Objectives: Some individuals develop type 2 diabetes mellitus (T2DM) despite significant metabolic improvements through lifestyle intervention. We tested the hypotheses that insulin growth factor 1 (IGF1) and its binding proteins 1 and 2 predict the onset of T2DM in prediabetes patients and determine the capacity for metabolic regeneration. Design: We measured fasting serum IGF1, insulin growth factor-binding protein 1 (IGFBP1) and IGFBP2 in three randomized controlled lifestyle intervention trials, covering at least 1 year of intervention period and 1 year of additional follow-up. Methods: Within a sample of 414 high-risk prediabetes patients (58% women; 28–80 years), we analyzed fasting serum concentrations of IGF1, IGFBP1 and IGFBP2 in relation to diabetes incidence and metabolic parameters over 2 years. Three hundred and forty-five subjects finished the first year of intervention. Results: The interventions significantly improved body weight (BMI: −3.24%, P < 0.001), liver fat (−36.8%, P < 0.001), insulin sensitivity (IS) (homeostatic model assessment-insulin resistance: −6.3%, P < 0.001) and insulin secretion (disposition index: +35%, P < 0.001) in the cohort. Fourteen percent developed T2DM within 2 years. Mean IGFBP1 levels at baseline were lower in prediabetes compared to a healthy population. Also, prediabetes patients with obesity and nonalcoholic fatty liver disease had lower IGFBP1. Those with impaired glucose tolerance had higher IGFBP1 compared to those with only impaired fasting glucose. Baseline IGF1 was lower (122.5 vs 146.6 µg/L) and IGFBP1 was higher (3.32 vs 2.09 µg/L) in subjects who developed T2DM (n = 57), resulting in a significant prediction of diabetes incidence (hazard ratio (HR) IGF1: 0.991 µg/L, P = 0.003; HR IGFBP1: 1.061 µg/L, P = 0.002). This translates into a 20% and 9% difference in T2DM incidence for IGF1 and IGFBP1, respectively. Despite reduced weight, visceral fat and hepatic fat in response to 1 year of lifestyle intervention, those who developed T2DM had not improved insulin sensitivity, glucose tolerance or IGFBP1. Conclusions: Lower IGF1 and higher IGFBP1 in prediabetes predicted the incidence of T2DM, indicating an impairment of beta-cell function, which explains the unresponsiveness to lifestyle intervention.

We assessed the effect of a dietary pattern rich in unsaturated fatty acids (UFA), protein and fibers, without emphasizing energy restriction, on visceral adipose tissue (VAT) and cardiometabolic risk profile. Within the 36-months randomized controlled NutriAct trial, we randomly assigned 502 participants (50–80 years) to an intervention or control group (IG, CG). The dietary pattern of the IG includes high intake of mono-/polyunsaturated fatty acids (MUFA/PUFA 15–20% E/10–15% E), predominantly plant protein (15–25% E) and fiber (≥30 g/day). The CG followed usual care with intake of 30% E fat, 55% E carbohydrates and 15% E protein. Here, we analyzed VAT in a subgroup of 300 participants via MRI at baseline and after 12 months, and performed further metabolic phenotyping. A small but comparable BMI reduction was seen in both groups (mean difference IG vs. CG: −0.216 kg/m² [−0.477; 0.045], partial η² = 0.009, p = 0.105). VAT significantly decreased in the IG but remained unchanged in the CG (mean difference IG vs. CG: −0.162 L [−0.314; −0.011], partial η² = 0.015, p = 0.036). Change in VAT was mediated by an increase in PUFA intake (ß = −0.03, p = 0.005) and induced a decline in LDL cholesterol (ß = 0.11, p = 0.038). The NutriAct dietary pattern, particularly due to high PUFA content, effectively reduces VAT and cardiometabolic risk markers, independent of body weight loss.

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.

Despite beneficial cardiovascular effects, substantial long-term modulation of food pattern could only be achieved in a limited number of participants. The impact of attitude towards healthy nutrition (ATHN) on successful modulation of dietary behavior is unclear, especially in the elderly. We aimed to analyze whether the personal ATHN influences 12-month adherence to two different dietary intervention regimes within a 36-month randomized controlled trial. Methods: 502 subjects were randomized to an intervention group (IG; dietary pattern focused on high intake of unsaturated fatty acids (UFA), plant protein and fiber) or control group (CG; dietary recommendation in accordance with the German Society of Nutrition) within a 36-month dietary intervention trial. Sum scores for effectiveness, appreciation and practice of healthy nutrition were assessed using ATHN questionnaire during the trial (n = 344). Linear regression models were used to investigate associations between ATHN and dietary patterns at baseline and at month 12. Results: Retirement, higher education level, age and lower body mass index (BMI) were associated with higher ATHN sum scores. ATHN was similar in CG and IG. Higher baseline intake of polyunsaturated fatty acids (PUFA) and fiber as well as lower intake in saturated fatty acids (SFA) were associated with higher scores in practice in both groups. The intervention resulted in a stronger increase of UFA, protein and fiber in the IG after 12 months, while intake of SFA declined (p < 0.01). Higher scores in appreciation were significantly associated with higher intake of fiber and lower intake of SFA in the CG at month 12, whereas no associations between ATHN and macronutrient intake were observed in the IG after 12 months. Conclusions: While ATHN appeared to play a role in general dietary behavior, ATHN did not affect the success of the specific dietary intervention in the IG at month 12. Thus, the dietary intervention achieved a substantial modification of dietary pattern in the IG and was effective to override the impact of the individual ATHN on dietary behavior.

Background: T2DM heterogeneity affects responsiveness to lifestyle treatment. Beta-cell failure and nonalcoholic fatty liver disease (NAFLD) independently predict T2DM, but NAFLD inconsistently predicts metabolic response to lifestyle intervention. Aim: We attempt to replicate a prediction model deducted from the Tübinger Lifestyle Intervention Program by assessing similar metabolic factors to predict conversion to normal glucose regulation (NGR) in a comparable lifestyle intervention trial. Methods: In the Optimal Fiber Trial (OptiFiT), 131 Caucasian participants with prediabetes completed a one-year lifestyle intervention program and received a fiber or placebo supplement. We compared baseline parameters for responders and non-responders, assessed correlations of major metabolic changes and conducted a logistic regression analysis for predictors of remission to NGR. Results: NGR was achieved by 33 participants, respectively. At baseline, for the placebo group only, 1 h and 2 h glucose levels, glucose AUC and Cederholm index predicted conversion to NGR. HOMA-beta, HOMA-IR or liver fat indices did not differ between responders and non-responders of the placebo or the fiber group. Changes in waist circumference or fatty liver index correlated with changes in glycemia and insulin resistance, but not with changes in insulin secretion. Insulin-resistant NAFLD did not predict non-response. Differences in compliance did not explain the results. Conclusions: Higher post-challenge glucose levels strongly predicted the metabolic non-response to complex lifestyle intervention in our cohort. Depending on the specific intervention and the investigated cohort, fasting glucose levels and insulin sensitivity might contribute to the risk pattern. Beta-cell function did not improve in accordance with other metabolic improvements, qualifying as a potential risk factor for non-response. We could not replicate previous data suggesting that an insulin-resistant fatty liver is a specific risk factor for treatment failure. Replication studies are required.