Cortical brain atrophy and intra-individual variability in neuropsychological test performance in HIV disease
- 272 Downloads
To characterize the relationship between dispersion-based intra-individual variability (IIVd) in neuropsychological test performance and brain volume among HIV seropositive and seronegative men and to determine the effects of cardiovascular risk and HIV infection on this relationship. Magnetic Resonance Imaging (MRI) was used to acquire high-resolution neuroanatomic data from 147 men age 50 and over, including 80 HIV seropositive (HIV+) and 67 seronegative controls (HIV-) in this cross-sectional cohort study. Voxel Based Morphometry was used to derive volumetric measurements at the level of the individual voxel. These brain structure maps were analyzed using Statistical Parametric Mapping (SPM2). IIVd was measured by computing intra-individual standard deviations (ISD’s) from the standardized performance scores of five neuropsychological tests: Wechsler Memory Scale-III Visual Reproduction I and II, Logical Memory I and II, Wechsler Adult Intelligence Scale-III Letter Number Sequencing. Total gray matter (GM) volume was inversely associated with IIVd. Among all subjects, IIVd -related GM atrophy was observed primarily in: 1) the inferior frontal gyrus bilaterally, the left inferior temporal gyrus extending to the supramarginal gyrus, spanning the lateral sulcus; 2) the right superior parietal lobule and intraparietal sulcus; and, 3) dorsal/ventral regions of the posterior section of the transverse temporal gyrus. HIV status, biological, and cardiovascular disease (CVD) variables were not linked to IIVd -related GM atrophy. IIVd in neuropsychological test performance may be a sensitive marker of cortical integrity in older adults, regardless of HIV infection status or CVD risk factors, and degree of intra-individual variability links with volume loss in specific cortical regions; independent of mean-level performance on neuropsychological tests.
KeywordsImaging Cognition HIV Voxel-based morphometry Intra-individual variability
The authors are grateful to the volunteers and the staff of the Multicenter AIDS Cohort Study for the time and effort that they contributed towards the successful completion of this project.
Compliance with ethical standards
Data in this manuscript were collected by the Multicenter AIDS Cohort Study (MACS) with centers at Baltimore (U01-AI35042): The Johns Hopkins University Bloomberg School of Public Health: Joseph B. Margolick (PI), Barbara Crain, Adrian Dobs, Homayoon Farzadegan, Joel Gallant, Lisette Johnson-Hill, Cynthia Munro, Michael W. Plankey, Ned Sacktor, James Shepard, Chloe Thio; Chicago (U01-AI35039): Feinberg School of Medicine, Northwestern University, and Cook County Bureau of Health Services: Steven M. Wolinsky (PI), John P. Phair, Sheila Badri, Maurice O’Gorman, David Ostrow, Frank Palella, Ann Ragin; Los Angeles (U01-AI35040): University of California, UCLA Schools of Public Health and Medicine: Roger Detels (PI), Otoniel Martínez-Maza (Co-PI), Aaron Aronow, Robert Bolan, Elizabeth Breen, Anthony Butch, Beth Jamieson, Eric N. Miller, John Oishi, Harry Vinters, Dorothy Wiley, Mallory Witt, Otto Yang, Stephen Young, Zuo Feng Zhang; Pittsburgh (U01-AI35041): University of Pittsburgh, Graduate School of Public Health: Charles R. Rinaldo (PI), Lawrence A. Kingsley (Co-PI), James T. Becker, Ross D. Cranston, Jeremy J. Martinson, John W. Mellors, Anthony J. Silvestre, Ronald D. Stall; and the Data Coordinating Center (UM1-AI35043): The Johns Hopkins University Bloomberg School of Public Health: Lisa P. Jacobson (PI), Alvaro Munoz (Co-PI), Alison, Abraham, Keri Althoff, Christopher Cox, Jennifer Deal, Gypsyamber D’Souza, Priya Duggal, Janet Schollenberger, Eric C. Seaberg, Sol Su, Pamela Surkan. The MACS is funded primarily by the National Institute of Allergy and Infectious Diseases (NIAID), with additional co-funding from the National Cancer Institute (NCI). Targeted supplemental funding for specific projects was also provided by the National Heart, Lung, and Blood Institute (NHLBI), and the National Institute on Deafness and Communication Disorders (NIDCD). MACS data collection is also supported by UL1-TR000424 (JHU CTSA). Website located at http://www.statepi.jhsph.edu/macs/macs.html. The contents of this publication are solely the responsibility of the authors and do not represent the official views of the National Institutes of Health (NIH).
