once new genetic associations are identified, researchers can use the information to develop better strategies to detect, treat and prevent the disease.

Why are such studies possible now?
With the completion of the Human Genome Project in 2003 and the International HapMap Project in 2005, researchers now have a set of research tools that make it possible to find the genetic contributions to common diseases. The tools include computerized databases that contain the reference human genome sequence, a map of human genetic variation and a set of new technologies that can quickly and accurately analyze whole-genome samples for genetic variations that contribute to the onset of a disease.

How will genome-wide association studies benefit human health?
The impact on medical care from genome-wide association studies could potentially be substantial. Such research is laying the groundwork for the era of personalized medicine, in which the current one-size-fits-all approach to medical care will give way to more customized strategies.

In the future, after improvements are made in the cost and efficiency of genome-wide scans and other innovative technologies, health professionals will be able to use such tools to provide patients with individualized information about their risks of developing certain diseases. The information will enable health professionals to tailor prevention programs to each person’s unique genetic makeup. In addition, if a patient does become ill, the information can be used to select the treatments most likely to be effective and least likely to cause adverse reactions in that particular patient.

How are genome-wide association studies conducted?
To carry out a genome-wide association study, researchers use two groups of participants: people with the disease being studied and similar people without the disease. Researchers obtain DNA from each participant, usually by drawing a blood sample or by rubbing a cotton swab along the inside of the mouth to harvest cells.

Each person’s complete set of DNA, or genome, is then purified from the blood or cells, placed on tiny chips and scanned on automated laboratory machines. The machines quickly survey each participant’s genome for strategically selected markers of genetic variation, which are called single nucleotide polymorphisms, or SNPs.

If certain genetic variations are found to be significantly more frequent in people with the disease compared to people without disease, the variations are said to be “associated” with the disease. The associated genetic variations can serve as powerful pointers to the region of the human genome where the disease-causing problem resides.

However, the associated variants themselves may not directly cause the disease. They may just be “tagging along” with the actual causal variants. For this reason, researchers often need to take additional steps, such as sequencing DNA base pairs in that particular region of the genome, to identify the exact genetic change involved in the disease.