Skip to main content Accessibility help
×
Home

Characterizing the Effects of Sex, APOE ɛ4, and Literacy on Mid-life Cognitive Trajectories: Application of Information-Theoretic Model Averaging and Multi-model Inference Techniques to the Wisconsin Registry for Alzheimer’s Prevention Study

  • Rebecca L. Koscik (a1), Derek L. Norton (a2), Samantha L. Allison (a1), Erin M. Jonaitis (a1), Lindsay R. Clark (a1) (a3) (a4), Kimberly D. Mueller (a1), Bruce P. Hermann (a1) (a5), Corinne D. Engelman (a1) (a6), Carey E. Gleason (a3) (a4), Mark A. Sager (a1) (a4), Richard J. Chappell (a2) (a7) and Sterling C. Johnson (a1) (a3) (a4)...

Abstract

Objectives: Prior research has identified numerous genetic (including sex), education, health, and lifestyle factors that predict cognitive decline. Traditional model selection approaches (e.g., backward or stepwise selection) attempt to find one model that best fits the observed data, risking interpretations that only the selected predictors are important. In reality, several predictor combinations may fit similarly well but result in different conclusions (e.g., about size and significance of parameter estimates). In this study, we describe an alternative method, Information-Theoretic (IT) model averaging, and apply it to characterize a set of complex interactions in a longitudinal study on cognitive decline. Methods: Here, we used longitudinal cognitive data from 1256 late–middle aged adults from the Wisconsin Registry for Alzheimer’s Prevention study to examine the effects of sex, apolipoprotein E (APOE) ɛ4 allele (non-modifiable factors), and literacy achievement (modifiable) on cognitive decline. For each outcome, we applied IT model averaging to a set of models with different combinations of interactions among sex, APOE, literacy, and age. Results: For a list-learning test, model-averaged results showed better performance for women versus men, with faster decline among men; increased literacy was associated with better performance, particularly among men. APOE had less of an association with cognitive performance in this age range (∼40–70 years). Conclusions: These results illustrate the utility of the IT approach and point to literacy as a potential modifier of cognitive decline. Whether the protective effect of literacy is due to educational attainment or intrinsic verbal intellectual ability is the topic of ongoing work. (JINS, 2019, 25, 119–133)

Copyright

Corresponding author

Correspondence and reprint requests to: Rebecca Koscik, 610 Walnut Street (Room 944), Madison, WI, 53726. E-mail: rekoscik@wisc.edu

