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DOSSIER

DOSSIER. Web site: http://statepi.jhsph.edu/macs/macs.html Prepared by CAMACS Fax: 410-955-7587.

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DOSSIER

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  1. 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

  2. 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

  3. 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

  4. MACS Working Groups • Hepatitis (C. Thio) • Malignancy/Pathology (O. Martinez-Maza) • Metabolic (L. Kingsley) • Neuropsychology (E. Miller) • Renal (F. Palella) • Viral Immune Pathogenesis (J. Margolick) • Behavioral (D. Ostrow) • Biomarker (C. Rinaldo) • Cardiovacular (W. Post) • Clinical (F. Palella) • Core Laboratory (A. Butch) • Data (L. Jacobson) • Genetics (S. Wolinsky) August 2010

  5. Semiannual Visit • Demographics • Physical Examination / Lipodystrophy / Frailty • Psychosocial • Quality of Life (SF36) • Depression (CESD) • Activities of Daily Living (IADL) • Neuropsychological Screening • 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. Incidence* of Seroconversion in the MACS by Center Kingsley, Zhou, . . ., Muñoz - AJE 1991 (update) Baltimore Chicago Pittsburgh Los Angeles * Incidence = # of seroconverters per 1,000 person-semesters September 1995

  12. Number of Participants withSpecimens Available* in the National RepositoryRelative to the Time of Seroconversion** * 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

  13. MACS Cohort Created 4/11 6972 Inactive 10/09 Seroprevalent: 2884 (41.4%) Seronegative: 4088 (58.6%) Seroconverter: 670 (16.4%) Seronegative: 3418 (83.6%) Not Censored: 1710 (50.0%) AIDS: 1611 (55.9%) AIDS-Free: 1273 (44.1%) AIDS: 314 (46.9%) AIDS-Free: 356 (53.1%) Censored:* 1708 (50.0%) Alive: 160 (9.9%) Dead: 1451 (90.1%) Alive: 1079 (84.8%) Dead: 194 (15.2%) Alive: 54 (17.2%) Dead: 260 (82.8%) Alive: 311 (87.4%) Dead: 45 (12.6%) Alive: 1578 (92.3%) Dead: 132 (7.7%) Active: 124 (77.5%) Active: 730 (67.7%) Active: 41 (75.9%) Active: 234 (75.2%) Active: 1182 (74.9%) * HIV seronegative participants were administratively censored from the MACS in 1993 May 2011

  14. Seronegative Seroconverter Seroprevalent Composition & Size of Cohort # Participants (thousands) Visit (Calendar year) * 1710 have been administratively censored May 2011

  15. Examples of Research Studies

  16. 1.0 Origin Event SC AIDS 1199/2137 CD4 200 DEATH 1093/1313 # 0.8 AIDS DEATH 1213/1620 0.6 1.3 2.7 8.9 median 0.4 0.2 5.3 10.3 5 percent 0.0 0 5 10 15 Time in Years Progression of HIV-1 InfectionPrior to Potent Antiretroviral Therapy Muñoz, Xu. Stat Med 1996; Enger et al. JAMA 1996; Jacobson et al. AJE 1993 (update) Proportion October 1998

  17. 4 0 22 35 4 2 35 40 2 3 35 60 62 2 8 10 60 76 76 16 8 33 1500 >750 60 76 76 1500 >750 8 16 33 1500-7K 501-750 86 94 1500-7K 501-750 40 48 >7K-50K 351-500 86 93 351-500 >7K-50K 40 64 CD4+ T-Lymphocyte HIV-RNA >20K-50K 201-350 >20K-50K (cells/mm3) 100 201-350 (copies/ml) CD4+ T-Lymphocyte (cells/mm3) 86 200 >55K RT-PCR >55K 200 HIV-RNA (copies/ml) 2 RT-PCR 10 17 17 14 17 37 37 37 55 67 1500 >750 37 55 67 1500-7K 501-750 73 78 >7K-50K 351-500 73 89 >20K-50K 201-350 98 HIV-RNA CD4+ T-Lymphocyte (cells/mm3) (copies/ml) >55K 200 RT-PCR Likelihood of Developing AIDS in Three, Six and Nine Years Mellors, Muñoz,…, Rinaldo. Ann Int Med 1997 Li, Buechner,…, Muñoz. Am Statistician 2003 17

  18. MarkerSurvival >18 months<6 monthsP 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 (1)

  19. Giorgi et al., JID 1999; 179:859-870 MarkerSurvival >18 months<6 monthsP 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 Predictors of Short- and Long-Term Survival after Reaching <50 CD4+ T-cells/mm3 (2) Interpretation: Activation is a more important determinant of survival at low CD4+ levels than viral load

  20. 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.

  21. 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.

  22. 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.

  23. 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.

  24. 100 90 80 70 60 Percent AIDS-Free 50 40 30 N AIDS RH (p-value) RT (p-value) Calendar 86.0 to 89.5 341 36 1.48 (0.119) 20 89.5 to 93.0 427 91 1 - 1 - 93.0 to 96.5 378 100 0.92 (0.626) 1.03 (0.690) 10 96.5 to 99.5 264 20 0.30 (<.001) 2.11 (<.001) 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 AIDS-Free Time by Calendar Detels, Muñoz, . . ., Phair - JAMA 1998 (update) Years since Seroconversion Interpretation: HAART delays onset of AIDS May 2000

  25. B*27 B*57 B*35Px others 1.0 1.0 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.6 RH=0.43 p<0.0001 Fraction AIDS 1993 free Fraction AIDS 1987 free RH=0.49 P=0.001 0.5 0.5 0.4 0.4 0.3 0.3 RH=0.5 P=0.003 RH=0.71 P=0.03 0.2 0.2 RH=1.92 p<0.0001 RH=1.63 p<0.0001 0.1 0.1 0 0 0 2 4 6 8 10 12 14 16 18 0 2 4 6 8 10 12 14 16 18 20 Time since seroconversion (year) Time since seroconversion (year) Effect of HLA-B Alleles on AIDS Progression (N=1,089) Gao, Bashirova, …, Carrington. Nat Med 2005 Interpretation: HLA-B allele influences progression May 2006

  26. 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

  27. 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

  28. - 3.5 - 3.0 2.5 - - 2.0 - - - - 1.5 Prevalence ratio - - - 1.0 - - - - - 0.5 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 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 Interpretation: Decreasing CD4+ level is associated with increasing CVD risk May 2009

  29. Premature Aging of T cells Is Associated With HIV-1 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 Percentages of CD8+ T-cell subsets defined by expression patterns of CD28 and CD57

  30. 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

  31. 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

  32. Keys to Success • Commitment of the participants!!! • Dedication of the staff • Standardization and quality control of data collection, laboratory procedures, and record keeping • Decision to establish a repository of specimens • Reaching out to other investigators with essential expertise • Staying on the “cutting edge” • Consistent funding • Foresight and competence of original and subsequent investigators

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