I N T R O D U C T I O N T O H I V

P A T H O P H Y S I O L O G Y

R O G E R PA R E D E S

M D, P H D

I N F E C T I O U S D I S E A S E S S E R V I C E & I R S I C A I X A A I D S R E S E A R C H I N S T I T U T E

H O S P I T A L U N I V E R S I T A R I G E R M A N S T R I A S I P U J O L

B A D A L O N A , C A T A L O N I A , S P A I N

DISCLOSURES

• I have received research grants from MSD, ViiV and Gilead

• I have participated in advisory boards for MSD and ViiV

• I don’t have stock options

Laboratory Testing for the Diagnosis of HIV Infection: Updated Recommendations Published June 27, 2014 11

Figure 1. Sequence of appearance of laboratory markers for HIV-1 infection

Note. Units for vertical axis are not noted because their magnitude differs for RNA, p24 antigen, and antibody.

Modified from MP Busch, GA Satten (1997)50 with updated data from Fiebig (2003),48 Owen (2008),49 and

Masciotra (2011, 2013).46,66

Need for updated recommendations for the laboratory diagnosis of HIV-1 and HIV-2 infection

The previous algorithm, consisting of a repeatedly reactive immunoassay for HIV antibodies and

positive HIV-1 Western blot or HIV-1 IFA, has been the gold standard for laboratory diagnosis

of HIV-1 infection in the United States since 1989. False-positive results from this combination

are rare.67

HIV-2 infection remains uncommon in the United States, and no definitive criteria

have been recommended for HIV-2 diagnosis.27

Developments and observations in five areas led

CDC to update recommendations for the laboratory diagnosis of HIV-1 and HIV-2 infections:

1. The previous testing algorithm for HIV-1 fails to identify acute HIV-1 infections

Since 1999, blood screening centers in the United States have used pooled HIV-1 NAT to

identify acute HIV infection in donors who had nonreactive 3rd generation immunoassay

results.68

(To reduce costs, multiple specimens are pooled for screening with a single NAT;

specimens from reactive pools undergo individual NAT to identify the specimen with HIV-1

RNA.) Among persons seeking HIV testing, programs that used pooled NAT after a nonreactive

Días

HIV LIFE CYCLE AND ART

VIRAL LOAD FOLLOWING TREATMENT INTERRUPTION

Ananworanich J. CROI 2017, Seattle, WA. #124.

Median time to viral rebound: 26 days (range 13-48)

Highest VL at rebound (median): 5169 (2005 – 13462)

• N=8

• ART started at Fiebig I (HIV RNA+,

p24 Ag-, Ab-) for ≥ 96 w.

• VL <50 c/mL ≥48 w & CD4 >400 cells.

• Resume ART if two VL >1000 c/ml or

two CD4 <350 cells.

• TI for 24 w. VL every 3-7 days.

Hypothesis.

• At least 30% of individuals will have

delayed time to VL rebound (VL<50 at

24 w).

• Proceed to stage 2 if ≥ 1 person has

VL <50 c/ml at week 12.

HIV is the greatest escapist

NK

B

CD8

CD4 Adaptive immunity

Innate immunity

HIV-1 Strategies to counteract host immunity

TRIM

TETHERIN

Intrinsic immunity

CypA

Vif

Vpx

Population level Individual level

HUGE GENETIC DIVERSITY

Sanger sequencing

Deep

sequencing

1. High replication rate: 109-12 new virions/day

2. Error-prone polymerase:

- 1 mutation / 10,000 bp

- 3-8 recombination events / mutation event

3. Cellular mechanisms: MDR1 gene codes for P-glycoprotein

4. Role of RNAseH

5. Selective pressure of Abs & CTLs against HIV epitopes

6. Viral pool size and availability of target cells

• Balance between mutation rate, drift and selection

QUASISPECIES

“A population of viruses that share a

common origin but which have distinct

genomic sequences as a result from

mutation, drift and the impact of

selection”