Additional grant funding
Additional funding for this work was provided by the UCLA CFAR grant 5P30 AI028697, T32-MH019535, from the Department of Veteran Affairs (VA Merit Review), and from the National Institute on Aging (AG034852 to JTB).
Conflict of interest
All authors have declared that he or she has no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent was obtained from all individual participants included in the study.
The data were analyzed by L.J. Hines, J.T. Becker and V. Maruca, with assistance from J. Sanders.
- Anstey, K. J., Mack, H. A., Christensen, H., Li, S.-C., Reglade-Meslin, C., Maller, J., et al. (2007). Corpus callosum size, reaction time speed and variability in mild cognitive disorders and in a normative sample. Neuropsychologia, 45(8), 1911–1920. doi:10.1016/j.neuropsychologia.2006.11.020.CrossRefPubMedGoogle Scholar
- Becker, J. T., Kingsley, L., Mullen, J., Cohen, B., Martin, E., Miller, E. N., et al. (2009). Vascular risk factors, HIV serostatus, and cognitive dysfunction in gay and bisexual men. [research support, N.I.H., extramural]. Neurology, 73(16), 1292–1299. doi:10.1212/WNL.0b013e3181bd10e7.CrossRefPubMedPubMedCentralGoogle Scholar
- Becker, J. T., Bajo, R., Fabrizio, M., Sudre, G., Cuesta, P., Aizenstein, H. J., et al. (2012a). Functional connectivity measured with magnetoencephalography identifies persons with HIV disease. [research support, N.I.H., extramural]. Brain Imaging and Behavior, 6(3), 366–373. doi:10.1007/s11682-012-9149-4.CrossRefPubMedPubMedCentralGoogle Scholar
- Becker, J. T., Cuesta, P., Fabrizio, M., Sudre, G., Vergis, E., Douaihy, A., et al. (2012b). Brain structural and functional recovery following initiation of combination antiretroviral therapy. Journal of Neurovirology, 18(5), 423–427. doi:10.1007/s13365-012-0115-0.CrossRefPubMedPubMedCentralGoogle Scholar
- Becker, J. T., Kingsley, L. A., Molsberry, S., Reynolds, S., Aronow, A., Levine, A. J., et al. (2014). Cohort Profile: Recruitment cohorts in the neuropsychological substudy of the Multicenter AIDS Cohort Study. International Journal of Epidemiology, doi:10.1093/ije/dyu092.
