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Boyle R, Connaughton M, McGlinchey E, Knight SP, De Looze C, Carey D, Stern Y, Robertson IH, Kenny RA, Whelan R. Connectome-based predictive modelling of cognitive reserve using task-based functional connectivity. Eur J Neurosci 2023; 57:490-510. [PMID: 36512321 PMCID: PMC10107737 DOI: 10.1111/ejn.15896] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 11/07/2022] [Accepted: 12/08/2022] [Indexed: 12/14/2022]
Abstract
Cognitive reserve supports cognitive function in the presence of pathology or atrophy. Functional neuroimaging may enable direct and accurate measurement of cognitive reserve which could have considerable clinical potential. The present study aimed to develop and validate a measure of cognitive reserve using task-based fMRI data that could then be applied to independent resting-state data. Connectome-based predictive modelling with leave-one-out cross-validation was applied to predict a residual measure of cognitive reserve using task-based functional connectivity from the Cognitive Reserve/Reference Ability Neural Network studies (n = 220, mean age = 51.91 years, SD = 17.04 years). This model generated summary measures of connectivity strength that accurately predicted a residual measure of cognitive reserve in unseen participants. The theoretical validity of these measures was established via a positive correlation with a socio-behavioural proxy of cognitive reserve (verbal intelligence) and a positive correlation with global cognition, independent of brain structure. This fitted model was then applied to external test data: resting-state functional connectivity data from The Irish Longitudinal Study on Ageing (TILDA, n = 294, mean age = 68.3 years, SD = 7.18 years). The network-strength predicted measures were not positively associated with a residual measure of cognitive reserve nor with measures of verbal intelligence and global cognition. The present study demonstrated that task-based functional connectivity data can be used to generate theoretically valid measures of cognitive reserve. Further work is needed to establish if, and how, measures of cognitive reserve derived from task-based functional connectivity can be applied to independent resting-state data.
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Affiliation(s)
- Rory Boyle
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Michael Connaughton
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Eimear McGlinchey
- School of Nursing and Midwifery, Trinity College Dublin, Dublin, Ireland
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Silvin P Knight
- The Irish Longitudinal Study on Aging (TILDA), School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Céline De Looze
- The Irish Longitudinal Study on Aging (TILDA), School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Daniel Carey
- The Irish Longitudinal Study on Aging (TILDA), School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Yaakov Stern
- Cognitive Neuroscience Division, Department of Neurology, Columbia University, New York City, New York, USA
| | - Ian H Robertson
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Rose Anne Kenny
- The Irish Longitudinal Study on Aging (TILDA), School of Medicine, Trinity College Dublin, Dublin, Ireland
- Mercer's Institute for Successful Ageing, St. James's Hospital, Dublin, Ireland
| | - Robert Whelan
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
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Kuller LH, Snitz BE, Hughes TM, Chang Y, Cohen AD, Mathis CA, Aizenstein HJ, Lopez OL. Low untreated systolic blood pressure over 18 years is associated with survival free of dementia age 90. Alzheimers Dement 2022; 18:2176-2187. [PMID: 35089640 PMCID: PMC9787390 DOI: 10.1002/alz.12493] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 08/11/2021] [Indexed: 01/31/2023]
Abstract
INTRODUCTION We hypothesized that lower untreated systolic blood pressure (SBP) would be associated with a lower risk of dementia and death up to age 95. METHODS SBP measured between 2000 and 2006 was evaluated in relationship to dementia risk and brain biomarkers from 2009-2020 (n = 177) in the Gingko Evaluation of Memory Study (GEMS), mean age 95 in 2020. Participants had measurements of brain amyloid beta (Aβ) and repeat clinical-cognitive evaluations every 6 months. RESULTS By 2020, only 9 of 177 patients (5%) were alive and cognitively unimpaired (CU). Mean SBP from 2000 to 2006 was 120 mm Hg for nine alive/CU, 125 mm Hg for alive/mild cognitive impairment (MCI), and 130 mm Hg for alive/dementia (P = .03). The amount of Aβ was directly related to SBP levels. In multivariate analysis, Aβ+ in 2009 and thinner cortex were significant predictors of dementia. Excluding Aβ, SBP became a significant predictor of dementia. DISCUSSION Low SBP untreated by antihypertensive medications was associated with significant decreased risk of dementia and less Aβ.
