HIV and the Kidney

Mohamed G. Atta, MD, MPH

X H I V / A I D S J o h n s H o p k i n s / B r a z i l April 11-13, 2012

Sofitel Rio de Janeiro

Copacabana, Brazil

Objectives

Multivariate hazard ratios for primary outcome in HOPE• CV death, MI, and stroke

Mann JFE, et al. Ann Intern Med. 2001;134:629-636.

Current markers of kidney disease

• Glomerular injury biomarkers: albuminuria/proteinuria

• Renal tubular injury biomarkers: proteinuria/phosphaturia/glycosuria

• Estimating equations of kidney function

Estimating equations

• Cockcroft-Gault

CrCl (mL/min) = (140-age) * weight * (0.85 if F)

sCr x 72

• MDRD

GFR (mL/min per 1.73 m2) = 186 * sCr-1.154 *

Age-0.203 * (0.742 if female) * (1.210 if black)

Cockcroft DW and Gault MH. Nephron. 1976;16:31-41

Levey AS, et al. J Am Soc Nephrol. 2000;11:A0828

A new equation to estimate glomerular filtration rate (CKD-EPI)

Levey et al. Ann Intern Med. 2009;150:604-612

Race and sex Serum creatinine level, µmol/L (mg/dL)

Equation

Black

Female ≤62 (≤0.7)

>62 (>0.7)

GFR = 166 x (Scr/0.7)-0.329 x (0.993)Age

GFR = 166 x (Scr/0.7)-1.209 x (0.993)Age

Male ≤80 (≤0.9)

>80 (>0.9)

GFR = 163 x (Scr/0.9)-0.411 x (0.993)Age

GFR = 163 x (Scr/0.9)-1.209 x (0.993)Age

White or other

Female ≤62 (≤0.7)

>62 (>0.7)

GFR = 144 x (Scr/0.7)-0.329 x (0.993)Age

GFR = 144 x (Scr/0.7)-1.209 x (0.993)Age

Male ≤80 (≤0.9)

>80 (>0.9)

GFR = 141 x (Scr/0.9)-0.411 x (0.993)Age

GFR = 141 x (Scr/0.9)-1.209 x (0.993)Age

Kidney function and the risk of cardiovascular events in HIV-1 infected patients

• Nested, matched, case-control study

• 315 HIV-infected patients (63 cases who had cardiovascular events and 252 controls)

• eGFR (CKD-EPI formula/MDRD), and proteinuria were the primary exposures of interest

George et. al AIDS, January 2010

Kidney function and the risk of cardiovascular events in HIV-1 infected patients

• eGFR of <60: – unadjusted OR 15·9 for cardiovascular event (p<0·001)

• Adjusted OR (eGFR 10 ml/min ↓): – 1.2 (95% CI 1·1–1·4) for cardiovascular event

• Prevalence of proteinuria: – 51% in cases vs. 25% in control, p<0·001)

• Proteinuria: – unadjusted OR 3·6 (95% CI 1·9–7·0) and adjusted OR 2·2 (95% CI

1·1–4·8)

George et. al AIDS, January 2010

Relationship between eGFR and cardiovascular event status HIV-1 infected patients

George E. AIDS 2010;24:387–94

Mean eGFR: 68·4 (cases) vs 103·2 ml/min (control) p <0·001

0 30 60 90 120 150

No

eve

nt

Eve

nt

Estimated GFR (CKD-EPI method)

Ca

rdio

va

scu

lar

eve

nt sta

tus

Microalbuminuria is associated with all-cause mortality in women• 1547 HIV-infected women (WIHS)

Confirmed albuminuria

Unconfirmed albuminuria

Confirmed proteinuria

No albuminuria

Wyatt et al. JAIDS 2010

70

80

90

100

% s

urv

ival fu

nction

0 100 200 300 400 500 600 700 800 900 1000

Time to all-cause death

Kidney Disease in HIV-Infected Individuals

Kidney disease in HIV-infected individuals

HIVAN: “Classic” clinical characteristics

• Exclusive disease of Africans

• Proteinuria (often nephrotic range)– Atta et al. Am J Med, 2005

• Detectable viremia or detectable Proviral DNA – Estrella et al. Clin Infect Dis 2006

– Izzedine et al. NDT (July, 2010)

• Normal size echogenic kidneys on ultrasound– Atta et al. J Ultrasound Med, 2004

• Progressive renal failure (weeks to months)

Why AA?

