Genetic Variants Linked to Differences in Food Intake:
Data from the National Health and Nutrition Examination Survey in 2018 found that the prevalence of obesity in American adults was 42.7% (Hales et al. 2018). This national epidemic has led to many severe chronic illnesses including heart disease, stroke, type two diabetes, and some cancers. Society today views these health issues as a result of social and environmental factors such as a lack of control around food, poor exercise, and easy access to processed, high fat food options. However, there has been a recent turning point in research that contests these assertions. A Study managed by Mass General Hospital and other institutions conducted a genome wide meta analysis study identifying two genetic regions and specialized neurons in the Central Nervous System correlated to an increase in carbohydrate, fat, and protein intake. This study dissects the inherited biological factors that play a role in eating behaviors which in turn affects human health. Though many would argue food intake in correlation to obesity, type two diabetes and other chronic illnesses are influenced by environmental and social factors, this European Ancestry participant study accentuates the biological and neural causes of dietary intake that can lead to future developments in preventing injurious food consumption and chronic conditions.
In the largest study done to date examining genetic factors related to food consumption, a multi-trait genome wide study including 283,119 participants from the UK biobank and CHARGE constitorium’s food intake was recorded. These approaches have unraveled 94 significant loci portraying into 288 genes which provide mechanistic insight into physiological, metabolic, or behavioral phenotypes. Twenty six regions were also identified to be associated with increased preference for foods containing fat, carbohydrates, and protein where dietary intake was recorded using a twenty four hour web based diet recall (Marino et al. 2021, 5-7). A key finding included the enrichment of dietary intake associated with signals of beta-one-tantyctes, an ependymal cell that significantly regulates metabolism. Identifying the variants that express phenotypic insight give way to substantial biological mechanisms into eating patterns.
Three genetic clusters were also found with specific association with type two diabetes and obesity. Bayesian nonnegative matrix factorization clustering approach was used as a process of aligning variants by their alleles associated with increased fat intake and twenty two other dietary traits. Cluster two, reduced carbohydrate and protein diet, and three, increased protein diet, were correlated with lower BMI. Genetic cluster three was also identified to have a lower type two diabetes expression. Outcomes of these findings suggest that increased fat intake as well as decreased carbohydrate intake may be associated with lower BMI, and increased fat and protein intake may be correlated to lower type two diabetes (Merino et al 2021, 10-11). These gene clusters share generalized functions and show specific genome patterns correlate to macronutrient consumption. This study also found that dietary intake is partially controlled by the central nervous system by testing enrichment for gene expression in 53 tissue types using GTeX, a genotype-expression project. This helps identify how genetics contribute to common human diseases. Signals were proven for genes expressed in the hypothalamus, cerebellum, frontal cortex, nucleus accumbens, and anterior cingulate cortex. These areas are specifically known to influence energy homeostasis and appetite control (Merino et al. 2021, p. 8).
Some inaccuracies in study methods and procedures were incorporated in this study. The study was geographically biased to Europe, using the UK Biobank and CHARGE Consortium. All included studies from these research databases received ethical approval and informed consent. However having studies focused on one geographical area can alter validity of research. Expanding to non European locations aids in determining generalizability of identified signals. This study was also limited to self reported dietary intake. Self reported data can be biased and misrepresentative. Having more precise quantifiable data would increase the studies accuracy and credibility.
These results have found that biological factors and neurological processes have at least some influence on the dietary intake of the major population. Because these findings are new and minimal research has been done in this area, this data is important for future research to be conducted in the field of genetics and nutrition. By identifying these biological causes, science can further prevent preferences for unhealthy foods. Specifically saturated fats, as well as overconsumption of certain foods. This study lays the groundwork for the future of healthy eating habits and in turn, healthy living.
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