Trait#101: TNNI3K and fat intake
Monday, July 5, 2021. Author FitnessGenes
Monday, July 5, 2021. Author FitnessGenes
TNNI3K is a gene that encodes an enzyme called cardiac troponin-I interacting kinase.
This enzyme is expressed by heart muscle cells (cardiac myocytes) and is thought to play a role in the muscular function and electrical conduction system of the heart.
Interestingly, the TNNI3K gene may also play a role in the control of food intake. On this note, studies have linked variants of the TNNI3K gene to increased fat consumption, unhealthy eating behaviours, and higher BMI.
The precise mechanism by which TNNI3K, a gene thought to be exclusively expressed by heart muscle cells, regulates food intake is unclear. It may be involved in control of satiety (feelings of fullness).
Your TNNI3K and fat intake trait looks at the rs1514175 SNP (Single Nucleotide Polymorphism) within the TNNI3K gene.
This SNP creates a single-letter change in DNA sequence from ‘A’ to ‘G’ giving rise to two different TNNI3K gene variants or ‘alleles’: the ‘A’ allele, and the ‘G’ allele.
As we’ll explain in the following sections, the ‘A’ allele has been linked to higher fat intake, reduced fat taste sensitivity and an increased obesity risk.
Fat taste sensitivity refers to our ability to detect the presence of fatty acids in mouth.
As detailed in the Fat taste sensitivity(CD36) trait article, our tongue has specialised fat taste receptors (e.g. CD36 receptors) that are activated by fatty acids formed from the partial breakdown of fats in the mouth.
Activation of these receptors alerts the brain and digestive system to the fact that we are consuming fat. In response, the digestive system pre-emptively releases enzymes (e.g. lipases) that break down fat and satiety hormones (e.g. cholecystokinin) that make us feel full. Similarly, the brain activates circuits that promote satiety, preventing excess food intake.
Source: Source: Gaillard, D., & Kinnamon, S. C. (2019). New evidence for fat as a primary taste quality. Acta physiologica (Oxford, England), 226(1), e13246.
Researchers can assess fat taste sensitivity by measuring something called fatty acid detection threshold.
In basic terms, this involves getting subjects to taste solutions of water with gradually increasing concentrations of a fatty acid (typically oleic acid).
The point (i.e. the lowest concentration of fatty acid) at which a subject can detect something that isn’t water is known as the detection threshold. A higher detection threshold suggests a poorer ability to detect fatty acids – in other words, reduced fat taste sensitivity.
On this note, a small study suggests that the ‘A’ allele (rs1514175) of the TNNI3K gene is linked to reduced fat taste sensitivity.
The study, which tested fat taste sensitivity in a group of 48 British women, found that those carrying the ‘A’ allele (i.e. those with the AA and AG genotypes) had a significantly higher fatty acid detection threshold compared to those with the GG genotype.
This poorer fat sensitivity, in turn, is predicted to lead to greater consumption of fat. This is because higher levels of fatty acids in the mouth would be required to activate fat taste receptors and drive a satiety response.
Some studies have found the ‘A’ allele of the TNNI3K gene related to higher overall caloric intake, with a greater intake of fat in particular.
For example, a small study which tracked the dietary habits of 55 British women over a year found that those carrying the ‘A’ allele consumed, on average, 1899 kcals per day. This was significantly higher than those with the GG genotype (1497 kcals per day).
When the analysis focussed on macronutrients, it was found that ‘A’ allele carriers consumed more total fat (82 g/day vs 60 g/day) than non-carriers (i.e. GG genotype), with a higher intake of monounsaturated fats (32g/day vs 23g/day) and saturated fat (28g/day vs 20g/day).
Another larger analysis of 2075 subjects enrolled in the Look AHEAD trial did not report any association between the ‘A’ allele and total calorie or fat intake. However, the study did find that, compared to non-carriers, ‘A’ allele carriers obtained a lower percentage of their daily calories from protein.
It’s thought that, as protein has a satiating effect and reduces appetite, a lower proportional intake of protein can lead to higher overall food intake.
It isn’t completely clear how the ‘A’ allele of the TNNI3K gene increases the risk of higher fat consumption, although it may be partly due to reduced fat taste sensitivity. As explained in the previous section, reduced fat taste sensitivity would necessitate a higher intake of fat in order to stimulate satiety responses that curb food intake.
Have you ever found yourself walking to fridge when you’re feeling down?
