Analysis of shared common genetic risk between amyotrophic lateral sclerosis and epilepsy

Because hyper-excitability has been shown to be a shared pathophysiological mechanism, we used the latest and largest genome-wide studies in amyotrophic lateral sclerosis (n = 36,052) and epilepsy (n = 38,349) to determine genetic overlap between these conditions. First, we showed no significant genetic correlation, also when binned on minor allele frequency. Second, we confirmed the absence of polygenic overlap using genomic risk score analysis. Finally, we did not identify pleiotropic variants in meta-analyses of the 2 diseases. Our findings indicate that amyotrophic lateral sclerosis and epilepsy do not share common genetic risk, showing that hyper-excitability in both disorders has distinct origins

Genetic correlation between amyotrophic lateral sclerosis and schizophrenia

A. Palotie on työryhmän Schizophrenia Working Grp Psychiat jäsen.We have previously shown higher-than-expected rates of schizophrenia in relatives of patients with amyotrophic lateral sclerosis (ALS), suggesting an aetiological relationship between the diseases. Here, we investigate the genetic relationship between ALS and schizophrenia using genome-wide association study data from over 100,000 unique individuals. Using linkage disequilibrium score regression, we estimate the genetic correlation between ALS and schizophrenia to be 14.3% (7.05-21.6; P = 1 x 10(-4)) with schizophrenia polygenic risk scores explaining up to 0.12% of the variance in ALS (P = 8.4 x 10(-7)). A modest increase in comorbidity of ALS and schizophrenia is expected given these findings (odds ratio 1.08-1.26) but this would require very large studies to observe epidemiologically. We identify five potential novel ALS-associated loci using conditional false discovery rate analysis. It is likely that shared neurobiological mechanisms between these two disorders will engender novel hypotheses in future preclinical and clinical studies.Peer reviewe

A Novel Biotelemetry System to Monitor Human Vital Signs

This paper presents a novel biotelemetry system based on a fully-passive architecture; High Electron Mobility Transistors are used as sensing elements. The main advantages and drawbacks related to the approach here proposed are deeply analyzed and some possible solutions identified. Furthermore, some preliminary experimental results are given and discussed

The deep-water rose shrimp in the Ionian Sea: a spatio-temporal analysis of zero-inflated abundance data

In the ecological field, the sampling of abundance data is often characterized by the zero inflation of population distributions. Constrained zero-inflated GAM’s (COZIGAM) are obtained assuming that the probability of non-zero inflation and the mean non-zero-inflated population abundance are linearly related. Models of this class have been applied to a spatio-temporal case study concerning the deep-water rose shrimp, Parapenaeus longirostris (Lucas, 1846). Abundance data were collected during 16 experimental trawl surveys conducted from 1995 to 2010 in the Ionian Sea. The sampling design adopted was random-stratified by depth, with proportional allocation of hauls to the area of each depth range and geographical sector. Density index (N/km2) and length (mm) were considered for each haul identified by time, depth, geographic coordinates and geographical sector

The deep-water rose shrimp in the Ionian Sea: a spatio-temporal analysis of zero-inflated abundance data

In the ecological field, the sampling of abundance data is often characterized by the zero inflation of population distributions. Constrained zero-inflated GAM’s (COZIGAM) are obtained assuming that the probability of non-zero inflation and the mean non-zero-inflated population abundance are linearly related. Models of this class have been applied to a spatio-temporal case study concerning the deep-water rose shrimp, Parapenaeus longirostris (Lucas, 1846). Abundance data were collected during 16 experimental trawl surveys conducted from 1995 to 2010 in the Ionian Sea. The sampling design adopted was random-stratified by depth, with proportional allocation of hauls to the area of each depth range and geographical sector. Density index (N/km2) and length (mm) were considered for each haul identified by time, depth, geographic coordinates and geographical sector