Genome wide search

tttctccatttgtcgtgacacctttgttgacaccttcatttctgcattctcaattctatttcactggtctatggcagagaacacaaaatatggccagtggcctaaatccagcctactaccttttttttttttttgtaacattttactaacatagccattcccatgtgtttccatgtgtctgggctgcttttgcactctaatggcagagttaagaaattgtagcagagaccacaatgcctcaaatatttactctacagccctttataaaaacagtgt

gccaactcctgatttatgaacttatcattatgtcaataccatactgtctttattactgtagttttataagtcatgacatcagataatgtaaatcctccaactttgtttttaatcaaaagtgttttggccatcctagatatactttgtattgccacataaatttgaagatcagcctgtcagtgtcta

caaaatagcatgctaggattttgatagggattgtgtagaatctatagattaattagaggagaatgactatcttgacaatactgctgcccctctgtattcgtgggggattggttccacaacaacacccaccccccactcggcaacccctgaaacccccacatcccccagcttttttc

ccctgctaccaaaatccatggatgctcaagtccatataaaatgccatactatttgcatataacctctgcaatcctcccctatagtttagatcatctctagattacttataatactaataaaatctaaatgctatgtaaatagttgctatactgtgttgagggttttttgttttgttttgttttatttgtttgtttgtttgtattttaagagatggtgtcttgctttgttgcccaggctggagtgcagtggtgagatcatagcttactgcagcctcaaact

cctggactcaaacagtcctcccacctcagcctcccaaagtgctgggatacaggtgtgacccactgtgcccagttattattttttatttgtattattttactgttgtattatttttaattattttttctgaatattttccatctatagttggttgaatcatggatgtggaacaggcaaatatggag

ggctaactgtattgcatcttccagttcatgagtatgcagtctctctgtttatttaaagttttagtttttctcaaccatgtttacttttcagtatacaagactttgacgttttttgttaaatgtatttgtaagtattttattatttgtgatgttatttaaaaagaaattgttgactgggcacagtggctcacgcctgtaatcccagcactttgggaggctgaggcgggcagatcacgaggtcaggagatcaagaccatcctggctaacatggtaaa

accccgtctctactaaaaatagaaaaaaattagccaggcgtggtggcgagtgcctgtagtcccagctactcgggaggctgaggcaggagaatggtgtgaacctgggaggcggagcttgcagtgagctgagatcgtgccactgcattccagcctgcgtgacagagcga

gactctgtcaaaaaaataaataaaatttaaaaaaagaagaagaaattattttcttaatttcattttcaggttttttatttatttctactatatggatacatgattgatttttgtatattgatcatgtatcctgcaaactagctaacatagtttattatttctctttttttgtggattttaaaggattttctac

atagataaataaacacacataaacagttttacttctttcttttcaacctagactggatgcattttttgtttttgtttgtttgtttgctttttaacttgctgcagtgactagagaatgtattgaagaatatattgttgaacaaaagcagtgagagtggacatccctgctttccccctgattttagggggaatgttttcagtctttcactatttaatatgattttagctataggtttatcctagatccctgttatcatgttgaggaaattcccttctatttcta

gtttgttgagattttttaattcatgtgattgcgctatctggctttgctctca

tc

ga

ga

ga

ga

ga

gc

gc

gc

tc

ga

ga

ga

ga

ga

tc

tc

tc

tc

ga

ga

tc

gc

tc

tc

tc

~95% of these differences have no phenotypic effects

Influenced just by demography

Useful to infer human origins and

migrations and also in gene mappingSmaller percentages encode phenotypic differences

An even smaller percentage cause or predispose to disease or variable drug response

Some 15 million SNPs total: 3 million differences between individuals

Non-diabetic ESKD in African Americans: Admixture scan

Chromosome 22(Kao et al.)

(Kopp et al.)

Smith panel

Smith panel

Admixture peak: centered on MYH9; >30 other genes were found in the 2 mb 95% interval• MYH9 encoding non-muscle myosin heavy

chain was chosen:

– Known Giant Platelet Syndromes caused by rare mutations with dominant Mendelian inheritance pattern sometimes cause ESKD

– Center of the peak

African

ancestry >90%

in cases

OR statistic for

each SNP

African

ancestry in controls

Adapted from Kopp et al 2008 and NIDDK 2010, Kao et al 2008

3635(Mb) 34

RAXLX

LOC284912

RP5–1119A7.4

LL22NC01–81G9.2

Oleksyk et al. PLoS One, 2010

Frequencies of risk (E-1), protective (E-2), and neutral MYH9 haplotypes (E-3-E-5) in the HapMap and HGDP

Genovese et al.

