Phenylketonuria (PKU) is an autosomal recessive inborn error of metabolism where high phenylalanine (Phe) concentrations cause irreversible intellectual disability that can be prevented by newborn screening and early treatment. Evidence suggests that PKU subjects not adherent to treatment could be at risk of insulin resistance (IR). We studied how Phe concentrations (PheCs) relate to IR using machine learning (ML) and derived potential biomarkers. In our cross-sectional study, we analyzed subjects with neonatal diagnoses of PKU, grouped as follows: 10 subjects who adhered to treatment (G1); 14 subjects who suspended treatment (G2); and 24 control subjects (G3). We analyzed plasma biochemical variables, as well as profiles of amino acids and acylcarnitines in dried blood spots (DBSs). Higher PheCs and plasma insulin levels were observed in the G2 group compared to the other groups. Additionally, a positive correlation between the PheCs and homeostatic measurement assessments (HOMA-IRs) was found, as well as a negative correlation between the HOMA-Sensitivity (%) and quantitative insulin sensitivity check index (QUICKI) scores. An ML model was then trained to predict abnormal HOMA-IRs using the panel of metabolites measured from DBSs. Notably, ranking the features’ importance placed PheCs as the second most important feature after BMI for predicting abnormal HOMA-IRs. Our results indicate that low adherence to PKU treatment could affect insulin signaling, decrease glucose utilization, and lead to IR.

Treatment and follow-up in Hereditary Tyrosinemia type 1 (HT-1) patients require comprehensive clinical and dietary management, which involves drug therapy with NTBC and the laboratory monitoring of parameters, including NTBC levels, succinylacetone (SA), amino acids, and various biomarkers of liver and kidney function. Good adherence to treatment and optimal adjustment of the NTBC dose, according to clinical manifestations and laboratory parameters, can prevent severe liver complications such as hepatocarcinogenesis (HCC). We analyzed several laboratory parameters for 15 HT-1 patients over one year of follow-up in a cohort that included long-term NTBC-treated patients (more than 20 years), as well as short-term patients (one year). Based on this analysis, we described the overall adherence by our cohort of 70% adherence to drug and dietary treatment. A positive correlation was found between blood and plasma NTBC concentration with a conversion factor of 2.57. Nonetheless, there was no correlation of the NTBC level with SA levels, αFP, liver biomarkers, and amino acids in paired samples analysis. By separating according to the range of the NTBC concentration, we therefore determined the mean concentration of each biochemical marker, for NTBC ranges above 15–25 μmol/L. SA in urine and αFP showed mean levels within controlled parameters in our group of patients. Future studies analyzing a longer follow-up period, as well as SA determination in the blood, are encouraged to confirm the present findings.

Hepatocellular carcinoma (HCC) is a major complication of tyrosinemia type 1 (HT-1), an inborn error of metabolism affecting tyrosine catabolism. The risk of HCC is higher in late diagnoses despite treatment. Alpha-fetoprotein (AFP) is widely used to detect liver cancer but has limitations in early-stage HCC detection. This study aimed to implement a machine-learning (ML) approach to identify the most relevant laboratory variables to predict AFP alteration using constrained multidimensional data from Chilean and Italian HT-1 cohorts. A longitudinal retrospective study analyzed 219 records from 35 HT-1 patients, including 8 with HCC and 5 diagnosed through newborn screening. The dataset contained biochemical and demographic variables that were analyzed using the eXtreme Gradient Boosting algorithm, which was trained to predict abnormal AFP levels (>5 ng/mL). Four key variables emerged as significant predictors: alanine transaminase (ALT), alkaline phosphatase, age at diagnosis, and current age. ALT emerged as the most promising indicator of AFP alteration, potentially preceding AFP level changes and improving HCC detection specificity at a cut-off value of 29 UI/L (AUROC = 0.73). Despite limited data from this rare disease, the ML approach successfully analyzed follow-up biomarkers, identifying ALT as an early predictor of AFP elevation and a potential biomarker for HCC progression.

