Personalized nutrition (PN) has gained much attention as a tool for empowerment of consumers to promote changes in dietary behavior, optimizing health status and preventing diet related diseases. Generalized implementation of PN faces different obstacles, one of the most relevant being metabolic characterization of the individual. Although omics technologies allow for assessment the dynamics of metabolism with unprecedented detail, its translatability as affordable and simple PN protocols is still difficult due to the complexity of metabolic regulation and to different technical and economical constrains. In this work, we propose a conceptual framework that considers the dysregulation of a few overarching processes, namely Carbohydrate metabolism, lipid metabolism, inflammation, oxidative stress and microbiota-derived metabolites, as the basis of the onset of several non-communicable diseases. These processes can be assessed and characterized by specific sets of proteomic, metabolomic and genetic markers that minimize operational constrains and maximize the information obtained at the individual level. Current machine learning and data analysis methodologies allow the development of algorithms to integrate omics and genetic markers. Reduction of dimensionality of variables facilitates the implementation of omics and genetic information in digital tools. This framework is exemplified by presenting the EU-Funded project PREVENTOMICS as a use case.

Background: Carboxylated osteocalcin (Gla‐OC) participates in bone remodeling, whereas the undercarboxylated form (Glu‐OC) takes part in energy metabolism. This study was undertaken to compare the blood levels of Glu‐OC and Gla‐OC in nonobese, healthy obese, and prediabetic volunteers and correlate it with the metabolic markers of insulin resistance and early markers of inflammation.Methods: Nonobese (body mass index [BMI] <30 kg/m²; n = 34) and obese subjects (30 <BMI <40 kg/m²; n = 98), both sexes, aged 25 to 65 years, were divided into healthy control, normal weight subjects, healthy obese, and obese with biochemical markers of prediabetes. The subgroups with obesity and low or high Gla‐OC or Glu‐OC were also considered for statistical analysis. After 2 weeks of diet standardization, venous blood was sampled for the determination of Gla‐OC, Glu‐OC, lipid profile, parameters of inflammation (hsCRP, interleukin 6, sE‐selectin, sPECAM‐1, and monocyte chemoattractant protein 1), and adipokines (leptin, adiponectin, visfatin, and resistin).Results: Gla‐OC in obese patients was significantly lower compared to nonobese ones (11.36 ± 0.39 vs 12.69 ± 0.90 ng/mL, P = .048) and weakly correlated with hsCRP (r = −0.18, P = .042), visfatin concentration (r = −0.19, P = .033), and BMI (r = −0.17, P = .047). Glu‐OC was negatively associated with fasting insulin levels (r = −0.18, P = .049) and reduced in prediabetic individuals compared with healthy obese volunteers (3.04 ± 0.28 vs 4.48 ± 0.57, P = .025).Conclusions: Decreased blood concentration of Glu‐OC may be a selective early symptom of insulin resistance in obesity, whereas the decreased level of Gla‐OC seems to be associated with the appearance of early markers of low grade inflammation accompanying obesity.

Nutrient excess enhances glucose-dependent insulinotropic polypeptide (GIP) secretion, which may in turn contribute to the development of liver steatosis. We hypothesized that elevated GIP levels in obesity may affect markers of liver injury through microRNAs. The study involved 128 subjects (body mass index (BMI) 25–40). Fasting and postprandial GIP, glucose, insulin, and lipids, as well as fasting alanine aminotransferase (ALT), γ-glutamyltransferase (GGT), cytokeratin-18, fibroblast growth factor (FGF)-19, and FGF-21 were determined. TaqMan low density array was used for quantitative analysis of blood microRNAs. Fasting GIP was associated with ALT [β = 0.16 (confidence interval (CI): 0.01–0.32)], triglycerides [β = 0.21 (95% CI: 0.06–0.36], and FGF-21 [β = 0.20 (95%CI: 0.03–0.37)]; and postprandial GIP with GGT [β = 0.17 (95%CI: 0.03–0.32)]. The odds ratio for elevated fatty liver index (>73%) was 2.42 (95%CI: 1.02–5.72) for high GIP versus low GIP patients. The miRNAs profile related to a high GIP plasma level included upregulated miR-136-5p, miR-320a, miR-483-5p, miR-520d-5p, miR-520b, miR-30e-3p, and miR-571. Analysis of the interactions of these microRNAs with gene expression pathways suggests their potential contribution to the regulation of the activity of genes associated with insulin resistance, fatty acids metabolism, and adipocytokines signaling. Exaggerated fasting and postprandial secretion of GIP in obesity are associated with elevated liver damage markers as well as FGF-21 plasma levels. Differentially expressed microRNAs suggest additional, epigenetic factors contributing to the gut–liver cross-talk.