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Affiliation(s)
- Lewis H. Kuller
- Department of EpidemiologyGraduate School of Public HealthUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Beth E. Snitz
- Department of NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Timothy M. Hughes
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Yuefang Chang
- Department of NeurosurgeryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Ann D. Cohen
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Chester A. Mathis
- Department of RadiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | | | - Oscar L. Lopez
- Department of NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
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Nguyen ML, Huie EZ, Whitmer RA, George KM, Dugger BN. Neuropathology Studies of Dementia in US Persons other than Non-Hispanic Whites. Free Neuropathol 2022; 3. [PMID: 35425946 PMCID: PMC9007571 DOI: 10.17879/freeneuropathology-2022-3795] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Alzheimer's disease (AD) and vascular dementia are two of the most prevalent dementias that afflict the aging population in the United States (US). Studies have made great strides in understanding the neuropathology of these diseases; however, many studies are conducted in the context of non-Hispanic whites (NHWs), and few include the rapidly growing underrepresented populations that reside in the US. We sought to characterize current knowledge of the neuropathologic landscape of AD and vascular dementia of the largest growing US minority groups, namely Latinos/Hispanics, Black Americans, and Asian Americans, compared with NHWs being the majority group. It is vital to note these historic categories are social constructs and cultural and social associations may underlie differences. We conducted a literature search utilizing specific criteria to yield neuropathology papers that addressed the demographics and neuropathologies of relevance, then collated the findings into this review. We reveal that while there has been much progress in neuropathological research involving Latinos/Hispanics and Black Americans in the past decade, no cohesive conclusions could be extrapolated from the existing data due to the dearth of minority participants and even smaller amount of information related to the heterogeneity within each minority group, especially Latinos/Hispanics. Furthermore, we reveal an even greater scarcity in neuropathological studies involving Asian Americans, also a very heterogeneous group. We hope the presented findings will illuminate the paucity of minority representation in not just neuropathological research but the field of clinical research overall and serve to inspire clinicians and researchers to help reduce the health disparities underrepresented groups in the US face.
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Affiliation(s)
- My-le Nguyen
- Department of Pathology and Laboratory Medicine, University of California, Davis
| | - Emily Z Huie
- Department of Pathology and Laboratory Medicine, University of California, Davis
| | - Rachel A Whitmer
- Department of Public Health Sciences, University of California, Davis
| | - Kristen M George
- Department of Public Health Sciences, University of California, Davis
| | - Brittany N Dugger
- Department of Pathology and Laboratory Medicine, University of California, Davis
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Zimmerman SC, Brenowitz WD, Calmasini C, Ackley SF, Graff RE, Asiimwe SB, Staffaroni AM, Hoffmann TJ, Glymour MM. Association of Genetic Variants Linked to Late-Onset Alzheimer Disease With Cognitive Test Performance by Midlife. JAMA Netw Open 2022; 5:e225491. [PMID: 35377426 PMCID: PMC8980909 DOI: 10.1001/jamanetworkopen.2022.5491] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
IMPORTANCE Identifying the youngest age when Alzheimer disease (AD) influences cognition and the earliest affected cognitive domains will improve understanding of the natural history of AD and approaches to early diagnosis. OBJECTIVE To evaluate the age at which cognitive differences between individuals with higher compared with lower genetic risk of AD are first apparent and which cognitive assessments show the earliest difference. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study used data from UK Biobank participants of European genetic ancestry, aged 40 years or older, who contributed genotypic and cognitive test data from January 1, 2006, to December 31, 2015. Data analysis was performed from March 10, 2020, to January 4, 2022. EXPOSURE The AD genetic risk score (GRS), which is a weighted sum of 23 single-nucleotide variations. MAIN OUTCOMES AND MEASURES Seven cognitive tests were administered via touchscreen at in-person visits or online. Cognitive domains assessed included fluid intelligence, episodic memory, processing speed, executive functioning, and prospective memory. Multiple cognitive measures were derived from some tests, yielding 32 separate measures. Interactions between age and AD-GRS for each of the 32 cognitive measures were tested with linear regression using a Bonferroni-corrected P value threshold. For cognitive measures with significant evidence of age by AD-GRS interaction, the youngest age of interaction was assessed with new regression models, with nonlinear specification of age terms. Models with youngest age of interaction from 40 to 70 years, in 1-year increments, were compared, and the best-fitting model for each cognitive measure was chosen. Results across cognitive measures were compared to determine which cognitive indicators showed earliest AD-related change. RESULTS A total of 405 050 participants (mean [SD] age, 57.1 [7.9] years; 54.1% female) were included. Sample sizes differed across cognitive tests (from 12 455 to 404 682 participants). The AD-GRS significantly modified the association with age on 13 measures derived from the pairs matching (range in difference in mean cognition per decade increase in age for 1-SD higher AD-GRS, 2.5%-11.5%), symbol digit substitution (range in difference in mean cognition per decade increase in age for 1-SD higher AD-GRS, 2.0%-5.8%), and numeric memory tests (difference in mean cognition per decade increase in age for 1-SD higher AD-GRS, 8.8%) (P = 1.56 × 10-3). Best-fitting models suggested that cognitive scores of individuals with a high vs low AD-GRS began to diverge by 56 years of age for all 13 measures and by 47 years of age for 9 measures. CONCLUSIONS AND RELEVANCE In this cross-sectional study, by early midlife, subtle differences in memory and attention were detectable among individuals with higher genetic risk of AD.
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Affiliation(s)
- Scott C. Zimmerman
- Department of Epidemiology and Biostatistics, University of California, San Francisco
| | - Willa D. Brenowitz
- Department of Epidemiology and Biostatistics, University of California, San Francisco
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco
| | - Camilla Calmasini
- Department of Epidemiology and Biostatistics, University of California, San Francisco
| | - Sarah F. Ackley
- Department of Epidemiology and Biostatistics, University of California, San Francisco
| | - Rebecca E. Graff
- Department of Epidemiology and Biostatistics, University of California, San Francisco
| | - Stephen B. Asiimwe
- Department of Epidemiology and Biostatistics, University of California, San Francisco
| | - Adam M. Staffaroni
- Weill Institute for Neurosciences, Department of Neurology, Memory and Aging Center, University of California, San Francisco
| | - Thomas J. Hoffmann
- Department of Epidemiology and Biostatistics, University of California, San Francisco
- Institute for Human Genetics, University of California, San Francisco
| | - M. Maria Glymour
- Department of Epidemiology and Biostatistics, University of California, San Francisco
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Brenowitz WD, Zimmerman SC, Filshtein TJ, Yaffe K, Walter S, Hoffmann TJ, Jorgenson E, Whitmer RA, Glymour MM. Extension of Mendelian Randomization to Identify Earliest Manifestations of Alzheimer Disease: Association of Genetic Risk Score for Alzheimer Disease With Lower Body Mass Index by Age 50 Years. Am J Epidemiol 2021; 190:2163-2171. [PMID: 33843952 DOI: 10.1093/aje/kwab103] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 04/06/2021] [Accepted: 04/07/2021] [Indexed: 01/08/2023] Open
Abstract
Weight loss or lower body mass index (BMI) could be an early symptom of Alzheimer disease (AD), but when this begins to emerge is difficult to estimate with traditional observational data. In an extension of Mendelian randomization, we leveraged variation in genetic risk for late-onset AD risk to estimate the causal effect of AD on BMI and the earliest ages at which AD-related weight loss (or lower BMI as a proxy) occurs. We studied UK Biobank participants enrolled in 2006-2010, who were without dementia, aged 39-73, with European genetic ancestry. BMI was calculated with measured height/weight (weight (kg)/height (m)2). An AD genetic risk score (AD-GRS) was calculated based on 23 genetic variants. Using linear regressions, we tested the association of AD-GRS with BMI, stratified by decade, and calculated the age of divergence in BMI trends between low and high AD-GRS. AD-GRS was not associated with BMI in 39- to 49-year-olds (β = 0.00, 95% confidence interval (CI): -0.03, 0.03). AD-GRS was associated with lower BMI in 50- to 59-year-olds (β = -0.03, 95% CI: -0.06, -0.01) and 60- to 73-year-olds (β = -0.09, 95% CI:-0.12, -0.07). Model-based BMI age curves for high versus low AD-GRS began to diverge after age 47 years. Sensitivity analyses found no evidence for pleiotropy or survival bias. Longitudinal replication is needed; however, our findings suggest that AD genes might begin to reduce BMI decades prior to dementia diagnosis.
