Genetica molecolare dell'autismo: studi di associazione ed analisi di geni candidati

Autism is a neurodevelpmental disorder characterized by impaired verbal communication, limited reciprocal social interaction, restricted interests and repetitive behaviours. Twin and family studies indicate a large genetic contribution to ASDs (Autism Spectrum Disorders). During my Ph.D. I have been involved in several projects in which I used different genetic approaches in order to identify susceptibility genes in autism on chromosomes 2, 7 and X: 1)High-density SNP association and CNV analysis of two Autism Susceptibility Loci. The International Molecular Genetic Study of Autism Consortium (IMGSAC) previously identified linkage loci on chromosomes 7 and 2, termed AUTS1 and AUTS5, respectively. In this study, we evaluated the patterns of linkage disequilibrium (LD) and the distribution of haplotype blocks, utilising data from the HapMap project, across the two strongest peaks of linkage on chromosome 2 and 7. More than 3000 SNPs have been selected in each locus in all known genes, as well as SNPs in non-genic highly conserved sequences. All markers have been genotyped to perform a high-density association analysis and to explore copy number variation within these regions. The study sample consisted of 127 and 126 multiplex families, showing linkage to the AUTS1 and AUTS5 regions, respectively, and 188 gender-matched controls. Association and CNV analysis implicated several new genes, including IMMP2L and DOCK4 on chromosome 7 and ZNF533 and NOSTRIN on the chromosome 2. Particularly, my contribution to this project focused on the characterization of the best candidate gene in each locus: On the AUTS5 locus I carried out a transcript study of ZNF533 in different human tissues to verify which isoforms and start exons were expressed. High transcript variability and a new exon, never described before, has been identified in this analysis. Furthermore, I selected 31 probands for the risk haplotype and performed a mutation screen of all known exons in order to identify novel coding variants associated to autism. On the AUTS1 locus a duplication was detected in one multiplex family that was transmitted from father to an affected son. This duplication interrupts two genes: IMMP2L and DOCK4 and warranted further analysis. Thus, I performed a screening of the cohort of IMGSAC collection (285 multiplex families), using a QMPSF assay (Quantitative Multiplex PCR of Short fluorescent Fragments) to analyse if CNVs in this genic region segregate with autism phenotype and compare their frequency with a sample of 475 UK controls. Evidence for a role of DOCK4 in autism susceptibility was supported by independent replication of association at rs2217262 and the finding of a deletion segregating in a sib-pair family. 2)Analysis of X chromosome inactivation. Skewed X chromosome inactivation (XCI) is observed in females carrying gene mutations involved in several X-linked syndromes. We aimed to estimate the role of X-linked genes in ASD susceptibility by ascertaining the XCI pattern in a sample of 543 informative mothers of children with ASD and in a sample of 164 affected girls. The study sample included families from different european consortia. I analysed the XCI inactivation pattern in a sample of italian mothers from singletons families with ASD and also a control groups (144 adult females and 40 young females). We observed no significant excess of skewed XCI in families with ASD. Interestingly, two mothers and one girl carrying known mutations in X-linked genes (NLGN3, ATRX, MECP2) showed highly skewed XCI, suggesting that ascertainment of XCI could reveal families with X-linked mutations. Linkage analysis was carried out in the subgroup of multiplex families with skewed XCI (≥80:20) and a modest increased allele sharing was obtained in the Xq27-Xq28 region, with a peak Z score of 1.75 close to rs719489. In this region FMR1 and MECP2 have been associated in some cases with austim and therefore represent candidates for the disorder. I performed a mutation screen of MECP2 in 33 unrelated probands from IMGSAC and italian families, showing XCI skewness. Recently, Xq28 duplications including MECP2, have been identified in families with MR, with asymptomatic carrier females showing extreme (>85%) skewing of XCI. For these reason I used the sample of probands from X-skewed families to perform CNV analysis by Real-time quantitative PCR. No duplications have been found in our sample. I have also confirmed all data using as alternative method the MLPA assay (Multiplex Ligation dependent Probe Amplification). 3)ASMT as functional candidate gene for autism. Recently, a possible involvement of the acetylserotonin O-methyltransferase (ASMT) gene in susceptibility to ASDs has been reported: mutation screening of the ASMT gene in 250 individuals from the PARIS collection revealed several rare variants with a likely functional role; Moreover, significant association was reported for two SNPs (rs4446909 and rs5989681) located in one of the two alternative promoters of the gene. To further investigate these findings, I carried out a replication study using a sample of 263 affected individuals from the IMGSAC collection and 390 control individuals. Several rare mutations were identified, including the splice site mutation IVS5+2T>C and the L326F substitution previously reported by Melke et al (2007), but the same rare variants have been found also in control individuals in our study. Interestingly, a new R319X stop mutation was found in a single autism proband of Italian origin and is absent from the entire control sample. Furthermore, no replication has been found in our case-control study typing the SNPs on the ASMT promoter B.

