HIV-1 Serodiscordant Couples:

Priority for Public Health and

Pathogenesis

Jairam Lingappa, MD, PhDDepartments of Global Health and Medicine

Key messages• Infectious diseases are transmitted in an

environmental context• The study of host HIV-1 susceptibility factors

should capture that context• Discordant couples are an important model for

public health and pathogenesis • Ongoing studies of HIV-1 discordant couples in

Africa will evaluate factors in heterosexual transmission

Caveats

• Focus on sexual transmission of HIV-1

• Much more data is published on risk factors for other forms of HIV-1 transmission and HIV-1 disease

Sexual Transmission of HIV-1

• All HIV-1 sexual transmission involves one HIV-1 infected/transmitting and one uninfected/exposed partner (discordant couple)

• This partnership is more traceable in some cases

• What are the factors that determine when transmission occurs

HIV-1 Transmission Factors

• The exposed partner ?

• The infected partner?

• Behavior ?

HIV-1 Transmission Risk: Is it the number of sex acts or number of individuals?

Model heterosexual and MSM transmission data:

- Known HIV-1 infected and uninfected partners

- Does infectivity depend on # sex acts or # partners (Peterman 1988; Grant 1987; Kaplan 1990)

• 55 heterosexual couples with 10 transmissions– Infectivity per sex act 0.0014 [0.0006-0.002] however:– 26 couples with fewest sex acts yielded 70% of transmissions– 27 couples with most sex acts accounted for 30%– 1980s data

Not consistent with model that transmission is proportional to exposure based solely on number of sex acts

HIV-1 Transmission: By individual or by sex act

• 138 MSM yielding 11 seroconversions– Infectivity per partner of 0.051 [0.022 – 0.08]

Transmission Probability Number of Partners

0.5 1

9.7 2

0.11 3-4

0.42 5

• Probability of transmission varied by number of partnerships, • Highest probability is for two partners.• Need additional biological data to characterize infectiousness and susceptibility

Heterosexual Couples Studies:Rakai, Uganda

• Community randomized trial of STD control for HIV prevention – 415 HIV-1 discordant couples– 174 monogamous

• Followed every 10 months for 3 visits; study conducted over 4 years– Sexual/clinical history – HIV-1 RNA, HIV-1 subtype, GUD/STD

• Compare SC to non-SC– Matched by age, gender and time of HIV RNA

Rakai Transmission data

Characteristic Adj RR

Age15-29 y 2.38 (1.3-4.4)

>30 y 1

Genital Ulcer Disease

Yes 2.05 (1-4.1)

No 1

HIV RNA quantile (log10)

>4.89 7.06 (2.3-21.8)

4.17-4.89 6.39 (2.1-19.4)

3.5-4.16 3.31 (1-10.8)

0-3.49 1

Stage of infectionIncident 4.98 (2-12.4)

Prevalent 1

Late stage 3.5 (1.8-6.9)

Wawer et al JID 2005

Rakai HIV-1 transmission per coital act

• Incident index partner in early infection:– 0.0082 (0.0039-0.0150)

• Prevalent index partner after 21-40 months of follow-up– 0.0004 (0-0.001)

• Compare to estimate from heterosexuals in US 5 years earlier (Kaplan et al 1990)

– 0.0014 [0.0006-0.002]

Meta-Analysis of Heterosexual Transmission Risk Probability and Co-factors

• Review of 29 observational studies with 15 heterosexual infectivity estimates

• 9/15 were discordant couples studies – 4 longitudinal– 5 cross-sectional

• Summarize infectivity estimates

• Quantify cofactor effects on infectivity

Powers et al Lancet 2008

Category # of estimates Rate/1000 (95% CI)

Region

USA/Europe 8 0.59 (0.44-0.75)

Africa 6 0·91 (0·59–1·22)

Asia 1 31·00 (25·00–40·00)

Sex actPenile-vaginal 5 0·84 (0·51–1·17)

Penile-anal 1 33·80 (18·51–49·09)

TransmissionMTF 10 0·66 (0·54–0·79)

FTM 6 2·76 (1·19–4·33)

GUDNo 4 3·72 (0·70–6·75)

Yes 5 30·55 (11·27–49·84)

STI (in exp)No 1 12·00 (6·00–25·00)

Yes 2 55·86 (4·43–107·29)

Male Circumcision

Circ 2 5·13 (3·37–6·89)

Not Circ 2 97·33 (0·00–295·16)

Age (exp)>30 y 6 1·06 (0·56–1·56)

<30 y 2 15·71 (0·00–45·20)

Disease Stage (inf)

Mid 4 0·71 (0·57–0·85)

Early 2 4·67 (0·00–10·46)

Late 4 3·18 (0·94–5·42)Powers et al Lancet 2008

Infectivity estimates and epidemiologic context

• Common estimate for HIV-1 infectivity in heterosexual contact: 0.001– Should be considered a lower bound

