Literature DB >> 31634185

Genetic clustering analysis for HIV infection among MSM in Nigeria: implications for intervention.

Yuruo Li1, Hongjie Liu1, Habib O Ramadhani2, Nicaise Ndembi2,3, Trevor A Crowell4,5, Gustavo Kijak4,5, Merlin L Robb4,5, Julie A Ake4, Afoke Kokogho6,7, Rebecca G Nowak2, Charlotte Gaydos8, Stefan D Baral9, Erik Volz10, Sodsai Tovanabutra4,5, Man Charurat2.   

Abstract

BACKGROUND: The HIV epidemic continues to grow among MSM in countries across sub-Saharan Africa including Nigeria. To inform prevention efforts, we used a phylogenetic cluster method to characterize HIV genetic clusters and factors associated with cluster formation among MSM living with HIV in Nigeria.
METHODS: We analyzed HIV-1 pol sequences from 417 MSM living with HIV enrolled in the TRUST/RV368 cohort between 2013 and 2017 in Abuja and Lagos, Nigeria. A genetically linked cluster was defined among participants whose sequences had pairwise genetic distance of 1.5% or less. Binary and multinomial logistic regressions were used to estimate adjusted odds ratios (AORs) and 95% confidence intervals (CIs) for factors associated with HIV genetic cluster membership and size.
RESULTS: Among 417 MSM living with HIV, 153 (36.7%) were genetically linked. Participants with higher viral load (AOR = 1.72 95% CI: 1.04-2.86), no female partners (AOR = 3.66; 95% CI: 1.97-6.08), and self-identified as male sex (compared with self-identified as bigender) (AOR = 3.42; 95% CI: 1.08-10.78) had higher odds of being in a genetic cluster. Compared with unlinked participants, MSM who had high school education (AOR = 23.84; 95% CI: 2.66-213.49), were employed (AOR = 3.41; 95% CI: 1.89-10.70), had bacterial sexually transmitted infections (AOR = 3.98; 95% CI: 0.89-17.22) and were not taking antiretroviral therapy (AOR = 6.61; 95% CI: 2.25-19.37) had higher odds of being in a large cluster (size > 4).
CONCLUSION: Comprehensive HIV prevention packages should include behavioral and biological components, including early diagnosis and treatment of both HIV and bacterial sexually transmitted infections to optimally reduce the risk of HIV transmission and acquisition.

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Year:  2020        PMID: 31634185      PMCID: PMC7219556          DOI: 10.1097/QAD.0000000000002409

Source DB:  PubMed          Journal:  AIDS        ISSN: 0269-9370            Impact factor:   4.632


  38 in total

1.  Phylogenetic analysis of HIV-1 subtypes and drug resistance profile among treatment-naïve people in Kuwait.

Authors:  Wassim Chehadeh; Osama Albaksami; Haya Altawalah; Suhail Ahmad; Nada Madi; Sonia E John; Priya S Abraham; Widad Al-Nakib
Journal:  J Med Virol       Date:  2015-05-14       Impact factor: 2.327

2.  Individual and Sexual Network Predictors of HIV Incidence Among Men Who Have Sex With Men in Nigeria.

Authors:  Rebecca G Nowak; Andrew Mitchell; Trevor A Crowell; Hongjie Liu; Sosthenes Ketende; Habib O Ramadhani; Nicaise Ndembi; Sylvia Adebajo; Julie Ake; Nelson L Michael; William A Blattner; Stefan D Baral; Manhattan E Charurat
Journal:  J Acquir Immune Defic Syndr       Date:  2019-04-01       Impact factor: 3.731

3.  Phylogenetic Investigation of a Statewide HIV-1 Epidemic Reveals Ongoing and Active Transmission Networks Among Men Who Have Sex With Men.

Authors:  Philip A Chan; Joseph W Hogan; Austin Huang; Allison DeLong; Marco Salemi; Kenneth H Mayer; Rami Kantor
Journal:  J Acquir Immune Defic Syndr       Date:  2015-12-01       Impact factor: 3.731

Review 4.  Amplified transmission of HIV-1: missing link in the HIV pandemic.

Authors:  Myron S Cohen
Journal:  Trans Am Clin Climatol Assoc       Date:  2006

5.  Social network-based recruitment successfully reveals HIV-1 transmission networks among high-risk individuals in El Salvador.

