Analysis of Synaptic Proteins in the Cerebrospinal Fluid as a New Tool in the Study of Inborn Errors of Neurotransmission

Abstract In a few rare diseases, specialised studies in cerebrospinal fluid (CSF) are required to identify the underlying metabolic disorder. We aimed to explore the possibility of detecting key synaptic proteins in the CSF, in particular dopaminergic and gabaergic, as new procedures that could be useful for both pathophysiological and diagnostic purposes in investigation of inherited disorders of neurotransmission. Dopamine receptor type 2 (D2R), dopamine transporter (DAT) and vesicular monoamine transporter type 2 (VMAT2) were analysed in CSF samplesfrom 30 healthy controls (11 days to 17 years) by western blot analysis. Because VMAT2 was the only protein with intracellular localisation, and in order to compare results, GABA vesicular transporter, which is another intracellular protein, was also studied. Spearman’s correlation and Student’s t tests were applied to compare optical density signals between different proteins. All these synaptic proteins could be easily detected and quantified in the CSF. DAT, D2R and GABA VT expression decrease with age, particularly in the first months of life, reflecting the expected intense synaptic activity and neuronal circuitry formation. A statistically significant relationship was found between D2R and DAT expression, reinforcing the previous evidence of DAT regulation by D2R. To our knowledge, there are no previous studies on human CSF reporting a reliable analysis of these proteins. These kinds of studies could help elucidate new causes of disturbed dopaminergic and gabaergic transmission as well as understanding different responses to L-dopa in inherited disorders affecting dopamine metabolism. Moreover, this approach to synaptic activity in vivo can be extended to different groups of proteins and diseases.

Optimal Cut-Off Value for Homeostasis Model Assessment (HOMA) Index of Insulin-Resistance in a Population of Patients Admitted Electively in a Portuguese Cardiology Ward

INTRODUCTION: Insulin resistance is the pathophysiological key to explain metabolic syndrome. Although clearly useful, the Homeostasis Model Assessment index (an insulin resistance measurement) hasn't been systematically applied in clinical practice. One of the main reasons is the discrepancy in cut-off values reported in different populations. We sought to evaluate in a Portuguese population the ideal cut-off for Homeostasis Model Assessment index and assess its relationship with metabolic syndrome. MATERIAL AND METHODS: We selected a cohort of individuals admitted electively in a Cardiology ward with a BMI < 25 Kg/m2 and no abnormalities in glucose metabolism (fasting plasma glucose < 100 mg/dL and no diabetes). The 90th percentile of the Homeostasis Model Assessment index distribution was used to obtain the ideal cut-off for insulin resistance. We also selected a validation cohort of 300 individuals (no exclusion criteria applied). RESULTS: From 7 000 individuals, and after the exclusion criteria, there were left 1 784 individuals. The 90th percentile for Homeostasis Model Assessment index was 2.33. In the validation cohort, applying that cut-off, we have 49.3% of individuals with insulin resistance. However, only 69.9% of the metabolic syndrome patients had insulin resistance according to that cut-off. By ROC curve analysis, the ideal cut-off for metabolic syndrome is 2.41. Homeostasis Model Assessment index correlated with BMI (r = 0.371, p < 0.001) and is an independent predictor of the presence of metabolic syndrome (OR 19.4, 95% CI 6.6 - 57.2, p < 0.001). DISCUSSION: Our study showed that in a Portuguese population of patients admitted electively in a Cardiology ward, 2.33 is the Homeostasis Model Assessment index cut-off for insulin resistance and 2.41 for metabolic syndrome. CONCLUSION: Homeostasis Model Assessment index is directly correlated with BMI and is an independent predictor of metabolic syndrome.

Predição de Pré-Eclâmpsia no Primeiro Trimestre em Gravidezes de Baixo Risco: Determinação do Cut-Off numa Amostra da População Portuguesa

Objective:We aimed to identify the cut-off for risk of pre-eclampsia (PE) in Portuguese population by applying the first trimester prediction model from Fetal Medicine Foundation (FMF) in a prospective enrolled cohort of low risk pregnant women. Population and methods: A prospective cohort of low risk singleton pregnancies underwent routine first-trimester scree - ning from 2011 through 2013. Maternal characteristics, blood pressure, uterine artery Doppler, levels of pregnancy-associated plasma protein-A (PAPP-A) and free b-human chorionic gonadotropin were evaluated. The prediction of PE in first trimester was calculated through software Astraia, the outcome obtained from medical records and the cutoff value was subse quently calculated. Results:Of the 273 enrolled patients, 7 (2.6%) developed PE. In first trimester women who developed PE presented higher uterine arteries resistance, represented by higher values of lowest and mean uterine pulsatility index, p <0.005. There was no statistical significance among the remaining maternal characteristics, body mass index, blood pressure and PAPP-A. Using the FMF first trimester PE algorithm, an ideal cut-off of 0.045 (1/22) would correctly detect 71% women who developed PE for a 12% false positive rate and a likelihood ratio of 12.98 (area under the curve: 0.69; confidence interval 95%: 0.39-0.99). By applying the reported cutoff to our cohort, we would obtain 71.4% true positives, 88.3% true negatives, 11.4% false positives and 28.6% false negatives. Conclusion: By applying a first trimester PE prediction model to low risk pregnancies derived from a Portuguese population, a significant proportion of patients would have been predicted as high risk. New larger studies are required to confirm the present findings.