Yes, some obesity is due to genetics. The largest and most powerful study to date has pinned down 14 variants in 13 genes that carry variations associated with body mass index. They provide new clues as to why some people tend to gain weight and have more trouble losing it. Eight of the variants were in genes not previously tied to human obesity.
The study, published last month, was conducted by the Genetic Investigation of Anthropometric Traits (GIANT) consortium, an international collaboration involving more than 250 research institutions — the same group that brought us height-related genes last year. It combined genetic data from more than 700,000 people and 125 different studies to find rare or low-frequency genetic variants that tracked with obesity.
The study focused on rarer variants in the coding portions of genes, which helped pinpoint causal genes and also helped discover variants with larger effects that those previously discovered by the GIANT consortium. For example, carriers of a variant in the gene MC4R (which produces a protein that tells the brain to stop eating and to burn more energy) weigh 15 pounds more, on average, than people without the variant.
Computational analysis provided some interesting insights into what the 13 genes do. Some, for example, play a role in brain pathways that affect food intake, hunger and satiety. Other variants affect fat-cell biology and how cells expend energy.
“This study provided an important confirmation of the role of the nervous system in body weight regulation,” says Joel Hirschhorn MD, PhD, a pediatric endocrinologist and researcher at Boston Children’s Hospital and the Broad Institute of MIT and Harvard, who co-led the study with Ruth Loos, PhD, of the Icahn School of Medicine at Mount Sinai. “Many of the genes from this study were not known to be associated with obesity, but our computational analysis independently implicates these new genes in strikingly similar neuronal pathways as the genes that emerged from our previous work. In addition, our approach newly highlighted a role for genes known to be important in ‘brown fat,’ a type of fat that burns energy and may help keep people lean.”
The researchers think the new findings could help focus the search for new therapeutic targets in obesity. Read more in Nature Genetics and this press release from Mount Sinai.
A large genetic analysis lends credence to the idea that insulin spikes after eating high-glycemic foods promote weight gain. People genetically predisposed to produce higher than normal levels of insulin after eating processed carbohydrates — “bad carbs” like white bread, potatoes and refined sugar — were more likely to be obese, the study found.
The researchers, led by David Ludwig, MD, PhD, of Boston Children’s Hospital, Joel Hirschhorn, MD, PhD, of Boston Children’s and the Broad Institute, and Jose Florez, MD, PhD, of the Broad Institute and Massachusetts General Hospital, tapped a collection of large-scale genome-wide association studies. Analyzing data from more than 26,000 people who had glucose challenges, they identified genetic variants linked with high insulin levels 30 minutes after the challenge. …
In 2007, when the first genome-wide association studies (GWAS) got underway, researchers began to realize just how poorly they had previously been able to predict which genes might be related to certain diseases.
Height is the “poster child” of complex genetic traits, meaning that it’s influenced by multiple genetic variants working together. Because height is easy to measure, it’s a relatively simple model for understanding traits produced by not one gene, but many.
“Mastering the complex genetics of height may give us a blueprint for studying multifactorial disorders that have eluded our complete understanding, such as diabetes and heart disease,” says Joel Hirschhorn, MD, PhD, a pediatric endocrinologist and researcher at Boston Children’s Hospital and the Broad Institute of MIT and Harvard.
Genome-wide association studies are huge undertakings that compare the genomes of large populations. They can turn up thousands to tens of thousands of genetic variants associated with disease. But which GWAS variants really matter?
That question becomes exponentially harder when the variants lie in the vast stretches of DNA that don’t encode proteins, but instead have regulatory functions.
Reporting in Cell, Sankaran’s team and two other groups at the Broad Institute describe a new tool that can looks at hundreds of thousands of genetic elements at once to pinpoint variants that truly affect gene expression or function. Called the massively parallel reporter assay (MPRA), it could help reveal subtle genetic influences on diseases and traits.
In Sankaran’s case, the MPRA is helping him understand how common variants contribute to blood disorders in children. “Most of the common variation is just tuning genetic function,” he says. “Just slightly, not turning it on or off, but actually just tuning it like a dimmer switch.”
Part of the problem may be that, until now, the right tools haven’t been available to exploit GWAS data. But a few recent studies—including two out of Dana-Farber/Boston Children’s Cancer and Blood Disorders Center—have used GWAS data to identify therapeutically promising targets, and then manipulated those targets using the growing arsenal of gene editing methods.
While it’s not yet clear what this means for patients with either disease, the findings help untangle some very perplexing data about human genetics and diabetes risk, and could change doctors’ thinking about the treatment of both conditions down the road.
Scientists have long known that cancerous and healthy cells don’t use sugar in the same ways. …