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Naturalistic assessment of reaction time variability in older adults at risk for Alzheimer’s disease
- Matthew S. Welhaf, Hannah Wilks, Andrew J. Aschenbrenner, David A. Balota, Suzanne E. Schindler, Tammie L.S. Benzinger, Brian A. Gordon, Carlos Cruchaga, Chengjie Xiong, John C. Morris, Jason Hassenstab
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- Journal:
- Journal of the International Neuropsychological Society , First View
- Published online by Cambridge University Press:
- 29 January 2024, pp. 1-11
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Objective:
Maintaining attention underlies many aspects of cognition and becomes compromised early in neurodegenerative diseases like Alzheimer’s disease (AD). The consistency of maintaining attention can be measured with reaction time (RT) variability. Previous work has focused on measuring such fluctuations during in-clinic testing, but recent developments in remote, smartphone-based cognitive assessments can allow one to test if these fluctuations in attention are evident in naturalistic settings and if they are sensitive to traditional clinical and cognitive markers of AD.
Method:Three hundred and seventy older adults (aged 75.8 +/− 5.8 years) completed a week of remote daily testing on the Ambulatory Research in Cognition (ARC) smartphone platform and also completed clinical, genetic, and conventional in-clinic cognitive assessments. RT variability was assessed in a brief (20-40 seconds) processing speed task using two different measures of variability, the Coefficient of Variation (CoV) and the Root Mean Squared Successive Difference (RMSSD) of RTs on correct trials.
Results:Symptomatic participants showed greater variability compared to cognitively normal participants. When restricted to cognitively normal participants, APOE ε4 carriers exhibited greater variability than noncarriers. Both CoV and RMSSD showed significant, and similar, correlations with several in-clinic cognitive composites. Finally, both RT variability measures significantly mediated the relationship between APOE ε4 status and several in-clinic cognition composites.
Conclusions:Attentional fluctuations over 20–40 seconds assessed in daily life, are sensitive to clinical status and genetic risk for AD. RT variability appears to be an important predictor of cognitive deficits during the preclinical disease stage.
6 Examining Interactions Between Longitudinal, Intraindividual Fluctuations in Cognition and Alzheimer’s Disease Biomarkers to Predict Eventual Disease Progression
- Hannah M Wilks, Carlos Cruchaga, Anne Fagan, Suzanne Schindler, John C Morris, Jason Hassenstab
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 410-411
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Objective:
The purpose of the present study was to study the clinical significance of fluctuations in cognitive impairment status in longitudinal studies of normal aging and dementia. Several prior studies have shown fluctuations in cognition in longitudinal studies is associated with greater risk of conversion to dementia. The present study defines “reverters” as participants who revert between cognitive normality and abnormality according to the Clinical Dementia Rating (CDRTM). A defining feature of the CDR at the Knight Alzheimer’s Disease Research Center (Knight ADRC) at Washington University in St. Louis is that the CDR is calculated by clinicians blinded to cognitive data and any prior assessments so that conclusions are drawn free of circularity and examiner bias. We hypothesized reverters, when compared to cognitively normal participants who remain unimpaired, would have worse cognition, abnormal biomarkers, and would eventually progress to a stable diagnosis of cognitive impairment.
Participants and Methods:From ongoing studies of aging and dementia at the Knight ADRC, we selected cognitively normal participants with at least three follow-up visits. Participants fell into three categories: stable cognitively normal (“stable CN”), converters to stable dementia (“converters”), and reverters. Cognitive scores at each visit were z-scored for comparison between groups. A subset of participants had fluid biomarker data available including cerebrospinal fluid (CSF) amyloid and phosphorylated-tau species, and plasma neurofilament light chain (NfL). Mixed effect models evaluated group relationships between biomarker status, APOE £4 status, and CDR progression.
Results:930 participants were included in the study with an average of 5 years of follow-up (Table 1). 661 participants remained cognitively normal throughout their participation while 142 progressed to stable dementia and 127 participants had at least one instance of reversion. Compared to stable CN, reverters had more abnormal biomarkers at baseline, were more likely to carry an APOE £4 allele, and had better cognitive performance at baseline (Table 2, Figure 1). Compared to converters, reverters had less abnormal biomarkers at baseline, were less likely to carry an APOE £4 allele, and had overall better cognitive performance at baseline. In longitudinal analyses, cognitive trajectories of reverters exhibited a larger magnitude of decline compared to stable CNs but the magnitude of decline was not as steep as converters.
