Functional interactions in hierarchically organized neural networks studied with spatiotemporal firing patterns and phase-coupling frequencies.

A scalable hardware/software hybrid module called Ubidule- endowed with bio-inspired ontogenetic and epigenetic features is configured to run a neural networks simulation with developmental and evolvable capabilities. We simulated the activity of hierarchically organized spiking neural networks characterized by an initial developmental phase featuring cell death followed by spike timing dependent synaptic plasticity in presence of background noise. An upstream 'sensory' network received a spatiotemporally organized external input and downstream networks were activated only via the upstream network. Precise firing sequences, formed by recurrent patterns of spikes intervals above chance levels, were observed in all recording conditions, thus suggesting the build-up of a connectivity able to sustain temporal information processing. The activity of a Ubinet -a network of Ubidules- is analyzed by means of virtual electrodes that recorded neural signals similar to EEG. The analysis of these signals was compared with a small set of human recordings and revealed common patterns of shift in quadratic phase coupling. The results suggest some interpretations of changes and plasticity of functional interactions between cortical areas driven by external stimuli and by learning/cognitive paradigms

Polymorphic variants within non-coding RNA and risk of pancreatic ductal adenocarcinoma

Purpose: Genome-wide association studies found that several polymorphisms affecting risk of pancreatic ductal adenocarcinoma (PDAC) are located in non-coding RNA (ncRNA). The majority of ncRNA are long non-coding RNAs (lncRNA) that are involved in biological processes such as cell growth, differentiation and proliferation. Several recent evidences also point to their role in cancer development and progression. Considering that lncRNA are highly polymorphic and that their expression has been associated with the development of cancer in several organs, including the pancreas, the purpose of this study was to test whether single nucleotide polymorphisms (SNPs) in lncRNA could affect the risk of developing PDAC. Materials and methods: In the human genome, there are 10,205,295 SNPs located in lncRNA (lincSNPs). To test their possible association with PDAC risk we used a two-phase approach: the first phase was conducted in 14,270 individuals (7,207 cases and 7,063 controls) pertaining to the Pancreatic Cancer cohort consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). The 5 lncSNPs with the lowest P-values of association with PDAC risk were genotyped in an additional group of 6,275 individuals, (3,062 PDAC patients and 3,213 controls) in the context of PANcreatic Disease ReseArch (PANDoRA) consortium. Results: In the first phase, we found 37 SNPs associated with PDAC risk with P<10-5. We replicated the best 5, and we observed that one was significant also in the second phase of the study. The T allele of rs7046076 was associated with an increased risk of developing PDAC with OR=1.13 (95%C.I. 1.09-1.18, P=0.003) in the PANDoRA population. A metanalysis of the two phases showed a genome-wide significant association: OR=1.13 (95%C.I. 1.09-1.18, P=1.28x10-8). The T allele disrupts the binding of the lncRNA (NONHSAT133783.2) with a miRNA (hsa-mir-1256) that regulates several genes involved in the cell cycle, such as CDKN2A. Conclusions: We propose a novel PDAC risk locus that lies in a lncRNA that could affect the risk of the disease through the de-regulation of lncRNA-miRNA interactions

Genome-wide scan of long noncoding RNA single nucleotide polymorphisms and pancreatic cancer susceptibility

Pancreatic ductal adenocarcinoma (PDAC) is projected to become the second cancer-related cause of death by 2030. Identifying novel risk factors, including genetic risk loci, could be instrumental in risk stratification and implementation of prevention strategies. Long noncoding RNAs (lncRNAs) are involved in regulation of key biological processes, and the possible role of their genetic variability has been unexplored so far. Combining genome wide association studies and functional data, we investigated the genetic variability in all lncRNAs. We analyzed 9893 PDAC cases and 9969 controls and identified a genome-wide significant association between the rs7046076 SNP and risk of developing PDAC (P = 9.73 × 10−9). This SNP is located in the NONHSAG053086.2 (lnc-SMC2-1) gene and the risk allele is predicted to disrupt the binding of the lncRNA with the micro-RNA (miRNA) hsa-mir-1256 that regulates several genes involved in cell cycle, such as CDKN2B. The CDKN2B region is pleiotropic and its genetic variants have been associated with several human diseases, possibly though an imperfect interaction between lncRNA and miRNA. We present a novel PDAC risk locus, supported by a genome-wide statistical significance and a plausible biological mechanism. © 2021 UIC