HAND Peripheral and CSF Biomarkers:

Pitfalls and Promises

BJ Brew and T Burdo

October 26, 2016

Disclosures

• BJ Brew

• Relationships with commercial interests• Grants: NIH, NHMRC; Research support: Biogen Idec,

Viiv• Patent: QUIN mAB• Speakers Honoraria: Biogen Idec, Viiv, AbbVie• Employee of St Vincent’s Health Australia, University of

New South Wales, and University of Notre Dame

• Tricia Burdo:

• No relationships with commercial interests• No conflicts of interest

Overview

• Introduction

• Principles and Pitfalls

• Individual biomarkers

• How each biomarker fits into a practical framework

INTRODUCTION

ART has reduced the severity of HIV-associated neurocognitive disorders

Pre ART

Adapted from: McArthur, J. C. et al. (2016) Nat. Rev. Neurol.

Post ART (after 1996)

The Therapeutic Paradox

0

5

10

15

20

25

30

35

40

45

Cysique (C-S) Robertson (C-S) Robertson (L) Sevigny (L)

21---59

319-----807

276-----717

15---40

3639 38 37.5

Neuropsychological impairment rates in those with plasma VL<50 cpml

21---59

15---40

HIV comorbidities are associated with chronic low-grade inflammation

Adapted from: Freund. et al. (2010) Trends Molecular Med

Chronic Inflammation/

immune activation

Cardiovasculardisease

Bonediseases

Cancers

Frality

Metabolic diseases, diabetes

HAND

Monocyte and macrophages are important targets of HIV

Campbell, J. H. et al. (2014) AIDS

Changes of monocytes during HIV infection

Campbell, J. H. et al. (2014) AIDS

Overview of HAND pathogenesis pre cART

Adapted from Gonzalez-Scarano F et al. Nat Rev Immunol 2005;5:69-81

1

3

2

5

4

-Autophagy*

ubiquitin proteosome systemImmunoproteosome**

*Gougeon ML et al. Apoptosis 2009;14:501-508**Nguyen TP, et al. Am J Pathol 2010;176:893-902

Neurotropism: CCR5 > CXCR4

Migration of microbial translocation products

HAND Cellular Pathogenesis

Macrophages:

• Critical to HIV mediated neuropathogenesis

• Serve as viral reservoirs within the CNS

• Release inflammatory mediators and neurotoxic viral and host proteins

• Central to HIV-associated neuroinflammation and neurocognitive dysfunction

Astrocytes are also crucial but monocytes/macrophages are important from a systemic perspective

Possible causes of sustained CNS inflammation during ART

• Latent and low level infection in the brain (CSF viral escape)

• Microglia priming (circulating products translocated from gut)

• Macrophages- harbors HIV, produce virions and are long-lived

• Disturbed cellular energy (infected macrophages release ATP)

• Neuronal and synaptic protein dynamics are altered

• Contributions from cerebrovascular dysfunction, metabolic alterations, ART regimens

PRINCIPLES AND PITFALLS

Principles• 1. HAND has a unitary pathogenesis:

– HAND with viral suppression = HAND without viral suppression?

– HAND with HIV encephalitis = HAND without HIV encephalitis (just less inflammation)?

– ANI/MND have the same pathogenetic pathway?

Principles• HAND has a unitary pathogenesis:

– HAND with viral suppression = driven by viral components eg tat nef etc?

– HAND without viral suppression = driven by whole virus especially env?

HAND + HIVE = HAND – HIVE?

Modified from Desplats et al Neurol 2013

12---59

12---32

10---32

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12---32

10---32

10---32

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Neuropsychological impairmentSevere6/6

Severe6/6

Severe6/6

Mild/mod5/9 6/8

Mild/mod5/9 6/8

Mild/mod5/9 6/8

Gelman et al PLoS One 2012

HAND + HIVE = HAND – HIVE?

ANI/MND have the same pathogenetic pathway?

• 3 cases of ANI = HIVE (Cherner et al J Nvirol 2007)

• 10 cases of mild/moderate neuropsychological impairment = latent HIV only (Desplats et al Neurol 2013)

HAND NEUROVIROLOGY BRAIN

Latent infection

Productive infectionANI/MND

HAD

Principles• 2. HAND is driven by systemic and CNS

(CSF/brain) disease (HIV/inflammation)

• But:

– Systemic and CNS equally?

– To differing extents at different time points in HIV disease course?