In ARV-naïve subjects chronically infected with a “wild-type” HIV-1

• All non-deletereous single mutants likely preexist

• Few double mutants preexist

• Almost no triple mutants are expected

Pressure 1

Pressure 2

Pressure 1

Stop pressure

Pressure 2

Pressure 1

Stop pressure

Mutation rate

Drift Selection

DIVERSITY

Drift

Pereyra et al, Science 2010

Kiepiela et al, Nature 2004

HLA-I molecules are a major driving force of HIV-1 evolution

K

A

F S

P E

V I

P

HLA-I

P2 P9

N

K P

E V I

P G

S F

CD8+ T-cell responses and HIV-1 escape

HLA class I alleles are also highly diverse

Host HLA genetics and HIV diversity: frequent transmission of

escaped epitopes and epitope loss over time

GP160 FROM THE OUTSIDE

RESTRICTION FACTORS Typesof Host RestrictionFactors

MX2

TRIM5

CD8 C

op

ies

Vir

al R

NA

/ml

CD

4+ T cells/m

l

HOST RACE HIV EVOLUTION

WT

R2

E1

R3

E2

R4

E3 E4

R1

Metzner K, Paredes R, CHAIN Training slides

QUASISPECIES AS A SURVIVAL STRATEGY

Brenchley J M et al. J Exp Med 2004;200:749-759

HIV INFECTION DAMAGES THE GALT

% CD4+ T-cells

MICROBIAL TRANSLOCATION IN HIV

Nature Reviews | Microbiology

Enterocytea

b

Commensalbacterium

Secretory IgA

Secretory IgA

HEV

NeutrophilCD4+ T cell

CD8+ T cell

B cell

Macrophage Defensin

BacteriumInfected CD4+ T cell

Dendritic cell

HEV

Increased TNF production

Loss of tightjunctions

Decreased IgAproduction

Increased TNFand IFNg production;failed ionic balance HIV infection

Villus

CD8+ T cell in ltration

Crypt

Decreased ratio ofvillus height to crypt depth

Abnormal enterocytedi erentiation

CD4+ T cell loss;preferential TH17 cell lossEnterocyte

apoptosis

Coeliac disease

A chronic inflammatory

condition of the upper small

intestine in humans that is

caused by immunological

hypersensitivity to gliadin, a

component of wheat gluten. It

often occurs in infants during

the introduction to solid foods.

It causes severe villus atrophy,

which can lead to malabsorption

and malnutrition if gluten-

containing foods are not

removed from the diet.

C-reactive protein

(CRP). An acute-phase reactant

protein produced in the liver.

The concentration of CRP in

plasma increases during

inflammation.

can bind, at sites with epithelial barrier disruption may

facilitate this microbial translocation79.

Loss of TH17 cells. Depletion of CD4+ T cells is greater in

the gastrointestinal tract than in blood or lymph nodes

during HIV infection80–84. C-C chemokine receptor type

5 (CCR5)+ CD4+ T cells are depleted probably because

they become directly infected by the virus78,85,86, as CCR5

acts as a receptor for HIV virions87. On the basis of stud-

ies on rhesus macaques, depletion of CD4+ T cells from

the gastrointestinal tract occurs primarily during acute

infection88,89. Of these T cells, TH17 cells, which express

both CCR5 and the gut homing marker CCR6, are pref-

erentially depleted21,84,90,91, probably because they are

more susceptible to HIV infection than CCR5+CCR6−

cells, although the exact mechanism underlying this

REVIEWS

658 | SEPTEM BER 2012 | VOLUM E 10 www.nature.com/reviews/micro

© 2012 Macmillan Publishers Limited. All rights reserved

MICROBIAL TRANSLOCATION IN HIV PATHOGENESIS

Marchetti et al. Clin Microbiol Rev. 2013

Bacterial translocation and clinical progression

Marchetti G, et al. AIDS 2011;25(11):1385-94.

ICONA Cohort

- Documented last HIV-negative test and

first HIV-positive

- Plasma sample stored while ART-naive

N=379.

Circulating LPS in the first year of infection is a good predictor of progression

INFLAMMAEGING

Immune senescence Inflammageing

CV disease

Metabolic disorders

Osteoporosis

Chronic kidney disease Liver disease (NASH)

Cognitive problems

HIV persistence

GALT + GI wall

damage

Bacterial translocation

HIV Disbyosis?

GUT BLOOD

Inflammation

Residual HIV

replication Other

diseases, Tx Other viral

infections

B-Debate 2015: The Human Microbiome, Present Status & Future Prospects

IS THERE AN HIV-SPECIFIC DYSBIOSIS?

MICROBIOME IN HIV

0e+00

1e−06

2e−06

250000 500000 750000

0.00000

0.00025

0.00050

0.00075

0.00100

3500 4000 4500 5000 5500

0

25

50

75

100

late

pre

sent

er

disc

ordan

t

conc

orda

nt

early

-trea

ted

ART n

aive

virem

ic co

ntro

ller

elite

con

trolle

r

HIV

-1 n

egat

ive

Fre

qu

ency

(%

)

0e+00

1e−06

2e−06

3e−06

250000 500000 750000

Gene richness, all subjects

HIV-1

negative

HIV-1

positive

0e+00

1e−06

2e−06

3e−06

4e−06

Gene richness, MSM

400000 800000600000

2

9

3

15

11

42

5

8

7

8

6

5

3

5

16

11

a b

c d

e

De

ns i

tyD

ensi ty

LGC HGC

HIV-1

positive

HIV-1

negative

Gene counts (10 M) KEGG counts (10 M)

Gene counts (10 M) Gene counts (10 M)