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Amanollahi M, Amanollahi S, Anjomshoa A, Dolatshahi M. Mitigating the negative impacts of aging on cognitive function; modifiable factors associated with increasing cognitive reserve. Eur J Neurosci 2021; 53:3109-3124. [PMID: 33715252 DOI: 10.1111/ejn.15183] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 02/28/2021] [Accepted: 03/03/2021] [Indexed: 12/21/2022]
Abstract
Research suggests that social, physical, and cognitively challenging activities during lifetime, could mitigate the negative effects of aging on cognitive function. This effect is explained by the increased cognitive reserve (CR) resulting from such factors; in fact, such activities, by altering structural and functional properties of the human brain, equip one with more effective compensatory mechanisms to resist brain damage before the presentation of severe clinical symptoms. Therefore, applying appropriate modifications in one's lifestyle and activities may be effective in lowering the risk of developing dementia and cognitive dysfunction in old age, especially in brain areas that are susceptible to aging. In this paper, we are going to review relevant studies discussing the association between important modifiable factors, known as CR proxies (i.e., educational attainment, occupational complexity, physical activity, social engagement, bilingualism, leisure activities, and Mediterranean diet), and different domains of cognitive function, which are affected either in the process of healthy aging or neurodegenerative diseases.
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Affiliation(s)
- Mobina Amanollahi
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.,NeuroImaging Network (NIN), Universal Scientific Education and Research Network (USERN), Tehran, Iran
| | - Saba Amanollahi
- School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
| | - Ali Anjomshoa
- Students' Scientific Research Center (SSRC), Tehran University of Medical Sciences, Tehran, Iran
| | - Mahsa Dolatshahi
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.,NeuroImaging Network (NIN), Universal Scientific Education and Research Network (USERN), Tehran, Iran
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7
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Brenowitz WD, Filshtein TJ, Yaffe K, Walter S, Ackley SF, Hoffmann TJ, Jorgenson E, Whitmer RA, Glymour MM. Association of genetic risk for Alzheimer disease and hearing impairment. Neurology 2020; 95:e2225-e2234. [PMID: 32878991 PMCID: PMC7713783 DOI: 10.1212/wnl.0000000000010709] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Accepted: 05/12/2020] [Indexed: 01/09/2023] Open
Abstract
OBJECTIVE To test the hypothesis that incipient Alzheimer disease (AD) may adversely affect hearing and that hearing loss may adversely affect cognition, we evaluated whether genetic variants that increase AD risk also increase problem hearing and genetic variants that increase hearing impairment risk do not influence cognition. METHODS UK Biobank participants without dementia ≥56 years of age with Caucasian genetic ancestry completed a Digit Triplets Test of speech-in-noise hearing (n = 80,074), self-reported problem hearing and hearing with background noise (n = 244,915), and completed brief cognitive assessments. A genetic risk score for AD (AD-GRS) was calculated as a weighted sum of 23 previously identified AD-related polymorphisms. A genetic risk score for hearing (hearing-GRS) was calculated using 3 previously identified polymorphisms related to hearing impairment. Using age-, sex-, and genetic ancestry-adjusted logistic and linear regression models, we evaluated whether the AD-GRS predicted poor hearing and whether the hearing-GRS predicted worse cognition. RESULTS Poor speech-in-noise hearing (>-5.5-dB speech reception threshold; prevalence 14%) was associated with lower cognitive scores (ß = -1.28; 95% confidence interval [CI] -1.54 to -1.03). Higher AD-GRS was significantly associated with poor speech-in-noise hearing (odds ratio [OR] 1.06; 95% CI 1.01-1.11) and self-reported problems hearing with background noise (OR 1.03; 95% CI 1.00-1.05). Hearing-GRS was not significantly associated with cognitive scores (ß = -0.05; 95% CI -0.17 to 0.07). CONCLUSIONS Genetic risk for AD also influences speech-in-noise hearing. We failed to find evidence that genetic risk for hearing impairment affects cognition. AD disease processes or a that shared etiology may cause speech-in-noise difficulty before dementia onset.