Mild HAND is prevalent

It is driven by compartmentalized brain viral

latency burden/activity Mild HAND isRelatively uncommon

It is driven by peripheral viral latency burden/activity

Mild HAND is prevalent

It is driven by compartmentalized brain viral

latency burden/activity Mild HAND isRelatively uncommon

It is driven by peripheral viral latency burden/activity

HIV-associated dementiaBBB disrupted

Peripheral & CNS viral latency

Cysique and Brew unpublished

Principles• 3. Activity of HAND:

– Progressing– Regressing– Stable but subclinically active: “simmering pot”– Stable inactive: “legacy” ?evidence

• 4. Reparative and remodelling aspects: emerging evidence

Modified from Cysique et al Neurology 2009

Differing Biomarker effects

EFFECT OF RECENT ARV CHANGE ON BIOMARKER INTERPRETATION

Cysique et al under review

Principles• 5. Account for confounds:

– Substance misuse– Hepatitis C– Overlap with other conditions associated with

aging:• Vascular disease• Degenerative: Alzheimer’s, Parkinson’s

HIV

AGE

Pathogenesis of Neurodegenerative Diseases

Pathogenic insult

misfolded protein stress/toxic proteins

mitochondrial dysfunction

inflammation

transcription dysregulation

excitotoxicity

Oxidative/Nitrosative stress

cell dysfunction/death

Defence failure: Hsps, ER chaperones, Ubiquitin-proteasome, autophagy, Pic, ?PgP

inflammation

Modified from Brew et al J Neuroimm Pharm 2009

proteasome, autophagy, Pic, ?PgP

mitochondrial dysfunction

inflammation

Defence failure: Hsps, ER chaperones, Ubiquitin-proteasome, autophagy, Pic, ?PgP

inflammation

ARV

CSF Biomarkers and Age Effect

De Oliveira et al Sci Rep 2015

A new model of chronic HAND pathogenesis?

HIV HIV duration

AgeCVD

cART

↓NAA

↓NAA

↑ mIo↓NAA

↑ mIo

-

-

Inflammation

Inflammation

Inflammation

~ ↑ neopterin~ ↑ Cr

Cysique et al PLoS One 2014

Principles

• 6. Universality-Selectivity:

• all patients are vulnerable?

• It is now clear that only some patients are susceptible ––The principle of selectivity

Principles

• Biomarkers must developed within latter framework accounting for concepts of activity and repair

Principles: Approach

Price et al Neurology 2007

Metabolic

VascularTrophic

S1oob

neopterin

Marcotte et al JNIP 2013

Suggested Solutions

• “Clean” large data sets (not a “wash out” strategy)

• Well characterised:– Presence and duration of viral suppression– ARV history– CD4 history– HAND history– Neuropathology

PERIPHERAL BIOMARKERS

Tricia Burdo, Ph.D.

Associate Professor

Neuroscience

215-707-1618 (office)

burdot@temple.edu (email)burdot@temple.edu

Peripheral biomarkers in HIV-associated neurocognitive disorders

Biomarkers of HIV-associated dementia (HAD) before ART

Decrease CD4+ T cells:current if naïve - permissive effect when <200 cells/μl, even

<350 cells/μl (Bhaskaran K et al Ann Neurol 2008)Nadir if experienced (Cysique LA et al. Neurology 2006, Valcour V et al. J

Neurovirol 2006, Robertson et al 2007)AnaemiaLow PlateletsImpaired glucose tolerance esp diabetes (Valcour V et al JAIDS 2005)

Plasma viral loadCSF viral loadCCL2IL-6sCD14NeopterinKynurenineQuinolinic acid

But none is specific for HAND

Elevated CD16+ monocytes [Pulliam Lancet 1997,Williams Clin Invest 2005, Campbell Plos One 2011]

Elevated sCD14 (receptor for LPS) [Lyons 2011, Ancuta 2008, Royal 2016]

Elevated sCD163 (Burdo 2013, Royal 2016)- increased in MNDNeither correlate with npsych/HAND but none on cART (McGuire JNvirol 2015)

Loss of CCR2+ CD14loCD16hi monos (Ndhlovu 2015)

CCR2+ on CD14+CD16+ (increased in HAND, not differentiate between ANI, MDN, HAD) (Williams 2014 Neurology)

High HIV DNA levels in CD16+ monocytes [Kusao 2012, Valcour et al 2013, Cysique et al 2015]

Vascular disease: HT, CVD, hypercholesterolaemia (Wright et al 2010)

Peripheral biomarkers of HAND

CCR2+ on CD14+CD16+ (increased in HAND, not differentiate between ANI, MDN, HAD)

