Title |
Inferences about the global scenario of human T-cell lymphotropic virus type 1 infection using data mining of viral sequences
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Published in |
Memórias do Instituto Oswaldo Cruz, May 2014
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DOI | 10.1590/0074-0276130587 |
Pubmed ID | |
Authors |
Thessika Hialla Almeida Araujo, Fernanda Khouri Barreto, Alcântara Luiz Carlos, Aline Cristina Andrade Mota Miranda |
Abstract |
Human T-cell lymphotropic virus type 1 (HTLV-1) is mainly associated with two diseases: tropical spastic paraparesis/HTLV-1-associated myelopathy (TSP/HAM) and adult T-cell leukaemia/lymphoma. This retrovirus infects five-10 million individuals throughout the world. Previously, we developed a database that annotates sequence data from GenBank and the present study aimed to describe the clinical, molecular and epidemiological scenarios of HTLV-1 infection through the stored sequences in this database. A total of 2,545 registered complete and partial sequences of HTLV-1 were collected and 1,967 (77.3%) of those sequences represented unique isolates. Among these isolates, 93% contained geographic origin information and only 39% were related to any clinical status. A total of 1,091 sequences contained information about the geographic origin and viral subtype and 93% of these sequences were identified as subtype "a". Ethnicity data are very scarce. Regarding clinical status data, 29% of the sequences were generated from TSP/HAM and 67.8% from healthy carrier individuals. Although the data mining enabled some inferences about specific aspects of HTLV-1 infection to be made, due to the relative scarcity of data of available sequences, it was not possible to delineate a global scenario of HTLV-1 infection. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Brazil | 2 | 7% |
Unknown | 27 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 7 | 24% |
Student > Master | 7 | 24% |
Student > Postgraduate | 2 | 7% |
Researcher | 2 | 7% |
Professor | 2 | 7% |
Other | 4 | 14% |
Unknown | 5 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 5 | 17% |
Biochemistry, Genetics and Molecular Biology | 4 | 14% |
Agricultural and Biological Sciences | 4 | 14% |
Nursing and Health Professions | 3 | 10% |
Neuroscience | 2 | 7% |
Other | 5 | 17% |
Unknown | 6 | 21% |