Alessandro Orro

Hippocampal Atrophy as a Quantitative Trait in a Genome-Wide Association Study Identifying Novel Susceptibility Genes for Alzheimer's Disease

Background With the exception of APOE ε4 allele, the common genetic risk factors for sporadic Alzheimers Disease (AD) are unknown. Methods and Findings We completed a genome-wide association study on 381 participants in the ADNI (Alzheimers Disease Neuroimaging Initiative) study. Samples were genotyped using the Illumina Human610-Quad BeadChip. 516,645 unique Single Nucleotide Polymorphisms (SNPs) were included in the analysis following quality control measures. The genotype data and raw genetic data are freely available for download (LONI, http://www.loni.ucla.edu/ADNI/Data/). Two analyses were completed: a standard case-control analysis, and a novel approach using hippocampal atrophy measured on MRI as an objectively defined, quantitative phenotype. A General Linear Model was applied to identify SNPs for which there was an interaction between the genotype and diagnosis on the quantitative trait. The case-control analysis identified APOE and a new risk gene, TOMM40 (translocase of outer mitochondrial membrane 40), at a genome-wide significance level of≤10−6 (10−11 for a haplotype). TOMM40 risk alleles were approximately twice as frequent in AD subjects as controls. The quantitative trait analysis identified 21 genes or chromosomal areas with at least one SNP with a p-value≤10−6, which can be considered potential “new” candidate loci to explore in the etiology of sporadic AD. These candidates included EFNA5, CAND1, MAGI2, ARSB, and PRUNE2, genes involved in the regulation of protein degradation, apoptosis, neuronal loss and neurodevelopment. Thus, we identified common genetic variants associated with the increased risk of developing AD in the ADNI cohort, and present publicly available genome-wide data. Supportive evidence based on case-control studies and biological plausibility by gene annotation is provided. Currently no available sample with both imaging and genetic data is available for replication. Conclusions Using hippocampal atrophy as a quantitative phenotype in a genome-wide scan, we have identified candidate risk genes for sporadic Alzheimers disease that merit further investigation.

Association Study on Long-Living Individuals from Southern Italy Identifies rs10491334 in the CAMKIV Gene That Regulates Survival Proteins.

Long-living individuals (LLIs) are used to study exceptional longevity. A number of genetic variants have been found associated in LLIs to date, but further identification of variants would improve knowledge on the mechanisms regulating the rate of aging. Therefore, we performed a genome-wide association study on 410 LLIs and 553 young control individuals with a 317K single-nucleotide polymorphism (SNP) chip to identify novel traits associated with aging. Among the top (p < 1 × 10(-4)) SNPs initially identified, we found rs10491334 (CAMKIV) (odds ratio [OR] = 0.55; 95% confidence interval [CI] 0.42-0.73; p = 2.88 × 10(-5)), a variant previously reported associated with diastolic blood pressure, associated also in a replication set of 116 LLIs and 160 controls (OR = 0.54; 95% CI 0.32-0.90; p = 9 × 10(-3)). Furthermore, in vitro analysis established that calcium/calmodulin-dependent protein kinase IV (CAMKIV) activates the survival proteins AKT, SIRT1, and FOXO3A, and we found that homozygous carriers of rs10491334 have a significant reduction in CAMKIV expression. This, together with the observed reduction in minor-allele carriers among centenarians, points to a detrimental role for the SNP. In conclusion, prolongevity genes are activated by CAMKIV, the levels of which are influenced by rs10491334, a SNP associated with human longevity.

Fine mapping of AHI1 as a schizophrenia susceptibility gene: from association to evolutionary evidence