Monocyte related

Micro RNAs

• HAND associations:miR-3665 > miR-4516 > miR-4707–5p• But: small n, no ANI, not virally suppressed

Asahchop et al AIDS 2016

Plasma NFL elevated in HAD

Gisslen, 2016

But NFL is quickly hydrolysed – cannot use stored samples

Insights from the SIV-infected rhesus macaque model

CD16+ monocytes peak during acute infection and with AIDS

Williams K., J Clin Invest 2005 Burdo T., PLoS Pathogens 2010

Monocyte expansion in the first weeks of infection predicts the rate of disease progression

Burdo et al. PLos Pathogens, 2010

Monocyte expansion from bone marrow correlates with rapid AIDS, severity of SIVE and sCD163 levels

sCD163 plasma is the best correlate of BrdUmonocytes

Shedding of the scavenger receptor CD163

CD163 exclusively expressed on monocytes and M2

macrophages (Zwadlo, Exp Cell Bio, 1987, Pulford, Immunol. 1992, Backe, J. Clin. Pathol. 1991)

CD14+CD16+ monocytes have the highest expression

of CD163 (Buechler, JLB 2000)

CD163 is a receptor for bacteria, CD163 on tissue macrophages acts as an innate immune receptor and

inducer of local inflammation (Fabriek Blood 2009)

Shedding of sCD163 occurs following activation of TLR-4 by LPS; crosslinking of the Fcg receptor; oxidative

stress, PMA or thrombin stimulation (Hintz, J Leukoc Biol 2002; Weaver, J Leukoc Biol 2006; Sulahian, J Leukoc Biol 2006; Chung, Thromb Res 2011).

The simultaneous release of CD163 and TNF-α is mediated by the enzyme ADAM17/TACE under

inflammatory stimuli (Etzerodt, J Leukoc Biol 2010)

Moller, Scand J Clin Lab Invest, 2012

Burdo et al. JID 2011

sCD163 plasma is elevated in chronic and early HIV-infected subjects and monocyte activation persists with ART

sCD163 is elevated in plasma of impaired HIV-infected patients

Burdo et al. AIDS, 2013

sCD163 decreased in patients that remained unimpaired

sCD163 levels dropped in patients who were stably GDS-unimpaired across visits

Levels remained elevated in those who remained GDS-impaired

Burdo et al. AIDS, 2013

CSF BIOMARKERS

NEURAL BIOMARKERS

CSF NFL

• Correlates with HAND severity (Gisslen et al 2005)

• Decreases with cART (Mellgren et al Neurol 2007)

• Predicts HAND (Gisslen et al JID 2007) SIVE (Beck et al Eur J Pharmacol 2015)

• Not correlated with plasma sCD14 or sCD163 at least in ARV naïve pts (McGuire et al J Nvirol 2015)

Brown et al Mol Neurodegen 2014

CSF NFL

Gisslen et al EBioMedicine 2016

?sensitive enough for ANI/MND in suppressed ptsPeterson et al 2015

CSF NFL

McGuire et al JNvirol 2015

Tau

• Microtubule associated protein largely found in the CNS

• Inflammation can phosphorylate tau• The major reasons for discordant results in

HIV relate to:– Differing ages of patient– Differing ARV history

Brown et al Mol Neurodegen 2014

CSF S100b

• Mainly a marker of astrocytes• Pro-inflammatory• Inhibits GFAP• Neurotoxic• Correlates with HAND severity (Pemberton Brew 2001,

Woods et al JCEN 2010)

CSF GFAP

• Mainly a marker of fibrillary astrocytes

• Variable and limited data on rel’p to HAND (Sporer 2001) (Andersson 2006)

CSF Neopterin• Macrophage/microglia marker• Correlates with HAND severity in ART naïve

(Brew et al Ann Neurol 1990) and SIV (Beck et al Eur J Pharmacol 2015)

• Predicts HAND (Pemberton JID 1996)

• Common for mild elevation despite suppressive cART (Yilmaz et al 2013)

• ?Evidence for neurotoxicity• Correlates with plasma sCD163

Brown et al Mol Neurodegen 2014

CSF BBB

Calcagno et al J Nvirol 2016

IMMUNOLOGICAL BIOMARKERS

CSF sCD14

• Soluble form of the monocyte lipopolysaccharide (LPS) receptor which is cleaved and released from the membrane following the activation of monocytes

• Correlates with HAND severity (Lyons et al 2011)

Brown et al Mol Neurodegen 2014

CSF sCD163

McGuire et al JNvirol 2015

CSF Neopterin and NFL and sCD14

Jespersen et al BMC inf Dis 2016

CSF Kynurenine Pathway and cART in SIV

Drewes et al J Nvirol 2015

CSF QUIN/TRP Predicts SIVE

CSF CCL2

• Correlates with HAND Severity and risk (Sevigny et al 2004) (Anderson et al J Nvirol 2015) (Thames et al AIDS 2015)

• Correlates with neopterin (Price 2007 Neurology)

CSF YKL-40

• Human cartilage glycoprotein 39• Expressed on chondrocytes, synoviocytes,

neutrophils, and monocytes in several chronic inflammatory and neoplastic conditions (Bonneh-Barkay et al, 2008).

