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Caratterizzazione molcolare di malattie multigeniche complesse.

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Presentazione sul tema: "Caratterizzazione molcolare di malattie multigeniche complesse."— Transcript della presentazione:

1 Caratterizzazione molcolare di malattie multigeniche complesse

2 AM-UniMi 2 biomarkers proteomica genome-wide association analysis

3 AM-UniMi 3 Proteomica – Proteoma Cosè la Proteomica? Il termine proteoma è stato coniato da Wilkins e Williams e indica il complesso di proteine derivanti da un dato genoma. La proteomica è lo studio del proteoma di un organismo La proteomica può essere classificata come : Classica o di espressione : lanalisi del genoma attraverso le proteine che esprime. Funzionale : lanalisi delle funzioni, interazioni, localizzazione cellulare e modificazioni post-traduzionali del prodotto genico

4 AM-UniMi 4 Proteomica – Proteoma Classical or expression proteomic, in which the proteomes of two (or more) differentially treated cell (or tissue) lines are initially separated and visualized by 2D gel electrophoresis upon which proteins that differ in abundance between the gels are identified by mass spectrometry.

5 AM-UniMi 5 Matrix Assisted Laser Desorption Ionization (MALDI) Si basa sulla possibilità di generare in fase vapore, ioni da macromolecole termicamente instabili, in una matrice non volatile per desorbimento/ionizzazione gli eventi di desorbimento/ionizzazione si verificano per azione di un raggio laser pulsante regolato sul massimo assorbimento della matrice Bakhtiar and Nelson, Biochem Pharm 59:891, 2000 si genera un pacchetto di ioni prevalentemente monocarica gli ioni vengono accellerati verso lanalizzatore solitamente a tempo di volo (TOF)

6 AM-UniMi 6 Analizzatore a tempo di volo (TOF) Laser a impulsi Tubo di volo Alto vuoto Alto voltaggio kV

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8 8 to confirm MW and identity of wild and recombinant protein to confirm MW and identity of wild and recombinant protein to identify post-translational modifications to identify post-translational modifications to characterize heterogeneous glycoproteins to characterize heterogeneous glycoproteins MALDI-TOF Applications in the protein field

9 AM-UniMi 9 Il lettore ha una sensibilità che arriva fino ad 1 fentomole e permette di assegnare la massa esatta alla classe di proteine legate Scegliere il chip sulla base dellapplicazione in studio. Applicare un volume di campione tra 5 e 500 l in ogni pozzetto Gli Ab fissati sulla superficie del chip catturano le proteine del campione. Un opportuno tampone assicura il legame ottimale tra proteine e Ab e ne migliora la selettività. Lavare i pozzetti per eliminare gli eventuali contaminanti. urface nhanced aser esorption nterface

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13 AM-UniMi 13 Abstract Surface-enhanced laser desorption time of flight mass spectrometry (SELDI-TOF-MS) is an important proteomic technology that is immediately available for the high throughput analysis of complex protein samples. Over the last few years, several studies have demonstrated that comparative protein profiling using SELDI-TOF-MS breaks new ground in diagnostic protein analysis particularly with regard to the identification of novel biomarkers.

14 AM-UniMi 14 Importantly, researchers have acquired a better understanding also of the limitations of this technology and various pitfalls in biomarker discovery. Bearing these in mind, great emphasis must be placed on the development of rigorous standards and quality control procedures for the pre-analytical as well as the analytical phase and subsequent bioinformatics applied to analysis of the data. To avoid the risk of false-significant results studies must be designed carefully and control groups accurately selected. In addition, appropriate tools, already established for analysis of highly complex microarray data, need to be applied to protein profiling data. To validate the significance of any candidate biomarker derived from pilot studies in appropriately designed prospective multi-center studies is mandatory; reproducibility of the clinical results must be shown over time and in different diagnostic settings. SELDI-TOF-MS-based studies that are in compliance with these requirements are now required; only a few have been published so far. In the meantime, further evaluation and optimization of both technique and marker validation strategies are called for before MS-based proteomic algorithms can be translated into routine laboratory testing.

15 AM-UniMi 15 Figure 3: Representative raw spectra and gel-view (grey-scale) of serum from a normal donor, and from patients with either BPH (benign prostate hyperplasia) or prostate cancer (PCA) using the IMAC3-Cu chip chemistry

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18 AM-UniMi 18 Indeed the real conclusion of these papers is not that the algorithm or the platform failed, but that the specifically selected ions, specific to the chip surface employed and the binding protocol conditions, were not robust and did not transcend sample variability. However, other investigators using different MALDI platforms, capture surfaces, and sample fractionization have recently described specific ion fingerprints that appear to contain diagnostic information and that hold up over time and over independent blinded sample sets (6–8, 12, 13 ). For example, Belluco et al. recently reported an ion classifier for detection of early-stage breast cancer that was robust across both blinded independent validation and independent prospective sample sets run 14 months later using the original ion classifier (12 ). Thus the utility of MS fingerprinting from body fluids for disease classification remains a very viable and attractive approach.

19 AM-UniMi 19 The solution to this problem is to generate a diagnostic biomarker readout that is independent of the measurement platform. In this case, sequencing and identification of the proteins or peptides underpinning the diagnostic peaks renders the output independent of the measurement platform. Once the proteins or protein isoforms are identified, then they can be measured by any suitable immunoassay or analytical system now or in the future. Instead of a pattern of unknown ions, the diagnostic test is based on a panel of known molecules. This approach is now the major one used for biomarker discovery. The output of an MS biomarker discovery workflow has become a list of specific identified proteins, or protein isoforms, that are differentially abundant between cases and controls (13, 14 ). The guiding principle for investigators pursuing biomarker discovery is to ensure that the biology, and the biomarkers themselves, remain independent from the changing technology.

