BACKGROUND: @entity6 ( @entity2175 ), also known as @entity2175 ( @entity2175 ) or adult-onset @entity6 , is a common disease. It is estimated that more than 300 million @entity1 worldwide suffer from @entity2175 . In this study, we investigated the @entity2175 , pre- @entity6 and healthy @entity1 (no @entity6 ) bloodstream samples using genomic, genealogical, and phonemic information. We identified differentially expressed genes and pathways. The study has provided deeper insights into the development of @entity2175 , and provided useful information for further effective prevention and treatment of the disease. RESULTS: A total of 142 bloodstream samples were collected, including 47 healthy @entity1 , 22 pre- @entity6 and 73 @entity2175 @entity1 . Whole genome scale gene expression profiles were obtained using the Agilent Oligo chips that contain over 20,000 @entity1 genes. We identified 79 significantly differentially expressed genes that have fold change >=  2. We mapped those genes and pinpointed locations of those genes on @entity1 chromosomes. Amongst them, 3 genes were not mapped well on the @entity1 genome, but the rest of 76 differentially expressed genes were well mapped on the @entity1 genome. We found that most abundant differentially expressed genes are on chromosome one, which contains 9 of those genes, followed by chromosome two that contains 7 of the 76 differentially expressed genes. We performed @entity74 ( @entity74 ) functional analysis of those 79 differentially expressed genes and found that genes involve in the regulation of cell proliferation were among most common pathways related to @entity2175 . The expression of the 79 genes was combined with clinical information that includes age, sex, and race to construct an optimal discriminant model. The overall performance of the model reached 95.1% accuracy, with 91.5% accuracy on identifying healthy @entity1 , 100% accuracy on pre- @entity6 @entity1 and 95.9% accuract on @entity2175 @entity1 . The higher performance on identifying pre- @entity6 @entity1 was resulted from more significant changes of gene expressions among this particular group of @entity1 , which implicated that @entity1 were having profound genetic changes towards disease development. CONCLUSION: Differentially expressed genes were distributed across chromosomes, and are more abundant on chromosomes 1 and 2 than the rest of the @entity1 genome. We found that regulation of cell proliferation actually plays an important role in the @entity2175 disease development. The predictive model developed in this study has utilized the 79 significant genes in combination with age, sex, and racial information to distinguish pre- @entity6 , @entity2175 , and healthy @entity1 . The study not only has provided deeper understanding of the disease molecular mechanisms but also useful information for pathway analysis and effective drug target identification.

Developing discriminate model and comparative analysis of differentially expressed genes and pathways for bloodstream samples of XXXX .

@entity2175 :: ('MESH:D003924', 'Disease') :: ['NIDDM', 'noninsulin-dependent diabetes mellitus', 'T2D'] @entity1 :: ('9606', 'Species') :: ['human', 'humans', 'patients', 'people'] @entity74 :: ('MESH:D030342', 'Disease') :: ['gene ontology', 'GO'] @entity6 :: ('MESH:D003920', 'Disease') :: ['Diabetes mellitus of type 2', 'diabetic', 'diabetes']
@entity6 :: (MESH:D003920,Disease) :: ['diabetes mellitus type 2']
