Visualizing Diseases

Visualizing Diseases

Diseasome: The Human Disease Network
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This week, as leading thinkers gather in California for an innovative summit on healthcare, a major new breast cancer study underscores the need for more nuanced understandings of genes and diseases.

We've long known that women with a mutation in the BRCA1 gene (pronounced "bracka one") have a substantially greater risk of developing breast cancer throughout their lives. Now, an international research team led by the Mayo Clinic has found that some women who carry this mutation may possess additional genetic variants that modify their risks of getting cancer in complex ways.

The findings, according to Mayo investigator Fergus Couch, will not only help women with BRCA1 mutations to better gauge their risks, but will shed light on breast cancer in the population at large.

Mutations in the BRCA1 gene gives carriers an increased risk of getting breast cancer. To determine if any genetic variations would modify or alter this risk, the Mayo-led team looked at some 500,000 genetic alterations from across the human genome. By comparing women with BRCA1 and breast cancer to women with BRCA1 but no breast cancer, they were able to identify five specific gene regions—dubbed "SNPs"—associated with breast cancer risk. They were even able to pinpoint the five SNPs to a spot on chromosome 19.

Interestingly, when researchers looked at those five SNPs in women with breast cancer but without the BRCA1 mutation, they found further important associations: One large group of women revealed risks for a certain class of tumors, while another large group of women was highly susceptible to so-called "triple-negative" breast cancer—a kind that accounts for around 12 percent of all breast cancers.

In essence, the Mayo findings reveal that BRCA1 doesn’t operate alone, but instead functions in concert with multiple other genes, with each of these relationships modifying the subtle calculus known as "risk." The findings crystallize what many complex systems scientists have intuited all along—that causal relationships are rarely one-to-one paths, but rather are multiply branching, iterative, and, well, complex.

This visualization, created a team of network scientists, depicts what we know to date about the links between genes and human diseases. The project of Albert-László Barabási and a team of researchers at the Human Disease Network, it indicates the common genetic origin of many human illnesses, including cancer.

The "Human Diseasome" viz features some 1,284 disorders and 1,777 genes, and allows viewers to explore the myriad relationships between the two (explore the interactive site here). Colored nodes represent types of diseases—cancer, for example, is orange and endocrine disorders are yellow—while white nodes represent genes. The lines connecting the nodes show correlations between diseases and genes. If the diseases have a gene in common, the lines show the relationships between diseases too. In that case, a line’s width is proportional to the number of genes they share.

As more data is integrated into the Diseasome, according to Barabási, phenotypes will move closer to genotypes. In other words, we'll able to discern how closely coupled a mutation in, say, "gene X" is with colon cancer, or a variation in "gene Y" is with diabetes.

This week, leading cancer researchers the likes of Barton Kamen will be brushing elbows with pioneering genomicists George Church, Nathaniel Pearson, and Craig Venter this week at TEDMED in San Diego. They will be joined by musicians and architects, neurologists and ecologists, venture capitalists and media moguls who are share a common interest in improving human health — both personal and on a global scale.

Visualizing.org, a partner of the TEDMED conference, offers this data-rich graphic as a challenge to this week's participants. As you gather to listen to one another speak, as you trade ideas, share stories, and cross-pollinate for future projects, think about how seeing these health problems writ large may also help you to see their granular detail and to mine their common connections. In short, we challenge you to consider how visualizing diseases may help you to envision health.

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