MYH9 gene, 110kbpContains dozens of ESKD

associated INTRONIC SNPs

APOL1 (15kbp)S342G and I384M

LD 279/280 Chromosomes

APOL3 Q58X FOXRED2

R71C

Arg182Cys

Corresponds to Genovese et al. G1 missense risk haplotype

Corresponds to Genovese et al. G2 nonsense deletiondel.N388/Y389

Genetic hitchhikingGenes 350 kbp around MYH9

APOL3 APOL4 APOL2 APOL1 MYH9 TXN2 FOXRED2

HIVAN prevention and treatment

• Presumed HIV-associated nephropathy incidence stratified by AIDS status and antiretroviral use

• Hopkins Nephrology HIV CohortARV treatment of HIVAN:

Dia

lysis

-fre

e S

urv

iva

l (%

)

(n=26)

No

ARV P = (0.025)

ARV

Treatment

(n=10)

10000 2000 3000

0

25

50

75

100

Time

(days)

Ca

se

s p

er

10

00

pe

rso

n-y

ea

rs

0

5

10

15

20

25

30

35

40

45 No Antiretroviral Therapy

Nucleoside Reverse Transcriptase Inhibitor Therapy

Highly Active Antiretroviral Therapy

0

Lucas GM, et al. AIDS. 2004;20:18(3):541-546; Atta et al., Nephrol Dial Transpl, 2006

No AIDS AIDS

26.3

14.4

6.82.6 5

DHHS. Guidelines for the use of antiretroviral agents in HIV-1-Infected adults and adolescents.

Washington, DC: January 10, 2011

Recommendations for initiating ART in the USA

*Panel was divided on the strength of this recommendation: 55% of panel members for

strong recommendation and 45% for moderate recommendation

Clinical condition and/or CD4+ cell count

Recommendation

History of AIDS-defining illness Treat

Pregnant women Treat

HIV-associated nephropathy (HIVAN) Treat

Hepatitis B co-infection requiring treatment Treat

CD4+ cell count <350 cells/mm3 Treat

CD4+ cell count 350–500 cells/mm3 Treatment recommended*

CD4+ cell count >500 cells/mm3

Expert opinions differ:

50% recommend treatment

50% view therapy as optional at

this CD4+ cell count

HIV-immune complex GN

• Lupus like GN

• Post infectious GN

• IgA GN

• MPGN and MN

• Non-specific ICGN

Nochy et al. Nephrol Dial Transplant 1993;8:11

Cumulative Incidence of ESRD

p = 0.005

* Unpublished data

83 with HIVICK

37 with HIVAN

19 with HIVICK + HIVAN

HIV-associated TMA

Malak S. et al. Scandinavian Journal of Immunology 2008;68:337–344

N=17N=45

0

50

100

150A

DA

MT

S1

3 a

ctivity

HIV+ patients(n=29)

HIV- patients(n=62)

HIV-associated TMA

ADAMTS13 <5% HIV+ patients:

• Lower AIDS-related complications

– (23.5% versus 91.6%, respectively, P = 0.0005)

• Higher median CD4+ T cell count (P = 0.05)

• Lower mortality (11.7% Vs. 50%, P = 0.04)

Malak S. et al. Scandinavian Journal of Immunology 2008;68:337–344

Drugs and Mechanism of Renal Injury in HIV

HAART-associated kidney disease

Renal syndrome Drug

Acute kidney injury

Toxic acute tubular necrosis TDF, DDI, Ritonavir

Acute interstitial nephritis ATZ, IDV, ABC

Crystal nephropathy IDV, ATZ

Tubular

Fanconi's syndrome TDF, DDI, ATZ, ritonavir

Renal tubular acidosis Lamivudine, STV

Nephrogenic diabetes insipidus TDF, DDI, IDV

Chronic kidney disease TDF, IDV, ATZ

Crystalluria and stone formation

Indinavir

Atazanavir

a: Kopp, J. Ann Intern Med 1997

b: Courtesy of Perazella M, Yale University

c, d: Couzigou et al. CID 2007

a b

c d

Urolithiasis in HIV positive patients treated with atazanavir

•Prevalence:

– 0.97% (11/1134) patients who were treated with ATZ from March 2004 through February 2007

•Risk factors:

– Alkaline pH: ≥6

– Duration on treatment

Couzigou et al. CID 2007:45 (15 October)

Tenofovir renal toxicity

•Acute renal failure

•Fanconi syndrome

•Nephrogenic diabetes insipidus

• . . .

