Analisi di “Copy Number Variants” ed identificazione di nuovi geni candidati per l’Autismo e Ritardo Mentale

I disturbi dello spettro autistico (DSA) ed il ritardo mentale (RM) sono caratterizzati da un’eziologia genetica complessa ed eterogenea. Grazie ai recenti sviluppi nella ricerca genomica, è stato possibile dimostrare il ruolo di numerose copy number variants (CNVs) nella patogenesi di questi disturbi, anche se nella maggior parte dei casi l’eziologia rimane ancora sconosciuta. Questo lavoro riguarda l’identificazione e la caratterizzazione dei CNVs in famiglie con DSA e RM. E’ stata studiata una microdelezione in 7q31 che coinvolge i geni IMMP2L e DOCK4, trasmessa dalla madre con dislessia a due figli con autismo ed una figlia con dislessia. Nella stessa famiglia segrega una seconda microdelezione in 2q14 che inattiva il gene CNTNAP5 ed è trasmessa dal padre (con tratti autistici) ai due figli con autismo. Abbiamo quindi ipotizzato che i geni DOCK4 e CNTNAP5 potessero essere implicati, rispettivamente, nella suscettibilità a dislessia e DSA. Lo screening di numerosi individui affetti ha supportato la nostra ipotesi, con l’identificazione di una nuova microdelezione di DOCK4 che segrega con la dislessia, e 3 nuove varianti missenso in CNTNAP5 in individui con autismo. Dall’analisi genomica comparativa su array (aCGH) di individui con RM, è stata identificata una delezione nella regione 7q31.32, che coinvolge il gene CADPS2, in due fratelli con RM e tratti autistici, probabilmente ereditata dalla madre. Lo screening di mutazione di questo gene in individui con autismo o RM, ha portato all’identificazione di 3 varianti non sinonime, assenti nei controlli, ed ereditate per via materna. Poiché CADPS2 risiede in una regione genomica che contiene loci soggetti ad imprinting, abbiamo ipotizzato che il gene CADPS2 possa essere anch’esso caratterizzato da imprinting, con espressione monoallelica materna. Lo studio di espressione di CADPS2 in cellule del sangue ha avvalorato questa ipotesi, implicando perciò CADPS2 come un nuovo gene di suscettibilità per il RM e DSA.

Multidimensional analysis of complex networks

Complex Networks analysis turn out to be a very promising field of research, testified by many research projects and works that span different fields. Those analysis have been usually focused on characterize a single aspect of the system and a study that considers many informative axes along with a network evolve is lacking. We propose a new multidimensional analysis that is able to inspect networks in the two most important dimensions, space and time. To achieve this goal, we studied them singularly and investigated how the variation of the constituting parameters drives changes to the network as a whole. By focusing on space dimension, we characterized spatial alteration in terms of abstraction levels. We proposed a novel algorithm that, by applying a fuzziness function, can reconstruct networks under different level of details. We verified that statistical indicators depend strongly on the granularity with which a system is described and on the class of networks. We keep fixed the space axes and we isolated the dynamics behind networks evolution process. We detected new instincts that trigger social networks utilization and spread the adoption of novel communities. We formalized this enhanced social network evolution by adopting special nodes (called sirens) that, thanks to their ability to attract new links, were able to construct efficient connection patterns. We simulated the dynamics of the system by considering three well-known growth models. Applying this framework to real and synthetic networks, we showed that the sirens, even when used for a limited time span, effectively shrink the time needed to get a network in mature state. In order to provide a concrete context of our findings, we formalized the cost of setting up such enhancement and provided the best combinations of system's parameters, such as number of sirens, time span of utilization and attractiveness.

Investigating the role of Copy Number Variants in Specific Language Impairment and identification of new candidate genes

Specific language impairment (SLI) is a complex neurodevelopmental disorder defined as an unexpected failure to develop normal language abilities for no obvious reason. Copy number variants (CNVs) are an important source of variation in the susceptibility to neuropsychiatric disorders. Therefore, a CNV study within SLI families was performed to investigate the role of structural variants in SLI. Among the identified CNVs, we focused on CNVs on chromosome 15q11-q13, recurrently observed in neuropsychiatric conditions, and a homozygous exonic microdeletion in ZNF277. Since this microdeletion falls within the AUTS1 locus, a region linked to autism spectrum disorders (ASD), we investigated a potential role of ZNF277 in SLI and ASD. Frequency data and expression analysis of the ZNF277 microdeletion suggested that this variant may contribute to the risk of language impairments in a complex manner, that is independent of the autism risk previously described in this region. Moreover, we identified an affected individual with a dihydropyrimidine dehydrogenase (DPD) deficiency, caused by compound heterozygosity of two deleterious variants in the gene DPYD. Since DPYD represents a good candidate gene for both SLI and ASD, we investigated its involvement in the susceptibility to these two disorders, focusing on the splicing variant rs3918290, the most common mutation in the DPD deficiency. We observed a higher frequency of rs3918290 in SLI cases (1.2%), compared to controls (~0.6%), while no difference was observed in a large ASD cohort. DPYD mutation screening in 4 SLI and 7 ASD families carrying the splicing variant identified six known missense changes and a novel variant in the promoter region. These data suggest that the combined effect of the mutations identified in affected individuals may lead to an altered DPD activity and that rare variants in DPYD might contribute to a minority of cases, in conjunction with other genetic or non-genetic factors.