Conclusions:Our results confirm prior studies that showed reversion in cognitive status, when compared to stable cognitive normality, is associated with worse overall genetic, biomarker and cognitive outcomes. Longitudinal analyses demonstrated reverters show significantly more decline than stable participants and a higher likelihood of eventual conversion to a stable dementia diagnosis. Reverters’ cognitive trajectories appear to occupy a transitional phase in disease progression between that of cognitive stability and more rapid and consistent progression to stable dementia. Identifying participants in the preclinical phase of AD who are most likely to convert to symptomatic AD is critical for secondary prevention clinical trials. Our results suggest that examining intraindividual variability in cognitive impairment using unbiased, longitudinal CDR scores may be a good indicator of preclinical AD and predict eventual conversion to symptomatic AD.
Chapter 31 - Alzheimer's disease
- Edited by John I. Nurnberger, Jr, Wade Berrettini, University of Pennsylvania School of Medicine
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- Book:
- Principles of Psychiatric Genetics
- Published online:
- 05 October 2012
- Print publication:
- 13 September 2012, pp 371-381
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Summary
This chapter reviews evidence supporting the hypothesis that genetic inheritance plays a substantial role in dependence on cocaine and (to a less well-studied degree) other illicit psychostimulants. The role of genes in cocaine dependence, however, may largely reflect a more general liability to develop dependence on a variety of substances. Studies of molecular genetic mechanisms in cocaine dependence remain in an early stage of development. A genome-wide association study (GWAS) of methamphetamine dependence, while yielding some interesting leads, requires replication in light of its small size, and reliance on pooled genotyping. While several intriguing candidate-gene associations between specific loci and cocaine dependence have been reported, to date there has yet to be a definitively replicated result reported. Clearly, more work is required in the human genetics of stimulant dependence, to identify and characterize how specific genes influence risk for this set of disorders.
Contributors
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- By Maricela Alarcón, Laura A. Baker, Trygve Bakken, Serena Bezdjian, Andrew W. Bergen, Laura J. Bierut, Andrew C. Chen, C. Robert Cloninger, David W. Craig, Anibal Cravchik, Raymond R. Crowe, Carlos Cruchaga, Joseph F. Cubells, Marcella Devoto, Stephen H. Dinwiddie, Howard J. Edenberg, Josephine Elia, Craig A. Erickson, Thomas V. Fernandez, Xiaowu Gai, Elliot Gershon, Daniel H. Geschwind, Alison M. Goate, Hugh M. D. Gurling, Hakon Hakonarson, Sarah M. Hartz, Akiko Hayashi-Takagi, Jinger Hoop, Hanna Jaaro-Peled, Atsushi Kamiya, John S. K. Kauwe, Walter H. Kaye, John R. Kelsoe, Karestan C. Koenen, Mary Jeanne Kreek, Francesca Lantieri, James F. Leckman, Ondrej Libiger, Falk W. Lohoff, Michael J. Lyons, Christopher J. McDougle, Andrew McQuillin, Kathleen Ries Merikangas, Maria G. Motlagh, Pablo R. Moya, Dennis L. Murphy, Eric J. Nestler, Alexander B. Niculescu, David A. Nielsen, Khendra I. Peay, Bernice Porjesz, James B. Potash, R. Arlen Price, Dmitri Proudnikov, Adrian Raine, Madhavi Rangaswamy, William Renthal, Akira Sawa, Nicholas J. Schork, Saurav Seshadri, Shelley D. Smith, Wanli W. Smith, Toshinobu Takeda, Ardesheer Talati, Yi-Lang Tang, Kiara Timpano, Ali Torkamani, Catherine Tuvblad, Myrna M. Weissman, Jens R. Wendland, Jennifer Wessel, Peter S. White, Vadim Yuferov, Tyler Zink
- Edited by John I. Nurnberger, Jr, Wade Berrettini, University of Pennsylvania School of Medicine
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- Book:
- Principles of Psychiatric Genetics
- Published online:
- 05 October 2012
- Print publication:
- 13 September 2012, pp vii-x
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