There are some other papers of interest in the May 2004 edition of the American Journal of Human Genetics. Here is one:
A High-Density Admixture Map for Disease Gene Discovery in African Americans
Michael W. Smith,1,2 Nick Patterson,3 James A. Lautenberger,1 Ann L. Truelove,1,2 Gavin J. McDonald,3,4 Alicja Waliszewska,3,5,6 Bailey D. Kessing,1,2 Michael J. Malasky,1,2 Charles Scafe,10 Ernest Le,3 Philip L. De Jager,3,5,6 Andre A. Mignault,4 Zeng Yi,11 Guy de Thé,12 Myron Essex,7 Jean-Louis Sankalé,7 Jason H. Moore,13,14 Kwabena Poku,16 John P. Phair,17 James J. Goedert,18 David Vlahov,19 Scott M. Williams,13,14,15 Sarah A. Tishkoff,20 Cheryl A. Winkler,1,2 Francisco M. De La Vega,10 Trevor Woodage,10 John J. Sninsky,21 David A. Hafler,3,5,6 David Altshuler,3,4,8,9 Dennis A. Gilbert,10 Stephen J. O'Brien,1 and David Reich3,4
1Laboratory of Genomic Diversity, National Cancer Institute, and 2Basic Research Program, Science Applications International Corporation, National Cancer Institute, Frederick, MD; 3Program in Medical and Population Genetics, Broad Institute, Cambridge, MA; 4Department of Genetics and 5Laboratory of Molecular Immunology, Harvard Medical School, 6Center for Neurologic Disease, Brigham and Women's Hospital, 7Harvard AIDS Institute and Department of Immunology and Infectious Diseases, Harvard School of Public Health, and Departments of 8Medicine and 9Molecular Biology, Massachusetts General Hospital, Boston; 10Applied Biosystems, Foster City, CA; 11Institute of Virology, Chinese Academy of Preventive Medicine, Beijing; 12Department of Viral Oncology-Epidemiology, Institut Pasteur, Centre National de la Recherche Scientifique, Paris; 13Department of Molecular Physiology and Biophysics, 14Center for Human Genetics Research, and 15Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University, Nashville, TN; 16School of Administration, University of Ghana, Legon, Ghana; 17Howard Brown Health Center and Department of Medicine, Northwestern University, Chicago; 18Viral Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD; 19Center for Urban Epidemiologic Studies, New York Academy of Medicine, New York; 20Department of Biology, University of Maryland, College Park, MD; and 21Celera Diagnostics, Alameda, CA
Received January 26, 2004; accepted for publication March 3, 2004; electronically published April 14, 2004.
Admixture mapping (also known as "mapping by admixture linkage disequilibrium," or MALD) provides a way of localizing genes that cause disease, in admixed ethnic groups such as African Americans, with 100 times fewer markers than are required for whole-genome haplotype scans. However, it has not been possible to perform powerful scans with admixture mapping because the method requires a dense map of validated markers known to have large frequency differences between Europeans and Africans. To create such a map, we screened through databases containing 450,000 single-nucleotide polymorphisms (SNPs) for which frequencies had been estimated in African and European population samples. We experimentally confirmed the frequencies of the most promising SNPs in a multiethnic panel of unrelated samples and identified 3,011 as a MALD map (1.2 cM average spacing). We estimate that this map is 70% informative in differentiating African versus European origins of chromosomal segments. This map provides a practical and powerful tool, which is freely available without restriction, for screening for disease genes in African American patient cohorts. The map is especially appropriate for those diseases that differ in incidence between the parental African and European populations.
Interestingly, two of the authors of this paper (Jason Moore and Scott Williams) are on Genomed's Scientific Advisory Board:
Jason Moore, Ph.D. Dr. Moore received his training in Applied Statistics (M.A.) and Human Genetics (M.S., Ph.D.) at the University of Michigan with a focus on the genetic epidemiology of common, complex diseases such as hypertension and cardiovascular disease. Now an Assistant Professor in the Program in Human Genetics at Vanderbilt University Medical School, Dr. Moore has established himself as a leader in the development and application of cutting-edge statistical and computational methods for identifying genes that influence the risk of common diseases only through complex interactions with other genes and environmental factors. Dr. Moore recently received the 2001 James V. Neel Young Investigator award from the International Genetic Epidemiology Society in connection with his work in this area. His current work includes the development of the Multifactor Dimensionality Reduction (MDR) approach that was used in the first study to demonstrate interactions between more than three single-nucleotide polymorphisms in a common, complex human disease -- sporadic breast cancer. The development of machine learning and pattern recognition approaches such as MDR and the establishment of a 110-processor supercomputer have positioned Dr. Moore to lead efforts to identify combinations of single-nucleotide polymorphisms from among thousands of candidates in order to better predict the risk of common disease such as hypertension, cardiovascular disease, cancer, depression, and diabetes.
Scott Williams, Ph.D., Dr. Williams is currently Associate Professor in the Department of Medicine, with appointments in both the Division of Cardiovascular Medicine and the Program in Human Genetics at Vanderbilt University, Nashville, Tennessee.
Dr. Williams is an expert in human genomics who has extensive knowledge of population genetics, genetic epidemiology, molecular genetics, and computing techniques. He has written over 35 articles in the human genomics field which have appeared in various publications, including "Combinations of variations in multiple genes are associated with hypertension," published in the Hypertension Journal during 2000. In 1997, Mr. Williams became Co- Director of Meharry Medical College's Computational Biology Core Facility and began directing a study to find hypertension genes among African American patients, as well as patients from Ghana.
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