HEPATITIS C VIRUS INFECTION IS UBIQUITOUS AMONG DRUG INJECTORS IN ST. PETERSBURG, RF Robert Heimer 1, Elijah Paintsil 1, Sergei Verevochkin 2, Russell Barbour 1, Edward d White 1, Olga Toussova 2, Linda M. Niccolai 1, & Andrei P. Kozlov 2 Yale University, New Haven, CT, USA Biomedical Center, St. Petersburg, RF
SATHCAP: The Role of Drug Use in Sexual Transmission of HIV Study funded by the National Institute on Drug Abuse to examine the transmission of HIV among drug using populations and from drug using to non-drug using populations. Specifically designed to determine the role of drug use in the sexual transmission of HIV and to identify bridge populations from drug users to non-drug users.
Four Cities, One Method St. Petersburg PIs: Robert Heimer (Yale) and Andre Kozlov (BMC) Los Angeles -- UCLA PIs: Steven Shoptaw and Pamina Gorbach Chicago -- U. of Illinois, i Chicago PI: Larry Ouellet Raleigh-Durham -- RTI PI: Bill Zule Scientific Coordinating Center -- RAND PIs: Martin Iguchi and Sandra Berry
Dual Risk Group Recruitment Simultaneous sampling of two primary and potentially overlapping risk groups using respondent driven sampling (RDS) drug users men who have sex with men (MSM) Secondary sample of Sexual Partners (SPs) and a tertiary sample of Partners of Partners (PPs) recruited using snowball sampling
Dual Risk Core Group Recruitment in St. Petersburg IDUs MSM 387 64 5 In St. Petersburg, populations of IDUs and MSM seem not to intersect to any great extent.
Extended Recruitment from RDS Core Sample to Sexual Partners Drug Users MSM Sexual Partners (n=44)
Sexual Partners Recruited Their Sexual Partners Drug Users MSM Sexual Partners Partners of Partners
Data Collection RDS included information on recruitment links and network sizes ACASI used to collect self-reported risk behaviors, including data on individual drug use and sexual partnerships Biological data included HCV testing, HIV testing, and other STI testing
Prevalence Data Drug user demographics: 387 of 416 drug users were injectors. Median age is late 20 s. 70% male. St. Petersburg is experiencing concentrated HIV and HCV epidemics among its drug users. IDU Non-IDU drug user Sex partner MSM MSM/IDU MSM/DU % HIV+ 50% 0% 16% 18% 60% 27% % HCV+ 95% 0% 14% 5% 100% 9%
Molecular Biology of HCV High degree of genetic heterogeneity As many as 11 genotypes and multiple subtypes Genotype can serve as a marker of transmission
Experimental Design for HCV Genotyping and Sequence Analysis HCV viral RNA was extracted from stored serum from HCV seropositive participants. Viral RNA was amplified using a one-step RT- PCR kit targeting the core and primers. The ~400 bp product was purified and sequenced by automated fluorescent sequencing. A dendrogram was created with DNADIST and NEIGHBOR, PHYLIP package. SEQBOOT was used to bootstrap 100 data sets.
Geographic Distribution of HCV 218 samples from IDUs sequenced Genotype 3a predominates (57.3% of 218 genotyped samples) citywide. More research is needed to understand d the 14% prevalence among non-du sex partners of IDUs.
Integrating Molecular Epidemiology and Network Information RDS recruitment chains tap into networks through h which h HCV and other infections are potentially transmitted. Hypothesis: Molecular linkages within networks and between dyads d will reflect transmission events. Data: Hepatitis C genomic sequences.
HCV Sequences within Recruitment Chains Are Not Clustered 1b 1a 3a 2
Social Connectedness between Dyads Does Not Predict HCV Genetic Similarity Degree of social Different genotype Median genetic distance connection 59 of 108 pairs 59 of 108 pairs Type of relationship Friend Acquaintance/Stranger Sex partner Yes No Drug gpartner Yes No Duration of relationship >5 years 5 years Proportion overlapping drug network 5 years <5 years 28 (60%) 30 (53%) p = 0.48 17 (57%) 42 (55%) p = 0.84 44 (56%) 15 (60%) p = 0.71 18 (62%) 37 (49%) p = 0.24 22 (54%) 25 (53%) p = 0.97 0.051 0.051 p = 0.93 0.034 0.051 p = 0.36 0.051 0.051 p = 0.99 0.068 0.051 p = 0.26 0.051 0.051 p = 0.61
Conclusions on HCV Transmission within Networks The ability of dyads or recruitment chains to capture transmission patterns for prevalent infections appears limited. Molecular epidemiological tools will provide support for transmission within social networks only if incident transmissions of infectious diseases are considered.
Final Observations Although HCV is ubiquitous, most infections are with treatable genotypes, especially 3a. High prevalence (14 14%) of HCV among non- IDU sex partners suggests sexual transmission. Further study, especially on role of HIV/HCV co- infection among transmitting IDUs, warrants detailed study. St. Petersburg might be one of the few places were such a study could be conducted.