The interaction between ultra-processed foods and genetic risk score on body adiposity index (BAI), appendicular skeletal muscle mass index (ASM), and lipid profile in overweight and obese women

Abstract

The interaction between ultra-processed foods and genetic risk score on body adiposity index (BAI), appendicular skeletal muscle mass index (ASM), and lipid profile in overweight and obese women Fatemeh Gholami a,d, Azadeh Lesani a, Neda Soveid a, Niloufar Rasaei a, Mahsa Samadi a, Niki Bahrampour c, Gholamali Javdan b,**, Khadijeh Mirzaei a,* a Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, Iran b Food Health Research Center, Hormozgan University of Medical Sciences, Bandar ʽAbbas, Iran c Department of Nutrition, Science and Research Branch Islamic Azad University (SRBIAU), Tehran, Iran d Department of Clinical Nutrition, Shahid Mohammadi Hospital, Hormozgan University of Medical Sciences, Bandar Abbas, Iran A R T I C L E I N F O Handling Editor: Prof A Angelo Azzi Keywords: Genetic risk score Ultra-processed foods Body composition Body adiposity index Appendicular skeletal muscle mass A B S T R A C T Background & aims: Ultra-processed foods (UPF) are formulations of ingredients, resulting from a series of industrial processes. Excess intake of UPF is associated with an increased risk of obesity and chronic disease. The present study investigates the interaction between the consumption of UPF and genetic risk score with body composition, body adiposity index (BAI), and appendicular skeletal muscle mass (ASM) in overweight and obese women. Method: The study is cross-sectional with 376 overweight and obese women aged 18–65 years. The food consumption was obtained with 147-item food frequency (FFQ), and food items were grouped according to the level of processing as per the NOVA classification. Three single nucleotide polymorphisms (SNPs), including Caveolin_1 (Cav_1), Melanocortin4 receptor (MC4R), and cryptochrome circadian regulator 1 (CRY1), were used to calculate GRS. The individual risk allele for each SNP was calculated using the incremental genetic model. Each SNP was recoded as 0, 1, or 2 based on the number of risk alleles associated with a higher body mass index (BMI). Subsequently, the unweighted GRS was computed by summing the number of risk alleles across the three SNPs. The GRS scale spans from 0 to 6, with each point representing a risk allele.Anthropometric measurements and some blood parameters were measured by standard protocols. Results: After controlling for confounders such as age, energy intake, and BMI a significant interaction was found for appendicular skeletal muscle mass (β = 􀀀 1.65, P = 0.04) and appendicular skeletal muscle mass index (β = 􀀀 0.38, P = 0.07) on the NOVA classification system and GRS. Conclusions: The findings of this study showed a significant interaction between GRS and the NOVA classification system on some body composition, including appendicular skeletal muscle mass. A higher intake of ultraprocessed foods may be associated with lower appendicular skeletal muscle mass in people with high obesity- GRS.