User talk:The Biology Group: Difference between revisions
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'''Type I Diabetes''' | '''Type I Diabetes''' | ||
From the interacting chromosomal regions explored by Bergholdt et. al, the WDR1, LMO7, HNRPLL and RPS15A genes are potential T1D candidate genes. These genes are involved in transcriptional regulation, DNA binding, RNA binding, ion channel activity, ATP synthesis, actin binding and natural killer cell mediated cytotoxicity and cell proliferation. Other networks with TNFA (a gene proposed to be essential to the onset of T1D because of its locus near HLA) include genes involved in signal transduction, regulation of transcription, protein biosynthesis and folding, histone activity, ubiquitin-protein ligase activity, as well as response to oxidative stress, also of potential relevance in T1D pathogenesis. | |||
[[Image: TD1.jpeg|thumb|right|Protein network interactions described by Bergholdt et. al in Type I Diabetes]] | [[Image: TD1.jpeg|thumb|right|Protein network interactions described by Bergholdt et. al in Type I Diabetes]] | ||
[[Image: TD12.jpeg|thumb|right|Significant functional modules described by Bergholdt et. al in Type I Diabetes]] | |||
'''Polygenic hypercholesterolemia''' | '''Polygenic hypercholesterolemia''' | ||
Revision as of 20:45, 2 November 2009
For Tuesday, November 3rd
Epistasis--what it means, what it doesn't mean...
Questions to Consider thus Far
1. Two-loci modeling, three-loci, four-loci...How complex do we want to get? We need to keep in mind that all though the epistatic interactions we want to characterize are the antithesis of the one-gene, one-phenotype characterization of Mendelian inheritance, a model for a two-locus characterization for multigenic traits may be an oversimplification...but certainly a good place to start!
2. Do we want to also consider plieotrophy in assessing risk? That is to say, if we find a SNP with multiple disease associations, how do we determine which disease risk is greatest, in conjunction with other SNP information/risk we may have?
Disease Investigations for Method Validation
Type 2 diabetes is a late-onset disease that may be of interest, as it is both polygenic and includes behavioral/environment risk. Janssens and van Duijn point out that rather than being predictive, genes contributing to heart disease and diabetes can lead to behavioral changes which try to lower risk of developing the disease [1].
Prior to this, Weedon et al. showed that having multiple allele copies increases risk in accordance with a multiplicative model [2] (this type of statistical information can be used in affirming the effectiveness of our modeling). However, other studies such as here [3] and here [4] found that lifestyle/phenotypic factors and family history were more predictive that genetics in whether someone would actually develop diabetes.
As a side-note, I was slightly amused that a google scholar search for "highly predictive polygenic disease" turns up zero hits. Hopefully this will change in the years to come...
Type I Diabetes
From the interacting chromosomal regions explored by Bergholdt et. al, the WDR1, LMO7, HNRPLL and RPS15A genes are potential T1D candidate genes. These genes are involved in transcriptional regulation, DNA binding, RNA binding, ion channel activity, ATP synthesis, actin binding and natural killer cell mediated cytotoxicity and cell proliferation. Other networks with TNFA (a gene proposed to be essential to the onset of T1D because of its locus near HLA) include genes involved in signal transduction, regulation of transcription, protein biosynthesis and folding, histone activity, ubiquitin-protein ligase activity, as well as response to oxidative stress, also of potential relevance in T1D pathogenesis.
Polygenic hypercholesterolemia SNPedia includes these SNPs as causitive in inheritance for high cholesterol, along with environmental factors: APOB, CEPT, INSIG2, PON1 (L55M), and PCSK9 (E670G), among others.
Rheumatoid arthritis SNPedia includes these SNPs as causitive in inheritance for rheumatoid arthritis: VARS2L, PTPN22, C5TRAF1, CTLA4, PADI4, and NOS3, among others.
