Nicholas T. Funderburg

EBioMedicine

PubMed

Funderburg, Nicholas T.

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EBioMedicine 8 (2016) 16–17
Contents lists available at ScienceDirect
EBioMedicine
j ourna l homepage: www.eb iomed ic ine.comCommentaryIdentiﬁcation of Immune Activation Proﬁles That May Predict Morbidity
During Antiretroviral Therapy Treated HIV InfectionNicholas T. Funderburg
School of Health and Rehabilitation Sciences, Division of Medical Laboratory Science, Ohio State University, 453 W. 10th Ave., 535 A Atwell Hall, Columbus, OH 43210, United StatesDOI of original article: http://dx.doi.org/10.1016/j.ebio
E-mail address: Nicholas.funderburg@osumc.edu.
http://dx.doi.org/10.1016/j.ebiom.2016.05.012
2352-3964/© 2016 The Author. Published by Elsevier B.Va r t i c l e i n f oArticle history:
Received 9 May 2016
Accepted 9 May 2016
Available online 13 May 2016
(insulinemia N24.9 mIU/L, odds ratio [OR] 12.17%, p = 0.011), high
tryglycerides (N2.85 mM, OR 4.18, p = 0.038) and lipodystorphy (OR
4.87, p= 0.015). Several studies have demonstrated that markers of in-
ﬂammation, including levels of TNFR-I and II, are predictive ofmorbidity
and mortality in persons infected with HIV (Hunt et al., 2014; Kalayjian
et al., 2010; Tenorio et al., 2014) and chronic inﬂammation is a likelyChronic elevation in markers of immune activation is a hallmark of
HIV infection, even when viral replication has been suppressed by anti-
retroviral therapy (ART) (Lederman et al., 2013). The Strategies for the
Management of Antiretroviral Therapy (SMART) study demonstrated
that plasma levels of interleukin-6 (IL-6), C-reactive protein, and D-
dimer are independent predictors of mortality in HIV infection, includ-
ing deaths related to cardiovascular disease (CVD) (Kuller et al., 2008;
Emery et al., 2008). The predictive value of markers of immune activa-
tion and inﬂammation has been conﬁrmed in several studies (Psomas
et al., 2016; Hunt et al., 2014; Kalayjian et al., 2010). Potential mecha-
nisms have also been identiﬁed thatmay contribute to increased activa-
tion of both the innate and the adaptive immune systems in chronic HIV
infection, including: copathogens, microbial translocation, pro-inﬂam-
matory lipids, low level viral replication, and the immune system's re-
sponse to cytopenia (Lederman et al., 2013).
In their manuscript in EBioMedicine, Psomas and colleagues used a
combination of 68 markers of immune activation and inﬂammation
and two independent hierarchical clustering analyses to identify 5
donor groups from among 120 HIV-infected virologic responders
(Psomas et al., 2016). These donor groups were characterized using
combinations of activation markers among CD4+ T cells, CD8+ T
cells (CD38, HLA-DR, CD279, CD57), B cells (serum levels of IgG, IgA,
IgM) natural killer cells (HLA-DR, CD69), monocytes (soluble CD14
and sCD163), and markers of inﬂammation and coagulation. The au-
thors propose to use these donor groups to establish relationships be-
tween HIV-infected individuals displaying certain activation
phenotypes and clinical indices that are related to morbidity and mor-
tality. For example, the “inﬂammatory group,”which was identiﬁed by
increased levels of inﬂammatory markers including tumor necrosis fac-
tor alpha receptor I (TNFR-I), was associated with markers of metabolicm.2016.05.008.
. This is an open access article undersyndrome. This group was enriched for donors with hyperinsulinemia
contributor to the development of metabolic syndrome and CVD risk.
The authors suggest that the characterization of these donor proﬁles
may identify differences in the causes of chronic immune activation
among these groups, provide linkages to associated disease states, and
enable clinicians to tailer treatment strategies speciﬁc for members of
these groups.
While identiﬁcation of distinct immune activation proﬁles among
HIV-infected individuals receiving ARTmay provide tools for improving
patient care, further assessment of the predictive value of these proﬁles,
and their feasibility in diverse clinical settings, is warranted. First, the
participants in this study were 95% Caucasian, and differences among
racial and ethnic backgrounds, as well as lifestyle choices including
diet and exercise, may contribute to several comorbidities. A panel con-
taining 68 biomarkers, and the interpretation of the subsequent results,
may not be feasible in all infectious disease clinics, particularly those
providing care in resource limited settings. The authors claim that
they can identify these donor groups using a single ﬂow cytometry
panel that includes 8markers; while this couldwiden the potential util-
ity of the authors' identiﬁcation strategy, it will still need to be validated
in diverse clinical settings. Also, it is not clear to what degree these
panels offer a signiﬁcant advance in the ability of a clinician to predict
morbidity or progression of comorbid disease states when compared
to indices that are measured as part of routine care, or when compared
to other individual biomarkers that have been linked previously to dis-
ease outcomes (Kuller et al., 2008; Emery et al., 2008; Psomas et al.,
2016; Hunt et al., 2014; Kalayjian et al., 2010; Tenorio et al., 2014).
The association between increased levels of TNFR-I and the prevalence
of metabolic syndrome is not entirely surprising, as inﬂammation
plays a key role in modulation of lipid levels, including decreased levels
of high density lipoprotein (HDL), increased levels of low density lipo-
protein (LDL), and decreased cholesterol efﬂux (Tall and Yvan-
Charvet, 2015). The use of standard clinical measurements may provide
insights into risk for comorbidities in ART-treated HIV+ individuals,
however, measurement of traditional lipid panels (LDL, HDL, and tri-
glycerides) (Munger et al., 2015) and risk calculators such as thethe CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
17N.T. Funderburg / EBioMedicine 8 (2016) 16–17American College of Cardiology/AmericanHeart Association pooled-risk
equations or the FraminghamRisk Scoremay underestimate CVD risk in
this population (Longenecker et al., 2016). The proﬁles identiﬁed by
Psomas et al. may provide incremental beneﬁt in the identiﬁcation of
HIV+ individuals whomay be at risk for CVD events or may help iden-
tify patients who could beneﬁt from lifestyle modiﬁcations or pharma-
ceutical lipid lowering intervention, when results from standard lipid
panels may not indicate treatment (Longenecker et al., 2016).
While many potential contributors to immune activation in ART-
treated HIV infection may activate similar intracellular signaling path-
ways (p38 andNFΚB, as examples), likely resulting in expression of sim-
ilar gene products (IL-6 and TNFα), the authors do provide interesting
relationships among several previously underappreciated markers. Of
note, the authors describe relationships between natural killer cell acti-
vation and markers of endothelial cell activation. Exploring relation-
ships among markers that cluster together in these donor groups, may
provide mechanistic insights to the development of morbidity in ART-
treated HIV infection. While the overall generalizability of these results
may not be readily applied in clinical settings, they do provide direc-
tions for future investigationwhichmay uncover targets for therapeutic
intervention.
Disclosure
The author currently receives funding from NHLBI and serves as a
consultant for Gilead Science Inc. Neither of these entities have any
role in this commentary.References
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Hunt, P.W., Sinclair, E., Rodriguez, B., et al., 2014. Gut epithelial barrier dysfunction and in-
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Identification of Immune Activation Profiles That May Predict Morbidity During Antiretroviral Therapy Treated HIV Infection 

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Identification of Immune Activation Profiles That May Predict Morbidity During Antiretroviral Therapy Treated HIV Infection

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Identification of Immune Activation Profiles That May Predict Morbidity During Antiretroviral Therapy Treated HIV Infection

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