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AbstractIntroductionThe human immunodeficiency virus 1 (HIV‐1) pandemic is characterized by numerous distinct sub‐epidemics (clusters) that continually fuel local transmission. The aims of this study were to identify active growing clusters, to understand which factors most influence the transmission dynamics, how these vary between different subtypes and how this information might contribute to effective public health responses.MethodsWe used HIV‐1 genomic sequence data linked to demographic factors that accounted for approximately 70% of all new HIV‐1 notifications in New South Wales (NSW). We assessed differences in transmission cluster dynamics between subtype B and circulating recombinant form 01_AE (CRF01_AE). Separate phylogenetic trees were estimated using 2919 subtype B and 473 CRF01_AE sequences sampled between 2004 and 2018 in combination with global sequence data and NSW‐specific clades were classified as clusters, pairs or singletons. Significant differences in demographics between subtypes were assessed with Chi‐Square statistics.ResultsWe identified 104 subtype B and 11 CRF01_AE growing clusters containing a maximum of 29 and 11 sequences for subtype B and CRF01_AE respectively. We observed a > 2‐fold increase in the number of NSW‐specific CRF01_AE clades over time. Subtype B clusters were associated with individuals reporting men who have sex with men (MSM) as their transmission risk factor, being born in Australia, and being diagnosed during the early stage of infection (p < 0.01). CRF01_AE infections clusters were associated with infections among individuals diagnosed during the early stage of infection (p < 0.05) and CRF01_AE singletons were more likely to be from infections among individuals reporting heterosexual transmission (p < 0.05). We found six subtype B clusters with an above‐average growth rate (>1.5 sequences / 6‐months) and which consisted of a majority of infections among MSM. We also found four active growing CRF01_AE clusters containing only infections among MSM. Finally, we found 47 subtype B and seven CRF01_AE clusters that contained a large gap in time (>1 year) between infections and may be indicative of intermediate transmissions via undiagnosed individuals.ConclusionsThe large number of active and growing clusters among MSM are the driving force of the ongoing epidemic in NSW for subtype B and CRF01_AE.

Background. Previous genetic association studies of human immunodeficiency virus-1 (HIV-1) progression have focused on common human genetic variation ascertained through genome-wide genotyping. Methods. We sought to systematically assess the full spectrum of functional variation in protein coding gene regions on HIV-1 progression through exome sequencing of 1327 individuals. Genetic variants were tested individually and in aggregate across genes and gene sets for an influence on HIV-1 viral load. Results. Multiple single variants within the major histocompatibility complex (MHC) region were observed to be strongly associated with HIV-1 outcome, consistent with the known impact of classical HLA alleles. However, no single variant or gene located outside of the MHC region was significantly associated with HIV progression. Set-based association testing focusing on genes identified as being essential for HIV replication in genome-wide small interfering RNA (siRNA) and clustered regularly interspaced short palindromic repeats (CRISPR) studies did not reveal any novel associations. Conclusions. These results suggest that exonic variants with large effect sizes are unlikely to have a major contribution to host control of HIV infection. ; This study has been financed in part within the framework of the Swiss HIV Cohort Study (www.shcs.ch) project #651 and supported by the Swiss National Science Foundation (www.snf.ch) grant #148522 (J.F.). The International HIV Controllers Study was made possible through a generous donation from the Mark and Lisa Schwartz Foundation and a subsequent award from the Collaboration for AIDS Vaccine Discovery of the Bill and Melinda Gates Foundation (www.cavd.org). This work was also supported in part by the Harvard University Center for AIDS Research (cfar.globalhealth.harvard.edu) grant P-30-AI060354; University of California San Francisco (UCSF) Center for AIDS Research (cfar.ucsf.edu) grant P-30 AI27763; UCSF Clinical and Translational Science Institute (https://ctsi.ucsf.edu) grant UL1 RR024131; Center for AIDS Research Network of Integrated Clinical Systems (http://cfar.globalhealth.harvard.edu) grant R24 AI067039; and the National Institutes for Health (www.nih.gov) grants AI28568 and AI030914 (B.D.W.). The AIDS Clinical Trials Group was supported by NIH grants AI069513, AI34835, AI069432, AI069423, AI069477, AI069501, AI069474, AI069428, AI69467, AI069415, Al32782, AI27661, AI25859, AI28568, AI30914, AI069495, AI069471, AI069532, AI069452, AI069450, AI069556, AI069484, AI069472, AI34853, AI069465, AI069511, AI38844, AI069424, AI069434, AI46370, AI68634, AI069502, AI069419, AI068636, RR024975, AI077505, AI110527, and TR000445 (D.W.H.). For the CASCADE Consortium, the research leading to these results has received funding from the European Union Seventh Programme (FP7/2007–2013) under EuroCoord (www.eurocoord.net) grant agreement no. 260694 (K.P.) and the Spanish Network of HIV/AIDS grant nos. RD06/006, RD12/0017/0018 and RD16CIII/0002/0006 (J.DA.). A portion of the data in this manuscript were collected by the Multicenter AIDS Cohort Study (MACS). MACS (Principal Investigators): Johns Hopkins University Bloomberg School of Public Health (Joseph Margolick, Todd Brown), U01-AI35042; Northwestern University (Steven Wolinsky), U01-AI35039; University of California, Los Angeles (Roger Detels, Oto Martinez-Maza, Otto Yang), U01-AI35040; University of Pittsburgh (Charles Rinaldo, Lawrence A. Kingsley, Jeremy J. Martinson), U01-AI35041; the Center for Analysis and Management of MACS, Johns Hopkins University Bloomberg School of Public Health (Lisa Jacobson, Gypsyamber D'Souza), UM1-AI35043. The MACS is funded primarily by the National Institute of Allergy and Infectious Diseases (NIAID), with additional co-funding from the National Cancer Institute (NCI), the National Institute on Drug Abuse (NIDA), and the National Institute of Mental Health (NIMH). Targeted supplemental funding for specific projects was also provided by the National Heart, Lung, and Blood Institute (NHLBI), and the National Institute on Deafness and Communication Disorders (NIDCD). MACS data collection is also supported by UL1-TR001079 (JHU ICTR) from the National Center for Advancing Translational Sciences (NCATS) a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research. The contents of this publication are solely the responsibility of the authors and do not represent the official views of the National Institutes of Health (NIH), Johns Hopkins ICTR, or NCATS. The MACS website is located at http://aidscohortstudy.org/ ; Sí