The association between dietary fiber and phenolic compounds allows the latter to reach the colon, where most polysaccharides undergo fermentation. This bioprocessing weakens the matrix and promotes the release of the phenolic compounds, which then exert beneficial effects on intestinal function. Although this notion is widely accepted, supporting evidence remains scarce. In this study, we subjected grape pomace skin to in vitro digestion to obtain an indigestible fraction suitable for SHIME bioreactors. Throughout these stages, we observed a sequential increase in the release of phenolic compounds, with colonic fermentation playing an important role. Although we did not observe an increase in short-chain fatty acid (SCFA) production by the gut microbiota, we performed a repeated-challenge design on differentiated Caco-2 monolayers. With this approach, we found that the phenolic-rich ferment prevented the transepithelial electrical resistance (TEER) drop on the second challenge and modulated the transcriptomic profile assessed by RNA-seq. Our findings indicate that the Caco-2 cellular responses mentioned above were SCFA-independent and likely due to the differential impact of phenolic compound load after colonic fermentation of grape pomace skin.

Dietary fiber usually comes associated with phenolic compounds either trapped in a network formed by indigestible polysaccharides or, in some cases, bound to this matrix by covalent bonds. This natural association protects some phenolic compounds during their journey through the gastrointestinal tract, reaching the colon, where most polysaccharides undergo fermentation, weakening the matrix and promoting the release of these compounds to exert benefits by modulating intestinal function. Unfortunately, there are still difficulties in investigating the impact of the human microbiota on the release of phenolic compounds from the indigestible fraction and on their effects on the intestinal epithelium. In this study, grape pomace skin was subjected to in vitro digestion to obtain an indigestible fraction, which was further incorporated into SHIME bioreactors with human colonic microbiota. Throughout these stages, we monitored the release of phenolic compounds using HPLC-DAD. We determined the impact of a phenolic-rich indigestible fraction on the fermentative capacity of human microbiota by measuring the short-chain fatty acids (SCFA) levels and the effect of the resulting colonic ferments on the barrier properties of differentiated monolayers of Caco-2 cells by monitoring the transepithelial electrical resistance and the transcriptomic profile by RNA sequencing. Our results indicated that digestive processing sequentially increases the release of phenolic compounds and that colonic fermentation releases even more phenolic compounds trapped in the polysaccharide network. Unexpectedly, neither the phenolic-rich nor the depleted fractions increased SCFA levels in the colonic microbiota. Despite the lack of effect on the microbial community, the phenolic-rich ferments had a positive impact in the manner that monolayers of Caco-2 cells adapted better to repeated exposures with the ferments compared with phenolic-depleted ferments. In addition to his subtle difference, Caco-2 cells exposed to phenolic-rich ferments showed a remarkable increase in proteins associated with tight junctions, like claudin-3, -4, -15 and − 19, other proteins that connect the cytoskeleton with tight junctions, such as VASP (Ena/vasodilator-stimulated phosphoprotein) and CGNL1 (cingulin), supporting the idea that phenolic-rich ferments strengthened intercellular communication. In addition to this finding, we observed significant decreases in the transcription of genes encoding apical ion channels, such as CFTR, and the basolateral Na ⁺ /K ⁺ /Cl ⁻ cotransporter, both of which are relevant to intestinal chloride secretion and therefore may reduce fluid loss by the gut. In conclusion, our data support the positive impact of a subset of phenolic compounds that reach the colon, independent of SCFA levels. To achieve this finding in a biologically relevant context, we had to process grape pomace through physiological processes of digestion and fermentation. The latter stage was performed in a realistic colonic environment with human microbiota. The transcriptomic profile induced by the phenolic-rich ferments was observed following repeated exposures, a characteristic that warrants exploration of experimental designs to simulate dietary habits.