References

Hide All
Altmann, A., Tian, L., Henderson, V.W., & Greicius, M.D. (2014). Sex modifies the APOE-related risk of developing Alzheimer disease. Annals of Neurology, 75(4), 563573.
Anderson, D.R., & Burnham, K.P. (2002). Avoiding pitfalls when using information-theoretic methods. The Journal of Wildlife Management, 66, 912918.
Anderson, E.D., Wahoske, M., Huber, M., Norton, D., Li, Z., Koscik, R.L., … Asthana, S. (2016). Cognitive variability—A marker for incident MCI and AD: An analysis for the Alzheimer’s Disease Neuroimaging Initiative. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, 4, 4755.
Ashendorf, L., Jefferson, A.L., Green, R.C., & Stern, R.A. (2009). Test–retest stability on the WRAT-3 reading subtest in geriatric cognitive evaluations. Journal of Clinical and Experimental Neuropsychology, 31(5), 605610. https://doi.org/10.1080/13803390802375557
Benton, A.L., Hamsher, K., & Sivan, A.B. (1994). Multilingual Aphasia Examination: Manual of instructions. Iowa City, IA: AJA Associates. Inc.
Berggren, R., Nilsson, J., & Lövdén, M. (2018). Education does not affect cognitive decline in aging: A Bayesian assessment of the association between education and change in cognitive performance. Frontiers in Psychology, 9, 1138.
Beydoun, M.A., Boueiz, A., Abougergi, M.S., Kitner-Triolo, M.H., Beydoun, H.A., Resnick, S.M., … Zonderman, A.B. (2012). Sex differences in the association of the apolipoprotein E epsilon 4 allele with incidence of dementia, cognitive impairment, and decline. Neurobiology of Aging, 33(4), 720731.e4.
Burnham, K.P., & Anderson, D.R. (2002). Model selection and multimodel inference (2nd ed.). New York, NY: Springer.
Burnham, K.P., & Anderson, D.R. (2003). Model selection and multimodel inference: A practical information-theoretic approach. New York: Springer Science & Business Media.
Burnham, K.P., Anderson, D.R., & Huyvaert, K.P. (2011). AIC model selection and multimodel inference in behavioral ecology: Some background, observations, and comparisons. Behavioral Ecology and Sociobiology, 65(1), 2335.
Cade, B.S. (2015). Model averaging and muddled multimodel inferences. Ecology, 96(9), 23702382. https://doi.org/10.1890/14-1639.1
Caselli, R.J., Dueck, A.C., Osborne, D., Sabbagh, M.N., Connor, D.J., Ahern, G.L., … Woodruff, B.K. (2009). Longitudinal modeling of age-related memory decline and the APOE ε4 effect. New England Journal of Medicine, 361(3), 255263.
Chang, Y.-L., Fennema-Notestine, C., Holland, D., McEvoy, L.K., Stricker, N.H., Salmon, D.P., … Alzheimer’s Disease Neuroimaging Initiative. (2014). APOE interacts with age to modify rate of decline in cognitive and brain changes in Alzheimer’s disease. Alzheimer’s & Dementia, 10(3), 336348.
Chen, M.-H., Ibrahim, J.G., Shao, Q.-M., & Weiss, R.E. (2003). Prior elicitation for model selection and estimation in generalized linear mixed models. Journal of Statistical Planning and Inference, 111(1), 5776. https://doi.org/10.1016/S0378-3758(02)00285-9
Claeskens, G., & Hjort, N.L. (2008). Model selection and model averaging (Vol. 330). Cambridge: Cambridge University Press.
Darst, B.F., Koscik, R.L., Racine, A.M., Oh, J.M., Krause, R.A., Carlsson, C.M., … Bendlin, B.B. (2017). Pathway-specific polygenic risk scores as predictors of amyloid-β deposition and cognitive function in a sample at increased risk for Alzheimer’s disease. Journal of Alzheimer’s Disease, 55(2), 473484.
Gleason, C.E., Norton, D., Anderson, E.D., Wahoske, M., Washington, D.T., Umucu, E., … Asthana, S. (2018). Cognitive variability predicts incident Alzheimer’s disease and mild cognitive impairment comparable to a cerebrospinal fluid biomarker. Journal of Alzheimer’s Disease, 61, 7989. https://doi.org/10.3233/JAD-170498
Hastie, T., Tibshirani, R., & Wainwright, M. (2015). Statistical learning with sparsity: The lasso and generalizations. Boca Raton, FL: CRC press.
Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning: Data mining, inference, and prediction (2nd ed.). New York, NY: Springer.
Hegyi, G., & Garamszegi, L.Z. (2011). Using information theory as a substitute for stepwise regression in ecology and behavior. Behavioral Ecology and Sociobiology, 65(1), 6976.
Hoeting, J.A., Madigan, D., Raftery, A.E., & Volinsky, C.T. (1999). Bayesian Model averaging: A tutorial. Statistical Science, 14(4), 382401.
