Accurate Genetic Detection of Hepatitis C Virus Transmissions in Outbreak Settings
Hepatitis C is a major public health problem in the United States and worldwide. Outbreaks of hepatitis C virus (HCV) infections are associated with unsafe injection practices, drug diversion, and other exposures to blood and are difficult to detect and investigate. Here, we developed and validated...
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| Veröffentlicht in: | The Journal of infectious diseases 2016-03, Vol.213 (6), p.957-965 |
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| creator | Campo, David S. Xia, Guo-Liang Dimitrova, Zoya Lin, Yulin Forbi, Joseph C. Ganova-Raeva, Lilia Punkova, Lili Ramachandran, Sumathi Thai, Hong Skums, Pavel Sims, Seth Rytsareva, Inna Vaughan, Gilberto Roh, Ha-Jung Purdy, Michael A. Sue, Amanda Khudyakov, Yury |
| description | Hepatitis C is a major public health problem in the United States and worldwide. Outbreaks of hepatitis C virus (HCV) infections are associated with unsafe injection practices, drug diversion, and other exposures to blood and are difficult to detect and investigate. Here, we developed and validated a simple approach for molecular detection of HCV transmissions in outbreak settings. We obtained sequences from the HCV hypervariable region 1 (HVR1), using end-point limiting-dilution (EPLD) technique, from 127 cases involved in 32 epidemiologically defined HCV outbreaks and 193 individuals with unrelated HCV strains. We compared several types of genetic distances and calculated a threshold, using minimal Hamming distances, that identifies transmission clusters in all tested outbreaks with 100% accuracy. The approach was also validated on sequences obtained using next-generation sequencing from HCV strains recovered from 239 individuals, and findings showed the same accuracy as that for EPLD. On average, the nucleotide diversity of the intrahost population was 6.2 times greater in the source case than in any incident case, allowing the correct detection of transmission direction in 8 outbreaks for which source cases were known. A simple and accurate distance-based approach developed here for detecting HCV transmissions streamlines molecular investigation of outbreaks, thus improving the public health capacity for rapid and effective control of hepatitis C. |
| doi_str_mv | 10.1093/infdis/jiv542 |
| format | Article |
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Outbreaks of hepatitis C virus (HCV) infections are associated with unsafe injection practices, drug diversion, and other exposures to blood and are difficult to detect and investigate. Here, we developed and validated a simple approach for molecular detection of HCV transmissions in outbreak settings. We obtained sequences from the HCV hypervariable region 1 (HVR1), using end-point limiting-dilution (EPLD) technique, from 127 cases involved in 32 epidemiologically defined HCV outbreaks and 193 individuals with unrelated HCV strains. We compared several types of genetic distances and calculated a threshold, using minimal Hamming distances, that identifies transmission clusters in all tested outbreaks with 100% accuracy. The approach was also validated on sequences obtained using next-generation sequencing from HCV strains recovered from 239 individuals, and findings showed the same accuracy as that for EPLD. On average, the nucleotide diversity of the intrahost population was 6.2 times greater in the source case than in any incident case, allowing the correct detection of transmission direction in 8 outbreaks for which source cases were known. A simple and accurate distance-based approach developed here for detecting HCV transmissions streamlines molecular investigation of outbreaks, thus improving the public health capacity for rapid and effective control of hepatitis C.