Real-time processing of neuronal network activity measured by a high density microelectrode matrix through a FPGA card

This work aims at measuring the electrical activity of a network of rat neurons with Multi-Transistor Array technology. The recorded signal analysis is made using the spike detection algorithm proposed after A. Lambacher ("Identifying firing mammalian neurons in networks with high-resolution multi-transistor array (MTA)", Applied Physics A. 102.1 (2011), pp. 1-11). After locating a group of neurons, the spike frequency of one of these is measured. The time correlation between spikes of different neurons allows the meaurement of inter-neuronal signal transmission velocity. Preliminary results are discussed. Furthermore the algorithm is implemented on a FPGA digital circuit. The on-line digital algorithm is tested and compared with off-line analysis to verify its working. A graphical interface is created to visualize neuronal activity on-line. This work aims at building an acquisition chain for real-time analysis of neuronal activity.ope

Sardinians genetic background explained by runs of homozygosity and genomic regions under positive selection

The peculiar position of Sardinia in the Mediterranean sea has rendered its population an interesting biogeographical isolate. The aim of this study was to investigate the genetic population structure, as well as to estimate Runs of Homozygosity and regions under positive selection, using about 1.2 million single nucleotide polymorphisms genotyped in 1077 Sardinian individuals. Using four different methods - fixation index, inflation factor, principal component analysis and ancestry estimation - we were able to highlight, as expected for a genetic isolate, the high internal homogeneity of the island. Sardinians showed a higher percentage of genome covered by RoHs>0.5 Mb (FRoH%0.5) when compared to peninsular Italians, with the only exception of the area surrounding Alghero. We furthermore identified 9 genomic regions showing signs of positive selection and, we re-captured many previously inferred signals. Other regions harbor novel candidate genes for positive selection, like TMEM252, or regions containing long non coding RNA. With the present study we confirmed the high genetic homogeneity of Sardinia that may be explained by the shared ancestry combined with the action of evolutionary forces

Blood Leukocyte Dna Methylation Predicts Risk of Future Myocardial infarction and Coronary Heart Disease

BACKGROUND: DNA methylation is implicated in coronary heart disease (CHD), but current evidence is based on small, cross-sectional studies. We examined blood DNA methylation in relation to incident CHD across multiple prospective cohorts. METHODS: Nine population-based cohorts from the United States and Europe profiled epigenome-wide blood leukocyte DNA methylation using the Illumina Infinium 450k microarray, and prospectively ascertained CHD events including coronary insufficiency/unstable angina, recognized myocardial infarction, coronary revascularization, and coronary death. Cohorts conducted race-specific analyses adjusted for age, sex, smoking, education, body mass index, blood cell type proportions, and technical variables. We conducted fixed-effect meta-analyses across cohorts. RESULTS: Among 11 461 individuals (mean age 64 years, 67% women, 35% African American) free of CHD at baseline, 1895 developed CHD during a mean follow-up of 11.2 years. Methylation levels at 52 CpG (cytosine-phosphate-guanine) sites were associated with incident CHD or myocardial infarction (false discovery rate CONCLUSION: Methylation of blood-derived DNA is associated with risk of future CHD across diverse populations and may serve as an informative tool for gaining further insight on the development of CHD

DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases.

BACKGROUND: Chronic low-grade inflammation reflects a subclinical immune response implicated in the pathogenesis of complex diseases. Identifying genetic loci where DNA methylation is associated with chronic low-grade inflammation may reveal novel pathways or therapeutic targets for inflammation. RESULTS: We performed a meta-analysis of epigenome-wide association studies (EWAS) of serum C-reactive protein (CRP), which is a sensitive marker of low-grade inflammation, in a large European population (n = 8863) and trans-ethnic replication in African Americans (n = 4111). We found differential methylation at 218 CpG sites to be associated with CRP (P < 1.15 × 10-7) in the discovery panel of European ancestry and replicated (P < 2.29 × 10-4) 58 CpG sites (45 unique loci) among African Americans. To further characterize the molecular and clinical relevance of the findings, we examined the association with gene expression, genetic sequence variants, and clinical outcomes. DNA methylation at nine (16%) CpG sites was associated with whole blood gene expression in cis (P < 8.47 × 10-5), ten (17%) CpG sites were associated with a nearby genetic variant (P < 2.50 × 10-3), and 51 (88%) were also associated with at least one related cardiometabolic entity (P < 9.58 × 10-5). An additive weighted score of replicated CpG sites accounted for up to 6% inter-individual variation (R2) of age-adjusted and sex-adjusted CRP, independent of known CRP-related genetic variants. CONCLUSION: We have completed an EWAS of chronic low-grade inflammation and identified many novel genetic loci underlying inflammation that may serve as targets for the development of novel therapeutic interventions for inflammation

Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function.

Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways

Real-time processing of neuronal network activity measured by a high density microelectrode matrix through a FPGA card

This work aims at measuring the electrical activity of a network of rat neurons with Multi-Transistor Array technology. The recorded signal analysis is made using the spike detection algorithm proposed after A. Lambacher ("Identifying firing mammalian neurons in networks with high-resolution multi-transistor array (MTA)", Applied Physics A. 102.1 (2011), pp. 1-11). After locating a group of neurons, the spike frequency of one of these is measured. The time correlation between spikes of different neurons allows the meaurement of inter-neuronal signal transmission velocity. Preliminary results are discussed. Furthermore the algorithm is implemented on a FPGA digital circuit. The on-line digital algorithm is tested and compared with off-line analysis to verify its working. A graphical interface is created to visualize neuronal activity on-line. This work aims at building an acquisition chain for real-time analysis of neuronal activity