• Meta-analysis:– Penile-vaginal contacts – 0.1– Penile-anal contact – 0.3

Epidemiologic context can greatly impact transmission risk

HIV-1 Transmission:Exposure Factors

• The exposed partner: – GUD/STD

– Gender

– Male Circumcision

– Age

• The infected partner: – GUD/STD

– Gender

– Stage of infection

– HIV-1 plasma/genital RNA

• Behavior: - Sex practices (anal vs. vaginal)- Condom use

HIV-1 Resistance: Cellular Immune Factors

• HIV-1 specific CD8-CTL– Kenyan CSW – US/Canadian discordant couples – US MSM +/-

• HIV-specific CD4+ IL-2/proliferative response– Kenyan CSW– Italian discordant couples

• Increased Immune activation – 2 discordant couples studies– 1 contradictory MSM study

HIV-1 Resistance: Humoral Immune Factors

• HIV-1 specific mucosal IgA responses– Italian discordant couples – Thai and Kenyan CSW– Contradictory findings in US discordant couples

• Autoantibodies (-CD4, CCR5, -HLA)– Italian discordant couples contradictory

HIV-1 Resistance: Innate factors

• CCR5-32– MSM and discordant couples at low frequency– Not present in African cohorts (CCR2-64I)– CCR5D32/CCR5-2459A/G haplotype in MSM

• CCL3L1 (MIP-1 natural ligand of CCR5)– Higher copy number in cross-sectional cohorts

HIV-1 Resistance: Innate factors

• Class I HLA– A2 supertype protects Kenyan EU not Zambian– A*36 in transmission in HIV-infected partners– Lower Class I allele sharing between partners

• Class II HLA– DRB1/DQB1 associated in Zambian EU– DR5, DQ4

• Non-classical HLA– HLA-E, HLA-G with increased susceptibility in African

women (cross-sectional)

HIV-1 Resistance: Innate factors

• KIR/Class I HLA– CSW in Cote d’Ivoire EU with NK-cell inhibitory

receptor (3DL1/2DL3) lacking HLA cognate (Bw4/C1)

• DC-SIGN/DC-SIGNR – DC-SIGN het repeat polymorphism in MSM– Cross-sectional cohort in North Indians (DC-SIGNR

7/7 homozygote with increased infection)– Cross-sectional MSM cohort (DC-SIGNR 7/5 het with

resistance)

• Trim5, APOBEC3G small MSM and cross-sectional heterosexual cohorts

Factors in HIV-1 Sexual Transmission

• How to make sense of it all:– Diversity in host factors could represent

• Many pathways to resistance• Lots of false positive associations

– Difficult to compare across many cohorts with candidate gene testing

• Given importance of characterizing exposure, use of convenience-based sampling of controls (blood donors or uncharacterized HIV-positives) may be comparing “apples” and “oranges”

What is needed

• Large cohorts

• Cases and comparison groups with well characterized HIV-1 exposure

• Wide evaluation of host genotypic, immunologic and viral characteristics in the same individuals

African HIV-1 Discordant Couples

• Public Health imperative: – >50% of all stable couples in which one partner is HIV-1

infected has an HIV-1 negative partner (i.e., are HIV-1 discordant)

– 50-60% of new HIV-1 infections in married couples may come from married partner (based on data from Kenya/Uganda)

– Important to develop couples counseling capacity and community awareness of HIV-1 discordance in African communities

African HIV-1 Discordant Couples

• Research potential:– High rates of retention (couples counseling)– Prospective follow-up for both couples

• Sexual history, demographics, clinical data

– Specimen collection for• Host genetic• Host immunologic• Viral sequencing

• Drawbacks: Increased cost and infrastructure

UW Studies of HIV-1 Discordant Couples in Africa

Study Purpose Cohort # SC Locations Follow-up Status

Partners Study

HSV-2 suppression to reduce HIV-1 transmission

3408 couples- HIV/HSV-2+CD4>250

~150 7 East Africa7 Southern Africa

12-24 mo Follow-up Complete

COS Observational 475 couples-few restrictions

~25 1 Uganda1 RSA

12 mo Sept 2009

Partners PrEP

Pre-Exposure prophylaxis in HIV-1 negative to reduce HIV-1 transmission

3900 couples ~190 4 Uganda4 Kenya

24-36 mo Enrl – 2010F/u - 2013

Total --- ~7800 couples ~365 --- 12-36 mo --

UW Discordant Couples Cohorts:Specimen Collection

Specimen type FrequencyPlasma Quarterly

Serum Quarterly

Cervical swab Quarterly

Semen 1 time point

PBMC 6-monthly*

Whole blood RNA 6-monthly*

* Collected at 2 sites in Partners Study and COS

Partners Study:Baseline Demographic Characteristics

Characteristic

Couples w/HIV-infected Women Couples w/HIV-infected Men

HIV-infected Female (#, %)

HIV-uninfected Male (#, %)

HIV-infected Male (#, %)

HIV-infected Female (#, %)