2p-value = 0.001

2p-value = 0.009

2p-value = 0.055

Gene richness KEGG richness

Gene richness by HIV-1 phenotype

HGC

LGC

f Gene richness by nadir CD4+ T-cell counts

< 100

100

- 200

200

- 500

> 500

0

25

50

75

100

18

1

18

4

34

16

21

15

11

16

2p-value = 0.002

HIV

-1 n

egat

ive

CD4+ T cells / mm3

Guillén et al. Mucosal Immunology 2018

DYSBIOSIS BY GENE RICHNESS

Guillén et al. Mucosal Immunology 2018

LOW MICROBIAL GENE RICHNESS LINKED TO NADIR CD4

Guillén et al. Mucosal Immunology 2018

MICROBIOME IN HIV

Guillén et al. Mucosal Immunology 2018

MICROBIOME IN HIV

Guillén et al. Mucosal Immunology 2018

VAGINAL DYSBIOSIS RECOGNIZABLE AS COMMUNITY-TYPES

CAPRISA-004

CAPRISA-004

TDF DEPLETED BY GARDENERELLA BUT NOT LACTOBACILLUS

TDF METABOLISED TO ADENINE

MULTIPLE BV BACTERIA (BUT NOT L ACTOBACILLUS) CAN METABOLIZE TENOFOVIR

Maier Nature 2018

EXTENSIVE IMPACT OF NON -ANTIBIOTIC DRUGS ON HUMAN GUT BACTERIA

MICROBIOME IN CANCER

Gopalakrishnan et al, Cancer Cell 2018

X4 (SI) R5 (NSI)

CXCR4 CCR5 CD4

T-cell lines Primary lymphocytes Monocyte/macrophages

CD4 Naïve CD4 memory

Dual tropic

TROPISM PREDICTION

Koot M, et al: Prognostic Value of HIV-1 Syncytium-Inducing Phenotype for Rate of CD4+ Cell Depletion and Progression to AIDS. Annals Int Med 1993

TROPISM

RATE OF PROGRESSION TO CD4+<350, INITIATION OF ART OR DEATH

Goetz. JAIDS 2009

TIME OF X4 VIRUS EMERGENCE IN RELATION TO CD4 INFLECTION POINT

Shepherd. MACS cohort, JID 2008

TROPISM & CD4 LOSS BEFORE ART

Waters CID 2008

TROPISM & CD4 GAIN AFTER ART

Waters CID 2008

WHY DO WE NEED TO CURE HIV?

Life expectancy remains reduced on cART

Ongoing morbidity on cART

Prevent HIV transmission

Substantial stigma and discrimination

Lifelong cART:

adherence toxicity long term-cost

J.Martinez-Picado

Lohse, Ann Int Med 2007; Hogg. Lancet 2008; Deeks & Phillips, BMJ 2009; May, BMJ 2011

Estimated 2015 AIDS investment for

universal prevention, treatment, care and

support

22 billion USD

BARRIERS TO CURE HIV INFECTION

J.Martinez-Picado

Where is the virus and how is it maintained in the

face of suppressive therapy?

Residual

replication

Latent

infection

inflammation

immune activation

HIV CURE: 2-MODELS

J.Martinez-Picado

J.Martinez-Picado

STRATEGIES TO CURE HIV

Treatment

optimization

& intensification

(eliminate

all replication)

Reversal of

HIV latency

(increase viral

production)

Immune-based

therapies

(reverse pro-latency signaling)

Therapeutic

vaccination

(to enhance host-

control)

Gene

therapy

CONCLUSIONS

• HIV is the great scapist

–Diversity

• HIV

• HLA

– Integrated DNA

–Env glycosylation

–GALT damage

– Inflammaging

FLSida: Isabel Bravo, Pep Coll, Carla Estany, Cristina HerreroBCN Checkpoint: Jorge SazIrsiCaixa: Bea Mothe, Jorge Carrillo, Christian Brander, Julià Blanco, 

Bonaventura ClotetVall d’Hebron: Manel Crespo, Jordi Navarro, Ariadna Torrela

UVIC-UCC: Malu Calle

This study is supported by the University and Resear ch Secretary - Department of Economy and Knowledge of the Government of Catalonia and the European Social Fund (Ref. 2015 FI_B 00184) and the Fondo de Investigaciones Sanitarias (PI13/02514) & Fondos FEDER & the RED de SIDA RD16/0025/0041

Marc Noguera

Yolanda Guillén

Cristina Rodríguez

Chiara Mancuso

Muntsa Rocafort

Maria Casadellà Mariona

Parera

Javier Rivera

Gràcies!

Thanks for the slides to : Christian Brander

Javier Martínez Picado

Miguel Ángel Martínez

Júlia Garcia-Prado

Ester Ballana

Josep Maria Llibre