{"title":"Application of molecular biology to mental illness. Analysis of genomic DNA and brain mRNA.","authors":"H Gurling","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>Techniques in molecular biology and genetics have made it possible to systematically study gene effects in human disease. The number of gene clusters specifically encoding human brain structure and function is probably about 1,600 or half of all clusters. Evolutionary effects such as linkage disequilibrium and conservation of exons (DNA encoding structural proteins) as well as the fact that there are a tractable number of gene clusters involved, tend to make it quite likely that DNA pathology or DNA variation (polymorphism) predisposing to mental illness can be detected. Genes involved in mental illness can be detected either by studying DNA obtained from blood samples (genomic DNA) directly or by the analysis of mRNA and proteins from suitable cell or tissue preparations. The study of gene expression in the human brain is still in its infancy, nevertheless there are some hints that non-poly-adenylated mRNAs may be important in brain development and certain transcribed sequences may have a specific role in gene expression of the brain. The advantage of studying genomic DNA by the use of linkage and association analysis in multiply affected families is that it will, in the end, almost certainly yield a positive result for a disease with a substantial genetic input. Analysis of gene products from tissues such as brain could in theory detect specific disease genes but the approach will also identify genes secondarily affected by the disease process. Differentiation of genes that are primarily causing mental illness from those that are secondarily affected can be carried out by using such candidate genes as linkage markers in multiply affected families.</p>","PeriodicalId":77773,"journal":{"name":"Psychiatric developments","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1985-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Psychiatric developments","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Techniques in molecular biology and genetics have made it possible to systematically study gene effects in human disease. The number of gene clusters specifically encoding human brain structure and function is probably about 1,600 or half of all clusters. Evolutionary effects such as linkage disequilibrium and conservation of exons (DNA encoding structural proteins) as well as the fact that there are a tractable number of gene clusters involved, tend to make it quite likely that DNA pathology or DNA variation (polymorphism) predisposing to mental illness can be detected. Genes involved in mental illness can be detected either by studying DNA obtained from blood samples (genomic DNA) directly or by the analysis of mRNA and proteins from suitable cell or tissue preparations. The study of gene expression in the human brain is still in its infancy, nevertheless there are some hints that non-poly-adenylated mRNAs may be important in brain development and certain transcribed sequences may have a specific role in gene expression of the brain. The advantage of studying genomic DNA by the use of linkage and association analysis in multiply affected families is that it will, in the end, almost certainly yield a positive result for a disease with a substantial genetic input. Analysis of gene products from tissues such as brain could in theory detect specific disease genes but the approach will also identify genes secondarily affected by the disease process. Differentiation of genes that are primarily causing mental illness from those that are secondarily affected can be carried out by using such candidate genes as linkage markers in multiply affected families.