Genomic convergence

Genomic convergence is a multifactor approach used in genetic research that combines different kinds of genetic data analysis to identify and prioritize susceptibility genes for a complex disease.

Early Applications

In January 2003, Michael Hauser along with fellow researchers at the Duke Center for Human Genetics (CHG) coined the term “genomic convergence” to describe their endeavor to identify genes affecting the expression of Parkinson disease (PD). Their work successfully combined serial analysis of gene expression (SAGE) with genetic linkage analysis. The authors explain, “While both linkage and expression analyses are powerful on their own, the number of possible genes they present as candidates for PD or any complex disorder remains extremely large”.[1] The convergence of the two methods allowed researchers to decrease the number of possible PD genes to consider for further study.

Their success prompted further use of the genomic convergence method at the CHG, and in July 2003 Yi-Ju Li, et al. published a paper revealing that glutathione S-transferase omega-1 (GSTO1) modifies the age-at-onset (AAO) of Alzheimer disease (AD) and PD.[2]

In May 2004, Dr. Margaret Pericak-Vance, currently the director of the John P. Hussman Institute for Human Genomics at the University of Miami Miller School of Medicine and then the director of the CHG, articulated the value of the genomic convergence method at a New York Academy of Sciences (NYAS) keynote address entitled "Novel Methods in Genetic Exploration of Neurodegenerative Disease." She stated, "No single method is going to get us where we need to be with these complex traits. It is going to take a combination of methods to dissect the underlying etiology of these disorders".[3]

Recent and Future Applications

Genomic convergence has a countless number of creative applications that combine the strengths of different analyses and studies. Maher Noureddine et al., note in their 2005 paper, “One of the growing problems in the study of complex diseases is how to prioritize research and make sense of the immense amount of data now readily available at the click of a computer mouse...The best approach may be to take advantage of the strengths of both…SAGE …and microarrays”.[4]

The results of combining methods of analysis have continued to be promising. Sofia Oliveira et al. (2005) combined gene expression, linkage data, and “iterative association mapping” to identify several genes associated with PD AAO.[5]

Future studies will continue to apply genomic convergence to elucidate the etiology of complex diseases. Dr. Jeff Vance, Director of the Morris K. Udall PD Research Center of Excellence, notes, “Genomic convergence is really no different from mathematical convergence – the more angles from which you can come at a problem, the better chance you have of solving it”.[6]

References

  1. Hauser MA, Li YJ, Takeuchi S, et al. (March 2003). "Genomic convergence: identifying candidate genes for Parkinson's disease by combining serial analysis of gene expression and genetic linkage". Hum. Mol. Genet. 12 (6): 671–7. doi:10.1093/hmg/12.6.671. PMID 12620972.
  2. Li YJ, Oliveira SA, Xu P, et al. (December 2003). "Glutathione S-transferase omega-1 modifies age-at-onset of Alzheimer disease and Parkinson disease". Hum. Mol. Genet. 12 (24): 3259–67. doi:10.1093/hmg/ddg357. PMID 14570706.
  3. "Genetic Exploration of Alzheimer's and Parkinson's Diseases". eBriefings. The New York Academy of Sciences.
  4. Noureddine MA, Li YJ, van der Walt JM, et al. (October 2005). "Genomic convergence to identify candidate genes for Parkinson disease: SAGE analysis of the substantia nigra". Mov. Disord. 20 (10): 1299–309. doi:10.1002/mds.20573. PMID 15966006.
  5. Oliveira SA, Li YJ, Noureddine MA, et al. (August 2005). "Identification of risk and age-at-onset genes on chromosome 1p in Parkinson disease". Am. J. Hum. Genet. 77 (2): 252–64. doi:10.1086/432588. PMC 1224528Freely accessible. PMID 15986317.
  6. "Udall Centers Meeting Points Up Parkinson's Work at Duke" (PDF). GenomeLIFE. 1: 10–4. September 2003.
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