Weight loss contributes to an increased risk of hip fracture, especially in postmenopausal women. Omega-3 polyunsaturated fatty acid (n-3 PUFA) supplementation could diminish the adverse effect of weight loss on bone health. The aim of this randomized, placebo-controlled, double-blind parallel trial was to investigate the effect of caloric restriction and n-3 PUFA supplement intake on osteogenic markers (carboxylated osteocalcin (Gla-OC); procollagen I N-terminal propeptide (PINP)), as well as a bone resorption marker (C-terminal telopeptide of type I collagen (CTX-I)) in a serum of 64 middle aged individuals (BMI 25–40 kg/m²) with abdominal obesity. Bone remodeling, metabolic and inflammatory parameters and adipokines were determined before and after 3 months of an isocaloric diet (2300–2400 kcal/day) or a low-calorie diet (1200 kcal/day for women and 1500 kcal/day for men) along with n-3 PUFA (1.8 g/day) or placebo capsules. CTX-I and adiponectin concentrations were increased following 7% weight loss independently of supplement use. Changes in CTX-I were positively associated with changes in adiponectin level (rho = 0.25, p = 0.043). Thus, an increase in serum adiponectin caused by body weight loss could adversely affect bone health. N-3 PUFAs were without effect.

We hypothesised that epigenetics may play an important role in mediating fibroblast growth factor 21 (FGF21) resistance in obesity. We aimed to evaluate DNA methylation changes and miRNA pattern in obese subjects associated with high serum FGF21 levels. The study included 136 participants with BMI 27–45 kg/m². Fasting FGF21, glucose, insulin, GIP, lipids, adipokines, miokines and cytokines were measured and compared in high serum FGF21 (n = 68) group to low FGF21 (n = 68) group. Human DNA Methylation Microarrays were analysed in leukocytes from each group (n = 16). Expression of miRNAs was evaluated using quantitative PCR-TLDA. The study identified differentially methylated genes in pathways related to glucose transport, insulin secretion and signalling, lipid transport and cellular metabolism, response to nutrient levels, thermogenesis, browning of adipose tissue and bone mineralisation. Additionally, it detected transcription factor genes regulating FGF21 and fibroblast growth factor receptor and vascular endothelial growth factor receptor pathways regulation. Increased expression of hsa-miR-875-5p and decreased expression of hsa-miR-133a-3p, hsa-miR-185-5p and hsa-miR-200c-3p were found in the group with high serum FGF21. These changes were associated with high FGF21, VEGF and low adiponectin serum levels. Our results point to a significant role of the epigenetic regulation of genes involved in metabolic pathways related to FGF21 action.

There is growing interest in the non-invasive identification and monitoring of the outcome of liver damage in obese patients. Plasma cytokeratin-18 (CK-18) fragment levels correlate with the magnitude of hepatocyte apoptosis and have recently been proposed to independently predict the presence of non-alcoholic steatohepatitis (NASH). The aim of the study was to analyze the associations of CK-18 with obesity and related complications: insulin resistance, impaired lipid metabolism and the secretion of hepatokines, adipokines and pro-inflammatory cytokines. The study involved 151 overweight and obese patients (BMI 25–40), without diabetes, dyslipidemia or apparent liver disease. Liver function was assessed based on alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT) and the fatty liver index (FLI). CK-18 M30 plasma levels, FGF-21, FGF-19 and cytokines were determined by ELISA. CK-18 values >150 U/l were accompanied by high ALT, GGT and FLI, insulin resistance, postprandial hypertriglyceridemia, elevated FGF-21 and MCP-1 and decreased adiponectin. ALT activity was the strongest independent factor influencing high CK-18 plasma levels, even after an adjustment for age, sex and BMI [β coefficient (95%CI): 0.40 (0.19–0.61)]. In conclusion, the applied CK-18 cut-off point at 150 U/l allows to distinguish between two metabolic phenotypes in obesity.