Angela Jaramillo-Ospina1, Paola Casanello2, María Luisa Garmendia1, Ross Andersen3, Robert D Levitan4, Michael J Meaney5,6,7, Patricia Pelufo Silveira8,9. 1. Institute of Nutrition and Food Technology, University of Chile, Santiago, Chile. 2. Department of Obstetrics & Department of Neonatology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile. 3. Department of Kinesiology and Physical Education, McGill University, Montreal, QC, Canada. 4. Centre for Addition and Mental Health (CAMH) and Department of Psychiatry, University of Toronto, Toronto, ON, Canada. 5. Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC, Canada. 6. Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada. 7. Translational Neuroscience Programme, Singapore Institute for Clinical Sciences, Singapore, Singapore. 8. Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC, Canada. patricia.silveira@mcgill.ca. 9. Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada. patricia.silveira@mcgill.ca.
Abstract
BACKGROUND: The relationship between eating behaviour and current body weight has been described. However little is known about the effect of polyunsaturated fatty acids (PUFA) in this relationship. Genetic contribution to a certain condition is derived from a combination of small effects from many genetic variants, and polygenic risk scores (PRS) summarize these effects. A PRS based on a GWAS for plasma docosahexaenoic fatty acid (DHA) has been created, based on SNPs from 9 genes. OBJECTIVE: To analyze the interaction between the PRS for plasma DHA concentration, body composition and eating behaviour (using the Children Eating Behaviour Questionnaire) in childhood. SUBJECTS/ METHODS: We analyzed a subsample of children from the Maternal, Adversity, Vulnerability and Neurodevelopment (MAVAN) cohort with PRS and measurements of eating behaviour performed at 4 years of age (n = 210), 6 y (n = 177), and body fat determined by bioelectric impedance at 4 y and 6 y or by air displacement plethysmography and dual-energy X-ray absorptiometry at 8 y (n = 42 and n = 37). PRS was based on the GWAS from Lemaitre et al. 2011 (p threshold = p < 5*10-6), and a median split created low and high PRS groups (high PRS = higher DHA level). RESULTS: In ALSPAC children, we observed an association between PRS and plasma DHA concentration (β = 0.100, p < 0.01) and proportion (β = 0.107, p < 0.01). In MAVAN, there were interactions between PRS and body fat on pro-intake scores in childhood, in which low PRS and higher body fat were linked to altered behaviour. There were also interactions between PRS and pro-intake scores early in childhood on body fat later in childhood, suggesting that the genetic profile and eating behaviour influence the development of adiposity at later ages. CONCLUSIONS: A lower PRS (lower plasma PUFA) can be a risk factor for developing higher body fat associated with non-adaptive eating behaviour in childhood; it is possible that the higher PRS (higher plasma PUFA) is a protective feature.
BACKGROUND: The relationship between eating behaviour and current body weight has been described. However little is known about the effect of polyunsaturated fatty acids (PUFA) in this relationship. Genetic contribution to a certain condition is derived from a combination of small effects from many genetic variants, and polygenic risk scores (PRS) summarize these effects. A PRS based on a GWAS for plasma docosahexaenoic fatty acid (DHA) has been created, based on SNPs from 9 genes. OBJECTIVE: To analyze the interaction between the PRS for plasma DHA concentration, body composition and eating behaviour (using the Children Eating Behaviour Questionnaire) in childhood. SUBJECTS/ METHODS: We analyzed a subsample of children from the Maternal, Adversity, Vulnerability and Neurodevelopment (MAVAN) cohort with PRS and measurements of eating behaviour performed at 4 years of age (n = 210), 6 y (n = 177), and body fat determined by bioelectric impedance at 4 y and 6 y or by air displacement plethysmography and dual-energy X-ray absorptiometry at 8 y (n = 42 and n = 37). PRS was based on the GWAS from Lemaitre et al. 2011 (p threshold = p < 5*10-6), and a median split created low and high PRS groups (high PRS = higher DHA level). RESULTS: In ALSPAC children, we observed an association between PRS and plasma DHA concentration (β = 0.100, p < 0.01) and proportion (β = 0.107, p < 0.01). In MAVAN, there were interactions between PRS and body fat on pro-intake scores in childhood, in which low PRS and higher body fat were linked to altered behaviour. There were also interactions between PRS and pro-intake scores early in childhood on body fat later in childhood, suggesting that the genetic profile and eating behaviour influence the development of adiposity at later ages. CONCLUSIONS: A lower PRS (lower plasma PUFA) can be a risk factor for developing higher body fat associated with non-adaptive eating behaviour in childhood; it is possible that the higher PRS (higher plasma PUFA) is a protective feature.