•Chronic kidney disease

Atta M. et al. Seminars in Nephrology 2008;6

Izzedine et.al. AJKD 2005;45

Winston, et.al. HIV Med 20067

Russel FG. Annu Rev Physiol 2002;64:563–94

Model of organic anion transporters in kidney proximal tubule

OAT-K1/(K2)

OATP1GSH

NPT1

OAT4?

MRP2

MRP4

PEPT1/2

OA-

OA-

OA-

Cl- (?)

OA-

OA-

OA-

H+

peptides

OA-

SDCT2

OAT1

OAT3

MRP6

lumeninterstitium

Na+

Dicarboxylates

OA-

OA-

?

α-KG2-

?

?

Factors influencing elimination

Old age

SNPs in transporter proteins

drugsRisk FactorsLow body weight

Underlying kidney

diseaseUse of DDI

Use of nephrotoxic drugs

Low CD4 count

Co-infection with HCV

Diabetes

Adapted from Expert Opin. Drug Saf. 2010;9:545-559

• PRTD was defined on the basis of the presence of at least 2/5 criteria (399 patients):

• � in FE phos, with low sr. phos. <0.80 mmol/l

• Non-diabetic glucosuria

• Metabolic acidosis (pH<7.34 and sr. bicarb. <22 mmol/l)

• Ratio B2-microglobulinuria/ur. cr. >40.3 mg/l

• Low sr. uric acid with � FE uric acid >15%

Dauchy et al. Kidney International 2011;80:302–309

Increased risk of abnormal proximal renal tubular function with HIV infection and antiretroviral therapy

• Prevalence: 6.5%

Dauchy et al. Kidney International 2011;80:302–309

Increased risk of abnormal proximal renal tubular function with HIV infection and antiretroviral therapy

Final model

OR (95% CI) P-value

Age 1.28 (1.05–1.58) 0.017

TDF 1.23 (1.02–1.47) 0.028

ATZ 1.28 (1.04–1.58) 0.021

Chronic kidney disease and antiretroviral drug use in HIV-positive patients

• 3.3% over a median follow-up of 3.7

Mocroft et al. AIDS 2010, EuroSIDA Study Group

0 6 12 18 24 30 36 42 48

Months from baseline

% p

rog

resse

d

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

N=6843 6598 5323 3789 2298

Hazard of CKD incidence

Mocroft et al. AIDS 2010, EuroSIDA Study Group

Tenofovir exposure and risk of outcomes

• 10,841 HIV-infected VA patients 1997-2007

• Median follow-up ranged from 3.9 years (proteinuria) to 5.5 years (CKD)

*** p<0.0001,

** p<0.001,

* p<0.01 Scherzer et al. AIDS, Feb 4, 2012 Epub ahead of print

Hazard ratio (95% CI)

Proteinuria

(n=3400 events)

Rapid decline

(n=3078 events)

CKD

(n=1712 events)

Cumulative exposure to tenofovir (per year)

1.34 (1.25–1.45)*** 1.11 (1.03–1.18)* 1.23 (1.12–1.35)***

Ever exposure to tenofovir (versus never)

1.68 (1.52–1.85)*** 1.36 (1.23–1.50)*** 1.38 (1.20–1.57)***

Risk of renal dysfunction in an HIV-infected patient

Time

Ris

k o

f re

nal d

ysfu

nction

AgeEthnicity

Family history

HIV infection

HIV RNA ↑↑↑↑CD4 cells ↓↓↓↓

HIVAN/

HIVIC/TMA

HAART

Non HIV

Kidney disease

Nephrotoxic

ARV

Metabolicdisturbances

(diabetes,

hypertension,bone disease)

Un-modifiable

Suggested recommendations

• In treated or untreated HIV

– Screen all patients with GFR/urine protein/albumin

• For high risk patients, monitor kidney disease regularly

– Every 3 months is optimal

• For those with CKD

– Address CV risk

• Patients on certain ART

– Close monitoring for renal/tubular abnormalities

– Be aware of PI/NRTI interactions

– Avoid in high renal risk patients

Acknowledgments

• Hopkins– Nephrology

D. Fine

M. Estrella

M. Foy

– PathologyM. Kuperman

L. Racusen

– ID

G. Lucas

J. Gallant

R. Moore

• NIHJ. Kopp

C. Winkler

G. Nelson

A. Warner

• Pitie-Salpetiere Hospital,Paris, France

– Nephrology G. Deray

H. Izzedine

• All India Institute of Medical Sciences,New Delhi, India

E. George

Thank you