GHTM

Global Health and Tropical Medicine

  • GHTM
    • Vision
    • Mission
    • Governance
    • Scientific Advisory Board
  • News
    • Outreach
    • Events
      • GHTM Sessions
      • Workshops
    • Articles
    • Jobs
  • Research
    • Cross-cutting issues
      • Global Pathogen Dispersion and Population Mobility
      • Drug Discovery and Drug Resistance
      • Diagnostics
      • Public Health Information
      • Fair Research Partnerships
    • Research Groups
      • PPS – Population health, policies and services
      • THOP – TB, HIV and opportunistic diseases and pathogens
      • VBD – Vector borne diseases and pathogens
      • IHC – Individual health care
    • Research in numbers
      • 2020
      • 2019
      • 2018
      • 2017
    • Projects
      • Ongoing Projects
    • Members
      • Population health, policies and services
        • PPS PhD members
        • PPS non PhD members
      • TB, HIV and opportunistic diseases and pathogens
        • THOP PhD members
        • THOP non PhD members
      • Vector-borne diseases and pathogens
        • VBD PhD members
        • VBD non PhD members
      • Individual Health Care
        • IHC PhD members
        • IHC non PhD members
      • Technical / administrative support
  • Publications
  • Education
    • Master Theses
    • PhD Theses
  • Services
Home / Publicações / Donor-Recipient Identification in Para- and Poly-phyletic Trees Under Alternative HIV-1 Transmission Hypotheses Using Approximate Bayesian Computation

Donor-Recipient Identification in Para- and Poly-phyletic Trees Under Alternative HIV-1 Transmission Hypotheses Using Approximate Bayesian Computation

  • Autores: Abecasis A, Azevedo-Pereira JM, Bártolo I, Bulla I, Hengartner N, Leitner T, Romero-Severson EO, Taveira N
  • Ano de Publicação: 2017
  • Journal: Genetics

Diversity of the founding population of Human Immunodeficiency Virus Type 1 (HIV-1) transmissions raises many important biological, clinical, and epidemiological issues. In up to 40% of sexual infections, there is clear evidence for multiple founding variants. These variants can influence the efficacy of putative prevention methods, and the reconstruction of epidemiologic histories.

The authors created an approximate Bayesian computation (ABC) method based on a set of statistics measuring phylogenetic topology, branch lengths, and genetic diversity. They made it to infer who-infected-whom. Also to compute the probability of alternative transmission scenarios while explicitly taking phylogenetic uncertainty into account.

In addition, they applied the method to a suspected heterosexual transmission case involving three individuals, showing a complex monophyletic-paraphyletic-polyphyletic phylogenetic topology. Furthermore, they detected that seven phylogenetic lineages had been transmitted between two of the individuals based on the available samples. This could imply that many more unsampled lineages had also been transmitted.

The authors tested whether the lineages had been transmitted at one time or over some length of time suggested that an ongoing superinfection process over several years was most likely. They also found, surprisingly, one individual unlinked to the other two. This happened when evaluating two competing epidemiological priors, the donor of the two that did infect each other was not identified by the host root-label. Thus, was also not the primary suspect in that transmission.

Moreover, this highlights the importance to take epidemiological information into account when analyzing support for one transmission hypothesis over another. The results may be nonintuitive and sensitive to details about sampling dates relative to possible infection dates.

In conclusion, the study provides a formal inference framework to include information on infection and sampling times. It also investigated the ancestral node-label states, transmission direction, transmitted genetic diversity, and frequency of transmission.

Share this:

  • Click to share on Facebook (Opens in new window)
  • Click to share on Twitter (Opens in new window)
  • Click to share on LinkedIn (Opens in new window)
  • Click to share on Pinterest (Opens in new window)
  • Click to share on WhatsApp (Opens in new window)
  • Click to print (Opens in new window)

Events

NOVA Sciencepreneur program: registration is open

  The Sciencepreneur ® program is aimed at NOVA scientists who are seeking to create value … [Read More...]

IHMT selected for the pilot phase of the Research Data Repository Service of the FCT

  In order to promote good practices in Open Science with regard to research data and … [Read More...]

Paulo Ferrinho interviewed for the new e-magazine of European and Developing Countries Clinical Trials Partnership (EDCTP)

Paulo Ferrinho, professor and Diretor of Public Global Health Departament at the Instituto de … [Read More...]

How can we improve the environmental performance of our laboratories?

  Every day in NOVA's laboratories research is carried out with the consumption of numerous … [Read More...]

Call for PhD Studentships

The Institute of Hygiene and Tropical Medicine (IHMT), Universidade Nova de Lisboa (NOVA), through … [Read More...]

IHMT | GHTM – APPLICATIONS ARE OPEN!

IHMT | GHTM - Applications are open for three research vacancies:   One position - PhD … [Read More...]

About GHTM

GHTM is a R&D Center that brings together researchers from IHMT with a track record in Tropical Medicine and International/Global Health. It aims at strengthening Portugal's role as a leading partner in the development and implementation of a global health research agenda. Our evidence-based interventions contribute to the promotion of equity in health and to improve the health of populations.

Contacts

Rua da Junqueira, 100
1349-008 Lisboa
Portugal
+351 213 652 600
+351 213 632 105

  • Facebook
  • YouTube

Subscribe Newsletter

  • How to get to GHTM/IHMT
  • GHTM Sessions
  • Research Groups
  • Cross-cutting issues
© Copyright 2023 IHMT-UNL Todos os Direitos Reservados.
  • Universidade Nova de Lisboa
  • Fundação para a Ciência e a Tecnologia

    Project UID/Multi/04413/2013