The tendency to eat in response to negative emotions (e.g. anxiety, loneliness, sadness) is known as emotional eating. People with higher measures of emotional eating behaviour are at elevated risk of weight gain, obesity, and failure of weight-loss interventions.
Emotional eating behaviour is commonly captured by a self-assessment scale known as the Three Factor Eating Questionnaire (TFEQ). This involves a series of statements about eating behaviours, to which a subject must rate how much each statement applies to them.
Some examples of statements related to emotional eating include:
Greater levels of agreement with these statements are given higher scores for emotional eating.
One large study administered the TFEQ to 3,852 people enrolled in the Nurses’ Health Study and Health Professionals Follow-Up Study. It then compared the results to the subjects’ genetic data to investigate whether there was a relationship between eating behaviour and various obesity susceptibility genes, including TNNI3K.
It found that carrying the ‘A’ allele (rs1514175) of the TNNI3K gene was linked to significantly higher scores for emotional eating. This association remained even when controlling for BMI.
Another unhealthy eating behaviour assessed by the TFEQ is uncontrolled eating. This refers to a tendency to experience a loss of control when eating accompanied by strong feelings of hunger, leading to excessive food intake.
Statements related to uncontrolled eating include:
The aforementioned large study (which compared TFEQ scores to genetic data) also found that the ‘A’ allele was significantly associated with uncontrolled eating scores.
Although not explicitly investigated in the above study, it’s possible that a tendency towards emotional and uncontrolled eating may partly explain the higher fat intake observed in ‘A’ allele carriers. People who eat in response to negative emotions, or who are prone to eating binges, often consume highly palatable, junk and comfort foods. These are invariably high in fat.
Some studies have associated the ‘A’ allele (rs1514175) of TNNI3K gene with increased BMI. Most of the evidence comes from a type of study known as a genome-wide association study (GWAS).
In GWAS studies of obesity, people with different BMIs have their DNA analysed to see if there is a significant difference in the frequency of any common genetic variants/SNPs. A significantly higher frequency of a certain gene variant/SNP in overweight and obese individuals (who have higher BMIs) would suggest that the SNP in question is associated with BMI and perhaps confers susceptibility to obesity.
On this note, a GWAS which looked at the genetic data of 249,796 individuals found that ‘A’ allele was associated with higher BMI.
It’s important to remember, however, that complex traits, such as bodyweight and BMI, are impacted by several different genes as well as lifestyle factors. Consequently, single gene variants often have a very small effect on BMI when observed in isolation.
In this respect, the GWAS found that the ‘A’ allele of TNNI3K gene explained 0.02% of the variance in BMI, with each copy of ‘A’ allele estimated to add 0.07 kg/m2 to BMI.
The effect of the ‘A’ allele on BMI may, however, be more pronounced in earlier life, including childhood, adolescence, and young adulthood.
For example, a meta-analysis of 10 different GWAS studies found that each ‘A’ allele added 0.24 kg/m2 to BMI in young adults aged 16 to 25 years. This was a greater effect than that observed in middle-aged adults (average age = 55 years old), where each ‘A’ allele was estimated to add 0.07 kg/m2 to BMI.
The stronger effect of TNNI3K gene variants in childhood and adolescence compared to later adulthood may be due to a variety of reasons. Genes may exert more of an effect on physiology earlier in life, including on factors such as metabolism and blood sugar control. By contrast, environmental factors (e.g. diet, physical activity, other lifestyle differences) may play a proportionally bigger role in later life.
The TNNI3K and fat intake trait also accounts for lifestyle variables, including your current BMI, body fat percentage, and waist circumference.
Elevated BMI and body fat percentage is frequently, though not always, the result of high dietary intakes of fat over time. Studies suggest that fat oxidation does not proportionally increase in response to high intakes of fat, leading to the accumulation of fat tissue in the body.
In turn, excessive amounts of (visceral) fat tissue can worsen insulin sensitivity, causing insulin levels to compensatorily ramped up. High insulin levels (hyperinsulinaemia) is shown to promote hunger and intake of high calorie (including high-fat) foods.
As explained in the Fat taste sensitivity(CD36) trait article, consuming large amounts of fat over time can also promote the further intake of fat, by causing desensitisation of fat taste receptors. Desensitisation of fat taste receptors means higher amounts of fat need to be consumed in order to activate satiety mechanisms that curb food intake.
Your TNNI3K and fat intake trait looks at the rs1514175 SNP near the TNNI3K gene, as well as your lifestyle survey data. Depending on your genetic and lifestyle data, you will be categorised into one of three groups:
To find out your result, please login to Truefeed.
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