Authors:  Ann M Dennis; Wendy Murillo; Flor de Maria Hernandez; Maria Elena Guardado; Ana Isabel Nieto; Ivette Lorenzana de Rivera; Joseph J Eron; Gabriela Paz-Bailey
Journal:  J Acquir Immune Defic Syndr       Date:  2013-05-01       Impact factor: 3.731

6.  Epidemiological study of phylogenetic transmission clusters in a local HIV-1 epidemic reveals distinct differences between subtype B and non-B infections.

Authors:  Kristen Chalmet; Delfien Staelens; Stijn Blot; Sylvie Dinakis; Jolanda Pelgrom; Jean Plum; Dirk Vogelaers; Linos Vandekerckhove; Chris Verhofstede
Journal:  BMC Infect Dis       Date:  2010-09-07       Impact factor: 3.090

Review 7.  Genetic Cluster Analysis for HIV Prevention.

Authors:  Mary Kate Grabowski; Joshua T Herbeck; Art F Y Poon
Journal:  Curr HIV/AIDS Rep       Date:  2018-04       Impact factor: 5.071

8.  HIV-1 Transmission Clustering and Phylodynamics Highlight the Important Role of Young Men Who Have Sex with Men.

Authors:  Ann M Dennis; Erik Volz; A S Md Simon D W Frost; Mukarram Hossain; Art F Y Poon; Peter F Rebeiro; Sten H Vermund; Timothy R Sterling; Marcia L Kalish
Journal:  AIDS Res Hum Retroviruses       Date:  2018-08-23       Impact factor: 2.205

9.  HIV-1 transmission networks in high risk fishing communities on the shores of Lake Victoria in Uganda: A phylogenetic and epidemiological approach.

Authors:  Sylvia Kiwuwa-Muyingo; Jamirah Nazziwa; Deogratius Ssemwanga; Pauliina Ilmonen; Harr Njai; Nicaise Ndembi; Chris Parry; Paul Kato Kitandwe; Asiki Gershim; Juliet Mpendo; Leslie Neilsen; Janet Seeley; Heikki Seppälä; Fred Lyagoba; Anatoli Kamali; Pontiano Kaleebu
Journal:  PLoS One       Date:  2017-10-12       Impact factor: 3.240

Review 10.  Inferring the age difference in HIV transmission pairs by applying phylogenetic methods on the HIV transmission network of the Swiss HIV Cohort Study.

Authors:  Katharina Kusejko; Claus Kadelka; Alex Marzel; Manuel Battegay; Enos Bernasconi; Alexandra Calmy; Matthias Cavassini; Matthias Hoffmann; Jürg Böni; Sabine Yerly; Thomas Klimkait; Matthieu Perreau; Andri Rauch; Huldrych F Günthard; Roger D Kouyos
Journal:  Virus Evol       Date:  2018-09-18
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  4 in total

1.  RFID Data Analysis and Evaluation Based on Big Data and Data Clustering.

Authors:  Lihua Lv
Journal:  Comput Intell Neurosci       Date:  2022-03-26

Review 2.  The Role of Phylogenetics in Discerning HIV-1 Mixing among Vulnerable Populations and Geographic Regions in Sub-Saharan Africa: A Systematic Review.

Authors:  George M Nduva; Jamirah Nazziwa; Amin S Hassan; Eduard J Sanders; Joakim Esbjörnsson
Journal:  Viruses       Date:  2021-06-19       Impact factor: 5.048

3.  Predictors of first-line antiretroviral therapy failure among adults and adolescents living with HIV/AIDS in a large prevention and treatment program in Nigeria.

Authors:  Nicaise Ndembi; Fati Murtala-Ibrahim; Monday Tola; Jibreel Jumare; Ahmad Aliyu; Peter Alabi; Charles Mensah; Alash'le Abimiku; Miguel E Quiñones-Mateu; Trevor A Crowell; Soo-Yon Rhee; Robert W Shafer; Ravindra Gupta; William Blattner; Manhattan E Charurat; Patrick Dakum
Journal:  AIDS Res Ther       Date:  2020-11-03       Impact factor: 2.250

4.  From general to specific: moving past the general population in the HIV response across sub-Saharan Africa.

Authors:  Keletso Makofane; Elise M van der Elst; Jeffrey Walimbwa; Steave Nemande; Stefan D Baral
Journal:  J Int AIDS Soc       Date:  2020-10       Impact factor: 5.396

  4 in total

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