Function and regulation of TRPM7, as well as intracellular magnesium content, are altered in cells expressing ΔF508-CFTR and G551D-CFTR.

Cystic fibrosis (CF), one of the most common fatal hereditary disorders, is caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. The CFTR gene product is a multidomain adenosine triphosphate-binding cassette (ABC) protein that functions as a chloride (Cl(-)) channel that is regulated by intracellular magnesium [Mg(2+)]i. The most common mutations in CFTR are a deletion of a phenylalanine residue at position 508 (ΔF508-CFTR, 70-80 % of CF phenotypes) and a Gly551Asp substitution (G551D-CFTR, 4-5 % of alleles), which lead to decreased or almost abolished Cl(-) channel function, respectively. Magnesium ions have to be finely regulated within cells for optimal expression and function of CFTR. Therefore, the melastatin-like transient receptor potential cation channel, subfamily M, member 7 (TRPM7), which is responsible for Mg(2+) entry, was studies and [Mg(2+)]i measured in cells stably expressing wildtype CFTR, and two mutant proteins (ΔF508-CFTR and G551D-CFTR). This study shows for the first time that [Mg(2+)]i is decreased in cells expressing ΔF508-CFTR and G551D-CFTR mutated proteins. It was also observed that the expression of the TRPM7 protein is increased; however, membrane localization was altered for both ΔF508del-CFTR and G551D-CFTR. Furthermore, both the function and regulation of the TRPM7 channel regarding Mg(2+) is decreased in the cells expressing the mutated CFTR. Ca(2+) influx via TRPM7 were also modified in cells expressing a mutated CFTR. Therefore, there appears to be a direct involvement of TRPM7 in CF physiopathology. Finally, we propose that the TRPM7 activator Naltriben is a new potentiator for G551D-CFTR as the function of this mutant increases upon activation of TRPM7 by Naltriben.

Quantitative EEG and apolipoprotein E-genotype improve classification of patients with suspected Alzheimer's disease.

OBJECTIVE: To establish a model for better identification of patients in very early stages of Alzheimer's disease, AD (including patients with amnestic MCI) using high-resolution EEG and genetic data. METHODS: A total of 26 patients in early stages of probable AD and 12 patients with amnestic MCI were included. Both groups were similar in age and education. All patients had a comprehensive neuropsychological examination and a high resolution EEG. Relative band power characteristics were calculated in source space (LORETA inverse solution for spectral data) and compared between groups. A logistic regression model was calculated including relative band-power at the most significant location, ApoE status, age, education and gender. RESULTS: Differences in the delta band at 34 temporo-posterior source locations (p<.01) between AD and MCI groups were detected after correction for multiple comparisons. Classification slightly increased when ApoE status was added (p=.06 maximum likelihood test). Adjustment of analyses for the confounding factors age, gender and education did not alter results. CONCLUSIONS: Quantitative EEG (qEEG) separates between patients with amnestic MCI and patients in early stages of probable AD. Adding information about Apo ε4 allele frequency slightly enhances diagnostic accuracy. SIGNIFICANCE: qEEG may help identifying patients who are candidates for possible benefit from future disease modifying treatments.