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Hunting for Disease Genes in Multi-Functional Diseases

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Published/Copyright: June 1, 2005
Clinical Chemistry and Laboratory Medicine (CCLM)
From the journal Volume 38 Issue 9

Abstract

Disease genes may be identified through functional, positional, and candidate gene approaches. Although extensive and often labor-intensive studies such as family linkage analysis, functional investigation of gene products and genome database searches are usually involved, thousands of human disease genes, especially for monogenic diseases with Mendelian transmission, have been identified. However, in diseases caused by more than one gene, or by a combination of genetic and environmental factors, identification of the genes is even more difficult. Common examples include atherosclerosis, cancer, Alzheimer's disease, asthma, diabetes, glaucoma, and age-related macular degeneration. There have been conflicting reports on the roles of associated genes. Even with population-based case-control studies and new statistical methods such as the sib-ship disequilibrium test and the discordant alleles test, there is no agreement on whether α2-macroglobulin (A2M) is a gene for Alzheimer's disease. Another example is the inconsistent association between age-related macular degeneration and ATP-binding cassette transporter (ABCR). Ethnic variation causes further complications. In our investigation of LDL-receptor variants in familial hypercholesterolemia, and the trabecular meshwork inducible glucocorticoid response protein, or myocillin (TIGR-MYOC) mutation pattern in primary open angle glaucoma, we did find dissimilar results in Chinese compared to Caucasians. New information from the Human Genome Project and advancements in technologies will aid the search for and confirm identification of disease genes despite such challenges.

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Published Online: 2005-06-01
Published in Print: 2000-09-18

Copyright © 2000 by Walter de Gruyter GmbH & Co. KG

Articles in the same Issue

  1. The Basis of the Medicine of Tomorrow "Validating and Using Pharmacogenomics" Joint IFCC-Roche Diagnostics Conference, Kyoto, Japan, 1619 April 2000
  2. Diagnostics and the Future of Medicine
  3. Operomics: Molecular Analysis of Tissues from DNA to RNA to Protein
  4. Idiosyncratic Reactions to Drugs: Can Medicine Response Profiles Provide a Dynamic Drug Surveillance System?
  5. Hunting for Disease Genes in Multi-Functional Diseases
  6. Familial Studies on the Genetics of Cardiovascular Diseases: the Stanislas Cohort
  7. Quantitative PCR
  8. Gene Amplification as Means for Determining Therapeutic Strategies in Human Cancers
  9. Apolipoprotein E Polymorphisms and Concentration in Chronic Diseases and Drug Responses
  10. Angiotensin I-Converting Enzyme Gene Polymorphism and Drug Response
  11. Drug-Metabolizing Enzymes, Polymorphisms and Interindividual Response to Environmental Toxicants
  12. Database Analysis and Gene Discovery in Pharmacogenetics
  13. How to Manage Individualized Drug Therapy: Application of Pharmacogenetic Knowledge of Drug Metabolism and Transport
  14. P-Glycoprotein and Bioavailability-Implication of Polymorphism
  15. Cancer Therapy and Polymorphisms of Cytochromes P450
  16. Polymorphisms in UDP Glucuronosyltransferase Genes: Functional Consequences and Clinical Relevance
  17. The Human Multidrug Resistance-Associated Protein (MRP) Gene Family: From Biological Function to Drug Molecular Design
  18. Ethnic Differences in Drug Metabolism
  19. Hypervariable Region 1 of Hepatitis C Virus Genome and Response to Interferon Therapy
  20. A Functional Genomic Study of the Effects of Antipsychotic Agent Chlorpromazine in PC12 Cells
  21. Influence of Glutathione S-Transferase M1 and T1 Genotypes on Larynx Cancer Risk among Korean Smokers
  22. CYP2D6 Genotyping in Patients on Psychoactive Drug Therapy
  23. Genotyping of CYP2D6 in Parkinsons's Disease
  24. Rapid Analysis of CGG Repeat Length in the FMR1 Gene
  25. Multiplex In-cell Reverse Transcription-Polymerase Chain Reaction for the Simultaneous Detection of p210 and p190 BCR-ABL mRNAs in Chronic Myeloid Leukemia and Philadelphia-Positive Acute Lymphoblastic Leukemia Cell Lines
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