Glycerol oxidehydration to acrylic acid on complex mixed-metal oxides

The project of this Ph.D. thesis is based on a co-supervised collaboration between Università di Bologna, ALMA MATER STUDIORUM (Italy) and Instituto de Tecnología Química, Universitat Politècnica de València ITQ-UPV (Spain). This Ph.D. thesis is about the synthesis, characterization and catalytic testing of complex mixed-oxide catalysts mainly related to the family of Hexagonal Tungsten Bronzes (HTBs). These materials have been little explored as catalysts, although they have a great potential as multifunctional materials. Their peculiar acid properties can be coupled to other functionalities (e.g. redox sites) by isomorphous substitution of tungsten atoms with other transition metals such as vanadium, niobium and molybdenum. In this PhD thesis, it was demonstrated how it is possible to prepare substituted-HTBs by hydrothermal synthesis; these mixed-oxide were fully characterize by a number of physicochemical techniques such as XPS, HR-TEM, XAS etc. They were also used as catalysts for the one-pot glycerol oxidehydration to acrylic acid; this reaction might represent a viable chemical route to solve the important issue related to the co-production of glycerin along the biodiesel production chain. Acrylic acid yields as high as 51% were obtained and important structure-reactivity correlations were proved to govern the catalytic performance; only fine tuning of acid and redox properties as well as the in-framework presence of vanadium are fundamental to achieve noteworthy yields into the acid monomer. The overall results reported herein might represent an important contribution for future applications of HTBs in catalysis as well as a general guideline for a multifaceted approach for their physicochemical characterization.

Engineering Complex Computational Ecosystems

Self-organising pervasive ecosystems of devices are set to become a major vehicle for delivering infrastructure and end-user services. The inherent complexity of such systems poses new challenges to those who want to dominate it by applying the principles of engineering. The recent growth in number and distribution of devices with decent computational and communicational abilities, that suddenly accelerated with the massive diffusion of smartphones and tablets, is delivering a world with a much higher density of devices in space. Also, communication technologies seem to be focussing on short-range device-to-device (P2P) interactions, with technologies such as Bluetooth and Near-Field Communication gaining greater adoption. Locality and situatedness become key to providing the best possible experience to users, and the classic model of a centralised, enormously powerful server gathering and processing data becomes less and less efficient with device density. Accomplishing complex global tasks without a centralised controller responsible of aggregating data, however, is a challenging task. In particular, there is a local-to-global issue that makes the application of engineering principles challenging at least: designing device-local programs that, through interaction, guarantee a certain global service level. In this thesis, we first analyse the state of the art in coordination systems, then motivate the work by describing the main issues of pre-existing tools and practices and identifying the improvements that would benefit the design of such complex software ecosystems. The contribution can be divided in three main branches. First, we introduce a novel simulation toolchain for pervasive ecosystems, designed for allowing good expressiveness still retaining high performance. Second, we leverage existing coordination models and patterns in order to create new spatial structures. Third, we introduce a novel language, based on the existing ``Field Calculus'' and integrated with the aforementioned toolchain, designed to be usable for practical aggregate programming.

Analysis of Copy Number Variants identifies new candidate genes for Autism Spectrum Disorder and Intellectual Disability

Autism spectrum disorder (ASD) and Intellectual Disability (ID) are complex neuropsychiatric disorders characterized by extensive clinical and genetic heterogeneity and with overlapping risk factors. The aim of my project was to further investigate the role of Copy Numbers Variants (CNVs), identified through genome-wide studies performed by the Autism Geome Project (AGP) and the CHERISH consortium in large cohorts of ASD and ID cases, respectively. Specifically, I focused on four rare genic CNVs, selected on the basis of their impact on interesting ASD/ID candidate genes: a) a compound heterozygous deletion involving CTNNA3, predicted to cause the lack of functional protein; b) a 15q13.3 duplication containing CHRNA7; c) a 2q31.1 microdeletion encompassing KLHL23, SSB and METTL5; d) Lastly, I investigated the putative imprinting regulation of the CADPS2 gene, disrupted by a maternal deletion in two siblings with ASD and ID. This study provides further evidence for the role of CTNNA3, CHRNA7, KLHL23 and CADPS2 as ASD and/or ID susceptibility genes, and highlights that rare genetic variation contributes to disease risk in different ways: some rare mutations, such as those impacting CTNNA3, act in a recessive mode of inheritance, while other CNVs, such as those occurring in the 15q13.3 region, are implicated in multiple developmental and/or neurological disorders possibly interacting with other susceptibility variants elsewhere in the genome. On the other hand, the discovery of a tissue-specific monoallelic expression for the CADPS2 gene, implicates the involvement of epigenetic regulatory mechanisms as risk factors conferring susceptibility to ASD/ID.