Four years ago, Valerie Arboleda accomplished something most young medical geneticists rarely do. She helped discover a rare congenital disease now known as KAT6A syndrome . From the original 10 cases to the more than 100 diagnosed today, KAT6A kids share a single altered gene that causes neuro-developmental delays, most prominently in learning to walk and talk, plus a spectrum of possible abnormalities involving the head, face, heart, and immune system.
Now, Arboleda wants to accomplish something even more groundbreaking. With a 2017 NIH Director’s Early Independence Award, she will develop ways to mine Big Data—the voluminous amounts of DNA sequence and other biological information now stored in public databases—to unearth new clues into the biology of rare disorders like KAT6A syndrome. If successful, Arboleda’s work could bring greater precision to the diagnosis and potentially treatment of Mendelian disorders, as well as provide greater clarity into the specific challenges that might lie ahead for an affected child.
Not so long ago, Hilary Finucane was a talented young mathematician about to complete a master’s degree in theoretical computer science. As much as she enjoyed exploring pure mathematics, Finucane had begun having second thoughts about her career choice. She wanted to use her gift for numbers in a way that would have more real-world impact.
The solution to her dilemma was, literally, standing right by her side. Her husband Yakir Reshef, also a mathematician, was developing a new algorithm at the Broad Institute of MIT and Harvard, Cambridge, MA, to improve detection of unexpected associations in large data sets. So, Finucane helped the Broad team with modeling biomedical topics ranging from the gut microbiome to global health. That work led to her co-authoring a paper in the journal Science , providing a strong start to what’s shaping up to be a rewarding career in computational biology.
When weight loss is the goal, the equation seems simple enough: consume fewer calories and burn more of them exercising. But for some people, losing and keeping off the weight is much more difficult for reasons that can include a genetic component. While there are rare genetic causes of extreme obesity, the strongest common genetic contributor discovered so far is a variant found in an intron of the FTO gene. Variations in this untranslated region of the gene have been tied to differences in body mass and a risk of obesity . For the one in six people of European descent born with two copies of the risk variant, the consequence is carrying around an average of an extra 7 pounds .
Now, NIH-funded researchers reporting in The New England Journal of Medicine  have figured out how this gene influences body weight. The answer is not, as many had suspected, in regions of the brain that control appetite, but in the progenitor cells that produce white and beige fat. The researchers found that the risk variant is part of a larger genetic circuit that determines whether our bodies burn or store fat. This discovery may yield new approaches to intervene in obesity with treatments designed to change the way fat cells handle calories.
Tags: beige fat, CRISPR-Cas, epigenomics, fat, fat cell progenitor, FTO gene, FTO Obesity Risk Variant, FTO obesity variant, genome-wide association studies, GWAS, IRX3, IRX5, obesity, obesity genes, weight loss, white fat