Holtzer, R., Verghese, J., Wang, C., Hall, C.B., & Lipton, R.B. (2008). Within-person across-neuropsychological test variability and incident dementia. JAMA, 300(7), 823830.
Hurvich, C.M., & Tsai, C.-L. (1989). Regression and time series model selection in small samples. Biometrika, 76(2), 297307. https://doi.org/10.1093/biomet/76.2.297
Jack, C.R. Jr., Wiste, H.J., Weigand, S.D., Knopman, D.S., Vemuri, P., Mielke, M.M., … Petersen, R.C. (2015). Age, sex, and apoe ε4 effects on memory, brain structure, and β-amyloid across the adult life span. JAMA Neurology, 72(5), 511519. https://doi.org/10.1001/jamaneurol.2014.4821
Johnson, S.C., Koscik, R.L., Jonaitis, E.M., Clark, L.R., Mueller, K.D., Berman, S.E., … Sager, M.A. (2017). The Wisconsin Registry for Alzheimer’s Prevention: A review of findings and current directions. Alzheimers & Dementia, 10, 130142.
Kaplan, E., Goodglass, H., & Weintraub, S. (2001). Boston naming test. Austin, TX: Pro-ed.
Kaup, A.R., Nettiksimmons, J., Harris, T.B., Sink, K.M., Satterfield, S., Metti, A.L., … Yaffe, K. (2015). Cognitive resilience to apolipoprotein E ε4: Contributing factors in black and white older adults. JAMA Neurology, 72(3), 340348.
Koran, M.E.I., Wagener, M., & Hohman, T.J. (2017). Sex differences in the association between AD biomarkers and cognitive decline. Brain Imaging and Behavior, 11(1), 205213.
Koscik, R.L., Berman, S.E., Clark, L.R., Mueller, K.D., Okonkwo, O.C., Gleason, C.E., … Johnson, S.C. (2016). Intraindividual cognitive variability in middle age predicts cognitive impairment 8–10 years later: Results from the Wisconsin Registry for Alzheimer’s Prevention. Journal of the International Neuropsychological Society, 22(10), 10161025.
Lee, J.D., Sun, D.L., Sun, Y., & Taylor, J.E. (2016). Exact post-selection inference, with application to the lasso. The Annals of Statistics, 44(3), 907927.
Lenehan, M.E., Summers, M.J., Saunders, N.L., Summers, J.J., & Vickers, J.C. (2015). Relationship between education and age-related cognitive decline: A review of recent research. Psychogeriatrics, 15(2), 154162.
Lezak, M.D., Howieson, D.B., Bigler, E.D., & Tranel, D. (2012). Neuropsychological assessment (5th ed.). New York, NY: Oxford University Press.
Manly, J.J., Touradji, P., Tang, M.-X., & Stern, Y. (2003). Literacy and memory decline among ethnically diverse elders. Journal of Clinical and Experimental Neuropsychology, 25(5), 680690.
McCarrey, A.C., An, Y., Kitner-Triolo, M.H., Ferrucci, L., & Resnick, S.M. (2016). Sex differences in cognitive trajectories in clinically normal older adults. Psychology and Aging, 31(2), 166175. https://doi.org/10.1037/pag0000070
Mielke, M.M., Vemuri, P., & Rocca, W.A. (2014). Clinical epidemiology of Alzheimer’s disease: Assessing sex and gender differences. Clinical Epidemiology, 6, 37.
Mortensen, E.L., & Høgh, P. (2001). A gender difference in the association between APOE genotype and age-related cognitive decline. Neurology, 57(1), 8995.
Neu, S.C., Pa, J., Kukull, W., Beekly, D., Kuzma, A., Gangadharan, P., … Redolfi, A. (2017). Apolipoprotein E genotype and sex risk factors for Alzheimer disease: A meta-analysis. JAMA Neurology, 74(10), 11781189.
Olsen, J.P., Fellows, R.P., Rivera-Mindt, M., Morgello, S., & Byrd, D.A. (2015). Reading ability as an estimator of premorbid intelligence: Does it remain stable among ethnically diverse HIV+ adults? The Clinical Neuropsychologist, 29(7), 10341052. https://doi.org/10.1080/13854046.2015.1122085
Payami, H., Zareparsi, S., Montee, K.R., Sexton, G.J., Kaye, J.A., Bird, T.D., … Litt, M. (1996). Gender difference in apolipoprotein E-associated risk for familial Alzheimer disease: A possible clue to the higher incidence of Alzheimer disease in women. American Journal of Human Genetics, 58(4), 803.
Price, J.L., McKeel, D.W., Buckles, V.D., Roe, C.M., Xiong, C., Grundman, M., … Dickson, D.W. (2009). Neuropathology of nondemented aging: Presumptive evidence for preclinical Alzheimer disease. Neurobiology of Aging, 30(7), 10261036.
Price, J.L., & Morris, J.C. (1999). Tangles and plaques in nondemented aging and “preclinical” Alzheimer’s disease. Annals of Neurology, 45(3), 358368.
Radloff, L.S. (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1(3), 385401.