- Brew, B. J. (2004). Evidence for a change in AIDS dementia complex in the era of highly active antiretroviral therapy and the possibility of new forms of AIDS dementia complex. [Review]. Aids, 18 Suppl 1, S75-S78.Google Scholar
- Butters, N., Grant, I., Haxby, J., Judd, L. L., Martin, A., McClelland, J., et al. (1990). Assessment of AIDS-related cognitive changes: recommendations of the NIMH workshop on neuropsychological assessment approaches. Journal of Clinical and Experimental Neuropsychology, 12(6), 963–978. doi:10.1080/01688639008401035.CrossRefPubMedGoogle Scholar
- Christensen, H., Mackinnon, A. J., Korten, A. E., Jorm, A. F., Henderson, A. S., & Jacomb, P. (1999). Dispersion in cognitive ability as a function of age: a longitudinal study of an elderly community sample. Aging, Neuropsychology, and Cognition (Neuropsychology, Development and Cognition: Section B), 6(3), 214–228. doi:10.1076/anec.220.127.116.119.CrossRefGoogle Scholar
- Cysique, L. A., Maruff, P., & Brew, B. J. (2004). Prevalence and pattern of neuropsychological impairment in human immunodeficiency virus–infected/acquired immunodeficiency syndrome (HIV/AIDS) patients across pre- and post-highly active antiretroviral therapy eras: a combined study of two cohorts clinical report. Journal of Neurovirology, 10(6), 350–357. doi:10.1080/13550280490521078.CrossRefPubMedGoogle Scholar
- Dawes, S., Suarez, P., Casey, C. Y., Cherner, M., Marcotte, T. D., Letendre, S., et al. (2008). Variable patterns of neuropsychological performance in HIV-1 infection. [research support, N.I.H., extramural]. Journal of Clinical and Experimental Neuropsychology, 30(6), 613–626. doi:10.1080/13803390701565225.CrossRefPubMedPubMedCentralGoogle Scholar
- Good, C. D., Johnsrude, I. S., Ashburner, J., Henson, R. N., Friston, K. J., & Frackowiak, R. S. (2001). A voxel-based morphometric study of ageing in 465 normal adult human brains. [research support, Non-U.S. Gov’t]. NeuroImage, 14(1 Pt 1), 21–36. doi:10.1006/nimg.2001.0786.CrossRefPubMedGoogle Scholar
- Heaton, R., Marcotte, T. D., Mindt, M. R., Sadek, J., Moore, D. J., Bentley, H., et al. (2004). The impact of HIV-associated neuropsychological impairment on everyday functioning. Journal of the International Neuropsychological Society : JINS, 10(3), 317–331. doi:10.1017/S1355617704102130.CrossRefPubMedGoogle Scholar
- Hilborn, J. V., Strauss, E., Hultsch, D. F., & Hunter, M. A. (2009). Intraindividual variability across cognitive domains: investigation of dispersion levels and performance profiles in older adults. Journal of Clinical and Experimental Neuropsychology, 31(4), 412–424. doi:10.1080/13803390802232659.CrossRefPubMedGoogle Scholar
- Hultsch, D. F., MacDonald, S. W., Hunter, M. A., Levy-Bencheton, J., & Strauss, E. (2000). Intraindividual variability in cognitive performance in older adults: comparison of adults with mild dementia, adults with arthritis, and healthy adults. Neuropsychology, 14(4), 588–598.CrossRefPubMedGoogle Scholar
- Letendre, S., Marquie-Beck, J., Capparelli, E., Best, B., Clifford, D., Collier, A. C., et al. (2008). Validation of the CNS penetration-effectiveness rank for quantifying antiretroviral penetration into the central nervous system. Archives of Neurology, 65(1), 65–70, doi:10.1001/archneurol.2007.31.
