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Analysis of differential expression of genes in a disease


geneCaotic

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I have a list of genes selected for a disease through microarray databases. The questions are as follows:

1. What is the implication of finding a biological pathway for these genes for a disease?

2. What is the implication of finding groups of genes that are associated with specific cellular functions (for example apoptosis, migration, ...), in a disease

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Well, I think that for the first question, a biological pathway can help to find interactions between gene products (proteins) and how these interactions are involved in the disease.

For the second question, I think that finding gene families with specific functions can give us an idea of the cellular processes involved in disease.

I do not know if I am correct, I have read but I have not been able to clarify the ideas. If you suddenly know of papers that can clarify these concepts for me, I would be grateful.

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This is one of the questions where there are a large number of "correct" answers. Also I do not think that it can be answered by one or two papers. It is one of the fundamental questions of "omics" research. I.e. how do molecular changes on the transcriptome/proteome/metabolome level relate to physiological changes in the organism. In some cases where the mechanisms are well known you could indeed find pathways that can explain certain features. However, they are not necessarily protein-protein interactions. Metabolic pathways, for example, are connected via the metabolites rather than direct protein interactions (for the most part).

But even identifying groups of genes involved in connected functions, it is often unclear how that affects the organism. Apoptosis, inflammation markers and so on are often indicative of damages of some sorts, but it does not necessarily tell you what kind of disease it is and how it causes these damages.

For microarrays there are additional challenges as they generally only indicate relative changes, which may or may not relate to physiological outcomes. Even more problematic, an increase in mRNA does not necessarily indicate a similar increase in protein. If you go through papers using microarray or other "omics" techniques, you will often see that authors often use these techniques as mere screening methods to identify significant changes (which has its own set of issues) and then often use validation studies or literature to hypothesize what their connection to a disease or condition is.

Other attempts are more quantitative, e.g. using a variety of modeling approaches, mostly using metabolomics and proteomics information, to reconstruct the metabolic pathways. This often is not as easy for other less well-known networks.

As a whole these are open-ended questions and instead of focusing on right or wrong you might want to explore what we can or cannot learn from this type of data (it also leads into the issue of high-dimensional data sets).

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