</description><identifier>ISSN: 0022-1899</identifier><identifier>EISSN: 1537-6613</identifier><identifier>DOI: 10.1093/infdis/jiv542</identifier><identifier>PMID: 26582955</identifier><language>eng</language><publisher>United States: Oxford University Press</publisher><subject>Cluster Analysis ; Disease Outbreaks ; Genetic Linkage ; Genetic Variation ; Genotype ; Hepacivirus - genetics ; Hepacivirus - isolation & purification ; Hepatitis C - epidemiology ; Hepatitis C - transmission ; Hepatitis C - virology ; Hepatitis C virus ; Humans ; Reproducibility of Results ; VIRUSES</subject><ispartof>The Journal of infectious diseases, 2016-03, Vol.213 (6), p.957-965</ispartof><rights>Copyright © 2016 Oxford University Press on behalf of the Infectious Diseases Society of America</rights><rights>Published by Oxford University Press for the Infectious Diseases Society of America 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c442t-2464b5054f7a233f357eb9aca67e6c861fe93f98e15c67131fc4fc465a379c993</citedby><cites>FETCH-LOGICAL-c442t-2464b5054f7a233f357eb9aca67e6c861fe93f98e15c67131fc4fc465a379c993</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/24716570$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/24716570$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,314,776,780,799,881,27901,27902,57992,58225</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26582955$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Campo, David S.</creatorcontrib><creatorcontrib>Xia, Guo-Liang</creatorcontrib><creatorcontrib>Dimitrova, Zoya</creatorcontrib><creatorcontrib>Lin, Yulin</creatorcontrib><creatorcontrib>Forbi, Joseph C.</creatorcontrib><creatorcontrib>Ganova-Raeva, Lilia</creatorcontrib><creatorcontrib>Punkova, Lili</creatorcontrib><creatorcontrib>Ramachandran, Sumathi</creatorcontrib><creatorcontrib>Thai, Hong</creatorcontrib><creatorcontrib>Skums, Pavel</creatorcontrib><creatorcontrib>Sims, Seth</creatorcontrib><creatorcontrib>Rytsareva, Inna</creatorcontrib><creatorcontrib>Vaughan, Gilberto</creatorcontrib><creatorcontrib>Roh, Ha-Jung</creatorcontrib><creatorcontrib>Purdy, Michael A.</creatorcontrib><creatorcontrib>Sue, Amanda</creatorcontrib><creatorcontrib>Khudyakov, Yury</creatorcontrib><title>Accurate Genetic Detection of Hepatitis C Virus Transmissions in Outbreak Settings</title><title>The Journal of infectious diseases</title><addtitle>J Infect Dis</addtitle><description>Hepatitis C is a major public health problem in the United States and worldwide. Outbreaks of hepatitis C virus (HCV) infections are associated with unsafe injection practices, drug diversion, and other exposures to blood and are difficult to detect and investigate. Here, we developed and validated a simple approach for molecular detection of HCV transmissions in outbreak settings. We obtained sequences from the HCV hypervariable region 1 (HVR1), using end-point limiting-dilution (EPLD) technique, from 127 cases involved in 32 epidemiologically defined HCV outbreaks and 193 individuals with unrelated HCV strains. We compared several types of genetic distances and calculated a threshold, using minimal Hamming distances, that identifies transmission clusters in all tested outbreaks with 100% accuracy. The approach was also validated on sequences obtained using next-generation sequencing from HCV strains recovered from 239 individuals, and findings showed the same accuracy as that for EPLD. On average, the nucleotide diversity of the intrahost population was 6.2 times greater in the source case than in any incident case, allowing the correct detection of transmission direction in 8 outbreaks for which source cases were known. A simple and accurate distance-based approach developed here for detecting HCV transmissions streamlines molecular investigation of outbreaks, thus improving the public health capacity for rapid and effective control of hepatitis C.