• Correlated with SIVE and increased CSF viral load (Bonneh-Barkay et al, 2008).

• Emerging data on correlation with HAND severity

CSF microRNAs

• miR125b (MMPs and cell-death proteins) and 146a (microglial infection)

• Correlate with HIVE (Pacifici J Cell Physiol 2013) but:– Small study (10 pts: 9 HAND – 4 with HIVE)– No data on ARVs or viral suppression

CSF microRNAs

Pacific et al J Cell Physiol

CSF MicroRNAs

VIRAL BIOMARKERS

CSF HIV DNA

• Insensitive – even with digital droplet PCR: 2 of 44 pts (de Oliveira et al Sci Rep 2015)

• ?related to insufficient volume of CSF• Issue of practicality….

TROPHIC FACTOR BIOMARKERS

CSF Progranulin

• Expressed by both neurons and microglia• Neuronal growth factor and modulator of

neuroinflammation• Lowered in HAND on suppressive cART (Suh

et al PLoS One 2014)

• ?through lack of neurotrophic support• Elevated in HIVE off cART (Suh et al PLoS One 2014)

CSF Insulin Like Growth Factors

• Pathway is disturbed but ?significance for HAND (Suh et al J Neuroinflamm)

CSF Growth Factors and HAND with cART

(HIVE: defects in adult neurogenesis in the hippocampus (Avraham et al. 2013; Lee et al. 2013)

METABOLIC BIOMARKERS

CSF Sphingolipids and Ceramide

• Sphingolipids elevated in mild-moderate HAND

• Ceramide elevated in more severe HAND• Similarity to lysosomal storage diseases• Shift from single to mutiple lipid specis with

HAND progression (Bandaru et al Neurol 2013)

CSF Lipids in HAND

Rahman and He Prog Neurobiol 2015

LATENCY BIOMARKERS

HAND BIOMARKERS

Desplats et al Neurol 2013

PRACTICAL FRAMEWORK FOR BIOMARKERS

How Can CSF Biomarkers Help?• Diagnosis:

– Presence– Severity– Activity

• Prediction:– HAND development– HAND treatment response: balance of

“drivers”• Immunological > viral?

• Identify and quantify latency

+ CART Sensitivity Activity Devlpmnt Response Latency

NFL yes Excellent Very good Very good Very good ?

Tau No Very good Very good ? Very good ?

S100b ? Yes Very good ? ? ? ?

GFAP ? ? ? ? ? ?

Neopterin Yes Very good Very good ?yes yes ?

BBB ?no Good ? ? ? ?

sCD14/sCD163 ? Very good ? ? ? ?

QUIN/TRP Yes (SIV) Very good ? ? ? ?

CCL2 ?yes Very good ? ? ? ?

YKL-40 ? Good ? ? ? ?

MicroRNA ? Good ? ? ? ?

HIV DNA ? Poor ? ? ? ?

HIV RNA (SCA) Yes Good ? ? ? ?

Growth Factors ? ? ? ? ? ?

Lipids Yes Good yes ? ? ?

BCL11b ? ? ? ? ? ?yes

More work needed

Collaborators and funding

Steve GrinspoonMarkella ZanniSara LoobyJanet LoMabel ToribioKatie FitchSuman Srinivasa

Ken WilliamsPatrick Autissier

TB’s Funding:R01 NS082116 (PI)U01 HL123336 (PI, sub)R01 AI123001 (PI, sub)R01 NR015738 (PI, sub)

Dr. Burdo has no disclosures

Burdo Lab:Jessica LakritzJake Robinson

Ron EllisScott Letendre

Xavier AlvarezCecily Midkiff

Andrew Miller

Walter Royal

Acknowledgements• Lucette Cysique UNSW

• Melissa Churchill RMIT

• Louise Pemberton CSU

• Edwina Wright Burnet Centre

• Magnus Gisslen SahlgrenskaUniversity

• Richard Price UCSF