Brain cells with gene activity changes related to obesity were identified in a new study, providing a starting point for future research into how different cell types affect this complex trait.
The study, “Genetic mapping of etiologic brain cell types for obesity,” was published in the journal eLife.
Genome-wide association studies (GWAS) are a commonly used tool in genetic research of obesity. The basic idea behind such studies is to look, in large populations, for certain genetic features that are more common in people with a given trait — typically body mass index (BMI), a ratio of weight to height, in the case of obesity.
In recent years, GWAS have identified hundreds of obesity-associated genetic variations. However, most variants identified are located in parts of the genome with regulatory functions, and do not implicate specific genes.
This suggests that studying gene expression, or the conversion of DNA to RNA to ultimately make proteins, may provide additional insights into obesity. Yet, such research is complicated by the fact that different cell types within the body have different gene expression profiles, even though the cells have the same genetic code.
As such, to understand how gene expression affects obesity, it is necessary to study the appropriate cells.
In the new study, a team at the University of Copenhagen, in Denmark, hypothesized that cell types with detectable expression of genes within specific spots associated with BMI are more likely to underlie obesity than cell types in which such genes are not expressed.
The researchers developed two new algorithms, called CELLECT (CELL type Expression-specific integration for Complex Traits) and CELLEX (CELL type EXpression-specificity), and used gene expression data derived from mice in combination with BMI-related GWAS data on more than 457,000 people obtained from the UK Biobank. Specifically, the scientists focused on cells in the nervous system.
Parallel analyses were also in agreement with known data; for example, cell types in the cerebral cortex known to be involved in psychiatric disorders were indeed implicated in such disorders.
“These data establish the ability of this approach to validate previous evidence … that BMI variants tend to colocalize with genes specifically expressed in neurons, while also demonstrating that CELLECT is able to prioritize relevant cell types across a number of complex traits,” the researchers wrote.
A more detailed analysis of BMI data indicated the involvement of 22 cell types, located in eight regions of the brain — namely the subthalamus, midbrain, hippocampus, thalamus, cortex, pons, medulla, and pallidum. Although these cell types are distinct in terms of structure, they showed similar gene expression.
Overall, the results indicate that brain cell types implicated in the genetics of obesity share RNA-related signatures not detected with current methods, the researchers said.
Further supporting the validity of the results, many of the identified cells were found to express high levels of genes with well-established links to obesity, such as the serotonin receptor 5-Htr2c, which is involved in regulating energy.
Notably, many of the implicated brain regions are known to play roles in sensation and behavior regulation, which likely affects feeding behavior — and, by extension, obesity. Regions involved in learning and memory were also implicated.
“Feeding is not an unconditioned response to an energy deficiency but rather reflecting behavior conditioned by learning and experience,” the scientists wrote.
“Our methodological framework provides a salient example of how human genetics data can be integrated with [mouse RNA]-data to identify and map components of brain circuits underlying obesity” they added.
Among the study’s limitations was not assessing the role of specific cell types across developmental stages and with known links to obesity in humans. Also, as the model relies on the assumption that higher gene expression equates to greater relevance to obesity, the researchers wrote, “our approach is not designed to detect cell types in which reduced expression of a specific gene predisposes to obesity.”
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