An obesity-associated risk allele within the FTO gene affects human brain activity for areas important for emotion, impulse control and reward in response to food images.

Understanding how genetics influences obesity, brain activity and eating behaviour will add important insight for developing strategies for weight-loss treatment, as obesity may stem from different causes and as individual feeding behaviour may depend on genetic differences. To this end, we examined how an obesity risk allele for the FTO gene affects brain activity in response to food images of different caloric content via functional magnetic resonance imaging (fMRI). Thirty participants homozygous for the rs9939609 single nucleotide polymorphism were shown images of low- or high-calorie food while brain activity was measured via fMRI. In a whole-brain analysis, we found that people with the FTO risk allele genotype (AA) had increased activity compared with the non-risk (TT) genotype in the posterior cingulate, cuneus, precuneus and putamen. Moreover, higher body mass index in the AA genotype was associated with reduced activity to food images in areas important for emotion (cingulate cortex), but also in areas important for impulse control (frontal gyri and lentiform nucleus). Lastly, we corroborate our findings with behavioural scales for the behavioural inhibition and activation systems. Our results suggest that the two genotypes are associated with differential neural processing of food images, which may influence weight status through diminished impulse control and reward processing.

Resting-State Brain and the FTO Obesity Risk Allele: Default Mode, Sensorimotor, and Salience Network Connectivity Underlying Different Somatosensory Integration and Reward Processing between Genotypes.

Single-nucleotide polymorphisms (SNPs) of the fat mass and obesity associated (FTO) gene are linked to obesity, but how these SNPs influence resting-state neural activation is unknown. Few brain-imaging studies have investigated the influence of obesity-related SNPs on neural activity, and no study has investigated resting-state connectivity patterns. We tested connectivity within three, main resting-state networks: default mode (DMN), sensorimotor (SMN), and salience network (SN) in 30 male participants, grouped based on genotype for the rs9939609 FTO SNP, as well as punishment and reward sensitivity measured by the Behavioral Inhibition (BIS) and Behavioral Activation System (BAS) questionnaires. Because obesity is associated with anomalies in both systems, we calculated a BIS/BAS ratio (BBr) accounting for features of both scores. A prominence of BIS over BAS (higher BBr) resulted in increased connectivity in frontal and paralimbic regions. These alterations were more evident in the obesity-associated AA genotype, where a high BBr was also associated with increased SN connectivity in dopaminergic circuitries, and in a subnetwork involved in somatosensory integration regarding food. Participants with AA genotype and high BBr, compared to corresponding participants in the TT genotype, also showed greater DMN connectivity in regions involved in the processing of food cues, and in the SMN for regions involved in visceral perception and reward-based learning. These findings suggest that neural connectivity patterns influence the sensitivity toward punishment and reward more closely in the AA carriers, predisposing them to developing obesity. Our work explains a complex interaction between genetics, neural patterns, and behavioral measures in determining the risk for obesity and may help develop individually-tailored strategies for obesity prevention.