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Affiliation(s)
- Willa D Brenowitz
- From the Department of Psychiatry and Behavioral Sciences (W.D.B., K.Y.), Department of Epidemiology and Biostatistics (K.Y., S.F.A., T.J.H., M.M.G.), Department of Neurology (K.Y.), and Institute for Human Genetics (T.J.H.), University of California, San Francisco; 23andMe (T.J.F.), Mountain View; San Francisco VA Health Care System (K.Y.), CA; Department of Medicine and Public Health (S.W.), Rey Juan Carlos University, Madrid, Spain; Kaiser Permanente Northern California Division of Research (E.J.), Oakland; and Public Health Sciences (R.A.W.), Division of Epidemiology, Alzheimer's Disease Research Center, UC Davis School of Medicine, CA.
| | - Teresa J Filshtein
- From the Department of Psychiatry and Behavioral Sciences (W.D.B., K.Y.), Department of Epidemiology and Biostatistics (K.Y., S.F.A., T.J.H., M.M.G.), Department of Neurology (K.Y.), and Institute for Human Genetics (T.J.H.), University of California, San Francisco; 23andMe (T.J.F.), Mountain View; San Francisco VA Health Care System (K.Y.), CA; Department of Medicine and Public Health (S.W.), Rey Juan Carlos University, Madrid, Spain; Kaiser Permanente Northern California Division of Research (E.J.), Oakland; and Public Health Sciences (R.A.W.), Division of Epidemiology, Alzheimer's Disease Research Center, UC Davis School of Medicine, CA
| | - Kristine Yaffe
- From the Department of Psychiatry and Behavioral Sciences (W.D.B., K.Y.), Department of Epidemiology and Biostatistics (K.Y., S.F.A., T.J.H., M.M.G.), Department of Neurology (K.Y.), and Institute for Human Genetics (T.J.H.), University of California, San Francisco; 23andMe (T.J.F.), Mountain View; San Francisco VA Health Care System (K.Y.), CA; Department of Medicine and Public Health (S.W.), Rey Juan Carlos University, Madrid, Spain; Kaiser Permanente Northern California Division of Research (E.J.), Oakland; and Public Health Sciences (R.A.W.), Division of Epidemiology, Alzheimer's Disease Research Center, UC Davis School of Medicine, CA
| | - Stefan Walter
- From the Department of Psychiatry and Behavioral Sciences (W.D.B., K.Y.), Department of Epidemiology and Biostatistics (K.Y., S.F.A., T.J.H., M.M.G.), Department of Neurology (K.Y.), and Institute for Human Genetics (T.J.H.), University of California, San Francisco; 23andMe (T.J.F.), Mountain View; San Francisco VA Health Care System (K.Y.), CA; Department of Medicine and Public Health (S.W.), Rey Juan Carlos University, Madrid, Spain; Kaiser Permanente Northern California Division of Research (E.J.), Oakland; and Public Health Sciences (R.A.W.), Division of Epidemiology, Alzheimer's Disease Research Center, UC Davis School of Medicine, CA
| | - Sarah F Ackley
- From the Department of Psychiatry and Behavioral Sciences (W.D.B., K.Y.), Department of Epidemiology and Biostatistics (K.Y., S.F.A., T.J.H., M.M.G.), Department of Neurology (K.Y.), and Institute for Human Genetics (T.J.H.), University of California, San Francisco; 23andMe (T.J.F.), Mountain View; San Francisco VA Health Care System (K.Y.), CA; Department of Medicine and Public Health (S.W.), Rey Juan Carlos University, Madrid, Spain; Kaiser Permanente Northern California Division of Research (E.J.), Oakland; and Public Health Sciences (R.A.W.), Division of Epidemiology, Alzheimer's Disease Research Center, UC Davis School of Medicine, CA
| | - Thomas J Hoffmann
- From the Department of Psychiatry and Behavioral Sciences (W.D.B., K.Y.), Department of Epidemiology and Biostatistics (K.Y., S.F.A., T.J.H., M.M.G.), Department of Neurology (K.Y.), and Institute for Human Genetics (T.J.H.), University of California, San Francisco; 23andMe (T.J.F.), Mountain View; San Francisco VA Health Care System (K.Y.), CA; Department of Medicine and Public Health (S.W.), Rey Juan Carlos University, Madrid, Spain; Kaiser Permanente Northern California Division of Research (E.J.), Oakland; and Public Health Sciences (R.A.W.), Division of Epidemiology, Alzheimer's Disease Research Center, UC Davis School of Medicine, CA
