genomic approaches to allergic disorders

genomic approaches to allergic disorders

Continuing Medical Education examination Application of genetic/genomic approaches to allergic disorders Instructions for category 1 Continuing Medic...

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Continuing Medical Education examination

Application of genetic/genomic approaches to allergic disorders Instructions for category 1 Continuing Medical Education credit The American Academy of Allergy, Asthma & Immunology is accredited as a provider of Continuing Medical Education (CME) by the Accreditation Council for Continuing Medical Education. Test ID no.: mai00205 Contact hours: 1.0 Expiration date: August 31, 2012 Category 1 credit can be earned by reading the text material and taking this CME examination online. For complete instructions, visit the Journal’s Web site at www.jacionline.org.

The Editors thank the Virginia Commonwealth University Allergy/Immunology training program for developing this CME examination. The individuals who contributed to its preparation were Jigisha Morosky, MD, Jennifer Stribling, MD, and Lawrence B. Schwartz, MD, PhD.

Learning objectives: ‘‘Application of genetic/genomic approaches to allergic disorders’’ 1. To differentiate between the research methodologies currently used to study disorders that are at least in part heritable. 2. To increase awareness of current major international studies of inherited disorders. 3. To understand different types of genetic variation.

CME items Question 1. The association of HLA-B27 with ankylosing spondylitis is best demonstrated by — A. linkage disequilibrium. B. copy number variations. C. Mendelian genetics. D. copy neutral variation. Question 2. Which of the following techniques would best identify the genetic basis of a disease that is only found in a given population in Africa? A. linkage analysis B. haplotype-tagging single nucleotide polymorphisms (SNPs) C. deep resequencing D. association analysis Question 3. The 1000 Genomes Project will best answer questions regarding — A. epigenetic modifications. B. micro-RNA expression. C. phosphotyrosine variations. D. private SNPs.

J ALLERGY CLIN IMMUNOL

Question 4. The Gene Ontology project provides information that is applicable to — A. regulatory genetic regions. B. gene products. C. origin of life. D. genetic markers for cancer. Question 5. The International HapMap project provides genotypic data for populations from — A. Africa, China, Japan, and South America. B. China, Europe, Australia, and Africa. C. South America, Japan, Europe, and Africa. D. Europe, China, Japan, and Africa. Question 6. Strong linkage disequilibrium in which there is coinheritance between SNP alleles allows for capturing most of the common genetic variations in a region by — A. haplotype-tagging SNPs. B. deep resequencing. C. admixture mapping. D. genome-wide association studies.

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438 BAYE, MARTIN, AND KHURANA HERSHEY

J ALLERGY CLIN IMMUNOL SEPTEMBER 2010

Question 7. SNPs occur at a rate of 1 SNP per how many base pairs of DNA? A. 100 B. 1,000 C. 10,000 D. 100,000

Question 9. Linkage analysis is a statistical approach to gene discovery that can be performed in — A. only family-based studies. B. only population-based studies. C. both population- and family-based studies. D. neither population- nor family-based studies.

Question 8. Aberrant DNA methylation of a 59-CpG island in the acyl-CoA synthetase long-chain family member (ACSL3) has been significantly associated with asthma risk in children born to mothers exposed to air pollutants. This is an example of which type of genetic variation? A. SNPs B. non-SNP variation C. copy number variation D. epigenetic reprogramming

Question 10. Association analysis detects disease-relevant genetic variation by determining whether — A. a genetic variant cosegregates with diseases in families. B. a genetic variant occurs more often in subjects with disease than in those without disease. C. particular regions of the genome at which inheriting DNA from ancestors from a certain region of the world predisposes one to a particular disease. D. combining information about known population history and information from a subject’s measured genotype can be used to localize disease genes.