- Researchers at Massachusetts General Hospital have conducted the largest study to date of genetic factors related to food intake, using data on 282,271 individuals of European ancestry
- They identified 31 genome-wide significant variants in 26 distinct genomic loci, including 14 not previously described
- Genes associated with dietary intake were predominantly expressed in specialized subtypes of GABAergic, dopaminergic and glutamatergic neurons distributed across several brain regions connected to the hypothalamus
- Two main clusters of genetic variants with different nutritional profiles were identified and may have distinct associations with obesity and coronary artery disease
Preliminary research at Massachusetts General Hospital, reported in Molecular Psychiatry, suggests the amount of carbohydrate, fat and protein people consume are partially affected by inherited biological differences. So far, though, most genetic association studies of dietary intake traits have focused on single nutrients or single foods.
Now, researchers in the Center for Genomic Medicine (CGM) at Massachusetts General Hospital, led by Jordi Merino, PhD, a research associate at the Diabetes Unit in the Endocrine Division, Jose C. Florez, MD, PhD, chief of the Diabetes Unit and Endocrine Division, and Richa Saxena, PhD, principal investigator in the Department of Anesthesia; and Josée Dupuis, PhD, of the Boston University School of Public Health, and colleagues have identified 26 genomic regions that may affect overall variation in dietary intake. They report the specifics in Nature Human Behaviour.
New Genetic Loci
The researchers accounted for the correlations between carbohydrate, fat and protein intake to investigate genetic effects on overall dietary intake among 191,157 participants in the UK Biobank and 91,114 individuals of European ancestry in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.
31 genome-wide significant variants were identified in 26 distinct genomic regions, including 14 not previously described. The strongest signal was for a cluster of four variants in FGF21. This gene was associated with increased fat and protein intake and reduced carbohydrate intake.
Central Nervous System Regulation
The team integrated the genetic findings with publicly available single-cell RNA sequencing datasets. Genes associated with dietary intake were predominantly expressed in specialized subtypes of GABAergic, dopaminergic and glutamatergic neurons distributed across several brain regions connected to the hypothalamus.
This observation aligns with previous research pinpointing the central nervous system as a critical regulator of energy homeostasis and body weight and is consistent with the view that obesity is a disease with primary defects in appetite control.
Clusters of Genetic Variants
The researchers classified dietary intake genetic loci into subgroups based on similarities in dietary composition. Two main diet clusters were identified:
- Increased fat, protein and polyunsaturated fat intake (“increased fat and protein”)
- Increased fat and reduced carbohydrate intake (“reduced carbohydrate”)
The most strongly weighted variants from each cluster were used to build a polygenic score (PS) and investigate their association with metabolic diseases. Using data from the UK Biobank:
- The PRS for the increased fat and protein cluster was associated with lower body mass index (estimated effect size, −0.04 kg/m2 per 1 SD increase in PS)
- The PS for the reduced carbohydrate cluster was associated with a lower risk of coronary artery disease (estimated OR, 0.97 per 1 SD increase in PS)
- There were no significant associations between PS and type 2 diabetes
These associations, although directionally consistent, could not be replicated when the researchers analyzed a health system’s multiethnic biobank. Potential reasons for these partial replications might be the inclusion of people with certain diseases or from ethnicities other than white ethnicities.
These results provide a starting place for developing new strategies to prevent and treat obesity and other metabolic diseases. Caution is needed about interpretation since the study was based on healthy individuals of European ancestry and the results could not be replicated in a demographically and clinically mixed population.