| Title |
Human Genomics of Mycobacterium tuberculosis Infection and Disease
|
|---|---|
| Published in |
Current Genetic Medicine Reports, July 2017
|
| DOI | 10.1007/s40142-017-0124-7 |
| Pubmed ID | |
| Authors |
Marianna Orlova, Erwin Schurr |
| Abstract |
The study of the genetic basis of tuberculosis pathogenesis has benefited from powerful technological innovations, a more structured definition of latent and clinical manifestations of the disease, and the application of functional genomics approaches. This short review aims to summarize recent advances and to provide a link with results of previous human genetic studies of tuberculosis susceptibility. Transcriptomics has been shown to be a useful tool to predict progression from latency to clinical disease while functional genomics has traced the molecular events that link pathogen-triggered gene expression and host genetics. Resistance to infection with Mycobacterium tuberculosis has been revealed to be strongly impacted by host genetics. Host genomics of clinical disease has been shown to be most powerful when focusing on carefully selected clinical entities and possibly by considering host pathogen combinations. Future studies need to build on the latest molecular findings to define disease subtypes to successfully elucidate the human genetic component in tuberculosis pathogenesis. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 29 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 6 | 21% |
| Student > Master | 4 | 14% |
| Student > Ph. D. Student | 3 | 10% |
| Lecturer | 2 | 7% |
| Student > Doctoral Student | 1 | 3% |
| Other | 4 | 14% |
| Unknown | 9 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 12 | 41% |
| Medicine and Dentistry | 4 | 14% |
| Computer Science | 2 | 7% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 3% |
| Nursing and Health Professions | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 9 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 December 2017.
All research outputs
#19,951,180
of 25,382,440 outputs
Outputs from Current Genetic Medicine Reports
#86
of 120 outputs
Outputs of similar age
#238,113
of 327,041 outputs
Outputs of similar age from Current Genetic Medicine Reports
#1
of 2 outputs
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