Does HIV genotype influence rate of disease progression?

dinnerworkableUrban and Civil

Nov 16, 2013 (3 years and 8 months ago)

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Does

HIV

genotype influence rate of disease progression?


Andrew Leigh Brown, Luc
y Weinert, (University of Edinburgh)
Andrew Phillips
(RFH/UCL)
David Dunn (MRC CTU), Deenan Pillay (UCL)


Background

It is generally hypothesised that the virulence of a pat
hogen responds to natural
selection for maximal transmission
1
-
4
. There has been

little evidence that HIV has
modulated its virulence in this way
5

but recently it was suggested that the wide
variation in set
-
point viral load observed in HIV
6

could have a viral, as well as a host
7
,
genetic basis
8
. A necessary condition for this hypothesis to hold is that viral loads are
correlated between index and contact cases
. This would be of considerable clinical
importance as it would imply that contacts of individuals who progressed rapidly
would themselves be expected to progress more rapidly, a contention that has been
highly controversial
9;10
.
If this was the case, it would open the way to evolutionary
changes in virulence over time
11;12
.

S
ome

recent evidence from

partner studies
13;14

suggested

a positive correlation
bet
ween transmitter and recipient, but in the absence of information regarding t
he
viral origin of the transmission

which in

one of the recent studies only 27% of
transmissions in this patient group could be strongly supported following a
phylogenetic analysis
15
.

Under the

current

UK
HIVRDB
project

Inferring HIV transmission networks from
time
-
resolved viral phylogenies for epidemiological

modelling


(
Authors: Leigh
Brown et al.;
Proposal
date 4/9/06), we have characterised time
-
resolved clusters
from the sequences in the database for

both a subset of subtype B/MSM
sequences
and
for all

non
-
B subtypes/heterosexual infections
16;17
. Current
ly this work continues
for all subtype B/MSM infections in the Database.

For many individuals in
the
phylodynamics studies described above
sequential viral
load data are available. It is therefore possible to address the question of correlation
of HIV vir
al load following transmission directly using only patients whose virus has
been shown to be phylogenetically associated.
The UKHIVRDB thus presents a
unique opportunity to test an epidemiologically very significant question.

Data


HIV pol sequences (PR+p
artial RT) from UK HIV Drug Resistance Database, 2008
download

all associated viral load data

from before initiation of antiretroviral therapy
.
Number of sequences: 44,721; Number of patients: 34,519; patients with viral load
data: 14,240, 58% MSM
. Data ar
e anonymised and irreversibly delinked from clinical
identifiers.


Methods

Identification and analysis of clusters as

performed in studies covered by previous
proposal
16;17
.

From the current

study we anticipate 25% of MSM (approx. 2100 individuals) will be
in clusters of size 10 or greater.

Analysis of viral load will be performed using (1) earliest availa
ble viral load as a
proxy for set point and (2) a longitudinal model for viral load
developed by
collaborator Dr Simon Frost
18
.

C
orrelation among individuals within clusters before
will

be estimated directly by
comparison with that obtained from a randomly generated sample of individuals
,
allo
wing a greatly increased power over partner studies
.

Estimated project duration

12 months


Database
/analysis

Requirements


Dataset download with additional viral load sequences; geographic locations pooled
for confidentiality. These are mostly already pro
vided.



Reference List



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