Transcript Multicenter AIDS Cohort Study

DOSSIER
Web site: http://statepi.jhsph.edu/macs/macs.html
Prepared by CAMACS
Fax: 410-955-7587
The MACS is funded by the National Institute of Allergy and Infectious Diseases, with additional supplemental
funding from the National Cancer Institute and the National Heart, Lung and Blood Institute. UO1-AI-35042,
UL1-RR025005, UO1-AI-35043, UO1-AI-35039, UO1-AI-35040, UO1-AI-35041.
May 2011
MACS Founding
Principal Investigators
Sites:
Baltimore, MD - Frank Polk
Chicago, IL - John Phair
Los Angeles, CA - Roger Detels
Pittsburgh, PA - Charles Rinaldo
Data Coordinating Center
Data Center – Alvaro Muñoz
November 2004
MACS Sites and
Principal Investigators
 Sites:
• Baltimore, MD (J. Margolick)
• Chicago, IL (J. Phair, S. Wolinsky)
• Los Angeles, CA (R. Detels, O. Martinez•
Maza)
Pittsburgh (C. Rinaldo, L. Kingsley)
 Data
Coordinating Center (CAMACS):
• Baltimore, MD
(L. Jacobson, A. Muñoz)
November 2004
MACS Working Groups

Behavioral
(D. Ostrow)

Hepatitis
(C. Thio)

Biomarker
(C. Rinaldo)

Malignancy/Pathology
(O. Martinez-Maza)

Cardiovacular
(W. Post)

Metabolic
(L. Kingsley)

Clinical
(F. Palella)

Neuropsychology
(E. Miller)

Core Laboratory
(A. Butch)

Renal
(F. Palella)

Data
(L. Jacobson)

Viral Immune Pathogenesis
(J. Margolick)

Genetics
(S. Wolinsky)
August 2010
Semiannual Visit

Questionnaire / ACASI
• Medical History, Health
•

Demographics

Physical Examination /
Lipodystrophy / Frailty

Psychosocial
• Quality of Life (SF36)
• Depression (CESD)
• Activities of Daily Living
Labs
• T-cells, HIV RNA, HBV &
•

Services, Behavior
Medications:
Antiretrovirals, OIspecific, Adherence

HCV serology
Lipids, liver and kidney
function tests / anal
cytology
(IADL)

Neuropsychological
Screening
Banked Specimens
• Plasma, Serum, Cells
• B-cell lines
• PBMC pellets
May 2009
Continuous Outcome Ascertainment

Seroconversion

Clinical Outcomes (medical records confirmation)
• AIDS diagnoses
• Non-AIDS diagnoses







Cardiovascular disease
Cerebrovascular disease
Kidney disease
Liver disease
Lung infection, bacterima, septicemia
Malignancies
Neurologic
• Mortality
November 2004
CAMACS

Planning and design of studies

Coordination of data acquisition
• Form development
• Codebooks
• Data transfer

Standardization and data management
•
•

Edits and updates
Data security
Data analysis, statistical computing and
methodological research
September 1995
MACS Database
(as of May 2011)
Publications (published & in press)
1,195
Participants
6,972
Person-Years
86,883
Variables
8,920
Repository aliquots
1,490,995
(plasma, serum, cells, urine)
HIV+
HIV-
Person-Visits
56,352
72,566
CD4 Measurements
51,798
57,808
HIV RNA Measurements
34,149
1,206
May 2011
MACS Subgroups of Particular Interest

Long-term seropositive individuals with
minimal declines in CD4 levels

Seropositive individuals with rapid declines
in CD4 levels

Long-term survivors with low CD4 levels

Seroconverters

High-risk seronegatives

Seropositives on treatment

>55 years old
Strengths of the MACS

Comparison groups of similar risk
• HIV-infected not receiving treatment
• Uninfected persons

Standardized, complete longitudinal data collected
with uniform frequency, before and after treatment
• Treatment information, behavior, physical examination,
standard laboratory measurements
• Facilitates implementation of new laboratory measurements