</description><subject>Cluster Analysis</subject><subject>Disease Outbreaks</subject><subject>Genetic Linkage</subject><subject>Genetic Variation</subject><subject>Genotype</subject><subject>Hepacivirus - genetics</subject><subject>Hepacivirus - isolation & purification</subject><subject>Hepatitis C - epidemiology</subject><subject>Hepatitis C - transmission</subject><subject>Hepatitis C - virology</subject><subject>Hepatitis C virus</subject><subject>Humans</subject><subject>Reproducibility of Results</subject><subject>VIRUSES</subject><issn>0022-1899</issn><issn>1537-6613</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkUtLJDEUhYMo2j6WLpUs3dSYdyobQdrXgCCMzmxDOt5o2u5Um6SE-feWlI9xN3DhLu7HuedwENqn5Aclhh_HFO5jOZ7HFynYGppQyXWjFOXraEIIYw1tjdlC26XMCSGCK72JtpiSLTNSTtCvU-_77CrgS0hQo8dnUMHX2CXcBXwFK1djjQVP8Z-Y-4LvsktlGUsZiIJjwjd9nWVwT_gWao3poeyijeAWBfbe9w76fXF-N71qrm8uf05PrxsvBKsNE0rMJJEiaMc4D1xqmBnnndKgfKtoAMODaYFKrzTlNHgxjJKOa-ON4TvoZNRd9bMl3HtINbuFXeW4dPmv7Vy03y8pPtqH7sVKSo3QehA4ehfI3XMPpdohl4fFwiXo-mKpbiXjkmr5H6hq6eBSvdlqRtTnrpQM4dMRJfatMjtWZsfKBv7w3xif9EdHA3AwAvNSu_x1F8M7qQl_Bb1Fnr8</recordid><startdate>20160315</startdate><enddate>20160315</enddate><creator>Campo, David S.</creator><creator>Xia, Guo-Liang</creator><creator>Dimitrova, Zoya</creator><creator>Lin, Yulin</creator><creator>Forbi, Joseph C.</creator><creator>Ganova-Raeva, Lilia</creator><creator>Punkova, Lili</creator><creator>Ramachandran, Sumathi</creator><creator>Thai, Hong</creator><creator>Skums, Pavel</creator><creator>Sims, Seth</creator><creator>Rytsareva, Inna</creator><creator>Vaughan, Gilberto</creator><creator>Roh, Ha-Jung</creator><creator>Purdy, Michael A.</creator><creator>Sue, Amanda</creator><creator>Khudyakov, Yury</creator><general>Oxford University Press</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7T2</scope><scope>7U2</scope><scope>7U9</scope><scope>C1K</scope><scope>H94</scope><scope>5PM</scope></search><sort><creationdate>20160315</creationdate><title>Accurate Genetic Detection of Hepatitis C Virus Transmissions in Outbreak Settings</title><author>Campo, David S. ; Xia, Guo-Liang ; Dimitrova, Zoya ; Lin, Yulin ; Forbi, Joseph C. ; Ganova-Raeva, Lilia ; Punkova, Lili ; Ramachandran, Sumathi ; Thai, Hong ; Skums, Pavel ; Sims, Seth ; Rytsareva, Inna ; Vaughan, Gilberto ; Roh, Ha-Jung ; Purdy, Michael A. ; Sue, Amanda ; Khudyakov, Yury</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c442t-2464b5054f7a233f357eb9aca67e6c861fe93f98e15c67131fc4fc465a379c993</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Cluster Analysis</topic><topic>Disease Outbreaks</topic><topic>Genetic Linkage</topic><topic>Genetic Variation</topic><topic>Genotype</topic><topic>Hepacivirus - genetics</topic><topic>Hepacivirus - isolation & purification</topic><topic>Hepatitis C - epidemiology</topic><topic>Hepatitis C - transmission</topic><topic>Hepatitis C - virology</topic><topic>Hepatitis C virus</topic><topic>Humans</topic><topic>Reproducibility of Results</topic><topic>VIRUSES</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Campo, David S.</creatorcontrib><creatorcontrib>Xia, Guo-Liang</creatorcontrib><creatorcontrib>Dimitrova, Zoya</creatorcontrib><creatorcontrib>Lin, Yulin</creatorcontrib><creatorcontrib>Forbi, Joseph C.</creatorcontrib><creatorcontrib>Ganova-Raeva, Lilia</creatorcontrib><creatorcontrib>Punkova, Lili</creatorcontrib><creatorcontrib>Ramachandran, Sumathi</creatorcontrib><creatorcontrib>Thai, Hong</creatorcontrib><creatorcontrib>Skums, Pavel</creatorcontrib><creatorcontrib>Sims, Seth</creatorcontrib><creatorcontrib>Rytsareva, Inna</creatorcontrib><creatorcontrib>Vaughan, Gilberto</creatorcontrib><creatorcontrib>Roh, Ha-Jung</creatorcontrib><creatorcontrib>Purdy, Michael A.