6/10/2015. Background. Background. Background. Background. Methods

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1 /1/1 The challenges of diversity: HIV-1 subtype distribution and transmission s within the Australian Molecular Epidemiology Network-HIV -1 Castley A, Sawleshwarkar S, Varma R, Herring B, Thapa K, Chibo D, Nguyen N, Hawke K, Ratcliff R, Dwyer DE, Nolan D: The Australian Molecular Epidemiology Network-HIV (AMEN-HIV). laboratories throughout Australia for >1 years 1 laboratories throughout Australia for >1 years C subtype laboratories throughout Australia for >1 years C subtype AE subtype Phylogenetic analysis: statistical approach, used globally. Viral sequence similarity: More likely from a transmission chain/ (does not infer direct transmission) More likely to be found in early versus long-term infection (host factors) Dependent on sequence quality and Data analysis at one site Sequence alignments checked 1 1 Duplicate sequences checked length of HIV-1 sequence assessed Complete dataset other than NSW Overall: 1 7 sequences Sainani K. Methods Australian Molecular Epidemiology Network (AMEN) formed December 1 All states and territories represented (NT + Tas Vic) Ethics and governance framework established De-identified HIV-1 sequence results Gender, age, state Year of sequencing HIV-1 sequences (RT + PR)

2 SA /1/1 Phylogenetic analysis Results: Proportion of HIV-1 sequences committed per to the AMEN study Evidence of of phylogenetic transmission cluster by (similar association: HIV-1 sequences) CLUSTERING CRITERIA Bootstrap 9% Genetic distance 1.% MEGA provides the Bootstrap test -reliability of Phylogenetic tree Nucleotide sequences are re-sampled 1 times. Maximum-Likelihood branch lengths are computed. How likely is it that sequences will cluster together statistically in repeated analyses? ( 9 out of 1 times) How genetically similar are the sequences? ( 9.% identical) 7 Non B (%) B (%) Total (17.9%) 19 (.1%) 179 SA 111 (1.%) (.%) 1 7 (.%) 11 (7.%) 1 97 (1.%) 7 (9.%) 7 1 (.1%) 7 (7.9%) 1 TOTAL 1 (.%) 1 (7.%) 7 Results: HIV-1 subtype distribution over time Results: HIV-1 subtype distribution per state in more detail Total number of sequences n=7 non 9 SA Vic Qld SA Vic W-NSW Qld Subtype B Subtype (%) CRF1_AE (%) C Subtype (%) CRF_AG (%) D Subtype (%) Inter-subtype forms (%) Other Subtypes (%) Results: Age and gender according to HIV-1 subtype Non Results: phylogenetic analysis distribution Female Male s Non s Sequences in phylogenetic clusters B-subtype: 9 / 1 (.%) Non-B-subtype: / 1 (.%) Overall: 11 / 7 (.%) C Non () () CRF1_AE Mean Std N Mean Std n Female Male p=.1 11 CRF_AG 1

3 /1/1 Results: Detection of HIV subtype pairs and s over time Results: Distribution of size for a given HIV subtype Non B C Subtype CRF1_AE Subtype B Subtype 1 1 Pairs Networks > Pairs Networks > Sequences C subtype (%) CRF1_AE subtype (%) (%) Pairs Network of Network of.. 1. Network of Network of 1. Significantly more non B pairs than non B larger s (p=.) Larger size (>) with s than the non s (p=.1). 1 Results: Gender distribution in HIV s for a given subtype Results: Proportion of B and Non-B sub-type s according to gender 7% of male only groups % groups are % AE subtype groups are 17% C subtype groups are 1% 9% % 7% % % % % % 1% % * * * CRF1_AE C subtype Female only Male+Female Male only 1 B- sequences SA Nationally 1 Non-B- sequences SA Nationally 1 1 * Anova: Male only Male+Female Female only Non-B - singleton Results: Age and gender according to HIV-1 subtype and size Mean=. Std Dev=1. N=7 Mean=9. Std Dev=1. N=7 Non-B - pairs Mean=1.1 Std Dev=11. N=7 Mean=. Std Dev=1. N=11 Non-B- (> in size) Mean=9. Std Dev=1. N= Mean=.7 Std Dev=11. N=9 s Results: comparison of interstate vs intra-state clusters Sequences in interstate versus intra-state clusters (> in size) B-subtype: 19 / (.%) Non-B-subtype: / 11 (.%) B - singleton Mean=7. Std Dev=11.1 N=19 Mean=9.7 Std Dev=11. B - pairs Mean=.1 Std Dev=1. N= Mean=. Std Dev=1. B - (> in size) Mean=. Std Dev=1. N= Mean=7.9 Std Dev=11.7 Non s CRF1_AE C Overall: / (.%) Sequences in interstate versus intra-state clusters (pairs) B-subtype: 7 / (.%) Non-B-subtype: / 1 (1.%) N=17 N= N=17 Overall: 11 / 7 (19.%) 17 CRF_AG 1

4 /1/1 AMEN collaboration has established a national approach to HIV-1 molecular epidemiology studies Ethics and Governance frameworks are in place National database: prospective as well as retrospective dataset Inclusion of NSW data underway Platform for research collaboration: non-affiliated. Not a contact tracing analysis De-identified baseline viral sequencing data 19 s in Australia Overall ~% of sequences are non-b-subtype Increasing proportions across all states, with a broad range of subtypes reflecting geographic origins. Reflects a growing influence of migration and travel Wide age distribution for both B- and non-bsubtype More pediatric cases with non-s More females with non-s (esp. C-subtype) B-subtype sequences remain predominantly associated with males HIV-1 phylogenetic clusters in Australia Overall ~% sequences classified within clusters Similar proportions of B-subtype (%) and non-bsubtype (%) sequences within clusters Higher proportion of male/female clusters in non-b C-subtype (S Africa, India): 9% AE-subtype (SE Asia): % B-subtype: 1% Highlights the national structure of HIV-1 in Australia Common challenges to all states Growing impact of travel and migration Benefits of engagement with international partners Provides a basis for creating and monitoring prevention strategies No obvious clustering according to state. Significant proportion of clusters involve sequences from more than 1 state (% of pairs, Valuable data: now and for future Collaborative : facilitated engagement with clinical, scientific and community organizations % of larger clusters) 1 Acknowledgements Western Australia George Guelfi Mina John NSW Tony Kelleher Angie Pinto Roger Garsia South Australia VIDRL Megan Gooey Mike Catton Queensland Helene Johanson STI/HIV conference (ISSTDR scholarship) allison.castley@health.wa.gov.au

5 /1/1 Results: Proportion of sequences from interstate or intra-state s according to size Networks with a B-subtype > Networks with a Non-B-subtype B sequences * Results: size in B and non-s for each state SA Non B sequences SA Network size pair Interstate Intrastate Results: Factors associated with a sequence being classified into a cluster (y,n:>1yo) Variables associated with the classification of sequences into larger size - or >. (>1yo, not pairs) Overall SA WM NSW Overall SA AGE p=. -.1 p= p=. AGE. p=. -.1 p= p=..1 p= p=.. p=.1 SEQ ERA...7. p=.. p=.1. p=.1 SEQ ERA. p=..9 p=. -. p=.9. p=.. p=.7. p=. Gender -.1 p=. -. p=.17. p= p=. -. p=.9 -. p=. Gender -.1 p=. -. p=.. p= p= p=. Non-B vs B -. p=.1.1 p= p=. -. p=.11. p=. -. p=.7.7 p= Non-B Vs B -. p=.. p= p=..9 p= p=.1. p=.7 Coefficient and significance 7 Coefficient and significance