Journal of Clinical Virology - Volume 82 - Supplement 1 - September 2016

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S46 Abstracts / Journal of Clinical Virology 82S (2016) S1–S142
Abstract no: 49
Presentation at ESCV 2016: Poster 50
Newly diagnosed HIV-1 cases: Decreased
proportion of recent infections based on a
multi-assay algorithm combining two
serological assays
J. Hassan ∗, J. Moran , H. Tuite , D. Igoe ,
C. De Gascun
1 National Virus Reference Laboratory, University
College Dublin, Dublin 4, Ireland
2 Galway University Hospital, Galway, Ireland
3 Health Protection Surveillance Centre, Gardiner
Street, Dublin 1, Ireland
Background: HIV surveillance requires monitoring of new HIV
diagnoses and differentiation of incident and older infections. Accu-
rate incidence estimates are needed to identify populations at
increased risk of HIV acquisition, monitor the HIV/AIDS epidemic
and evaluate interventions for HIV prevention. Unfortunately,
serologic assays developed for cross-sectional incidence estima-
tion often overestimate HIV incidence because some long term
infections are classified as assay positive (incident). The use of
multi-assay algorithms to estimate the incidence is a promising
alternative approach.
Objectives: To develop amulti-assay algorithmwhich combines
use of routine serological laboratory diagnostic tools for determi-
nation of accurate HIV-1 recent infection.
Study design: Newly confirmed HIV infections from
January–April 2016 (n = 163) were extracted from the NVRL
HIV Database. For each new HIV diagnosis, HIV INNO-LIA assay
(LIA) results and risk factor data, where available, were obtained
from the NVRL laboratory information system. Recent HIV infec-
tions were identified using the following criteria: Evidence of
an HIV negative test in the previous 12 months, detection of
p24 antigen on first diagnosis and application of the LIA HIV
confirmatory assay banding pattern. All samples were also tested
using the Sedia HIV Limiting Antigen Avidity assay (LAg). The
assays were performed in both screening (tested in singlet) and
confirmatory (tested in triplicate) modes. The normalised cut-off in
the screening assay was ODn = 2 and in the confirmatory assay was
ODn = 1.5. In order to develop a multi-assay algorithm (MAA) for
determination of accurate HIV-1 recent infection, results of the LAg
assay were combined with the LIA using Algorithm 15.1 developed
by Schupbach J et al., 2015. These algorithms are derived from
antibody reaction scores to the seven HIV antigen bands present
on the LIA strip (sgp120, gp41, p31, p24, p17, sgp105 and gp36).
Results: All patients were HIV-1 subtype B. Excluding four
patients who were receiving antiretroviral treatment, a subset of
31 patients had low avidity suggestive of recent infections accord-
ing to the LAg assay (19.5%). Applying Algorithm 15.1, divided this
group into 15 patients with recent infection (9.4%) (Group 1) and
16with long-term infection (Group 2). Mann-Whitney test analysis
showed that Group 1 patients had significantly lower LAg avidity
(ODn: 0.370 ± 0.10) when compared with Group 2 patients (ODn:
0.672 ±0.089, p < 0.01). HIV viral loads were measured in a sub-
set of patients and tended to be higher in Group 1. Although there
was no significant difference in age between the groups, 9 patients
(56.3%) in Group 2 were older than all the patients in Group 1.
Both groups comprised mainly males, 86.7% and 87.5% respectively
and the predominant cohort was MSM, comprising 80% and 70%
respectively.
Conclusions: In this preliminary study, the 2-assay MAA which
combined LAg and LIA Algorithm 15.1 decreased the proportion of
recent HIV infections from 19.5% to 9.4%. Identification of an MAA
that can be performed entirely on stored serum or plasma samples
and does not require CD4 cell count or HIV viral load has major
implications for HIV surveillance. Nevertheless, it is intended now
to combine the results of the MAA with clinical epidemiological
data to provide the most accurate information on incident cases
defined by risk groups.
Abstract no: 50
Presentation at ESCV 2016: Poster 51
Lateral flow immunochromatographic assay for
detection of Porcine Respiratory Reproductive
Syndrome Virus type 1-specific antibodies
I.O. Ouh , J.E. Yu , K.M. Cheong , J. Lee ,
H. Kang Cho . Cha ∗
1 Viral Disease Division, Animal and Plant
Quarantine Agency, Gimcheon 39660, Republic of
Korea
2 Median diagnostics, Chuncheion, Republic of Korea
Introduction: Porcine reproductive and respiratory syndrome
virus (PRRSV) is an enveloped, single-stranded positive-sense RNA
virus that belongs to the family Arteriviridae, order Nidovirales
(Cavanagh, 1997). It was first discovered in 1987 in the USA (Hill,
1990) and was discovered later in Europe in 1991 (Collins et al.,
1992). The pathogenic organism is one of the most economically
noteworthy infectious diseases of swine in many regions of world
(Christianson et al., 1992, Meulenberg et al., 1993). It is highly
required to discriminate the genotype of PRRSV so that the appro-
priate control measure will be applied to the PRRSV infected farm
to minimize economic loss. Therefore, we have developed the lat-
eral flow immunochromatographic assay (LFIC) as a highly useful
point-of-care testing for the early detection of antibodies induced
only by PRRSV type 1.
Materials and methods: The type 1 PRRSV (Lelystad) recom-
binant nucleocapsid proteins were produced by using E. coli
expression system. And used for immunization to the Balb/c
mouse for generation of specific monoclonal antibodies against
it. The recombinant nucleocapsid proteins were coupled to the
gold nanoparticles (about 40 nm) in appropriate conditions as a
detector, and the monoclonal antibodies were immobilized to the
nitrocellulose membrane as a capture.
Results: This analysis of samples from PRRSV-negative field
samples was used. A total of 126 pigs serum samples were tested
by ELISA (IDEXX), IFA, and LFIC assay for detection of PRRSV type
1. The specificity was determined to be 124/126%. To evaluate the
distinction between detection of PRRSV type 1 and type 2 antibod-
ies, sera from 6 pigs infected with PRRSV type 1 (E38) and type 2
(LMY, PL97-1) were collected during days post infection (to 52 pi).
In the case of the PRRSV type 1 antibodies, the reaction signals were
detected at the test zone of this kit but no reaction signals were
detected in PRRSV type 2 antibodies. In addition, to determine the
assay at early stages of the infection, sera from 8 pigs infected with
type 1 (LV) and type 2 (VR2332) were collected during days 9 pi.
While standard methods showed low sensitivity rates before day
9 pi, LFIC assay detected seropositive samples at days 7 pi showing
greater sensitivity at early stages of the PRRSV type 1.
Conclusions: In conclusion, the high consent between LFIC
assay and commercial ELISA assay suggests that the LFIC assay is
a very useful method for the early detection of pigs infected with
type 1 PRRSV. Thus, the LFIC assay may be a useful alternative to
the current diagnostic tools used to detect PRRSV type 1-specific
antibodies