In previous studies, we identified a locus for schizophrenia on 6q23.3 and proposed the Abelson helper integration site 1 (AHI1) as the candidate gene. AHI1 is expressed in the brain and plays a key role in neurodevelopment, is involved in Joubert syndrome, and has been recently associated with autism. The neurodevelopmental role of AHI1 fits with etiological hypotheses of schizophrenia. To definitively confirm our hypothesis, we searched for associations using a dense map of the region. Our strongest findings lay within the AHI1 gene: single‐nucleotide polymorphisms rs11154801 and rs7759971 showed significant associations (P=6.23E‐06; P=0.84E‐06) and haplotypes gave P values in the 10E‐8 to 10E‐10 range. The second highest significant region maps close to AHI1 and includes the intergenic region between BC040979 and PDE7B (rs2038549 at P=9.70E‐06 and rs1475069 at P=6.97E‐06), and PDE7B and MAP7. Using a sample of Palestinian Arab families to confirm these findings, we found isolated signals. While these results did not retain their significance after correction for multiple testing, the joint analysis across the 2 samples supports the role of AHI1, despite the presence of heterogeneity. Given the hypothesis of positive selection of schizophrenia genes, we resequenced a 11 kb region within AHI1 in ethnically defined populations and found evidence for a selective sweep. Network analysis indicates 2 haplotype clades, with schizophrenia‐susceptibility haplotypes clustering within the major clade. In conclusion, our data support the role of AHI1 as a susceptibility gene for schizophrenia and confirm it has been subjected to positive selection, also shedding light on new possible candidate genes, MAP7 and PDE7B.—Torri, F., Akelai, A., Lupoli, S., Sironi, M., Amann‐Zalcenstein, D., Fumagalli, M., Dal Fiume, C., Ben‐Asher, E., Kanyas, K., Cagliani, R., Cozzi, P., Trombetti, G., Lievers, L. S., Salvi, E., Orro, A., Beckmann, J. S., Lancet, D., Kohn, Y., Milanesi, L., Ebstein, R. B., Lerer, B., Macciardi, F. Fine mapping of AHI1 as a schizophrenia susceptibility gene: from association to evolutionary evidence. FASEB J. 24, 3066–3082 (2010). www.fasebj.org

Molecular Interaction Studies of HIV-1 Matrix Protein p17 and Heparin IDENTIFICATION OF THE HEPARIN-BINDING MOTIF OF p17 AS A TARGET FOR THE DEVELOPMENT OF MULTITARGET ANTAGONISTS

Background: HIV-1 p17 binds heparin and heparan sulfate proteoglycans of the cell surface. Results: Heparin/p17 interaction occurs through heparin sulfate groups and a linear basic motif of p17 N terminus, also involved in p17/CXCR1 interaction. Conclusion: Targeting the basic motif inhibits p17-receptors interaction and consequent biological activities. Significance: Heparin-like molecules represent template for the development of new treatments of p17-dependent/AIDS-associated pathologies. Once released by HIV+ cells, p17 binds heparan sulfate proteoglycans (HSPGs) and CXCR1 on leukocytes causing their dysfunction. By exploiting an approach integrating computational modeling, site-directed mutagenesis of p17, chemical desulfation of heparin, and surface plasmon resonance, we characterized the interaction of p17 with heparin, a HSPG structural analog, and CXCR1. p17 binds to heparin with an affinity (Kd = 190 nm) that is similar to those of other heparin-binding viral proteins. Two stretches of basic amino acids (basic motifs) are present in p17 N and C termini. Neutralization (Arg→Ala substitution) of the N-terminal, but not of the C-terminal basic motif, causes the loss of p17 heparin-binding capacity. The N-terminal heparin-binding motif of p17 partially overlaps the CXCR1-binding domain. Accordingly, its neutralization prevents also p17 binding to the chemochine receptor. Competition experiments demonstrated that free heparin and heparan sulfate (HS), but not selectively 2-O-, 6-O-, and N-O desulfated heparins, prevent p17 binding to substrate-immobilized heparin, indicating that the sulfate groups of the glycosaminoglycan mediate p17 interaction. Evaluation of the p17 antagonist activity of a panel of biotechnological heparins derived by chemical sulfation of the Escherichia coli K5 polysaccharide revealed that the highly N,O-sulfated derivative prevents the binding of p17 to both heparin and CXCR1, thus inhibiting p17-driven chemotactic migration of human monocytes with an efficiency that is higher than those of heparin and HS. Here, we characterized at a molecular level the interaction of p17 with its cellular receptors, laying the basis for the development of heparin-mimicking p17 antagonists.

