Huntington disease is a neurodegenerative condition for which there is no cure to date. Activation of AMP-activated protein kinase has previously been shown to be beneficial in in vitro and in vivo models of Huntington’s disease. Moreover, a recent cross-sectional study demonstrated that treatment with metformin, a well-known activator of this enzyme, is associated with better cognitive scores in patients with this disease. We performed a preclinical study using metformin to treat phenotypes of the zQ175 mouse model of Huntington disease. We evaluated behavior (motor and neuropsychiatric function) and molecular phenotypes (aggregation of mutant huntingtin, levels of brain-derived neurotrophic factor, neuronal inflammation, etc.). We also used two models of polyglutamine toxicity in Caenorhabditis elegans to further explore potential mechanisms of metformin action. Our results provide strong evidence that metformin alleviates motor and neuropsychiatric phenotypes in zQ175 mice. Moreover, metformin intake reduces the number of nuclear aggregates of mutant huntingtin in the striatum. The expression of brain-derived neurotrophic factor, which is reduced in mutant animals, is partially restored in metformin-treated mice, and glial activation in mutant mice is reduced in metformin-treated animals. In addition, using worm models of polyglutamine toxicity, we demonstrate that metformin reduces polyglutamine aggregates and restores neuronal function through mechanisms involving AMP-activated protein kinase and lysosomal function. Our data indicate that metformin alleviates the progression of the disease and further supports AMP-activated protein kinase as a druggable target against Huntington’s disease.

Background: Alzheimer Disease (AD) is the most prevalent dementia. However, the physiopathological mechanisms involved in its development are unclear. In this sense, a multi-omics approach could provide some progress. Methods: Epigenomic and lipidomic analysis were carried out in plasma samples from patients with mild cognitive impairment (MCI) due to AD (n = 22), and healthy controls (n = 5). Then, omics integration between microRNAs (miRNAs) and lipids was performed by Sparse Partial Least Squares (s-PLS) regression and target genes for the selected miRNAs were identified. Results: 25 miRNAs and 25 lipids with higher loadings in the sPLS regression were selected. Lipids from phosphatidylethanolamines (PE), lysophosphatidylcholines (LPC), ceramides, phosphatidylcholines (PC), triglycerides (TG) and several long chain fatty acids families were identified as differentially expressed in AD. Among them, several fatty acids showed strong positive correlations with miRNAs studied. In fact, these miRNAs regulated genes implied in fatty acids metabolism, as elongation of very long-chain fatty acids (ELOVL), and fatty acid desaturases (FADs). Conclusions: The lipidomic–epigenomic integration showed that several lipids and miRNAs were differentially expressed in AD, being the fatty acids mechanisms potentially involved in the disease development. However, further work about targeted analysis should be carried out in a larger cohort, in order to validate these preliminary results and study the proposed pathways in detail.

Objective: The aim of this work was to compare the accuracy of the cerebroplacental ratio (CPR), Intergrowth 21st standards (IG21), customized growth (CG), and local population references (LPR) in the prediction of intrapartum fetal compromise (IFC). Methods: This was a prospective study of 714 fetuses that underwent an ultrasound examination at 34–41 weeks and were delivered within a 2-week interval. The CPR was converted into multiples of the median and the estimated fetal weight (EFW) transformed into CG, IG21, and LPR centiles. IFC was defined as a composite of abnormal cardiotocogram, intrapartum pH requiring cesarean section, 5-min Apgar score, and admission to pediatric care units. The accuracies of the CPR and the EFW centiles for the prediction of IFC were evaluated alone and in combination with other gestational characteristics using univariate and multivariate analysis. Results: Individually, the CPR was the parameter that best predicted the existence of IFC (AUC = 0.66). The multivariate analysis showed that the best prediction was again achieved with the CPR, alone or in combination with any of the EFW centiles (AUC = 0.74). No significant differences were seen between the different centile methods. Conclusion: The best prediction of IFC is obtained with CPR. Evaluation of CPR should be encouraged in term and late-preterm fetuses.

Objective: To evaluate whether the addition of the mean uterine arteries pulsatility index (mUtA PI) to the cerebroplacental ratio (CPR) improves its ability to predict adverse perinatal outcome (APO) at the end of pregnancy. Methods: This was a prospective study of 891 fetuses that underwent an ultrasound examination at 34–41 weeks. The CPR and the mUtA PI were converted into multiples of the median (MoM) and the estimated fetal weight (EFW) into centiles according to local references. APO was defined as a composite of abnormal cardiotocogram, intrapartum pH requiring cesarean section, 5′ Apgar score <7, neonatal pH <7.10 and admission to pediatric care units. The accuracies of the different parameters were evaluated alone and in combination with gestational characteristics using univariate and multivariate analyses by means of the Akaike Information Criteria (AIC) and the area under the curve (AUC). Finally, a comparison was similarly performed between the CPR and the cerebro-placental-uterine ratio (CPUR; CPR/mUtA PI) for the prediction of APO. Results: The univariate analysis showed that CPR MoM was the best parameter predicting APO (AIC 615.71, AUC 0.675). The multivariate analysis including clinical data showed that the best prediction was also achieved with the CPR MoM (AIC 599.39, AUC 0.718). Moreover, when EFW centiles were considered, the addition of UtA PI MoM did not improve the prediction already obtained with CPR MoM (AIC 591.36, AUC 0.729 vs. AIC 589.86, AUC 0.731). Finally, the prediction by means of CPUR did not improve that of CPR alone (AIC 623.38, AUC 0.674 vs. AIC 623.27, AUC 0.66). Conclusion: The best prediction of APO at the end of pregnancy is obtained with CPR whatever is the combination of parameters. The addition of uterine Doppler to the information yielded by CPR does not result in any prediction improvement.