title: Effects of Two Different Dietary Patterns on Inflammatory Markers, Advanced Glycation End Products and Lipids in Subjects without Type 2 Diabetes: A Randomised Crossover Study.
abstract: Epidemiological studies suggest that consumption of red and processed meat and refined grains are associated with type 2 diabetes and metabolic syndrome and increased inflammatory and fibrinolytic markers. We hypothesised that a diet high in red and processed meat and refined grains (HMD) would increase inflammatory markers and advanced glycation end products (AGEs) compared with a diet high in dairy, whole grains, nuts and legumes (HWD). We performed a randomised crossover study of two four-week interventions in 51 participants without type 2 diabetes (15 men and 36 women aged 35.1 ± 15.6 years; body mass index: 27.7 ± 6.9 kg/m²). No baseline measurements were performed. Plasma fluorescent AGEs, carboxymethyllysine, glucose, insulin, lipids, hs-CRP, interleukin 6 (IL-6) and plasminogen activator inhibitor-1 (PAI-1) were analysed after four weeks on each diet. IL-6, hs-CRP, AGEs and carboxymethyllysine were not different between diets but PAI-1 was higher after the HMD than after HWD ((median and interquartile range) 158, 81 vs. 121, 53 ng/mLp< 0.001). PAI-1 on the HWD diet was inversely correlated with whole grains intake (p= 0.007). PAI-1 was inversely correlated with insulin sensitivity index (r = -0.45;p= 0.001) and positively correlated with serum total cholesterol (r = 0.35;p= 0.012) and serum triglyceride (r = 0.32;p= 0.021) on HMD. This trial was registered with the Australian New Zealand Clinical Trials Registry (ACTRN12614000519651).
authors.affiliation: School of Pharmacy and Medical Sciences, University of South Australia, Adelaide SA 5001, Australia. yoona.kim@mymail.unisa.edu.au.
authors.forename: Yoona
authors.initials: Y
authors.lastname: Kim
authors.affiliation: School of Pharmacy and Medical Sciences, University of South Australia, Adelaide SA 5001, Australia. Jennifer.Keogh@unisa.edu.au.
authors.forename: Jennifer B
authors.initials: JB
authors.lastname: Keogh
authors.affiliation: School of Pharmacy and Medical Sciences, University of South Australia, Adelaide SA 5001, Australia. peter.clifton@unisa.edu.au.
authors.forename: Peter M
authors.initials: PM
authors.lastname: Clifton
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000097:blood; D002784:Cholesterol / Q000097:blood; D018592:Cross-Over Studies; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000517:prevention & control*; D000072001:Diet, Healthy; D066273:Diet, Western; D005247:Feeding Behavior; D005260:Female; D005511:Food Handling; D017127:Glycation End Products, Advanced / Q000097:blood*; D006801:Humans; D007249:Inflammation / Q000097:blood / Q000209:etiology*; D007333:Insulin Resistance; D008055:Lipids / Q000097:blood*; D008239:Lysine / Q000031:analogs & derivatives / Q000097:blood; D008297:Male; D008875:Middle Aged; D015849:Plasminogen Inactivators / Q000097:blood; D012016:Reference Values; D014280:Triglycerides / Q000097:blood; D055815:Young Adult
chemical_list: D015415:Biomarkers; D017127:Glycation End Products, Advanced; D008055:Lipids; D015849:Plasminogen Inactivators; D014280:Triglycerides; C048496:N(6)-carboxymethyllysine; D002784:Cholesterol; D008239:Lysine
keywords: advanced glycation products; dietary pattern; insulin sensitivity; plasminogen activator inhibitor type 1