By Michael Nova, M.D.
Chief Innovation Officer
There has recently (2013-15) been a flurry of human clinical trial publications regarding gene-diet interactions, primarily concerning obesity and related phenotypes.
A new finding by the Genetic Investigation of Anthropometric Traits, or GIANT, consortium has identified 97 gene regions associated with obesity, tripling the number of such genes previously known.
Despite this strong influence of genes in obesity, the environment can play as strong a part. It is estimated that 40 to 70 percent of the variation in obesity is caused by genetics. The remaining 30 to 60 percent can be attributed to the environment you live in.
There is now clear evidence that variants of genes such as APOA2, FTO, PPARg, FOXO, KLOTHO, DRD4 and others directly interact with micronutrients (or insulin) to regulate differing metabolism effects, and subsequently can tip individuals over to an obesogenic phenotype depending on environmental factors such as type of food consumed or eating behaviors (DRD4). As an example, FOXO is a transcription factor that plays important roles in regulation of gluconeogenesis and glycogenolysis by insulin signaling, and is also central to the decision for negatively regulating adipogenesis (fat production) and its vital in stem cell maintenance. FOXO has been found to be particularly active in centenarians — people older than one hundred years, which is why many believe that FOXO plays a key role in aging.
Genetic variants in KLOTHO have been associated with human aging, and KLOTHO protein has been shown to be a circulating factor detectable in blood serum that declines with age. It is also coincidental, that many of the gene combinations implicated in obesity and increased BMI are also manifest in the metabolism pathways now linked to aging.
As another example, mTOR (mechanistic target of rapamycin) signaling pathway senses and integrates a variety of environmental cues to regulate organismal growth and homeostasis. The pathway regulates many major cellular processes and is implicated in an increasing number of pathological conditions, including cancer, obesity, type 2 diabetes, and neurodegeneration.
Much new data linking obesity/diabetes genotypes and anti-aging pathways and possible therapeutics (Rapamycin, Metformin) have also been shown. In fact, Rapamycin, an inhibitor of mechanistic target of Rapamycin (mTOR), has the strongest experimental support to date as a potential anti-aging therapeutic in lower life forms, such as c-elegans, and also mammals (mice, rats).
With the sum of all medical/healthcare knowledge doubling every three years, we are living in exciting times. With the new ‘omics and healthcare IT/computational biology technologies, we now have the ability to tease out the linkages between very complex biological pathways. This will assuredly lead to better and more personalized precision medicine treatments for chronic conditions (like obesity) and maybe also into generalized anti-aging therapeutics or even micronutrients.
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