Phylogenetic Insight into HIV Transmission Networks in a Southeastern US Cohort

Ann Dennis1, Stéphane Hué2, Christopher Hurt1, Sonia Napravnik1, Deenan Pillay2, and Joseph Eron1

1University of North Carolina at Chapel Hill; 2University College London, UK

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New HIV diagnoses continue in the US Southeast

• Minorities hardest hit in North Carolina: • Blacks accounted for 66% of new diagnoses in 2009• Latinos account for 8% ( from 1% in 1995)

• Primarily sexual transmission => MSM ~55% of new diagnoses ( from 49% in 2004)

North Carolina DHHS. 2010 Epidemiologic Profile for HIV/STD Prevention & Care Planning. www.epi.state.nc.us/epi/hiv/

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Phylogenetic inference using HIV-1 pol sequences• Population based sequence data can help characterize the structure

of epidemics - a new approach to HIV epidemiology • Paired with epidemiologic data, may provide insight into groups

responsible for on-going transmission1 • Pol sequences derived from HIV resistance testing have sufficient

variability to allow phylogenetic reconstruction2

1Chalmet K, et al. BMC Infectious Diseases. 2010;10(1):262.2Hué S, et al. AIDS 2004;18(5):719-728

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Objectives

Use phylogenetic analyses of HIV pol sequences in conjunction with epidemiologic data to better characterize groups where ongoing HIV transmission is occurring in North Carolina or identify potential gaps in HIV case finding

Overall

Specific

Determine composition of transmission clusters (n≥3 individuals)

Assess factors associated with cluster membership for newly diagnosed subset (2000-2009)

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Study Population – 1672 Patients

•one pol sequence available (earliest sequence used) •HIV Subtype B

Inclusion Criteria:

1. UNC CFAR Clinical Cohort (n=1373) “Unknown”/chronic duration44% ART naïve; sequences collected 1997-2009

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Study Population – 1672 Patients

•one pol sequence available (earliest sequence used) •HIV Subtype B

Inclusion Criteria:

1. UNC CFAR Clinical Cohort (n=1373)

2. Duke-UNC Acute HIV Consortium (n=298)

“Unknown”/chronic duration44% ART naïve; sequences collected 1997-2009

100% ART-naïve; sequences collected 1998-200957% Acute 43% Recent

(1) non-reactive ELISA or indeterminate WB with pos. RNA or p24 ag, or

(2) neg. ELISA and WB ≤45 days of pos. ELISA or WB

(1) neg. ELISA or WB between 45-180 days of documented pos. test, or

(2) results of duration <180 days by both less sensitive ELISA and avidity-modified third generation immunoassay

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Sequence sampling was proportional to racial demographics

Sequences • Derived from

commercial genotypes• Full PR and partial RT

(codons 1-400)• Resistance mutations

identified 1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

0

50

100

150

200Other/Unknown Latino

White Black

Sample Year

Sam

ple

coun

t

Race/Ethnicity: 59% Black , 30% White, 7% Latino

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Sexual transmission routes predominate

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Phylogenetic Analyses

1. Censored major drug resistance mutations2. Selected closely related sequences using Neighbor joining:

≤4.5% pairwise genetic distance (nucleotide substitutions/site) with at least one other sequence

3. Bayesian trees inferred using GTR+G model of nucleotide substitution

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Phylogenetic Analyses

1. Censored major drug resistance mutations2. Selected closely related sequences using Neighbor joining:

≤4.5% pairwise genetic distance (nucleotide substitutions/site) with at least one other sequence

3. Bayesian trees inferred using GTR+G model of nucleotide substitution

confidentcluster members share this ancestor

Transmission clusters:• Clades with ≥3 sequences

(individuals) • Rigid statistical support

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Results - Transmission Clusters

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Discrete onward transmission among MSM and heterosexuals

Majority: >50% of members share same transmission riskHomogenous: 100% of members share same transmission risk

Patients in Clusters

In Majority Cluster

MSM HET

MSM n=147 76% 7%

HET n=157 11% 73%

MSM Heterosexual Mixed

3026

1611 10

Number of Clusters

Majority Homogenous

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Clusters are associated with race

Majority: >50% of members are same race/ethnicityHomogenous: 100% of members are same race/ethnicity

Black White Latino Mixed

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1

8

21

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Number of Clusters

MajorityHomogenous

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Few Latinos were represented in clusters

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We found 5 Clusters with majority Transmitted Drug Resistance

Cluster ID No. Cluster Size TDR No. Acute Mutation

7 3 3 1 K103S, G190A

13 3 3 0 G190A

23 5 3* 0 D67N, K219Q

65 3 3 2 K103N

70 3 3 0 K103N

*all 5 members with same mutation

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Multivariable analysis: Factors associated with cluster membership for patients diagnosed 2000-2009

Characteristic Total n=889 OR (95% CI) P-value

Age at diagnosis ≤30 years 1.52 (1.10-2.12) .01

Race/Ethnicity*

White 0.78 (0.54-1.13) .19

Latino 0.30 (0.14-0.61) .001

Other/Unknown 0.93 (0.28-3.14) .91

Transmitted drug resistance 1.70 (1.04-2.77) .03

*Referent group Black race

Variables not significant: year of diagnosis, sex, transmission risk, ART-naïve status, genotype <1 year of diagnosis, duration of infection (unknown/acute/recent), CD4 count, RNA viral load (closest to diagnosis) 16

Limitations

• Reconstruction of networks only an estimate of the local epidemic

• Incomplete sampling – individuals undiagnosed, receiving care at another clinic, or who never had a genotype will be missed

• Cannot tell directionality of transmission • Only including clades with very robust statistical

support may underestimate number of clusters

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Conclusions

• Discrete onward transmission among both MSM and heterosexuals

• For newly diagnosed patients: non-Latino ethnicity, younger age, and transmitted drug resistance (TDR) were significantly associated with membership in transmission clusters

• Younger age and TDR - markers for very high risk behavior and rapid ongoing transmission?

• Latino epidemic incompletely delineated

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Implications for Intervention

• Phylogenetic analyses coupled with traditional epidemiologic data offers additional insight into local HIV epidemics

• Identifying groups at highest risk for on-going transmission can lead to enhanced or more targeted intervention programs

• Method to evaluate “hidden” populations such as Latino immigrants

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Acknowledgments

• Co-authors• Patients• UNC Center for AIDS Research • Duke-UNC Acute HIV Consortium • Mike Cohen

Supported by: NIAID (T32 AI007001-33), UNC Center for AIDS Research (P30 AI50410), and the Bristol-Meyers Squibb Virology Fellows Research Program

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