Median age (IQR) 30 (25-35) 35 (30-42) 37 (32-45) 31 (25-38)Yrs living w/ partner (median, IQR)† 5 (2-9) -- 6 (3-13) --

Number of children (median, IQR) † 2 (1-3) -- 3 (2-5) --

Total sex acts (median, IQR) † 4 (2-8) -- 4 (2-8) --

Unprotected sex acts (median, IQR) † 0 (0-1) -- 0 (0-1) --

Couples reporting any unprotected sex acts 661 (29%) -- 311 (28%) --

Use condoms for contraception 1062 (46%) -- -- 490 (44%)

Use no contraception 727 (32%) -- -- 372 (33%)

Partners Study:Baseline Clinical and Lab Characteristics

Characteristic

Couples w/HIV-infected Women Couples w/HIV-infected Men

HIV-infected Female (#, %)

HIV-uninfected Male (#, %)

HIV-infected Male (#, %)

HIV-infected Female (#, %)

Symptoms of GUD (previous 3 mos)

174 (8%) 46 (2%) 63 (6%) 54 (5%)

HSV-2 seropositive 2272 (99%) 1361 (59%) 1080 (97%) 954 (85%)

N. gonorrhoeae +(TMA) 40 (2%) 13 (1%) 10 (1%) 10 (1%)

C. trachomatis + (TMA) 46 (2%) 66 (0.3%) 16 (1%) 19 (2%)

T. vaginalis + (TMA) 314 (14%) 157 (7%) 52 (5%) 102 (9%)

Positive RPR 140 (6%) 107 (5%) 61 (6%) 43 (4%)

CD4 count (cells/mcL) (median, IQR)

483 (355-665) -- 424 (334-571) --

HIV-1 plasma RNA Log10 (median,IQR) 4.0 (3.4-4.6) -- 4.4 (3.7-4.9) --

Pathogenesis Studies Planned

• Envelope sequencing of transmitted variants (Mullins)• Genome-Wide Association Study (CHAVI)• Candidate Gene Genotyping (D. Nickerson/M. Bamshad)• HLA typing• Pre-seroconversion Gene Expression Arrays studies• Pre-seroconversion HIV-1 specific CD4 and CD8 studies

and risk of HIV-1 acquisition (McElrath)• Immune activation studies: Risk of acquisition, effect on

set-point viral load in seroconverters (McElrath)• HIV-1 clade studies: HIV transmission risk and set point

in seroconverters• Neutralizing antibody studies

Acknowledgments: Clinical Trial Coordinating Center

Coordinating Center:• Principal Investigator: Connie Celum• Co-Investigators: Anna Wald, Julie McElrath, Jared Baeten, Jai Lingappa, Larry Corey • Program Management: Linda Barnes • Regional Directors: Nelly Mugo, & Andrew Mujugira, Patrick Ndase• Clinical Monitors: Marothodi Semenya, Apollo Odika, Hilda O’Hara• Coordinating Center Operations: Margaret Warner-Lubin, Dana Panteleeff, Meighan Krows,

Heena Shaw, Ellen Wilcox• Biostatisticians/Data Management: Jim Hughes, Deborah Donnell, Amalia Meier, Richard

Wang, Erin Kahle, Lara Kidoguchi, Renee Hefforn, Jennifer Broad • Fiscal/Admin: Linda Barnes, Darcie Somera, Carlos Flores, Becky Karschney, Matt Leidholm,

Toni Maddox, Alice Rose, Troy Sexton, Calvin Tran, Christy Wilson • Central Repository: Harald Haugen, Justin Brantley, Shauna Durbin, Vikram Nayani Coordinating Center Contractors:• Site Laboratory Oversight: Wendy Stevens, Clinical Lab Services, Univ of Wits• HIV-1 Retrovirology Labs: Bob Coombs, Joan Dragavon; Jane Kuypers, Reggie Sampoleo • HSV-2 Virology Lab: Rhoda Ashley, Anne Cent• HIV Virology (Endpoint Analysis) Lab: Jim Mullins, Mary Campbell• Data Management Contractor: Darryl Pahl & Lisa Ondrajeck

DSMB: Rich Whitley, ChairFunding: Bill & Melinda Gates Foundation

Partners Study Site Investigators

– Nairobi: J Kiarie, C. Farquhar, G. John-Stewart– Kisumu: E. Bukusi, C. Cohen– Eldoret: E. Were, K. Fife– Thika: N. Mugo– Tanzania: R. Manongi, S. Kapiga– Kampala: E. Nakku-Joloba, L. Kavuma, A. Ronald, E. Katabira– Kigali: B Bekan, K. Kayatenkore, S. Allen– Soweto/PHRU: G. Gray, G. DeBryn, J. McIntyre– Orange Farm/RHRU: S. Delaney & H. Rees– Cape Town: A. DeCock, D. Coetzee– Gaborone: P. Dusara, J. Makhema , M. Essex– Lusaka, Ndola & Kitwe: M. Inambao, W. Kanweka, S. Allen

And above all: thanks to all study participants