Associations between CD36 gene polymorphisms, fat tolerance and oral fat preference in a young-adult population

Genetic determinants of food preferences: a systematic review of observational studies

BACKGROUND

Over the last decade, the results of several studies have indicated that adults' food preferences, consumption, and dietary choices vary depending on their genotype characteristics. However, the results of studies related to genes and polymorphisms involved in this phenomenon are contradictory. This study is a systematic review designed to evaluate the genetic determinants of food preferences.

METHODS

This study was conducted following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Searches were conducted to identify articles testing the impact of genotypes on food choices, preferences, and intake in healthy adults. The search included all relevant keywords, and studies published between 1/1/1994 and October 2022 were considered. We assessed the quality of included studies and evaluated the risk of bias using the Newcastle-Ottawa Scale (NOS) for observational studies.

RESULTS

A total of 8,510 records were identified through our search method, and finally, 50 studies were included in this study. The majority of the studies evaluated the association of genetic variants with preferences for macronutrients, sweet, bitter, and fatty foods. The results of our study suggest a significant correlation between TAS2R38 variants (rs713598, rs1726866, rs10246939) and bitter and sweet taste preferences. Additionally, we found a considerable association between the T102C polymorphism of the 5-HT2A receptor gene and a higher intake of protein, and rs1761667 (CD36) was associated with fat preference.

CONCLUSION

In conclusion, this study revealed a significant association between certain genetic variants and food preferences among adults.

Quantile-dependent expressivity of postprandial lipemia

Purpose

“Quantile-dependent expressivity” describes an effect of the genotype that depends upon the level of the phenotype (e.g., whether a subject’s triglycerides are high or low relative to its population distribution). Prior analyses suggest that the effect of a genetic risk score (GRS) on fasting plasma triglyceride levels increases with the percentile of the triglyceride distribution. Postprandial lipemia is well suited for testing quantile-dependent expressivity because it exposes each individual’s genotype to substantial increases in their plasma triglyceride concentrations. Ninety-seven published papers were identified that plotted mean triglyceride response vs. time and genotype, which were converted into quantitative data. Separately, for each published graph, standard least-squares regression analysis was used to compare the genotype differences at time t (dependent variable) to average triglyceride concentrations at time t (independent variable) to assess whether the genetic effect size increased in association with higher triglyceride concentrations and whether the phenomenon could explain purported genetic interactions with sex, diet, disease, BMI, and drugs.

Results

Consistent with the phenomenon, genetic effect sizes increased (P≤0.05) with increasing triglyceride concentrations for polymorphisms associated with ABCA1, ANGPTL4, APOA1, APOA2, APOA4, APOA5, APOB, APOC3, APOE, CETP, FABP2, FATP6, GALNT2, GCKR, HL, IL1b, LEPR, LOX-1, LPL, MC4R, MTTP, NPY, SORT1, SULF2, TNFA, TCF7L2, and TM6SF2. The effect size for these polymorphisms showed a progressively increasing dose-response, with intermediate effect sizes at intermediate triglyceride concentrations. Quantile-dependent expressivity provided an alternative interpretation to their interactions with sex, drugs, disease, diet, and age, which have been traditionally ascribed to gene-environment interactions and genetic predictors of drug efficacy (i.e., personalized medicine).

Conclusion

Quantile-dependent expressivity applies to the majority of genetic variants affecting postprandial triglycerides, which may arise because the impaired functionalities of these variants increase at higher triglyceride concentrations. Purported gene-drug interactions may be the manifestations of quantile-dependent expressivity, rather than genetic predictors of drug efficacy.