- Levine, A. J., Hardy, D. J., Barclay, T. R., Reinhard, M. J., Cole, M. M., & Hinkin, C. H. (2008). Elements of attention in HIV-infected adults: evaluation of an existing model. Journal of Clinical and Experimental Neuropsychology, 30(1), 53–62. doi:10.1080/13803390601186684.CrossRefPubMedGoogle Scholar
- Lin, J. J., Salamon, N., Dutton, R. A., Lee, A. D., Geaga, J. A., Hayashi, K. M., et al. (2005). Three-dimensional preoperative maps of hippocampal atrophy predict surgical outcomes in temporal lobe epilepsy. Neurology, 65(7), 1094–1097. doi:10.1212/01.wnl.0000179003.95838.71.CrossRefPubMedPubMedCentralGoogle Scholar
- MacDonald, S. W., Nyberg, L., Sandblom, J., Fischer, H., & Backman, L. (2008). Increased response-time variability is associated with reduced inferior parietal activation during episodic recognition in aging. [research support, Non-U.S. Gov’t]. Journal of Cognitive Neuroscience, 20(5), 779–786. doi:10.1162/jocn.2008.20502.CrossRefPubMedGoogle Scholar
- Morgan, E. E., Woods, S. P., Delano-Wood, L., Bondi, M. W., & Grant, I. (2011). Intraindividual variability in HIV infection: evidence for greater neurocognitive dispersion in older HIV seropositive adults. [research support, N.I.H., extramural]. Neuropsychology, 25(5), 645–654. doi:10.1037/a0023792.CrossRefPubMedPubMedCentralGoogle Scholar
- Morgan, E. E., Woods, S. P., & Grant, I. (2012). Intra-individual neurocognitive variability confers risk of dependence in activities of daily living among HIV-seropositive individuals without HIV-associated neurocognitive disorders. [research support, N.I.H., extramural]. Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists, 27(3), 293–303. doi:10.1093/arclin/acs003.CrossRefGoogle Scholar
- Rapp, M. A., Schnaider-Beeri, M., Sano, M., Silverman, J. M., & Haroutunian, V. (2005). Cross-domain variability of cognitive performance in very old nursing home residents and community dwellers: relationship to functional status. Gerontology, 51(3), 206–212. doi:10.1159/000083995.CrossRefPubMedGoogle Scholar
- Sacktor, N., Lyles, R. H., Skolasky, R. L., Anderson, D. E., McArthur, J. C., McFarlane, G., et al. (1999). Combination antiretroviral therapy improves psychomotor speed performance in HIV-seropositive homosexual men. Multicenter AIDS cohort study (MACS). [clinical trial, multicenter study, research support, U.S. Gov’t, P.H.S.]. Neurology, 52(8), 1640–1647.CrossRefPubMedGoogle Scholar
- Schretlen, D. J., Munro, C. A., Anthony, J. C., & Pearlson, G. D. (2003). Examining the range of normal intraindividual variability in neuropsychological test performance. Journal of the International Neuropsychological Society, 9(6), 864–870. doi:10.1017/S1355617703960061.CrossRefPubMedGoogle Scholar
- Thompson, P. M., Dutton, R. A., Hayashi, K. M., Toga, A. W., Lopez, O. L., Aizenstein, H. J., et al. (2005). Thinning of the cerebral cortex visualized in HIV/AIDS reflects CD4+ T lymphocyte decline. Proceedings of the National Academy of Sciences of the United States of America, 102(43), 15647–15652. doi:10.1073/pnas.0502548102.CrossRefPubMedPubMedCentralGoogle Scholar
- Wechsler, D. (1987). WMS-R : Wechsler Memory Scale–Revised : manual. San Antonio: Psychological Corp. : Harcourt Brace JovanovichGoogle Scholar
- Wechsler, D. (1997). Wechsler Adult Intelligence Scale—3rd Edition (WAIS-3®). San Antonio, TX:Harcourt Assessment.Google Scholar
- Wetter, S. R., Delis, D. C., Houston, W. S., Jacobson, M. W., Lansing, A., Cobell, K., et al. (2006). Heterogeneity in verbal memory: a marker of preclinical alzheimer’s disease? Neuropsychology, development, and cognition. Section B, Aging, neuropsychology and cognition, 13(3–4), 503–515. doi:10.1080/138255890969492.CrossRefGoogle Scholar
- Woods, S. P., Morgan, E. E., Dawson, M., Cobb Scott, J., Grant, I., & Group, H. I. V. N. R. C. (2006). Action (verb) fluency predicts dependence in instrumental activities of daily living in persons infected with HIV-1. Journal of Clinical and Experimental Neuropsychology, 28(6), 1030–1042. doi:10.1080/13803390500350985.CrossRefGoogle Scholar