Đang chuẩn bị liên kết để tải về tài liệu:
Báo cáo y học: " Phenotypic connections in surprising places."

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Wertheim cung cấp cho các bạn kiến thức về ngành y đề tài: Phenotypic connections in surprising places. | Linghu and DeLisi Genome Biology 2010 11 116 http genomebiology.eom 2010 11 4 116 w Genome Biology RESEARCH HIGHLIGHT L__ Phenotypic connections in surprising places Bolan Linghu1 and Charles DeLisi2 Abstract Surprising correlations between human disease phenotypes are emerging. Recent work now reveals startling phenotype connections between species which could provide new disease models. The human disease landscape The past few years have witnessed a growing number of well documented connections between and among human disease phenotypes whose relationship would not have been obvious within the current disease classification framework. The evidence stems from a variety of sources spanning clinical epidemiology computational genomics and various model systems 1-5 . The implications are potentially so fundamental to disease etiology drug development and the general diagnostic paradigm that there have been calls for an NIH Roadmap large trans-institute transformational grants focused on delineating the human disease landscape - a quantitative bipartite correlation map relating disease phenotypes and their genetic structures. A new study of phenotype correlations 6 now takes this idea further. One of the earliest comprehensive studies of human phenotype correlations was by Rzhetsky et al. 5 who established a correlation network between 161 diseases and disorders using evidence of comorbidities obtained from some 1.5 million patient records. Among other results they found suggestive evidence for genetic relations between autism which manifests in childhood and several late onset diseases including bipolar disorder and schizophrenia. A different approach was taken by Goh et al. 1 who constructed a human disease network by linking genetic disorders that are known to share causative genes. The network was based on an analysis of the Online Mendelian Inheritance in Man OMIM database the Correspondence delisi@bu.edu departments of Biomedical Engineering .