Efficacy and tolerability of vigabatrin in West syndrome

West syndrome (WS) is a severe epileptic encephalopathy of childhood, characterized by spasms, developmental deterioration and hipsarhythymia. Objective: To evaluate the safety and efficacy of vigabatrin (VGB) in the treatment of WS. Method: We evaluated every patient diagnosed with WS seen at the pediatric epilepsy clinic and exposed to VGB. Patients were interviewed according to a semistructured questionnaire and we analyzed gender, age, etiology (cryptogenic or symptomatic), associated diseases, age of seizure onset, neuroimaging findings, EEG prior and after VGB, use of other antiepileptic drugs, time for seizure control, electroretinogram, visual complaints, adverse events and family history of epilepsy. Results: Twenty-three patients were evaluated, 16 boys, ages ranging from 1.25 years to 11.5 years (mean=5y3m). Sixteen (69.5%) patients were seizure free, five (22%) had partial seizure control and in two (8.5%) there was no improvement. Only one patient presented gabaergic retinopathy. Six (26%) patients presented adverse events: somnolence, aggressivity or retinopathy. Patients with seizure onset after 6 months of age presented better results after VGB introduction (p 0.05). After VGB, no patient presented hipsarrhythymia and 50% had a normal EEG. Conclusion: Although VGB may be associated with serious adverse events such as gabaergic retinopathy, our results show that it should be considered in the treatment of WS.632B46947

Genome-wide association study of Alzheimer's disease

In addition to apolipoprotein E (APOE), recent large genome-wide association studies (GWASs) have identified nine other genes/loci (CR1, BIN1, CLU, PICALM, MS4A4/MS4A6E, CD2AP, CD33, EPHA1 and ABCA7) for late-onset Alzheimer's disease (LOAD). However, the genetic effect attributable to known loci is about 50%, indicating that additional risk genes for LOAD remain to be identified. In this study, we have used a new GWAS data set from the University of Pittsburgh (1291 cases and 938 controls) to examine in detail the recently implicated nine new regions with Alzheimer's disease (AD) risk, and also performed a meta-analysis utilizing the top 1% GWAS single-nucleotide polymorphisms (SNPs) with P<0.01 along with four independent data sets (2727 cases and 3336 controls) for these SNPs in an effort to identify new AD loci. The new GWAS data were generated on the Illumina Omni1-Quad chip and imputed at ∼2.5 million markers. As expected, several markers in the APOE regions showed genome-wide significant associations in the Pittsburg sample. While we observed nominal significant associations (P<0.05) either within or adjacent to five genes (PICALM, BIN1, ABCA7, MS4A4/MS4A6E and EPHA1), significant signals were observed 69–180 kb outside of the remaining four genes (CD33, CLU, CD2AP and CR1). Meta-analysis on the top 1% SNPs revealed a suggestive novel association in the PPP1R3B gene (top SNP rs3848140 with P=3.05E–07). The association of this SNP with AD risk was consistent in all five samples with a meta-analysis odds ratio of 2.43. This is a potential candidate gene for AD as this is expressed in the brain and is involved in lipid metabolism. These findings need to be confirmed in additional samples

TYROBP genetic variants in early-onset Alzheimer's disease

We aimed to identify new candidate genes potentially involved in early-onset Alzheimer's disease (EOAD). Exome sequencing was conducted on 45 EOAD patients with either a family history of Alzheimer's disease (AD, <65 years) or an extremely early age at the onset (≤55 years) followed by multiple variant filtering according to different modes of inheritance. We identified 29 candidate genes potentially involved in EOAD, of which the gene TYROBP, previously implicated in AD, was selected for genetic and functional follow-up. Using 3 patient cohorts, we observed rare coding TYROBP variants in 9 out of 1110 EOAD patients, whereas no such variants were detected in 1826 controls (p = 0.0001), suggesting that at least some rare TYROBP variants might contribute to EOAD risk. Overexpression of the p.D50_L51ins14 TYROBP mutant led to a profound reduction of TREM2 expression, a well-established risk factor for AD. This is the first study supporting a role for genetic variation in TYROBP in EOAD, with in vitro support for a functional effect of the p.D50_L51ins14 TYROBP mutation on TREM2 expression

β-globin haplotypes in normal and hemoglobinopathic individuals from Reconcavo Baiano, State of Bahia, Brazil

