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Lisa Brooks

Eastern Illinois University

Publishes on Genomics and Rare Diseases, Genetic Associations and Epidemiology, American Environmental and Regional History. 56 papers and 50.6k citations.

56Publications
50.6kTotal Citations

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Top publicationsby citations

ClinGen — The Clinical Genome Resource
Heidi L. Rehm, Jonathan S. Berg, Lisa Brooks et al.|New England Journal of Medicine|2015
Cited by 1.5kOpen Access

On autopsy, a patient is found to have hypertrophic cardiomyopathy. The patient’s family pursues genetic testing that shows a “likely pathogenic” variant for the condition on the basis of a study in an original research publication. Given the dominant inheritance of the condition and the risk of sudden cardiac death, other family members are tested for the genetic variant to determine their risk. Several family members test negative and are told that they are not at risk for hypertrophic cardiomyopathy and sudden cardiac death, and those who test positive are told that they need to be regularly monitored for cardiomyopathy on echocardiography. Five years later, during a routine clinic visit of one of the genotype-positive family members, the cardiologist queries a database for current knowledge on the genetic variant and discovers that the variant is now interpreted as “likely benign” by another laboratory that uses more recently derived population-frequency data. A newly available testing panel for additional genes that are implicated in hypertrophic cardiomyopathy is initiated on an affected family member, and a different variant is found that is determined to be pathogenic. Family members are retested, and one member who previously tested negative is now found to be positive for this new variant. An immediate clinical workup detects evidence of cardiomyopathy, and an intracardiac defibrillator is implanted to reduce the risk of sudden cardiac death.

A HapMap harvest of insights into the genetics of common disease
Teri A. Manolio, Lisa Brooks, Francis S. Collins|Journal of Clinical Investigation|2008
Cited by 892Open Access

The International HapMap Project was designed to create a genome-wide database of patterns of human genetic variation, with the expectation that these patterns would be useful for genetic association studies of common diseases. This expectation has been amply fulfilled with just the initial output of genome-wide association studies, identifying nearly 100 loci for nearly 40 common diseases and traits. These associations provided new insights into pathophysiology, suggesting previously unsuspected etiologic pathways for common diseases that will be of use in identifying new therapeutic targets and developing targeted interventions based on genetically defined risk. In addition, HapMap-based discoveries have shed new light on the impact of evolutionary pressures on the human genome, suggesting multiple loci important for adapting to disease-causing pathogens and new environments. In this review we examine the origin, development, and current status of the HapMap; its prospects for continued evolution; and its current and potential future impact on biomedical science.

A DNA Polymorphism Discovery Resource for Research on Human Genetic Variation: Table 1.
Cited by 830Open Access

perform association analysis on many affected and unaffected individuals, which would require hundreds of thousands of variants spread over the entire genome (Risch and Merikangas 1996). Such a large number of variants is currently not available. The DNA Polymorphism Discovery Resource is designed to promote their discovery. About 90% of sequence variants in humans are differences in single bases of DNA, called single nucleotide polymorphisms (SNPs). SNPs in the coding regions of genes (cSNPs) or in regulatory regions are more likely to cause functional differences than SNPs elsewhere. Although most SNPs do not affect gene function, a large number of mapped SNPs will be valuable as markers throughout the genome for finding SNPs that do affect gene function, as linkage disequilibrium over tens to hundreds of kilobases is expected to be found in many regions of the human genome. Both SNPs and cSNPs can be identified by using the DNA Polymorphism Discovery Resource. When two random chromosomes are