Inter-country mixing in HIV transmission clusters: A pan-european phylodynamic study
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1 Inter-country mixing in HIV transmission clusters: A pan-european phylodynamic study Prabhav Kalaghatgi Max Planck Institute for Informatics March 20th 2013
2 HIV epidemic (2009) Prabhav Kalaghatgi 2/18
3 The Complex Epidemiology of HIV Geographic variance in epidemic characteristics Dominant transmission modes MSM, HET in west and center Europe HET, IDU in east Europe Incidence Rate in east Europe 4 times that in west, center Europe Transmission on unknown networks Propagates on sexual (MSM, HET) and drug (IDU) networks A better understanding of this complex epidemic is required to mitigate its spread Prabhav Kalaghatgi 3/18
4 Epidemiology from sequences For fast evolving pathogens, transmission and ecological dynamics shape phylogeny Phylogenetic epidemiology Estimate evolutionary relationship Infer epidemic dynamics Infer epidemic spread Prabhav Kalaghatgi 4/18
5 Previous work Geographic segregation Pan-mixing Switzerland [Kouyos et. al., 2010] French vs German Italy [Prosperi et. al., 2011] North vs South Germany [Lawyer et. al., 2012] Cologne vs Dusseldorf Non-uniform sample of patients (showing transmission linkage) 10 countries [Paraskevis et. al., 2009] Cross-country migration Uniform sample of patients (90 per country) Prabhav Kalaghatgi 5/18
6 Aim Quantifying the extent of cross-country transmission in Europe EuResist Country Patients Italy 8384 Germany 2082 Sweden 992 Portugal 522 Unknown 7813 Transmission Patients MSM 5198 HET 3459 IDU 3707 Unknown 9130 Total Oldest sequence per patient Subtype B, subtyped with COMET Protease, Reverse transcriptase Remove sites under selective pressure, 705 nt long Prabhav Kalaghatgi 6/18
7 Transmission graph over thresholds Prabhav Kalaghatgi 7/18
8 Quantifying mixing on a graph Assortativity coefficient M. E. J. Newman: Mixing patterns in networks, Phys. Rev. E 67, (2003) e i,i ai 2 i i r = 1 ai 2 i 1 pro preference r = 0 no preference 1 anti preference e i,j = fraction of edges connecting type i vertices to type j vertices a i =fraction of edges with at least one vertex type i Prabhav Kalaghatgi 8/18
9 Inter-country mixing on graph Prabhav Kalaghatgi 9/18
10 At highest feasible threshold 5514 (25%) patients linked to at least one other patient High node degree (max 350) Use bootstrapped trees to robustly infer transmission linkage Prabhav Kalaghatgi 10/18
11 Quantifying robustness in transmission linkage Select 5514 patients linked at highest feasible threshold Bootstrap sequences by sampling alignment columns Construct trees for 1000 bootstrap replicates FastTree Measure of robustness is clade frequency Transmission clades = clades with frequency > 0.9 Prabhav Kalaghatgi 11/18
12 Transmission clades 4775 (87%) patients robustly linked to at least one other sequence Log-det threshold captured transmission edges Clade size distribution size # clades s = < s < s Germany Belgium Italy Unknown How homogenous are the large clades (s 10) in origin of infection? Prabhav Kalaghatgi 12/18
13 Transmission clades 4775 (87%) patients robustly linked to at least one other sequence Log-det threshold captured transmission edges Clade size distribution size # clades s = < s < s Germany Belgium Italy Unknown How homogenous are the large clades (s 10) in origin of infection? Prabhav Kalaghatgi 12/18
14 Country-wise homogeneity in large clades Homogeneity = highest proportion of patients from same country Origin of infection known for at least 40% Measured for 65 clades, 1081 patients Prabhav Kalaghatgi 13/18
15 Conclusion HIV epidemic is characterized by 1. Local spreading within countries Similar results as German, Italian and Swiss study 2. Migration between countries In agreement with Paraskevis s study Large scale studies are imperative for reconstructing epidemic routes Prabhav Kalaghatgi 14/18
16 Bibliography 1. Kouyos, R. D. et. al. Molecular epidemiology reveals long-term changes in HIV type 1 subtype B transmission in Switzerland. J. Infect. Dis. 201, (2010). 2. Lawyer, G. et. al. Endogenous or exogenous spreading of HIV-1 in Nordrhein-Westfalen, Germany, investigated by phylodynamic analysis of the RESINA Study cohort. Med Microbiol. Immunol. 201(3): (2012). 3. Paraskevis, D. et. al. Tracing the HIV-1 subtype B mobility in Europe: a phylogeographic approach. Retrovirology, 6:49 (2009). 4. Prosperi, M. C. F. et. al. A novel methodology for large-scale phylogeny partition. Nat. Commun. 2:321 doi: /ncomms1325 (2011). Prabhav Kalaghatgi 15/18
17 Acknowledgments Glenn Lawyer Thomas Lengauer Department of Computational Biology and Applied Algorithmics EuResist Network Study Group Prabhav Kalaghatgi 16/18
18 Thank you for your attention! Questions? Poster: O 07 Prabhav Kalaghatgi 17/18
19 Building a transmission graph Add edge between patients if inter-sequence distance < threshold Distance = Log-det, a measure of evolutionary divergence Threshold feasibility Low thresholds = some true edges, small components Large thresholds = true + false edges, one large component Select threshold just before components start coagulating m i=1 coag = C i 2 N 2, coag [ 2 N, 1] Prabhav Kalaghatgi 18/18
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