Five restriction site polymorphisms in the β-globin gene cluster (HincII-5‘ ε, HindIII-G γ, HindIII-A γ, HincII- ψβ1 and HincII-3‘ ψβ1) were analyzed in three populations (n = 114) from Reconcavo Baiano, State of Bahia, Brazil. The groups included two urban populations from the towns of Cachoeira and Maragojipe and one rural Afro-descendant population, known as the “quilombo community”, from Cachoeira municipality. The number of haplotypes found in the populations ranged from 10 to 13, which indicated higher diversity than in the parental populations. The haplotypes 2 (+ - - - -), 3 (- - - - +), 4 (- + - - +) and 6 (- + + - +) on the βA chromosomes were the most common, and two haplotypes, 9 (- + + + +) and 14 (+ + - - +), were found exclusively in the Maragojipe population. The other haplotypes (1, 5, 9, 11, 12, 13, 14 and 16) had lower frequencies. Restriction site analysis and the derived haplotypes indicated homogeneity among the populations. Thirty-two individuals with hemoglobinopathies (17 sickle cell disease, 12 HbSC disease and 3 HbCC disease) were also analyzed. The haplotype frequencies of these patients differed significantly from those of the general population. In the sickle cell disease subgroup, the predominant haplotypes were BEN (Benin) and CAR (Central African Republic), with frequencies of 52.9% and 32.4%, respectively. The high frequency of the BEN haplotype agreed with the historical origin of the afro-descendant population in the state of Bahia. However, this frequency differed from that of Salvador, the state capital, where the CAR and BEN haplotypes have similar frequencies, probably as a consequence of domestic slave trade and subsequent internal migrations to other regions of Brazil

STC1 and PTHrP modify carbohydrate and lipid metabolism in liver of a teleost fish

Stanniocalcin 1 (STC1) and parathyroid hormone-related protein (PTHrP) are calciotropic hormones in vertebrates. Here, a recently hypothesized metabolic role for these hormones is tested on European sea bass treated with: (i) teleost PTHrP(1-34), (ii) PTHrP(1-34) and anti-STC1 serum (pro-PTHrP groups), (iii) a PTHrP antagonist PTHrP(7-34) or (iv) PTHrP(7-34) and STC1 (pro-STC1 groups). Livers were analysed using untargeted metabolic profiling based on proton nuclear magnetic resonance (1H-NMR) spectroscopy. Concentrations of branched-chain amino acid (BCAA), alanine, glutamine and glutamate increased in pro-STC1 groups suggesting their mobilization from the muscle to the liver for degradation and gluconeogenesis from alanine and glutamine. In addition, only STC1 treatment decreased the concentrations of succinate, fumarate and acetate, indicating slowing of the citric acid cycle. In the pro-PTHrP groups the concentrations of glucose, erythritol and lactate decreased, indicative of gluconeogenesis from lactate. Taurine, trimethylamine, trimethylamine N-oxide and carnitine changed in opposite directions in the pro-STC1 versus the pro-PTHrP groups, suggesting opposite effects, with STC1 stimulating lipogenesis and PTHrP activating lipolysis/β-oxidation of fatty acids. These findings suggest a role for STC1 and PTHrP related to strategic energy mechanisms that involve the production of glucose and safeguard of liver glycogen reserves for stressful situations.Portuguese Foundation for Science and Technology (FCT) SFRH/BD/103185/2014info:eu-repo/semantics/publishedVersio

Neuropsychological predictors of conversion from mild cognitive impairment to Alzheimer’s disease: a feature selection ensemble combining stability and predictability

Background Predicting progression from Mild Cognitive Impairment (MCI) to Alzheimer’s Disease (AD) is an utmost open issue in AD-related research. Neuropsychological assessment has proven to be useful in identifying MCI patients who are likely to convert to dementia. However, the large battery of neuropsychological tests (NPTs) performed in clinical practice and the limited number of training examples are challenge to machine learning when learning prognostic models. In this context, it is paramount to pursue approaches that effectively seek for reduced sets of relevant features. Subsets of NPTs from which prognostic models can be learnt should not only be good predictors, but also stable, promoting generalizable and explainable models. Methods We propose a feature selection (FS) ensemble combining stability and predictability to choose the most relevant NPTs for prognostic prediction in AD. First, we combine the outcome of multiple (filter and embedded) FS methods. Then, we use a wrapper-based approach optimizing both stability and predictability to compute the number of selected features. We use two large prospective studies (ADNI and the Portuguese Cognitive Complaints Cohort, CCC) to evaluate the approach and assess the predictive value of a large number of NPTs. Results The best subsets of features include approximately 30 and 20 (from the original 79 and 40) features, for ADNI and CCC data, respectively, yielding stability above 0.89 and 0.95, and AUC above 0.87 and 0.82. Most NPTs learnt using the proposed feature selection ensemble have been identified in the literature as strong predictors of conversion from MCI to AD. Conclusions The FS ensemble approach was able to 1) identify subsets of stable and relevant predictors from a consensus of multiple FS methods using baseline NPTs and 2) learn reliable prognostic models of conversion from MCI to AD using these subsets of features. The machine learning models learnt from these features outperformed the models trained without FS and achieved competitive results when compared to commonly used FS algorithms. Furthermore, the selected features are derived from a consensus of methods thus being more robust, while releasing users from choosing the most appropriate FS method to be used in their classification task.PTDC/EEI-SII/1937/2014; SFRH/BD/95846/2013; SFRH/BD/118872/2016info:eu-repo/semantics/publishedVersio