SNPLims: a data management system for genome wide association studies

BackgroundRecent progresses in genotyping technologies allow the generation high-density genetic maps using hundreds of thousands of genetic markers for each DNA sample. The availability of this large amount of genotypic data facilitates the whole genome search for genetic basis of diseases.We need a suitable information management system to efficiently manage the data flow produced by whole genome genotyping and to make it available for further analyses.ResultsWe have developed an information system mainly devoted to the storage and management of SNP genotype data produced by the Illumina platform from the raw outputs of genotyping into a relational database.The relational database can be accessed in order to import any existing data and export user-defined formats compatible with many different genetic analysis programs.After calculating family-based or case-control association study data, the results can be imported in SNPLims. One of the main features is to allow the user to rapidly identify and annotate statistically relevant polymorphisms from the large volume of data analyzed. Results can be easily visualized either graphically or creating ASCII comma separated format output files, which can be used as input to further analyses.ConclusionsThe proposed infrastructure allows to manage a relatively large amount of genotypes for each sample and an arbitrary number of samples and phenotypes. Moreover, it enables the users to control the quality of the data and to perform the most common screening analyses and identify genes that become “candidate” for the disease under consideration.

Homology Modeling, Docking Studies and Molecular Dynamic Simulations Using Graphical Processing Unit Architecture to Probe the Type‐11 Phosphodiesterase Catalytic Site: A Computational Approach for the Rational Design of Selective Inhibitors

Phosphodiesterase 11 (PDE11) is the latest isoform of the PDEs family to be identified, acting on both cyclic adenosine monophosphate and cyclic guanosine monophosphate. The initial reports of PDE11 found evidence for PDE11 expression in skeletal muscle, prostate, testis, and salivary glands; however, the tissue distribution of PDE11 still remains a topic of active study and some controversy. Given the sequence similarity between PDE11 and PDE5, several PDE5 inhibitors have been shown to cross‐react with PDE11. Accordingly, many non‐selective inhibitors, such as IBMX, zaprinast, sildenafil, and dipyridamole, have been documented to inhibit PDE11. Only recently, a series of dihydrothieno[3,2‐d]pyrimidin‐4(3H)‐one derivatives proved to be selective toward the PDE11 isoform. In the absence of experimental data about PDE11 X‐ray structures, we found interesting to gain a better understanding of the enzyme–inhibitor interactions using in silico simulations. In this work, we describe a computational approach based on homology modeling, docking, and molecular dynamics simulation to derive a predictive 3D model of PDE11. Using a Graphical Processing Unit architecture, it is possible to perform long simulations, find stable interactions involved in the complex, and finally to suggest guideline for the identification and synthesis of potent and selective inhibitors.

A tool for mapping Single Nucleotide Polymorphisms using Graphics Processing Units

BackgroundSingle Nucleotide Polymorphism (SNP) genotyping analysis is very susceptible to SNPs chromosomal position errors. As it is known, SNPs mapping data are provided along the SNP arrays without any necessary information to assess in advance their accuracy. Moreover, these mapping data are related to a given build of a genome and need to be updated when a new build is available. As a consequence, researchers often plan to remap SNPs with the aim to obtain more up-to-date SNPs chromosomal positions. In this work, we present G-SNPM a GPU (Graphics Processing Unit) based tool to map SNPs on a genome.MethodsG-SNPM is a tool that maps a short sequence representative of a SNP against a reference DNA sequence in order to find the physical position of the SNP in that sequence. In G-SNPM each SNP is mapped on its related chromosome by means of an automatic three-stage pipeline. In the first stage, G-SNPM uses the GPU-based short-read mapping tool SOAP3-dp to parallel align on a reference chromosome its related sequences representative of a SNP. In the second stage G-SNPM uses another short-read mapping tool to remap the sequences unaligned or ambiguously aligned by SOAP3-dp (in this stage SHRiMP2 is used, which exploits specialized vector computing hardware to speed-up the dynamic programming algorithm of Smith-Waterman). In the last stage, G-SNPM analyzes the alignments obtained by SOAP3-dp and SHRiMP2 to identify the absolute position of each SNP.Results and conclusionsTo assess G-SNPM, we used it to remap the SNPs of some commercial chips. Experimental results shown that G-SNPM has been able to remap without ambiguity almost all SNPs. Based on modern GPUs, G-SNPM provides fast mappings without worsening the accuracy of the results. G-SNPM can be used to deal with specialized Genome Wide Association Studies (GWAS), as well as in annotation tasks that require to update the SNP mapping probes.

Genome and Phenotype Microarray Analyses of Rhodococcus sp. BCP1 and Rhodococcus opacus R7: Genetic Determinants and Metabolic Abilities with Environmental Relevance

In this paper comparative genome and phenotype microarray analyses of Rhodococcus sp. BCP1 and Rhodococcus opacus R7 were performed. Rhodococcus sp. BCP1 was selected for its ability to grow on short-chain n-alkanes and R. opacus R7 was isolated for its ability to grow on naphthalene and on o-xylene. Results of genome comparison, including BCP1, R7, along with other Rhodococcus reference strains, showed that at least 30% of the genome of each strain presented unique sequences and only 50% of the predicted proteome was shared. To associate genomic features with metabolic capabilities of BCP1 and R7 strains, hundreds of different growth conditions were tested through Phenotype Microarray, by using Biolog plates and plates manually prepared with additional xenobiotic compounds. Around one-third of the surveyed carbon sources was utilized by both strains although R7 generally showed higher metabolic activity values compared to BCP1. Moreover, R7 showed broader range of nitrogen and sulphur sources. Phenotype Microarray data were combined with genomic analysis to genetically support the metabolic features of the two strains. The genome analysis allowed to identify some gene clusters involved in the metabolism of the main tested xenobiotic compounds. Results show that R7 contains multiple genes for the degradation of a large set of aromatic and PAHs compounds, while a lower variability in terms of genes predicted to be involved in aromatic degradation was found in BCP1. This genetic feature can be related to the strong genetic pressure exerted by the two different environment from which the two strains were isolated. According to this, in the BCP1 genome the smo gene cluster involved in the short-chain n-alkanes degradation, is included in one of the unique regions and it is not conserved in the Rhodococcus strains compared in this work. Data obtained underline the great potential of these two Rhodococcus spp. strains for biodegradation and environmental decontamination processes.

New insights into selective PDE4D inhibitors: 3-(Cyclopentyloxy)-4-methoxybenzaldehyde O-(2-(2,6-dimethylmorpholino)-2-oxoethyl) oxime (GEBR-7b) structural development and promising activities to restore memory impairment

Phosphodiesterase type 4D (PDE4D) has been indicated as a promising target for treating neurodegenerative pathologies such as Alzheimers Disease (AD). By preventing cAMP hydrolysis, PDE4 inhibitors (PDE4Is) increase the cAMP response element-binding protein (CREB) phosphorylation, synaptic plasticity and long-term memory formation. Pharmacological and behavioral studies on our hit GEBR-7b demonstrated that selective PDE4DIs could improve memory without causing emesis and sedation. The hit development led to new molecule series, herein reported, characterized by a catechol structure bonded to five member heterocycles. Molecular modeling studies highlighted the pivotal role of a polar alkyl chain in conferring selective enzyme interaction. Compound 8a showed PDE4D3 selective inhibition and was able to increase intracellular cAMP levels in neuronal cells, as well as in the hippocampus of freely moving rats. Furthermore, 8a was able to readily cross the blood-brain barrier and enhanced memory performance in mice without causing any emetic-like behavior. These data support the view that PDE4D is an adequate molecular target to restore memory deficits in different neuropathologies, including AD, and also indicate compound 8a as a promising candidate for further preclinical development.

CUDA-quicksort: an improved GPU-based implementation of quicksort

Sorting is a very important task in computer science and becomes a critical operation for programs making heavy use of sorting algorithms. General‐purpose computing has been successfully used on Graphics Processing Units (GPUs) to parallelize some sorting algorithms. Two GPU‐based implementations of the quicksort were presented in literature: the GPU‐quicksort, a compute‐unified device architecture (CUDA) iterative implementation, and the CUDA dynamic parallel (CDP) quicksort, a recursive implementation provided by NVIDIA Corporation. We propose CUDA‐quicksort an iterative GPU‐based implementation of the sorting algorithm. CUDA‐quicksort has been designed starting from GPU‐quicksort. Unlike GPU‐quicksort, it uses atomic primitives to perform inter‐block communications while ensuring an optimized access to the GPU memory. Experiments performed on six sorting benchmark distributions show that CUDA‐quicksort is up to four times faster than GPU‐quicksort and up to three times faster than CDP‐quicksort. An in‐depth analysis of the performance between CUDA‐quicksort and GPU‐quicksort shows that the main improvement is related to the optimized GPU memory access rather than to the use of atomic primitives. Moreover, in order to assess the advantages of using the CUDA dynamic parallelism, we implemented a recursive version of the CUDA‐quicksort. Experimental results show that CUDA‐quicksort is faster than the CDP‐quicksort provided by NVIDIA, with better performance achieved using the iterative implementation. Copyright