DOSSIER

Web site: http://statepi.jhsph.edu/macs/macs.htmlPrepared by CAMACS

Fax: 410-955-7587

May 2011

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.

MACS FoundingPrincipal 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 andPrincipal 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)

Biomarker (C. Rinaldo)

Cardiovacular (W. Post)

Clinical (F. Palella)

Core Laboratory (A. Butch)

Data (L. Jacobson)

Genetics (S. Wolinsky) August 2010

Hepatitis (C. Thio)

Malignancy/Pathology (O. Martinez-Maza)

Metabolic (L. Kingsley)

Neuropsychology (E. Miller)

Renal (F. Palella)

Viral Immune Pathogenesis (J. Margolick)

Semiannual Visit Questionnaire / ACASI

• Medical History, Health Services, Behavior

• Medications: Antiretrovirals, OI-specific, Adherence

Labs• T-cells, HIV RNA, HBV &

HCV serology

• Lipids, liver and kidney function tests / anal cytology

Banked Specimens• Plasma, Serum, Cells• B-cell lines• PBMC pellets

May 2009

Demographics

Physical Examination / Lipodystrophy / Frailty

Psychosocial • Quality of Life (SF36)• Depression (CESD)• Activities of Daily Living

(IADL)

Neuropsychological Screening

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)

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

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

0

10

20

30

40

50

60

84 86 88 90 92 94

Calendar Time (years)

Inc

ide

nc

e

September 1995

Baltimore

Chicago

Pittsburgh

Los Angeles

Kingsley, Zhou, . . ., Muñoz - AJE 1991 (update)

* Incidence = # of seroconverters per 1,000 person-semesters

Number of Participants withSpecimens Available* in the National Repository

Relative to the Time of Seroconversion**

May 2011

* 2 or more tubes according to repository inventory as of 04/01/11

** A total of 642 participants have a known seroconversion date

SpecimenType

LastSeronegative

Visit

FirstSeropositive

Visit

Plasma 465 508

Serum 487 486

Cells 450 443

MACS Cohort

6972

Seroconverter: 670 (16.4%) Seronegative: 3418 (83.6%)

Seroprevalent: 2884 (41.4%) Seronegative: 4088 (58.6%)

* HIV seronegative participants were administratively censored from the MACS in 1993

Active:730

(67.7%)

Active:124

(77.5%)

Active:234

(75.2%)

Active:41

(75.9%)

Active:1182

(74.9%)

Dead:1451

(90.1%)

Dead:194

(15.2%)

Dead:260

(82.8%)

Dead:45

(12.6%)

Dead:132

(7.7%)

Alive:160

(9.9%)

Alive:1079

(84.8%)

Alive:54

(17.2%)

Alive:311

(87.4%)

Alive:1578

(92.3%)

Created 4/11

Inactive 10/09

May 2011

AIDS:1611

(55.9%)

AIDS-Free:1273

(44.1%)

AIDS:314

(46.9%)

AIDS-Free:356

(53.1%)

Not Censored:

1710(50.0%)

Censored:*1708

(50.0%)

Composition & Size of Cohort

0

1

2

3

4

5

1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010

May 2011

Visit (Calendar year)

# P

arti

cip

ants

(th

ou

san

ds)

Seronegative

Seroconverter

Seroprevalent

* 1710 have been administratively censored

Examples of Research Studies

Progression of HIV-1 InfectionPrior to Potent Antiretroviral Therapy

October 1998

2.7

10.3

8.9 median1.3

5.3 5 percent

SC AIDSCD4 200 DEATHAIDS DEATH

1199/21371093/13131213/1620

Origin Event1.0

0.8

0.6

0.4

0.2

0.0

50 10 15Time in Years

Muñoz, Xu. Stat Med 1996; Enger et al. JAMA 1996; Jacobson et al. AJE 1993 (update)

Pro

po

rtio

n

17

98

89

78

67

67

73

73

55

55

37

37

37

37

14

17

17

1710

2

CD4+ T-Lymphocyte(cells/mm3)200

201-350

351-500

501-750

>750

HIV-RNA(copies/ml)

RT-PCR>55K

>20K-50K

>7K-50K

1500-7K

1500

100

93

94

76

76

86

86

76

76

62

60

60

60

40

35

35

3522

4

CD4+ T-Lymphocyte(cells/mm3)200

201-350

351-500

501-750

>750

HIV-RNA(copies/ml)