Analysis of eruptive and seismic sequences to improve the short-and long-term eruption forecasting

Forecasting the time, location, nature, and scale of volcanic eruptions is one of the most urgent aspects of modern applied volcanology. The reliability of probabilistic forecasting procedures is strongly related to the reliability of the input information provided, implying objective criteria for interpreting the historical and monitoring data. For this reason both, detailed analysis of past data and more basic research into the processes of volcanism, are fundamental tasks of a continuous information-gain process; in this way the precursor events of eruptions can be better interpreted in terms of their physical meanings with correlated uncertainties. This should lead to better predictions of the nature of eruptive events. In this work we have studied different problems associated with the long- and short-term eruption forecasting assessment. First, we discuss different approaches for the analysis of the eruptive history of a volcano, most of them generally applied for long-term eruption forecasting purposes; furthermore, we present a model based on the characteristics of a Brownian passage-time process to describe recurrent eruptive activity, and apply it for long-term, time-dependent, eruption forecasting (Chapter 1). Conversely, in an effort to define further monitoring parameters as input data for short-term eruption forecasting in probabilistic models (as for example, the Bayesian Event Tree for eruption forecasting -BET_EF-), we analyze some characteristics of typical seismic activity recorded in active volcanoes; in particular, we use some methodologies that may be applied to analyze long-period (LP) events (Chapter 2) and volcano-tectonic (VT) seismic swarms (Chapter 3); our analysis in general are oriented toward the tracking of phenomena that can provide information about magmatic processes. Finally, we discuss some possible ways to integrate the results presented in Chapters 1 (for long-term EF), 2 and 3 (for short-term EF) in the BET_EF model (Chapter 4).

Antipodal random sequences with prescribed second-order statistics: application to Compressive Sensing and UWB system based on DS-CDMA

It is usual to hear a strange short sentence: «Random is better than...». Why is randomness a good solution to a certain engineering problem? There are many possible answers, and all of them are related to the considered topic. In this thesis I will discuss about two crucial topics that take advantage by randomizing some waveforms involved in signals manipulations. In particular, advantages are guaranteed by shaping the second order statistic of antipodal sequences involved in an intermediate signal processing stages. The first topic is in the area of analog-to-digital conversion, and it is named Compressive Sensing (CS). CS is a novel paradigm in signal processing that tries to merge signal acquisition and compression at the same time. Consequently it allows to direct acquire a signal in a compressed form. In this thesis, after an ample description of the CS methodology and its related architectures, I will present a new approach that tries to achieve high compression by design the second order statistics of a set of additional waveforms involved in the signal acquisition/compression stage. The second topic addressed in this thesis is in the area of communication system, in particular I focused the attention on ultra-wideband (UWB) systems. An option to produce and decode UWB signals is direct-sequence spreading with multiple access based on code division (DS-CDMA). Focusing on this methodology, I will address the coexistence of a DS-CDMA system with a narrowband interferer. To do so, I minimize the joint effect of both multiple access (MAI) and narrowband (NBI) interference on a simple matched filter receiver. I will show that, when spreading sequence statistical properties are suitably designed, performance improvements are possible with respect to a system exploiting chaos-based sequences minimizing MAI only.

Low Correlated Sequences & Architectures and Algorithms for Analog-to-Information Converters: Theory, Design, Implementation and Applications.

Most electronic systems can be described in a very simplified way as an assemblage of analog and digital components put all together in order to perform a certain function. Nowadays, there is an increasing tendency to reduce the analog components, and to replace them by operations performed in the digital domain. This tendency has led to the emergence of new electronic systems that are more flexible, cheaper and robust. However, no matter the amount of digital process implemented, there will be always an analog part to be sorted out and thus, the step of converting digital signals into analog signals and vice versa cannot be avoided. This conversion can be more or less complex depending on the characteristics of the signals. Thus, even if it is desirable to replace functions carried out by analog components by digital processes, it is equally important to do so in a way that simplifies the conversion from digital to analog signals and vice versa. In the present thesis, we have study strategies based on increasing the amount of processing in the digital domain in such a way that the implementation of analog hardware stages can be simplified. To this aim, we have proposed the use of very low quantized signals, i.e. 1-bit, for the acquisition and for the generation of particular classes of signals.

Seismic sequences analysis for estimation of earthquake source parameters: corner frequency, stress drop, and seismic moment observations

The present study has been carried out with the following objectives: i) To investigate the attributes of source parameters of local and regional earthquakes; ii) To estimate, as accurately as possible, M0, fc, Δσ and their standard errors to infer their relationship with source size; iii) To quantify high-frequency earthquake ground motion and to study the source scaling. This work is based on observational data of micro, small and moderate -earthquakes for three selected seismic sequences, namely Parkfield (CA, USA), Maule (Chile) and Ferrara (Italy). For the Parkfield seismic sequence (CA), a data set of 757 (42 clusters) repeating micro-earthquakes (0 ≤ MW ≤ 2), collected using borehole High Resolution Seismic Network (HRSN), have been analyzed and interpreted. We used the coda methodology to compute spectral ratios to obtain accurate values of fc , Δσ, and M0 for three target clusters (San Francisco, Los Angeles, and Hawaii) of our data. We also performed a general regression on peak ground velocities to obtain reliable seismic spectra of all earthquakes. For the Maule seismic sequence, a data set of 172 aftershocks of the 2010 MW 8.8 earthquake (3.7 ≤ MW ≤ 6.2), recorded by more than 100 temporary broadband stations, have been analyzed and interpreted to quantify high-frequency earthquake ground motion in this subduction zone. We completely calibrated the excitation and attenuation of the ground motion in Central Chile. For the Ferrara sequence, we calculated moment tensor solutions for 20 events from MW 5.63 (the largest main event occurred on May 20 2012), down to MW 3.2 by a 1-D velocity model for the crust beneath the Pianura Padana, using all the geophysical and geological information available for the area. The PADANIA model allowed a numerical study on the characteristics of the ground motion in the thick sediments of the flood plain.