Richards, S.A. (2005). Testing ecological theory using the information-theoretic approach: Examples and cautionary results. Ecology, 86(10), 28052814.
Richards, S.A., Whittingham, M.J., & Stephens, P.A. (2011). Model selection and model averaging in behavioural ecology: The utility of the IT-AIC framework. Behavioral Ecology and Sociobiology, 65(1), 7789.
Riedel, B.C., Thompson, P.M., & Brinton, R.D. (2016). Age, APOE and sex: Triad of risk of Alzheimer’s disease. The Journal of Steroid Biochemistry and Molecular Biology, 160, 134147.
Roberts, R.O., Geda, Y.E., Knopman, D.S., Cha, R.H., Pankratz, V.S., Boeve, B.F., … Petersen, R.C. (2012). The incidence of MCI differs by subtype and is higher in men: The Mayo Clinic Study of Aging. Neurology, 78(5), 342351. https://doi.org/10.1212/WNL.0b013e3182452862
Schelldorfer, J., Bühlmann, P., & Van de Geer, S. (2011). Estimation for high-dimensional linear mixed-effects models using ℓ1-penalization. Scandinavian Journal of Statistics, 38(2), 197214.
Schmidt, M. (1996). Rey auditory verbal learning test: A handbook. Los Angeles, CA: Western Psychological Services.
Strittmatter, W.J., & Roses, A.D. (1996). Apolipoprotein E and Alzheimer’s disease. Annual Review of Neuroscience, 19(1), 5377.
Sundermann, E.E., Biegon, A., Rubin, L.H., Lipton, R.B., Landau, S., & Maki, P.M. (2017). Does the Female advantage in verbal memory contribute to underestimating Alzheimer’s disease pathology in women versus men? Journal of Alzheimer’s Disease, 56(3), 947957.
Sundermann, E.E., Maki, P.M., Rubin, L.H., Lipton, R.B., Landau, S., Biegon, A., & For the Alzheimer’s Disease Neuroimaging Initiative. (2016). Female advantage in verbal memory: Evidence of sex-specific cognitive reserve. Neurology, 87(18), 19161924. https://doi.org/10.1212/WNL.0000000000003288
Symonds, M.R., & Moussalli, A. (2011). A brief guide to model selection, multimodel inference and model averaging in behavioural ecology using Akaike’s information criterion. Behavioral Ecology and Sociobiology, 65(1), 1321.
Tang, M.-X., Maestre, G., Tsai, W.-Y., Liu, X.-H., Feng, L., Chung, W.-Y., … Tycko, B. (1996). Relative risk of Alzheimer disease and age-at-onset distributions, based on APOE genotypes among elderly African Americans, Caucasians, and Hispanics in New York City. American Journal of Human Genetics, 58(3), 574.
Tang, M.-X., Stern, Y., Marder, K., Bell, K., Gurland, B., Lantigua, R., … Mayeux, R. (1998). The APOE-∊ 4 allele and the risk of Alzheimer disease among African Americans, whites, and Hispanics. JAMA, 279(10), 751755.
Taylor, J., & Tibshirani, R.J. (2015). Statistical learning and selective inference. Proceedings of the National Academy of Sciences of the United States of America, 112(25), 7629. https://doi.org/10.1073/pnas.1507583112
Trenerry, M.R., Crosson, B., DeBoe, J., & Leber, W.R. (1989). Stroop neuropsychological screening test. Odessa, FL: Psychological Assessment Resources.
Tucker-Drob, E.M., Johnson, K.E., & Jones, R.N. (2009). The Cognitive Reserve Hypothesis: A longitudinal examination of age-associated declines in reasoning and processing speed. Developmental Psychology, 45(2), 431446. https://doi.org/10.1037/a0014012
Vemuri, P., Lesnick, T.G., Przybelski, S.A., Machulda, M., Knopman, D.S., Mielke, M.M., … Jack, C.R. Jr. (2014). Association of lifetime intellectual enrichment with cognitive decline in the older population. JAMA Neurology, 71(8), 10171024. https://doi.org/10.1001/jamaneurol.2014.963
Wechsler, D. (1997). WAIS-III: Wechsler adult intelligence scale. Lutz, FL: Psychological Corporation.
Wilkinson, G.S. (1993). WRAT-3: Wide range achievement test administration manual. Wide Range, Incorporated. Retrieved from https://www.librarything.com/work/17422599
Wisdom, N.M., Callahan, J.L., & Hawkins, K.A. (2011). The effects of apolipoprotein E on non-impaired cognitive functioning: A meta-analysis. Neurobiology of Aging, 32(1), 6374.
Yu, L., Boyle, P.A., Leurgans, S., Schneider, J.A., & Bennett, D.A. (2014). Disentangling the effects of age and APOE on neuropathology and late life cognitive decline. Neurobiology of Aging, 35(4), 819826.

Keywords

Type Description Title
UNKNOWN
Supplementary materials

Koscik et al. supplementary material
Koscik et al. supplementary material 1

 Unknown (120 KB)
120 KB

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed