Invasive Group A Streptococcus disease is a severe and sometimes life-threatening infection with ... more Invasive Group A Streptococcus disease is a severe and sometimes life-threatening infection with only few cases reported in literature. We describe the case of a 49-day-old male infant with invasive Group A Streptococcus infection characterized by acute otitis media and development of septicemia within a probably community-acquired cluster. The causative agent resulted to be a rare emm-89 genotype of Streptococcus pyogenes. Group A Streptococcus must be considered responsible for sepsis in newborns and young infants.
Pruning in neurons has been suggested to be strongly involved in Schizophrenia's (SKZ) etiopathog... more Pruning in neurons has been suggested to be strongly involved in Schizophrenia's (SKZ) etiopathogenesis in recent biological, imaging, and genetic studies. We investigated the impact of protein-coding genes known to be involved in pruning, collected by a systematic literature research, in shaping the risk for SKZ in a case-control sample of 9,490 subjects (Psychiatric Genomics Consortium). Moreover, their modifications through evolution (humans, chimpanzees, and rats) and subcellular localization (as indicative of their biological function) were also investigated. We also performed a biological pathways (Gene Ontology) analysis. Genetics analyses found four genes (DLG1, NOS1, THBS4, and FADS1) and 17 pathways strongly involved in pruning and SKZ in previous literature findings to be significantly associated with the sample under analysis. The analysis of the subcellular localization found that secreted genes, and so regulatory ones, are the least conserved through evolution and also the most associated with SKZ. Their cell line and regional brain expression analysis found that their areas of primary expression are neuropil and the hippocampus, respectively. At the best of our knowledge, for the first time, we were able to describe the SKZ neurodevelopmental hypothesis starting from a single biological process. We can also hypothesize how alterations in pruning fine regulation and orchestration, strongly related with the evolutionary newest (and so more sensitive) secreted proteins, may be of particular relevance in the hippocampus. This early alteration may lead to a mis-structuration of neural connectivity, resulting in the different brain alteration that characterizes SKZ patients.
Genome-wide association studies (GWAS) are able to identify the role of individual SNPs in influe... more Genome-wide association studies (GWAS) are able to identify the role of individual SNPs in influencing a phenotype. Nevertheless, such analysis is unable to explain the biological complexity of several diseases. We elaborated an algorithm that starting from genes in molecular pathways implicated in a phenotype is able to identify SNP–SNP interaction’s role in association with the phenotype. The algorithm is based on three steps. Firstly, it identifies the biological pathways (gene ontology) in which the genes under analysis play a role (GeneMANIA). Secondly, it identifies the group of SNPs that best fits the phenotype (and covariates) under analysis, not considering individual SNP regression coefficients but fitting the regression for the group itself. Finally, it operates an analysis of SNP interactions for each possible couple of SNPs within the group. The sensitivity and specificity of our algorithm was validated in simulated datasets (HapGen and Simulate Phenotypes programs). The impact on efficiency deriving from changes in the number of SNPs/patients under analysis, linkage disequilibrium and minor allele frequency thresholds was analyzed. Our algorithm showed a strong stability throughout all analysis operated, resulting in an overall sensitivity of 81.67 % and a specificity of 98.35 %. We elaborated a stable algorithm that may detect SNPs interactions, especially those effects that pass undetected in classical GWAS. This method may contribute to face the two relevant limitations of GWAS: lack of biological informative power and amount of time needed for the analysis.
Journal of neural transmission (Vienna, Austria : 1996), Jul 2014
The efficacy of current antidepressant (AD) drugs for the treatment of major depressive disorder ... more The efficacy of current antidepressant (AD) drugs for the treatment of major depressive disorder (MDD) lays behind expectations. The correct genetic differentiation between severe and less severe cases before treatment may pave the way to the most correct clinical choices in clinical practice. Genetics may pave the way such identification, which in turns may provide perspectives for the synthesis of new ADs by correcting the molecular unbalances that differentiate severe and less severe depressive patients. We investigated 1,903 MDD patients from the STAR*D study. Outcome was the number of severe depressive records, defined as a Quick Inventory of Depressive Symptomatology (QIDS)-Clinician rated (C) total score >15, corrected for the number of observations for each patient during the first 14 weeks of citalopram treatment. Predictors were the genetic variations harbored by genes involved in the glutamatergic-monoaminergic interplay as defined in a previous work published by our group. Clinical and socio-demographic stratification factor analyses were taken in cases and controls. Covariated linear regression was the statistical model for the analysis. SNPs were analyzed in groups (molecular pathway analysis) testing the hypothesis that the distribution of significant (p < 0.05) associations between SNPs and the outcome segregates within each pathway/gene subset. The best associated results are relative to two signle SNPs, (rs7744492 in AKAP12 p = 0.0004 and rs17046113 in CAMK2D p = 0.0006) and a molecular pathway (cAMP biosynthetic process p = 0.005). After correction for multitesting, none of them resulted to be significantly associated. These results are consistent with previous findings in literature and further stress that the molecular mechanisms targeted by current ADs may not be the key biological variables that differentiate severe from mild depression.
Second-generation antipsychotics (SGA) have been associated with risk of stroke in elderly patien... more Second-generation antipsychotics (SGA) have been associated with risk of stroke in elderly patients, but the molecular and genetic background under this association has been poorly investigated. The aim of the present study was to prioritize a list of genes with an SGA altered expression in order to characterize the genetic background of the SGA-associated stroke risk. Genes with evidence of an altered expression after SGA treatments in genome-wide investigations, both in animals and men, were identified. The Genetic Association Database (GAD) served to verify which of these genes had a proven positive association with an increased stroke risk, and along with it each evidence was tested and recorded. Seven hundred and forty five genes had evidence of a change of their expression profile after SGA administration in various studies. Nine out of them have also been significantly related to an increased strokes risk. We identified and described nine genes as potential candidates for future genetic studies aimed at identifying the genetic background of the SGA-related stroke risk. Further, we identify the molecular pathways in which these genes operate in order to provide a molecular framework to understand on which basis SGA may enhance the risk for stroke.
Invasive Group A Streptococcus disease is a severe and sometimes life-threatening infection with ... more Invasive Group A Streptococcus disease is a severe and sometimes life-threatening infection with only few cases reported in literature. We describe the case of a 49-day-old male infant with invasive Group A Streptococcus infection characterized by acute otitis media and development of septicemia within a probably community-acquired cluster. The causative agent resulted to be a rare emm-89 genotype of Streptococcus pyogenes. Group A Streptococcus must be considered responsible for sepsis in newborns and young infants.
Pruning in neurons has been suggested to be strongly involved in Schizophrenia's (SKZ) etiopathog... more Pruning in neurons has been suggested to be strongly involved in Schizophrenia's (SKZ) etiopathogenesis in recent biological, imaging, and genetic studies. We investigated the impact of protein-coding genes known to be involved in pruning, collected by a systematic literature research, in shaping the risk for SKZ in a case-control sample of 9,490 subjects (Psychiatric Genomics Consortium). Moreover, their modifications through evolution (humans, chimpanzees, and rats) and subcellular localization (as indicative of their biological function) were also investigated. We also performed a biological pathways (Gene Ontology) analysis. Genetics analyses found four genes (DLG1, NOS1, THBS4, and FADS1) and 17 pathways strongly involved in pruning and SKZ in previous literature findings to be significantly associated with the sample under analysis. The analysis of the subcellular localization found that secreted genes, and so regulatory ones, are the least conserved through evolution and also the most associated with SKZ. Their cell line and regional brain expression analysis found that their areas of primary expression are neuropil and the hippocampus, respectively. At the best of our knowledge, for the first time, we were able to describe the SKZ neurodevelopmental hypothesis starting from a single biological process. We can also hypothesize how alterations in pruning fine regulation and orchestration, strongly related with the evolutionary newest (and so more sensitive) secreted proteins, may be of particular relevance in the hippocampus. This early alteration may lead to a mis-structuration of neural connectivity, resulting in the different brain alteration that characterizes SKZ patients.
Genome-wide association studies (GWAS) are able to identify the role of individual SNPs in influe... more Genome-wide association studies (GWAS) are able to identify the role of individual SNPs in influencing a phenotype. Nevertheless, such analysis is unable to explain the biological complexity of several diseases. We elaborated an algorithm that starting from genes in molecular pathways implicated in a phenotype is able to identify SNP–SNP interaction’s role in association with the phenotype. The algorithm is based on three steps. Firstly, it identifies the biological pathways (gene ontology) in which the genes under analysis play a role (GeneMANIA). Secondly, it identifies the group of SNPs that best fits the phenotype (and covariates) under analysis, not considering individual SNP regression coefficients but fitting the regression for the group itself. Finally, it operates an analysis of SNP interactions for each possible couple of SNPs within the group. The sensitivity and specificity of our algorithm was validated in simulated datasets (HapGen and Simulate Phenotypes programs). The impact on efficiency deriving from changes in the number of SNPs/patients under analysis, linkage disequilibrium and minor allele frequency thresholds was analyzed. Our algorithm showed a strong stability throughout all analysis operated, resulting in an overall sensitivity of 81.67 % and a specificity of 98.35 %. We elaborated a stable algorithm that may detect SNPs interactions, especially those effects that pass undetected in classical GWAS. This method may contribute to face the two relevant limitations of GWAS: lack of biological informative power and amount of time needed for the analysis.
Journal of neural transmission (Vienna, Austria : 1996), Jul 2014
The efficacy of current antidepressant (AD) drugs for the treatment of major depressive disorder ... more The efficacy of current antidepressant (AD) drugs for the treatment of major depressive disorder (MDD) lays behind expectations. The correct genetic differentiation between severe and less severe cases before treatment may pave the way to the most correct clinical choices in clinical practice. Genetics may pave the way such identification, which in turns may provide perspectives for the synthesis of new ADs by correcting the molecular unbalances that differentiate severe and less severe depressive patients. We investigated 1,903 MDD patients from the STAR*D study. Outcome was the number of severe depressive records, defined as a Quick Inventory of Depressive Symptomatology (QIDS)-Clinician rated (C) total score >15, corrected for the number of observations for each patient during the first 14 weeks of citalopram treatment. Predictors were the genetic variations harbored by genes involved in the glutamatergic-monoaminergic interplay as defined in a previous work published by our group. Clinical and socio-demographic stratification factor analyses were taken in cases and controls. Covariated linear regression was the statistical model for the analysis. SNPs were analyzed in groups (molecular pathway analysis) testing the hypothesis that the distribution of significant (p < 0.05) associations between SNPs and the outcome segregates within each pathway/gene subset. The best associated results are relative to two signle SNPs, (rs7744492 in AKAP12 p = 0.0004 and rs17046113 in CAMK2D p = 0.0006) and a molecular pathway (cAMP biosynthetic process p = 0.005). After correction for multitesting, none of them resulted to be significantly associated. These results are consistent with previous findings in literature and further stress that the molecular mechanisms targeted by current ADs may not be the key biological variables that differentiate severe from mild depression.
Second-generation antipsychotics (SGA) have been associated with risk of stroke in elderly patien... more Second-generation antipsychotics (SGA) have been associated with risk of stroke in elderly patients, but the molecular and genetic background under this association has been poorly investigated. The aim of the present study was to prioritize a list of genes with an SGA altered expression in order to characterize the genetic background of the SGA-associated stroke risk. Genes with evidence of an altered expression after SGA treatments in genome-wide investigations, both in animals and men, were identified. The Genetic Association Database (GAD) served to verify which of these genes had a proven positive association with an increased stroke risk, and along with it each evidence was tested and recorded. Seven hundred and forty five genes had evidence of a change of their expression profile after SGA administration in various studies. Nine out of them have also been significantly related to an increased strokes risk. We identified and described nine genes as potential candidates for future genetic studies aimed at identifying the genetic background of the SGA-related stroke risk. Further, we identify the molecular pathways in which these genes operate in order to provide a molecular framework to understand on which basis SGA may enhance the risk for stroke.
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Papers by Enrico Cocchi