Collect and reposit specimens
• Facilitates nested studies
• Allows retrospective testing of specimens as new laboratory
•
procedures become available
Genetic data for predicting disease course/outcome and
response to therapy
Incidence* of Seroconversion in the MACS by Center
Kingsley, Zhou, . . ., Muñoz - AJE 1991 (update)
60
Incidence
Baltimore
50
Chicago
40
Pittsburgh
Los Angeles
30
20
10
0
84
86
88
90
92
94
Calendar Time (years)
* Incidence = # of seroconverters per 1,000 person-semesters
September 1995
Number of Participants with
Specimens Available* in the National Repository
Relative to the Time of Seroconversion**
Specimen
Type
Last
Seronegative
Visit
First
Seropositive
Visit
Plasma
465
508
Serum
487
486
Cells
450
443
* 2 or more tubes according to repository inventory as of 04/01/11
** A total of 642 participants have a known seroconversion date
May 2011
MACS Cohort
6972
Seroprevalent: 2884 (41.4%)
Created
Inactive 10/09
Seronegative: 4088 (58.6%)
Seroconverter: 670 (16.4%)
AIDS:
1611
(55.9%)
Alive:
160
(9.9%)
Active:
124
(77.5%)
Dead:
1451
(90.1%)
AIDS-Free:
1273
(44.1%)
Alive:
1079
(84.8%)
Active:
730
(67.7%)
Dead:
194
(15.2%)
4/11
AIDS:
314
(46.9%)
Alive:
54
(17.2%)
Active:
41
(75.9%)
Dead:
260
(82.8%)
AIDS-Free:
356
(53.1%)
Alive:
311
(87.4%)
Active:
234
(75.2%)
Dead:
45
(12.6%)
Seronegative:
3418 (83.6%)
Not
Censored: Censored:*
1708
1710
(50.0%)
(50.0%)
Alive:
1578
(92.3%)
Dead:
132
(7.7%)
Active:
1182
(74.9%)
* HIV seronegative participants were administratively censored from the MACS in 1993
May 2011
Composition & Size of Cohort
# Participants (thousands)
5
Seronegative
Seroconverter
4
Seroprevalent
3
2
1
0
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
Visit (Calendar year)
* 1710 have been administratively censored
May 2011
Examples of Research Studies
Progression of HIV-1 Infection
Prior to Potent Antiretroviral Therapy
Muñoz, Xu. Stat Med 1996; Enger et al. JAMA 1996; Jacobson et al. AJE 1993 (update)
1.0
Origin
SC
CD4#
200
AIDS
Proportion
0.8
Event
AIDS
DEATH
DEATH
1199/2137
1093/1313
1213/1620
0.6
1.3
2.7
8.9
median
0.4
0.2
5.3
0.0
0
5
10.3
Time in Years
10
5 percent
15
October 1998
Likelihood of Developing AIDS in Three, Six and Nine Years
Mellors, Muñoz,…, Rinaldo. Ann Int Med 1997
Li, Buechner,…, Muñoz. Am Statistician 2003
0
4
2
2
10
2
17
3
17
2
8
8
1500-7K
16
40
>7K-50K
HIV-RNA
(copies/ml)
RT-PCR
40
>20K-50K
>55K
33
14
37
37
>750
33
#1500
501-750
48
64
86
17
16
8
#1500
10
37
1500-7K
351-500
201-350
HIV-RNA
(copies/ml)
RT-PCR
#200 CD4+ T-Lymphocyte
(cells/mm3)
55
55
73
>7K-50K
73
>20K-50K
>55K
37
>750
67
501-750
78
351-500
89
98
67
201-350
#200
CD4+ T-Lymphocyte
(cells/mm3)
4
22
35
35
35
40
60
60
#1500
60
1500-7K
>7K-50K
76
76
86
86
62
>750
76
94
93
76
501-750
351-500
HIV-RNA >20K-50K
201-350
100
(copies/ml)
CD4+ T-Lymphocyte
#200
>55K
(cells/mm3)
RT-PCR
17
Predictors of Short- and Long-Term Survival
after Reaching <50 CD4+ T-cells/mm3 (1)
Marker
T-cell reserve
Survival
>18 months
<6 months
(N=26)
P
(N=11)
