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Papers of the Month

By Jerry Phelps
May 2006

1) Walsh T, Casadei S, Coats KH, Swisher E, Stray SM, Higgins J, Roach KC, Mandell J, Lee MK, Ciernikova S, Foretova L, Soucek P, King MC. Spectrum of mutations in BRCA1, BRCA2, CHEK2, and TP53 in families at high risk of breast cancer. JAMA. 2006 Mar 22;295(12):1379-88. (Mary-Claire King, Ph.D., Departments of Medicine and Genome Sciences, University of Washington, NIEHS Grant R01ES013160.)

Implications: This study demonstrates that commercial genetic testing does not detect all mutations in women with a strong familial history of breast and ovarian cancer. According to Dr. King, these findings are important because "risk reduction interventions for those with mutations are highly effective." The results suggest that commercial testing should be expanded to include these and possibly other mutations so that at-risk women have the best information available when deciding to undergo invasive interventions such as preventive mastectomy or ovary removal.

2) Dominici F, Peng RD, Bell ML, Pham L, McDermott A, Zeger SL, Samet JM. Fine particulate air pollution and hospital admission for cardiovascular and respiratory diseases. JAMA. 2006 Mar 8;295(10):1127-34. (Francesca Dominici, Ph.D.; Scott L. Zeger, Ph.D.; and Jonathan M. Samet, MD; Departments of Biostatistics and Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, NIEHS Grants R01ES12054 and P30ES03819.)

Implications: This study shows that exposure to PM2.5 at levels within the current standard is a risk factor for cardiovascular disease in elderly persons. Additional efforts need to be targeted towards identifying the sources of these particles and designing new strategies to prevent their release. Additional biomedical strategies include identifying the characteristics of fine particles responsible for these adverse effects so that new strategies can be developed to prevent or treat them.

3) Stephens M, Sloan JS, Robertson PD, Scheet P, Nickerson DA. Automating sequence-based detection and genotyping of SNPs from diploid samples. Nat Genet. 2006 Mar; 38(3):375-81. (Deborah Nickerson, Ph.D. Department of Genome Sciences, University of Washington, NIEHS Contract N01ES15478.)

Implications: The new algorithm presented by these investigators makes considerable advances in methods for SNP identification and genotyping and could greatly ease and enhance automation in these efforts. PolyPhred is available free-of-charge to academic and non-profit institutions and is compatible with a number of computing platforms. To learn more about the software, visit: http://droog.gs.washington.edu/PolyPhred.html.

4) Thomas DM, Francescutti-Verbeem DM, Kuhn DM. Gene expression profile of activated microglia under conditions associated with dopamine neuronal damage. FASEB J. 2006 Mar;20(3):515-7. (Donald M. Kuhn, Ph.D., Department of Psychiatry and Behavioral Neurosciences and Center for Molecular Medicine and Genetics, Wayne State University, NIEHS Grant P30ES06639.)

Implications: Microglial activation has been linked to numerous neurological conditions including Alzheimer's disease, amyotropic lateral sclerosis, Creutsfeldt-Jakob disease, and especially those that target the dopamine-producing neurons such as Parkinson's disease. Therefore the panel of genes differentially regulated by the three microglial activators in these experiments provides a number of possibilities for future studies to search for early biomarkers of neuronal damage associated with activated microglia.



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