RESUMO
Lifestyle interventions can prevent type 2 diabetes (T2DM). However, some individuals do not experience anticipated improvements despite weight loss. Biomarkers to identify such individuals at early stages are lacking. Insulin-like growth factor 1 (IGF- 1) and Insulin-like growth factor binding protein 1(IGFBP-1) were shown to predict T2DM onset in prediabetes. We assessed whether these markers also predict the success of lifestyle interventions, thereby possibly guiding personalized strategies. We analyzed the fasting serum levels of IGF-1, IGFBP-1, and Insulin-like growth factor binding protein 2 (IGFBP-2) in relation to changes in metabolic and anthropometric parameters, including intrahepatic lipids (IHLs) and visceral adipose tissue (VAT) volume, measured by magnetic resonance imaging (MRI), in 345 participants with a high risk for prediabetes (54% female; aged 36-80 years). Participants were enrolled in three randomized dietary intervention trials and assessed both at baseline and one year post-intervention. Statistical analyses were performed using IBM SPSS Statistics (version 28), and significance was set at p < 0.05. Within the 1-year intervention, overall significant improvements were observed. Stratifying individuals by baseline IGF-1 and IGFBP-1 percentiles revealed significant differences: higher IGF-1 levels were associated with more favorable changes compared to lower levels, especially in VAT and IHL. Lower baseline IGFBP-1 levels were associated with greater improvements, especially in IHL and 2 h glucose. Higher bioactive IGF-1 levels might predict better metabolic outcomes following lifestyle interventions in prediabetes, potentially serving as biomarkers for personalized interventions.
Assuntos
Biomarcadores , Diabetes Mellitus Tipo 2 , Proteína 1 de Ligação a Fator de Crescimento Semelhante à Insulina , Fator de Crescimento Insulin-Like I , Estilo de Vida , Humanos , Feminino , Masculino , Proteína 1 de Ligação a Fator de Crescimento Semelhante à Insulina/sangue , Pessoa de Meia-Idade , Fator de Crescimento Insulin-Like I/metabolismo , Fator de Crescimento Insulin-Like I/análise , Idoso , Adulto , Diabetes Mellitus Tipo 2/sangue , Biomarcadores/sangue , Idoso de 80 Anos ou mais , Estado Pré-Diabético/sangue , Estado Pré-Diabético/terapia , Gordura Intra-Abdominal/metabolismo , Proteína 2 de Ligação a Fator de Crescimento Semelhante à Insulina/sangueRESUMO
Aging is associated with a decline in physiological functions and an increased risk of age-related diseases, emphasizing the importance of identifying dietary strategies for healthy aging. Minerals play a crucial role in maintaining optimal health during aging, making them relevant targets for investigation. Therefore, we aimed to analyze the effect of different dietary pattern on mineral status in the elderly. We included 502 individuals aged 50-80 years in a 36-month randomized controlled trial (RCT) (NutriAct study). This article focuses on the results within the two-year intervention period. NutriAct is not a mineral-modulating-targeted intervention study, rather examining nutrition in the context of healthy aging in general. However, mineral status might be affected in an incidental manner. Participants were assigned to either NutriAct dietary pattern (proportionate intake of total energy consumption (%E) of 35-45â¯%E carbohydrates, 35-40â¯%E fats, and 15-25â¯%E protein) or the German Nutrition Society (DGE) dietary pattern (proportionate intake of total energy consumption (%E) of 55â¯%E carbohydrates, 30â¯%E fats, and 15â¯%E protein), differing in the composition of macronutrients. Data from 368 participants regarding dietary intake (energy, calcium, magnesium, iron, and zinc) and serum mineral concentrations of calcium, magnesium, iron, copper, zinc, selenium, iodine, and manganese, free zinc, and selenoprotein P were analyzed at baseline, as well as after 12 and 24 months to gain comprehensive insight into the characteristics of the mineral status. Additionally, inflammatory status - sensitive to changes in mineral status - was assessed by measurement of C-reactive protein and interleukin-6. At baseline, inadequate dietary mineral intake and low serum concentrations of zinc and selenium were observed in both dietary patterns. Throughout two years, serum zinc concentrations decreased, while an increase of serum selenium, manganese and magnesium concentrations was observable, likely influenced by both dietary interventions. No significant changes were observed for serum calcium, iron, copper, or iodine concentrations. In conclusion, long-term dietary interventions can influence serum mineral concentrations in a middle-aged population. Our findings provide valuable insights into the associations between dietary habits, mineral status, and disease, contributing to dietary strategies for healthy aging.