HLA-DR- CD38(resting) CD4 %
36 (8-49)
20 (4-43)
.02
HLA-DR- CD38(resting) CD8 %
22 (5-51)
13 (2-29)
.01
Predictors of Short- and Long-Term Survival
after Reaching <50 CD4+ T-cells/mm3 (2)
Giorgi et al., JID 1999; 179:859-870
Marker
T-cell activation
Survival
>18 months
<6 months
(N=26)
(N=11)
P
CD4 T-cell expression
of CD38 (RFI)
87 (28-466)
221 (59-487)
.002
CD8 T-cell expression
of CD38 (RFI)
190 (81-638)
411 (163-661)
.001
HLA-DR+ CD38CD8 %
7 (0.7-18)
1.9 (0.4-8)
.002
Plasma HIV-1
copies/mL
105.2 (104.5-106.3)
105.6 (104.9-106.1) .02
Interpretation: Activation is a more important determinant
of survival at low CD4+ levels than viral load
Detels/Imagawa Study, 1989 (1)
Methods: Isolation studies (unique protocol) of
133 repeatedly exposed MSM
Results:
HIV isolations from 31; subsequently, four
seroconverted 11-17 months after positive
isolation
27 isolation/PCR-positive MSM persistently
antibody-negative 36+ months
Interpretation: The 27 men cleared the virus
Imagawa DT, et al. Human immunodeficiency virus type 1 infection in homosexual men who
remain seronegative for prolonged periods. N Engl J Med 1989; 320(22):1458-1462.
Resistant vs Susceptible MSM Detels, 1994
Resistant MSM: 100 persistently HIVnegative highly exposed MSM
Susceptible MSM: 77 low-risk
seronegatives
Results: Increased levels of neutrophils
and CD8+ cells in resistant men
Interpretation: CD8 cells may modulate
outcome of HIV exposure
Detels R, et al. Resistance to HIV-1 infection. J Acquir Immune Defic Syndr 1994; 7:1263-1269.
Genetic and Immunologic Studies of
Resistant MSM - Detels, 1996
Immunologic Study
13 “resistant” MSM
27 seroconverters
Results: Median percentage of CD25+/CD8+ activated
cells higher in resistant men
Genetic Study
23 resistant men
137 low-risk seroconverters
Results: Significantly higher levels of TAP 1.4 and TAP
1.4/2.3 genes in resistant men
Interpretation: Genetic factors (MHC transport?) are
associated with resistance to infection
Detels R, et al. Persistently seronegative men from whom HIV-1 has been isolated are genetically
and immunologically distinct. Immunol Lett 1996; 51:29-33.
CCR5 Confers Protection
Methods/Results:
111 resistant, 4.5% CCR5 homozygous
614 seropositive, 0% CCR5 homozygous
Interpretation: 100% absence of CCR5
receptor on CD4 cells confers 100%
protection
Zimmerman PA, et al. Inherited resistance to HIV-1 conferred by an inactivating mutation in CC
chemokine receptor 5: studies in populations with contrasting clinical phenotypes, defined racial
background, and quantified risk. Mol Med 1997; 3(1):23-36.
AIDS-Free Time by Calendar
Detels, Muñoz, . . ., Phair - JAMA 1998 (update)
100
90
Percent AIDS-Free
80
70
60
50
40
30
20
10
Calendar
N
AIDS
RH
86.0 to 89.5
89.5 to 93.0
93.0 to 96.5
96.5 to 99.5
341
427
378
264
36
91
100
20
1.48
1
0.92
0.30
4
5
(p-value)
(0.119)
(0.626)
(<.001)
RT
(p-value)
1
1.03
2.11
(0.690)
(<.001)
0
0
1
2
3
6
7
8
9
10
11
12
13
14
Years since Seroconversion
Interpretation: HAART delays onset of AIDS
May 2000
