The distribution of hepatitis C viral genotypes shifted among chronic hepatitis C patients in Yunnan, China, between 2008–2018

Jia, Yuanyuan; Zou, Xiu; Yue, Wei; Liu, Jin; Yue, Ming; Liu, Yang; Liu, Li; Huang, Peng; Feng, Yue; Xia, Xueshan

doi:10.3389/fcimb.2023.1092936

Cited by 3 publications

References 29 publications

(41 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

Auto-Tune: Selecting the Distance Threshold for Inferring Hiv Transmission Clusters

Weaver,

Dávila-Conn,

et al. 2024

Preprint

View full text Add to dashboard Cite

Molecular surveillance of viral pathogens and inference of transmission networks from genomic data play an increasingly important role in public health efforts, especially for HIV-1. For many methods, the genetic distance threshold used to connect sequences in the transmission network is a key parameter informing the properties of inferred networks. Using a distance threshold that is too high can result in a network with many spurious links, making it difficult to interpret. Conversely, a distance threshold that is too low can result in a network with too few links, which may not capture key insights into clusters of public health concern. Published research using the HIV-TRACE software package frequently uses the default threshold of 0.015 substitutions/site for HIV pol gene sequences, but in many cases, investigators heuristically select other threshold parameters to better capture the underlying dynamics of the epidemic they are studying. Here, we present a general heuristic scoring approach for tuning a distance threshold adaptively, which seeks to prevent the formation of giant clusters. We prioritize the ratio of the sizes of the largest and the second largest cluster, maximizing the number of clusters present in the network. We apply our scoring heuristic to outbreaks with different characteristics, such as regional or temporal variability, and demonstrate the utility of using the scoring mechanism's suggested distance threshold to identify clusters exhibiting risk factors that would have otherwise been more difficult to identify. For example, while we found that a 0.015 substitutions/site distance threshold is typical for US-like epidemics, recent outbreaks like the CRF07\_BC subtype among men who have sex with men (MSM) in China have been found to have a lower optimal threshold of 0.005 to better capture the transition from injected drug use (IDU) to MSM as the primary risk factor. Alternatively, in communities surrounding Lake Victoria in Uganda, where there has been sustained heterosexual transmission for many years, we found that a larger distance threshold is necessary to capture a more risk factor-diverse population with sparse sampling over a longer period of time. Such identification may allow for more informed intervention action by respective public health officials.

show abstract

Auto-Tune: Selecting the Distance Threshold for Inferring Hiv Transmission Clusters

Weaver,

Dávila-Conn,

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Hepatitis C virus subtype diversity and transmission clusters characteristics among drug users in Zhuhai, South China

Li,

Huang,

Huang

et al. 2024

BMC Infect Dis

View full text Add to dashboard Cite

Background Hepatitis C virus (HCV) infection poses a major public health challenge globally, especially among injecting drug users. China has the world’s largest burden of HCV infections. However, little is known about the characteristics of transmission networks among drug user populations. This study aims to investigate the molecular epidemiology and transmission characteristics of HCV infections among drug users in Zhuhai, a bustling port city connecting Mainland China and its Special Administrative Regions. Methods Participants enrolled in this study were drug users incarcerated at Zhuhai’s drug rehabilitation center in 2015. Their sociodemographic and behavioral information, including gender, promiscuity, drug use method, and so forth, was collected using a standardized questionnaire. Plasmas separated from venous blood were analyzed for HCV infection through ELISA and RT-PCR methods to detect anti-HCV antibodies and HCV RNA. The 5’UTR fragment of the HCV genome was amplified and further sequenced for subtype identifications and phylogenetic analysis. The phylogenetic tree was inferred using the Maximum Likelihood method based on the Tamura-Nei model, and the transmission cluster network was constructed using Cytoscape3.8.0 software with a threshold of 0.015. Binary logistic regression models were employed to assess the factors associated with HCV infection. Results The overall prevalence of HCV infection among drug users was 44.37%, with approximately 19.69% appearing to clear the HCV virus successfully. Binary logistic regression analysis revealed that those aged over 40, engaging in injecting drug use, and being native residents were at heightened risk for HCV infection among drug user cohorts. The predominant HCV subtypes circulating among those drug users were 6a (60.26%), followed by 3b (16.7%), 3a (12.8%), 1b (6.41%) and 1a (3.85%), respectively. Molecular transmission network analysis unveiled the presence of six transmission clusters, with the largest propagation cluster consisting of 41 individuals infected with HCV subtype 6a. Furthermore, distinct transmission clusters involved eight individuals infected with subtype 3b and seven with subtype 3a were also observed. Conclusion The genetic transmission networks revealed a complex transmission pattern among drug users in Zhuhai, emphasizing the imperative for a targeted and effective intervention strategy to mitigate HCV dissemination. These insights are pivotal for shaping future national policies on HCV screening, treatment, and prevention in port cities.

show abstract

AUTO-TUNE: selecting the distance threshold for inferring HIV transmission clusters

Weaver,

Dávila Conn,

et al. 2024

Front. Bioinform.

View full text Add to dashboard Cite

Molecular surveillance of viral pathogens and inference of transmission networks from genomic data play an increasingly important role in public health efforts, especially for HIV-1. For many methods, the genetic distance threshold used to connect sequences in the transmission network is a key parameter informing the properties of inferred networks. Using a distance threshold that is too high can result in a network with many spurious links, making it difficult to interpret. Conversely, a distance threshold that is too low can result in a network with too few links, which may not capture key insights into clusters of public health concern. Published research using the HIV-TRACE software package frequently uses the default threshold of 0.015 substitutions/site for HIV pol gene sequences, but in many cases, investigators heuristically select other threshold parameters to better capture the underlying dynamics of the epidemic they are studying. Here, we present a general heuristic scoring approach for tuning a distance threshold adaptively, which seeks to prevent the formation of giant clusters. We prioritize the ratio of the sizes of the largest and the second largest cluster, maximizing the number of clusters present in the network. We apply our scoring heuristic to outbreaks with different characteristics, such as regional or temporal variability, and demonstrate the utility of using the scoring mechanism’s suggested distance threshold to identify clusters exhibiting risk factors that would have otherwise been more difficult to identify. For example, while we found that a 0.015 substitutions/site distance threshold is typical for US-like epidemics, recent outbreaks like the CRF07_BC subtype among men who have sex with men (MSM) in China have been found to have a lower optimal threshold of 0.005 to better capture the transition from injected drug use (IDU) to MSM as the primary risk factor. Alternatively, in communities surrounding Lake Victoria in Uganda, where there has been sustained heterosexual transmission for many years, we found that a larger distance threshold is necessary to capture a more risk factor-diverse population with sparse sampling over a longer period of time. Such identification may allow for more informed intervention action by respective public health officials.

show abstract

The distribution of hepatitis C viral genotypes shifted among chronic hepatitis C patients in Yunnan, China, between 2008–2018

Cited by 3 publications

References 29 publications

Auto-Tune: Selecting the Distance Threshold for Inferring Hiv Transmission Clusters

Auto-Tune: Selecting the Distance Threshold for Inferring Hiv Transmission Clusters

Hepatitis C virus subtype diversity and transmission clusters characteristics among drug users in Zhuhai, South China

AUTO-TUNE: selecting the distance threshold for inferring HIV transmission clusters

Contact Info

Product

Resources

About