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dc.contributor.authorWuni, Ramatues
dc.contributor.authorCuri-Quinto, Katherinees
dc.contributor.authorLiu, Litaies
dc.contributor.authorEspinoza, Dianelaes
dc.contributor.authorAquino, Anthony I.es
dc.contributor.authordel Valle-Mendoza, Juanaes
dc.contributor.authorAguilar-Luis, Miguel Angeles
dc.contributor.authorMurray, Claudiaes
dc.contributor.authorNunes, Richardes
dc.contributor.authorMethven, Lisaes
dc.contributor.authorLovegrove, Julie Annees
dc.contributor.authorPenny, Mary E.es
dc.contributor.authorFavara, Marthaes
dc.contributor.authorSánchez, Alanes
dc.contributor.authorSanthanakrishnan Vimaleswaran, Karanies
dc.date.accessioned2025-10-29T15:13:58Z
dc.date.available2025-10-29T15:13:58Z
dc.date.issued2024-09
dc.identifier.urihttps://hdl.handle.net/20.500.12820/835es
dc.description.abstractBackground & aims: Cardiometabolic traits are complex interrelated traits that result from a combination of genetic and lifestyle factors. This study aimed to assess the interaction between genetic variants and dietary macronutrient intake on cardiometabolic traits [body mass index, waist circumference, total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol, triacylglycerol, systolic blood pressure, diastolic blood pressure, fasting serum glucose, fasting serum insulin, and glycated haemoglobin]. Methods: This cross-sectional study consisted of 468 urban young adults aged 20 ± 1 years, and it was conducted as part of the Study of Obesity, Nutrition, Genes and Social factors (SONGS) project, a substudy of the Young Lives study. Thirty-nine single nucleotide polymorphisms (SNPs) known to be associated with cardiometabolic traits at a genome-wide significance level (P < 5 10 8) were used to construct a genetic risk score (GRS). Results: There were no significant associations between the GRS and any of the cardiometabolic traits. However, a significant interaction was observed between the GRS and carbohydrate intake on HDL-C concentration (Pinteraction ¼ 0.0007). In the first tertile of carbohydrate intake ( 327 g/day), participants with a high GRS (>37 risk alleles) had a higher concentration of HDL-C than those with a low GRS ( 37 risk alleles) [Beta ¼ 0.06 mmol/L, 95 % confidence interval (CI), 0.01e0.10; P ¼ 0.018]. In the third tertile of carbohydrate intake (>452 g/day), participants with a high GRS had a lower concentration of HDL-C than those with a low GRS (Beta¼ 0.04 mmol/L, 95 % CI e0.01 to 0.09; P ¼ 0.027). A significant interaction was also observed between the GRS and glycaemic load (GL) on the concentration of HDL-C.es
dc.description.sponsorshipThis study was funded by the Medical Research Council (grant number MR/S024778/1); PROCIENCIA (CONCYTEC/FONDECYT) (grant number 030-2019); and the UK's Foreign, Commonwealth and Development Office (FCDO) (grant number GB-GOV-1-301108).es
dc.formatapplication/pdfes
dc.language.isospaes
dc.publisherElsevieres
dc.relation.urihttps://hdl.handle.net/20.500.12820/825es
dc.rightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/es
dc.subjectNutriciónes
dc.subjectObesidades
dc.subjectEstudio RIESGOes
dc.titleInteraction between genetic risk score and dietary carbohydrate intake on high-density lipoprotein cholesterol levels: Findings from the study of obesity, nutrition, genes and social factors (SONGS)es
dc.typeinfo:eu-repo/semantics/articlees
dc.subject.ocdehttp://purl.org/pe-repo/ocde/ford#3.03.04es
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.publisher.countryNLes
dc.identifier.doihttps://doi.org/10.1016/j.clnesp.2024.12.027es
dc.relation.isPartOfurn:issn: 24054577es


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