Plasma protein patterns as comprehensive indicators of health.

Proteins are effector molecules that mediate the functions of genes and modulate comorbidities, behaviors and drug treatments. They represent an enormous potential resource for personalized, systemic and data-driven diagnosis, prevention, monitoring and treatment. However, the concept of using plasma proteins for individualized health assessment across many health conditions simultaneously has not been tested.

Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use.

Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders. They are heritable and etiologically related behaviors that have been resistant to gene discovery efforts. In sample sizes up to 1.

Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci.

Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants).

Longitudinal whole genome analysis of pre and post drug treatment Mycobacterium tuberculosis isolates reveals progressive steps to drug resistance.

Tuberculosis (TB) is one of the leading causes of death due to an infectious disease in the world. Understanding the mechanisms of drug resistance has become pivotal in the detection and treatment of newly emerging resistant TB cases. We have analyzed three pairs of Mycobacterium tuberculosis strains pre- and post-drug treatment to identify mutations involved in the progression of resistance to the drugs rifampicin and isoniazid.

MycoBASE: expanding the functional annotation coverage of mycobacterial genomes.

Background: Central to most omic scale experiments is the interpretation and examination of resulting gene lists corresponding to differentially expressed, regulated, or observed gene or protein sets. Complicating interpretation is a lack of functional annotation assigned to a large percentage of many microbial genomes. This is particularly noticeable in mycobacterial genomes, which are significantly divergent from many of the microbial model species used for gene and protein functional characterization, but which are extremely important clinically.

Blood Transcriptional Biomarkers for Active Tuberculosis among Patients in the United States: a Case-Control Study with Systematic Cross-Classifier Evaluation.

Unlabelled: Blood transcriptional signatures are promising for tuberculosis (TB) diagnosis but have not been evaluated among U.S.

Patients: To be used clinically, transcriptional classifiers need reproducible accuracy in diverse populations that vary in genetic composition, disease spectrum and severity, and comorbidities.

Network and matrix analysis of the respiratory disease interactome.

Background: Although respiratory diseases exhibit in a wide array of clinical manifestations, certain respiratory diseases may share related genetic mechanisms or may be influenced by similar chemical stimuli. Here we explore and infer relationships among genes, diseases, and chemicals using network and matrix based clustering methods.

Results: In order to better understand and elucidate these shared genetic mechanisms and chemical relationships we analyzed a comprehensive collection of gene, disease, and chemical relationships pertinent to respiratory disease, using network and matrix based analysis approaches.