| | - Eric Jorgenson
- From the Department of Psychiatry and Behavioral Sciences (W.D.B., K.Y.), Department of Epidemiology and Biostatistics (K.Y., S.F.A., T.J.H., M.M.G.), Department of Neurology (K.Y.), and Institute for Human Genetics (T.J.H.), University of California, San Francisco; 23andMe (T.J.F.), Mountain View; San Francisco VA Health Care System (K.Y.), CA; Department of Medicine and Public Health (S.W.), Rey Juan Carlos University, Madrid, Spain; Kaiser Permanente Northern California Division of Research (E.J.), Oakland; and Public Health Sciences (R.A.W.), Division of Epidemiology, Alzheimer's Disease Research Center, UC Davis School of Medicine, CA
| | - Rachel A Whitmer
- From the Department of Psychiatry and Behavioral Sciences (W.D.B., K.Y.), Department of Epidemiology and Biostatistics (K.Y., S.F.A., T.J.H., M.M.G.), Department of Neurology (K.Y.), and Institute for Human Genetics (T.J.H.), University of California, San Francisco; 23andMe (T.J.F.), Mountain View; San Francisco VA Health Care System (K.Y.), CA; Department of Medicine and Public Health (S.W.), Rey Juan Carlos University, Madrid, Spain; Kaiser Permanente Northern California Division of Research (E.J.), Oakland; and Public Health Sciences (R.A.W.), Division of Epidemiology, Alzheimer's Disease Research Center, UC Davis School of Medicine, CA
| | - M Maria Glymour
- From the Department of Psychiatry and Behavioral Sciences (W.D.B., K.Y.), Department of Epidemiology and Biostatistics (K.Y., S.F.A., T.J.H., M.M.G.), Department of Neurology (K.Y.), and Institute for Human Genetics (T.J.H.), University of California, San Francisco; 23andMe (T.J.F.), Mountain View; San Francisco VA Health Care System (K.Y.), CA; Department of Medicine and Public Health (S.W.), Rey Juan Carlos University, Madrid, Spain; Kaiser Permanente Northern California Division of Research (E.J.), Oakland; and Public Health Sciences (R.A.W.), Division of Epidemiology, Alzheimer's Disease Research Center, UC Davis School of Medicine, CA
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Leng Y, Ackley SF, Glymour MM, Yaffe K, Brenowitz WD. Genetic Risk of Alzheimer's Disease and Sleep Duration in Non-Demented Elders. Ann Neurol 2020; 89:177-181. [PMID: 32951248 DOI: 10.1002/ana.25910] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 09/10/2020] [Accepted: 09/11/2020] [Indexed: 12/12/2022]
Abstract
Growing evidence has suggested an association between sleep duration and Alzheimer's disease (AD), but it is unclear if sleep duration is a manifestation of the AD disease process. We studied whether genetic liability for AD predicts sleep duration using a genetic risk score (GRS) for AD (AD-GRS), in 406,536 UK Biobank participants with European ancestry and without dementia at enrollment. Higher AD-GRS score was associated with shorter sleep (b = -0.014, 95% confidence interval [CI] = -0.022 to -0.006), especially in those aged 55+. Using AD-GRS as an instrumental variable for AD diagnosis, incipient AD reduced sleep duration by 1.87 hours (95% CI = 0.96, 2.78). Short sleep duration might be an early marker of AD. ANN NEUROL 2021;89:177-181.
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Affiliation(s)
- Yue Leng
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA
| | - Sarah F Ackley
- Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA
| | - Maria M Glymour
- Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA
| | - Kristine Yaffe
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA.,Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA.,Department of Neurology, University of California, San Francisco, San Francisco, CA.,San Francisco Veterans Affairs Health Care System, San Francisco, CA
| | - Willa D Brenowitz
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA
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