</creatorcontrib><creatorcontrib>Sue, Amanda</creatorcontrib><creatorcontrib>Khudyakov, Yury</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Safety Science and Risk</collection><collection>Virology and AIDS Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>The Journal of infectious diseases</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Campo, David S.</au><au>Xia, Guo-Liang</au><au>Dimitrova, Zoya</au><au>Lin, Yulin</au><au>Forbi, Joseph C.</au><au>Ganova-Raeva, Lilia</au><au>Punkova, Lili</au><au>Ramachandran, Sumathi</au><au>Thai, Hong</au><au>Skums, Pavel</au><au>Sims, Seth</au><au>Rytsareva, Inna</au><au>Vaughan, Gilberto</au><au>Roh, Ha-Jung</au><au>Purdy, Michael A.</au><au>Sue, Amanda</au><au>Khudyakov, Yury</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Accurate Genetic Detection of Hepatitis C Virus Transmissions in Outbreak Settings</atitle><jtitle>The Journal of infectious diseases</jtitle><addtitle>J Infect Dis</addtitle><date>2016-03-15</date><risdate>2016</risdate><volume>213</volume><issue>6</issue><spage>957</spage><epage>965</epage><pages>957-965</pages><issn>0022-1899</issn><eissn>1537-6613</eissn><abstract>Hepatitis C is a major public health problem in the United States and worldwide. Outbreaks of hepatitis C virus (HCV) infections are associated with unsafe injection practices, drug diversion, and other exposures to blood and are difficult to detect and investigate. Here, we developed and validated a simple approach for molecular detection of HCV transmissions in outbreak settings. We obtained sequences from the HCV hypervariable region 1 (HVR1), using end-point limiting-dilution (EPLD) technique, from 127 cases involved in 32 epidemiologically defined HCV outbreaks and 193 individuals with unrelated HCV strains. We compared several types of genetic distances and calculated a threshold, using minimal Hamming distances, that identifies transmission clusters in all tested outbreaks with 100% accuracy. The approach was also validated on sequences obtained using next-generation sequencing from HCV strains recovered from 239 individuals, and findings showed the same accuracy as that for EPLD. On average, the nucleotide diversity of the intrahost population was 6.2 times greater in the source case than in any incident case, allowing the correct detection of transmission direction in 8 outbreaks for which source cases were known. A simple and accurate distance-based approach developed here for detecting HCV transmissions streamlines molecular investigation of outbreaks, thus improving the public health capacity for rapid and effective control of hepatitis C.</abstract><cop>United States</cop><pub>Oxford University Press</pub><pmid>26582955</pmid><doi>10.1093/infdis/jiv542</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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| identifier | ISSN: 0022-1899 |
| ispartof | The Journal of infectious diseases, 2016-03, Vol.213 (6), p.957-965 |
| issn | 0022-1899 1537-6613 |
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| source | Jstor Complete Legacy; Oxford University Press Journals All Titles (1996-Current); MEDLINE; Alma/SFX Local Collection |
| subjects | Cluster Analysis Disease Outbreaks Genetic Linkage Genetic Variation Genotype Hepacivirus - genetics Hepacivirus - isolation & purification Hepatitis C - epidemiology Hepatitis C - transmission Hepatitis C - virology Hepatitis C virus Humans Reproducibility of Results VIRUSES |
| title | Accurate Genetic Detection of Hepatitis C Virus Transmissions in Outbreak Settings |
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