another until recently. Over the last two years however, they have been putting their heads together and are currently working on their first major publication. “We are now using what I would call an integrated functional genomic approach for LOAD, which is based on combining the genetic expression data with mechanistic studies,” says Huttunen. By bringing together genetic and
molecular data, the researchers have now defined a comprehensive set of in vivo and in vitro platforms that allows the researchers
outcome measures
to assess and elucidate the of
the risk genes.
Focusing on the pathways that are relevant to LOAD, it has been possible to identify the mechanisms that underlie each particular risk gene. Having a group that encompasses the whole range of
research in this way is
almost unprecedented, as Hiltunen explains: “Usually a consortium will focus upon one topic. In our case, for example, they might focus on identifying genes. But by combining data from a variety of angles, a considerable amount of value is added to the work.”
working on ways of combining genetic data with molecular studies in order to try and paint a clearer picture of the way in which each gene
contributes to the aetiology
(causes) of LOAD. “We want to look at how these risk genes are changed in regards to expression and splicing in affected brains in relation to Alzheimer’s Disease-related pathology,” explains Hitunen. “We also
has been focused upon the genetic assessment and analysis of LOAD. They have been a part of many of the major findings recently published in the field relating to identifying novel candidate genes. Although most of the common variants have now already been identified, there is still much work to be done in terms of sequencing and assessing and identifying the rare variants.
“We are currently working on combing clinical biochemical imaging data with genetic data so that we can calculate risk values for individuals”
want to combine this with functional studies, looking at cells in the laboratory, silencing genes one by one and really seeing how they affect certain pathways known to be essential in the disease process.” Hiltunen’s group at the University of Eastern Finland over the last two decades
www.projectsmagazine.eu.com Huttunen’s work, on the other hand, is
more neuroscience oriented, looking at LOAD as well as other neurodegenerative diseases from a cellular and molecular level. Although both professors’ work deals with the same disease, their research has remained
largely independent of one
Predicting disease risk Understanding the way in which the target genes affect molecular mechanisms in the brain of LOAD patients helps the researchers in identifying therapeutic targets. However, the same information can also be exploited to provide information that can be used for risk assessments, biomarker analysis and early diagnosis so that future patients can be identified earlier. At the University of Eastern Finland, Hiltunen has been compiling individual assessors that can be used to help in prediction: “We are currently working on combining clinical biochemical data with genetic data so that we can calculate risk values for individuals. In the future, we want to combine data from every possible source: DNA, cerebrospinal fluid, saliva, plasma, MRI scans and more, to create a comprehensive biomarker-based prediction tool. The aim is to start identifying patients before they are even exhibiting any outwards signs of Alzheimer’s disease.” At present, the history of mechanism-
based drug trials for Alzheimer’s disease has been one of abject failure. One of the contributing reasons
to this failure has
been the inability to stratify the patients who are at severe risk. “In all of the Alzheimer’s disease clinical trials to date, very mixed populations of patients have
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