ADNI data is made available to researchers around the world. As such, there are many active research projects accessing and applying the shared ADNI data. To further encourage Alzheimer’s disease research collaboration, and to help prevent duplicate efforts, the list below shows the specific research focus of the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Pablo Moscato |
| Institution: | University of Newcastle |
| Department: | Information-Based Medicin |
| Country: | |
| Proposed Analysis: | Our research group has been pioneering the use of multivariate approaches based on combinatorial optimization to identify molecular signatures of different diseases, in some cases leading the analysis for international consortium studies (e.g. Riveros et al, 2010). One of our main focuses in recent years has been the identification of biomarker signatures for Alzheimer’s disease (AD) based on levels of plasma proteins. We have published two manuscripts demonstrating the utility of our methods in the context of AD biomarkers (Gomez Ravetti & Moscato, 2008; Rocha de Paula et al., 2011), based on the dataset contributed by Ray and colleagues (Ray et al., 2007). However this dataset has various limitations. Firstly, raw data are not available, raising concerns about the absolute levels of certain proteins in the plasma and their detectability by other assays. Secondly, and possibly consequently, other groups have not been able to replicate the findings reported from the original study by Ray and colleagues (e.g. Soares et al. 2009). The ADNI Plasma Proteome Dataset represents a substantial improvement on the datasets to which we have previously had access, with a larger sample, availability of raw data and detailed documentation relating to the experimental procedures and data analysis. We propose to apply our analytical approaches to the ADNI Plasma Proteome Dataset to identify protein signatures that might be useful for: 1) the diagnosis of pre-clinical AD 2) differentiating MCI patients that develop AD from those who do not Following these analyses, we will attempt to validate the sensitivity and specificity of these signatures in an Australian cohort. We anticipate that by applying our analytical methods to the ADNI dataset we will be able to make a unique contribution to the quest for finding reliable and reproducible biomarkers of early AD. References Gomez Ravetti M, Moscato P (2008) Identification of a 5-protein biomarker molecular signature for predicting Alzheimer’s disease. PLoS ONE 3: e3111 Ray S, Britschgi M, Herbert C, Takeda-Uchimura Y, Boxer A, Blennow K, Friedman LF, Galasko DR, Jutel M, Karydas A, Kaye JA, Leszek J, Miller BL, Minthon L, Quinn JF, Rabinovici GD, Robinson WH, Sabbagh MN, So YT, Sparks DL, Tabaton M, Tinklenberg J, Yesavage JA, Tibshirani R, Wyss-Coray T (2007) Classification and prediction of clinical Alzheimer’s diagnosis based on plasma signalling proteins. Nat Med 13: 1359-62 Riveros C, Mellor D, Gandhi KS, McKay FC, Cox MB, Berretta R, Vaezpour SY, Inostroza-Ponta M, Broadley SA, Heard RN, Vucic S, Stewart GJ, Williams DW, Scott RJ, Lechner-Scott J, Booth DR, Moscato P; ANZgene Multiple Sclerosis Genetics Consortium (2010) A transcription factor map as revealed by a genome-wide gene expression analysis of whole-blood mRNA transcriptome in multiple sclerosis. PLoS ONE 5: e14176. Rocha de Paula M, Gomez Ravetti M, Berretta R, Moscato P (2011) Differences in abundances of cell-signalling proteins in blood reveal novel biomarkers for early detection of clinical Alzheimer’s disease. PLoS ONE (accepted pending minor revisions) Soares HD, Chen Y, Sabbagh M, Rohrer A, Schrijvers E, Breteler M (2009) Identifying early markers of Alzheimer’s disease using quantitative multiplex proteomic immunoassay panels. Ann NY Acad Sci 1180: 56-67 |
| Additional Investigators | |
| Investigator's Name: | Dan Johnstone |
| Proposed Analysis: | This investigator will be involved in the analyses outlined by the Prinicpal Investigator. |
| Investigator's Name: | Liz Milward |
| Proposed Analysis: | This investigator will be involved in the analyses outlined by the Prinicpal Investigator. |
| Investigator's Name: | Regina Berretta |
| Proposed Analysis: | This investigator will be involved in the analyses outlined by the Prinicpal Investigator. |
| Investigator's Name: | Carlos Riveros |
| Proposed Analysis: | Dear Colleagues, With Dr. Riveros, who is a Computational Scientist employed in my Centre, we are interested in analysis of GWAS data available from ADNI. We have developed a new supercomputing-based approach to investigate gene-gene interaction analysis. The method has been developed over the past two years and has not been applied to AD data. We are looking for collaborations with other members of ADNI to use it in a variety of datasets. At present, we have used for the analysis of age-related macular degeneration (a project that was funded for approximately one million dollars). We have conducted a preliminary analysis that was already published and we have a paper submitted to PLoS ONE which describes the methodology in detail. We think that due to our expertise in AD, it would be useful for us to now analyze other GWAS available to the consortia in this second state of our algorithmic development process. References can be provided about the method, or a more in-depth explanation if necessary. We hope to liase with other collaborators and or to cooperate in being co-investigator of future grants. This is also an important issue for us to show the internationalization of our activities, apart of that of doing secondary analyses of data. In particular, I aim to help in the experimental design. With some of my current proposed biomarkers for AD now being confirmed/validated by some other groups, I hope my advice on the introduction of some of them into ADNI experimental design would help to improve both the specificity and sensitivity of the tests. I look forward to more collaboration with this group (and receive advice on GWAS available and the need or not of secondary analyses on these). There are other areas that interest us like gene expression, automated image analysis, EEG data analysis, etc. Our expertise is not only in proteomics. Sincerely Yours, Professor Pablo Moscato Co-Director - Priority Research Centre for Bioinformatics, Biomarker Discovery and Information-based Medicine http://www.newcastle.edu.au/research/cibm/ Chief Investigator - ARC Centre of Excellence in Bioinformatics http://bioinformatics.org.au Strategic Research Advisory Panel and Deputy Director of the Information-based Medicine Program, Hunter Medical Research Institute http://www.hmri.net.au/ Research Coordinator for Computer Science and Software Engineering and School International Student Advisor School of Electrical Engineering and Computer Science The University of Newcastle, Callaghan, 2308, NSW AUSTRALIA "Multi famam, conscientiam pauci verentur." Email: Pablo.Moscato@newcastle.edu.au Phone : +61 2 4921 6056 Fax: +61-2-4921-6929 |