Effect of HLA-B Alleles on AIDS Progression (N=1,089)
Gao, Bashirova, …, Carrington. Nat Med 2005
B*57
B*35Px
1.0
1.0
0.9
0.9
0.8
0.7
0.6
RH=0.43
p<0.0001
0.5
0.4
0.3
0.2
0.1
RH=1.63
p<0.0001
RH=0.71
P=0.03
Fraction AIDS 1987 free
Fraction AIDS 1993 free
B*27
others
0.8
0.7
0.6
0.5
RH=0.4
9
P=0.001
0.4
0.3
RH=0.5
P=0.003
0.2
RH=1.92
p<0.0001
0.1
0
0
0 2 4 6 8 10 12 14 16 18
Time since seroconversion (year)
0
2 4 6 8 10 12 14 16 18 20
Time since seroconversion (year)
Interpretation: HLA-B allele influences progression
May
2006
Kaplan-Meier Survival Curves for Genotypes of SNP rs17762192,
Representing a Haplotype Located 36kb Upstream of PROX1 and
Chromosome 1, Showing Strong Associations with Differing Rates of
Progression to Clinical AIDS
Herbeck, Gottlieb, … Mullins. J Infect Dis 2010
A. Replication cohort (ALIVE, MACS, MHCS, SFCC, individuals genotyped by Steve O’Brien
B. Combined analysis of replication and discovery cohorts (156 MACS individuals enriched with
rapid progressors and long-term non-progressors
May 2010
Time to AIDS Following HAART
According to Selected Genotypings
Hendrickson, Jacobson, . . ., O’Brien - JAIDS 2008
Interpretation: CCR5-∆32 + SDF1-3’UTR delay
onset of AIDS
May 2009
Association between CD4+ T-cell Count (cells/µℓ) and Prevalence of
Carotid Lesions among Participants in Men (MACS) and Women (WIHS)
Kaplan, Kingsley, . . ., Hodis - AIDS 2008
3.5
-
-
3.0
Prevalence ratio
2.5
-
2.0
-
1.5
-
-
1.0
-
-
-
-
-
0.5
HIV-
HIV+
HIV+
CD4>500 350-500 200-349
N=325 N=303 N=147 N=100
HIV+
HIV+
<200
N=50
Men
HIV-
HIV+
HIV+
CD4>500 350-500 200-349
N=496 N=487 N=269 N=288
HIV+
HIV+
<200
N=187
Women
Interpretation: Decreasing CD4+ level is associated with increasing CVD risk
May 2009
Premature Aging of T cells Is Associated With HIV-1
Percentages of CD57+ cells within the CD4+ or CD8+ T cells
Interpretation:
HIV-1 infection is
associated with
shift toward aged
conformation of Tcells; i.e., HIV
induces
accelerated aging
of T-lymphocytes
Cao et al., JAIDS 50:142, 2009
Percentages of CD8+ T-cell subsets defined by expression patterns of CD28 and CD57
An Evolving Scientific Agenda (partial) (1)

1985: HIV virology

1986: Neuropsychology

1987: Biostatistical methodology and
therapeutics

1989: Cancer

1993: Health care utilization

1999: Metabolic complications
An Evolving Scientific Agenda (partial) (2)

2001: Hepatitis

2003: Cardiovascular disease

2005: Aging and sleep

2008: Renal complications and hearing and
balance

2010: Genetic determinants of immune
response and response to treatment

2010: Premature aging of immune function
Keys to Success
1.
Commitment of the participants!!!
2.
Dedication of the staff
3.
Standardization and quality control of data
collection, laboratory procedures, and record
keeping
4.
Decision to establish a repository of specimens
5.
Reaching out to other investigators with
essential expertise
6.
Staying on the “cutting edge”
7.
Consistent funding
8.
Foresight and competence of original and subsequent investigators