The GCC repeat length in the 5'UTR of MRP1 gene is polymorphic: a functional characterization of its relevance for cystic fibrosis

BACKGROUND: Among the members of the ATP binding cassette transporter superfamily, MRPs share the closest homology with the CFTR protein, which is defective in CF disease. MRP1 has been proposed as a potential modifier gene and/or as novel target for pharmacotherapy of CF to explain the clinical benefits observed in some CF patients treated with the macrolide AZM. The 5'UTR of the MRP1 gene contains a GCC triplet repeat that could represent a polymorphic site and affect the activity of the promoter. METHODS: The MRP1 5' flanking region was amplified by PCR from 36 CF patients and 100 non-CF subjects and the number of GCC triplets of each allele was determined by sequence and electrophoretic analysis. We performed gene reporter studies in CF airway epithelial cells 16HBE14o-AS3, in basal conditions and in the presence of AZM. RESULTS: We found that the GCC repeat is polymorphic, ranging from 7 to 14 triplets either in CF or in non-CF subjects. Our data are preliminary and have to be confirmed on a larger population of CF subjects. The transcriptional activity of the proximal MRP1 5' regulatory region revealed no statistically significant correlations between the number of repeats and treatment with AZM. CONCLUSION: We identified a novel polymorphism in the 5'UTR of MRP1 gene that provides multiple alleles in a gene relevant for multidrug resistance as well as for CF, determining that this region is transcriptionally active and that this activity does not appear to be influenced by AZM treatment

Human Intracranial High Frequency Oscillations (HFOs) Detected by Automatic Time-Frequency Analysis

OBJECTIVES: High frequency oscillations (HFOs) have been proposed as a new biomarker for epileptogenic tissue. The exact characteristics of clinically relevant HFOs and their detection are still to be defined. METHODS: We propose a new method for HFO detection, which we have applied to six patient iEEGs. In a first stage, events of interest (EoIs) in the iEEG were defined by thresholds of energy and duration. To recognize HFOs among the EoIs, in a second stage the iEEG was Stockwell-transformed into the time-frequency domain, and the instantaneous power spectrum was parameterized. The parameters were optimized for HFO detection in patient 1 and tested in patients 2–5. Channels were ranked by HFO rate and those with rate above half maximum constituted the HFO area. The seizure onset zone (SOZ) served as gold standard. RESULTS: The detector distinguished HFOs from artifacts and other EEG activity such as interictal epileptiform spikes. Computation took few minutes. We found HFOs with relevant power at frequencies also below the 80–500 Hz band, which is conventionally associated with HFOs. The HFO area overlapped with the SOZ with good specificity > 90% for five patients and one patient was re-operated. The performance of the detector was compared to two well-known detectors. CONCLUSIONS: Compared to methods detecting energy changes in filtered signals, our second stage - analysis in the time-frequency domain - discards spurious detections caused by artifacts or sharp epileptic activity and improves the detection of HFOs. The fast computation and reasonable accuracy hold promise for the diagnostic value of the detector

Electrophysiological Biomarkers of Epilepsy

In patients being evaluated for epilepsy and in animal models of epilepsy, electrophysiological recordings are carried to capture seizures to determine the existence of epilepsy. Electroencephalography recordings from the scalp, or sometimes directly from the brain, are also used to locate brain areas where seizure begins, and in surgical treatment help plan the area for resection. As seizures are unpredictable and can occur infrequently, ictal recordings are not ideal in terms of time, cost, or risk when, for example, determining the efficacy of existing or new anti-seizure drugs, evaluating potential anti-epileptogenic interventions, or for prolonged intracerebral electrode studies. Thus, there is a need to identify and validate other electrophysiological biomarkers of epilepsy that could be used to diagnose, treat, cure, and prevent epilepsy. Electroencephalography recordings in the epileptic brain contain other interictal electrophysiological disturbances that can occur more frequently than seizures, such as interictal spikes (IIS) and sharp waves, and from invasive studies using wide bandwidth recording and small diameter electrodes, the discovery of pathological high-frequency oscillations (HFOs) and microseizures. Of IIS, HFOs, and microseizures, a significant amount of recent research has focused on HFOs in the pathophysiology of epilepsy. Results from studies in animals with epilepsy and presurgical patients have consistently found a strong association between HFOs and epileptogenic brain tissue that suggest HFOs could be a potential biomarker of epileptogenicity and epileptogenesis. Here, we discuss several aspects of HFOs, as well as IIS and microseizures, and the evidence that supports their role as biomarkers of epilepsy. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s13311-014-0259-0) contains supplementary material, which is available to authorized users