RT-PCR>55K

>20K-50K

>7K-50K

1500-7K

1500

86

64

48

33

33

40

40

16

16

10

8

8

8

3

2

2

24

0

CD4+ T-Lymphocyte(cells/mm3)

200

201-350

351-500

501-750

>750

HIV-RNA(copies/ml)

RT-PCR>55K

>20K-50K

>7K-50K

1500-7K

1500

Mellors, Muñoz,…, Rinaldo. Ann Int Med 1997Li, Buechner,…, Muñoz. Am Statistician 2003

Likelihood of Developing AIDS in Three, Six and Nine Years

Predictors of Short- and Long-Term Survival after Reaching <50 CD4+ T-cells/mm3 (1)

Marker Survival>18 months <6 months P

T-cell reserve (N=26) (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)

Marker Survival>18 months <6 months P

T-cell activation (N=26) (N=11)

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+ CD38-

CD8 % 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

Giorgi et al., JID 1999; 179:859-870

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 HIV-negative 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 Study13 “resistant” MSM27 seroconverters

Results: Median percentage of CD25+/CD8+ activated cells higher in resistant men

Genetic Study

23 resistant men137 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

May 2000

Detels, Muñoz, . . ., Phair - JAMA 1998 (update)

Years since Seroconversion0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

0

10

20

30

40

50

60

70

80

90

100

Calendar

86.0 to 89.5 341 36 1.48 (0.119)89.5 to 93.0 427 91 1 - 1 -

93.0 to 96.5 378 100 0.92 (0.626) 1.03 (0.690)

96.5 to 99.5 264 20 0.30 (<.001) 2.11 (<.001)

N AIDS RH (p-value) RT (p-value)

Per

cen

t A

IDS

-Fre

e

Interpretation: HAART delays onset of AIDS

Effect of HLA-B Alleles on AIDS Progression (N=1,089)

B*27 B*57 B*35Px others

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0 2 4 6 8 10 12 14 16 18 20Time since seroconversion (year)

Fra

ctio

n A

IDS

198

7 fr

ee

RH=0.49 P=0.001

RH=0.5 P=0.003

RH=1.92 p<0.0001

1.0

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 2 4 6 8 10 12 14 16 18Time since seroconversion (year)

Fra

ctio

n A

IDS

199

3 fr

ee

RH=1.63 p<0.0001

RH=0.43 p<0.0001

RH=0.71 P=0.03

May 2006

Gao, Bashirova, …, Carrington. Nat Med 2005

Interpretation: HLA-B allele influences progression

A. Replication cohort (ALIVE, MACS, MHCS, SFCC, individuals genotyped by Steve O’BrienB. Combined analysis of replication and discovery cohorts (156 MACS individuals enriched with

rapid progressors and long-term non-progressors

Herbeck, Gottlieb, … Mullins. J Infect Dis 2010

May 2010

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

Time to AIDS Following HAART According to Selected Genotypings

May 2009

Hendrickson, Jacobson, . . ., O’Brien - JAIDS 2008

Interpretation: CCR5-∆32 + SDF1-3’UTR delay onset of AIDS

Association between CD4+ T-cell Count (cells/µℓ) and Prevalence of

Carotid Lesions among Participants in Men (MACS) and Women (WIHS)

May 2009

Kaplan, Kingsley, . . ., Hodis - AIDS 2008P

reva

len

ce r

atio

0.5

1.0

1.5

2.0

2.5

3.0

3.5

-

- -

-

--

-

-

-

- -

--

- -

-

HIV- HIV+ HIV+ HIV+ HIV+ HIV- HIV+ HIV+ HIV+ HIV+CD4>500 350-500 200-349 <200 CD4>500 350-500 200-349 <200

N=325 N=303 N=147 N=100 N=50 N=496 N=487 N=269 N=288 N=187

Men Women

Interpretation: Decreasing CD4+ level is associated with increasing CVD risk

Premature Aging of T cells Is Associated With HIV-1

Percentages of CD8+ T-cell subsets defined by expression patterns of CD28 and CD57

Interpretation: HIV-1 infection is associated with shift toward aged conformation of T-cells; i.e., HIV induces accelerated aging of T-lymphocytes

Percentages of CD57+ cells within the CD4+ or CD8+ T cells

Cao et al., JAIDS 50:142, 2009

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 Success1. 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 funding8. Foresight and competence of original and subsequent investigators