20 AM-UniMi 20 Sciencexpress, April 2007

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22 AM-UniMi 22 Nanotecnologie e diabete Genome wide association studies (GWSA) Affymetrix / Illumina – SNPs Confermati studi precedenti (linkage/candidate gene) Identificati nuovi geni candidati

23 AM-UniMi 23 Frayling T. Nature Review Genetics September 2007

24 AM-UniMi 24 Varianti associate al diabete di tipo 2 KCNJ11 componente canale K/cellule beta/target farmaci classe sulphonylurea PPARG differenziazione adipociti/target farmaci classe thiazolodinedione TCF2 Fattore di trascrizione epatico WFS1 4 16p.3 AR diabete mellito + atrofia ottica Frayling T. Nature Review Genetics September 2007

25 AM-UniMi 25 Varianti associate al diabete di tipo 2 TCF7L2 TF espresso pancreas fetale/influenza secrezione di insulina/HHEX è un suo target/WNT pathways HHEX-IDE TF ruolo sviluppo pancreas/alterata secrezione insulina SCL30A8 trasportatore di zinco/espresso cellule beta CDKAL1/CDKN2A-2B IGF2BP2 FTO

26 AM-UniMi 26 Can Fishing for New Genes Catch Patients at Risk of Coronary Artery Disease? Clinical Chemistry 54:3 453–455 (2008) Editorial Joseph Emmerich1,2* Paul M Ridker3 1 INSERM, Paris, France 2 Universite´ Paris Descartes Faculte´ des Sciences Biologiques et Pharmaceutiques Paris, France 3 Center for Cardiovascular Disease Prevention Brigham and Womens Hospital Harvard Medical School Boston, MA

27 AM-UniMi 27.. in June of 2007 by a consortium of more than 50 British research groups participating in the Wellcome Trust Case-Control Consortium (WTCCC). Working collaboratively, the WTCCC investigators studied cases of 7 common diseases and 3000 shared controls and identified 24 independent association signals, 1 in bipolar disease, 1 in coronary disease, 9 in Crohn disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes, and 3 in type 2 diabetes, each with a statistical effect approaching or exceeding genome–wide levels of significance (1 ).

28 AM-UniMi 28 Remarkably, the key finding in this study for coronary heart diseasea clear association between vascular risk and common variation in the region of chromosome 9p21.3was rapidly validated in a series of similar GWAS studies, including the Cardiogenics Consortium; the Ottawa, Dallas, and Framingham Heart Studies; and the DeCode Genetics program in Iceland (2–5 ). The chromosome 9p21.3 region contains the coding sequences of genes for 2 cyclin-dependent kinase inhibitors known to play roles in tumor suppression, cell proliferation, and apoptosis. Thus, these validated GWAS findings for coronary disease not only raise the concept of a novel genetic determinant of disease, but also provide strong pathophysiologic support for prior work linking each of these processes directly to atherogenesis and plaque disruption.

29 AM-UniMi 29 What is less clear from emerging GWAS studies is whether or not the discovery of new gene-disease associations will ultimately help identify persons at high risk, particularly for complex disorders such as atherothrombosis, for which major environmental determinants exist.

30 AM-UniMi 30 Heath SHeath S. Robledo R. Beggs W. Feola G. Parodo C. Rinaldi A. Contu L. Dana D. Stambolian D. Siniscalco M.Robledo RBeggs WFeola GParodo CRinaldi AContu LDana DStambolian DSiniscalco M A novel approach to search for identity by descent in small samples of patients and controls from the same mendelian breeding unit: a pilot study on myopia. Human Heredity. 52(4):183-90, Autosomal dominant high myopia, a genetic disorder already mapped to region 18p11.31, is common in Carloforte (Sardinia, Italy), an isolated village of 8,000 inhabitants descending from a founder group of 300 in the early 1700s. Fifteen myopic propositi and 36 normal controls were selected for not having ancestors in common at least up to the grandparental generation, although still descendants of the original founders. All subjects were genotyped for 14 markers located on autosome 18 at a resolution of about 10 cM. Allelic distributions were found to be similar at all tested loci in propositi and controls, except for the candidate marker D18S63 known to segregate in close linkage association with high myopia. In particular, the frequency of allele 85 among the propositi was almost double that of the controls (Fisher's exact test, p = 0.037). The association is more striking when the frequency of the genotype 85/85 in the two groups is compared (Fisher's exact test, p = 0.005). This conclusion was further evaluated through a bootstrap analysis by computing the overall probability of the observed data under the null hypothesis (i.e. no difference between the two groups in frequency distributions for the chromosome 18 markers). Again, marker D18S63 was found to have a sample probability lower than 0.004, which is significant at the 0.05 level after correcting for simultaneous testing of multiple loci. The study demonstrates the efficiency of our novel strategy to detect identity by descent (IBD) in small numbers of patients and controls when they are both part of well-defined Mendelian breeding units (MBUs). The iterative application of our strategy in separate MBUs is expected to become the method of choice to evaluate the ever-growing number of reported associations between candidate genes and multifactorial traits and diseases.


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