Prediction of Alzheimer’s disease biomarker status defined by the ‘ATN framework’ among cognitively healthy individuals: results from the EPAD longitudinal cohort study

Abstract Background The Amyloid/Tau/Neurodegeneration (ATN) framework has been proposed as a means of evidencing the biological state of Alzheimer’s disease (AD). Predicting ATN status in pre-dementia individuals therefore provides an important opportunity for targeted recruitment into AD interventional studies. We investigated the extent to which ATN-defined biomarker status can be predicted by known AD risk factors as well as vascular-related composite risk scores. Methods One thousand ten cognitively healthy older adults were allocated to one of five ATN-defined biomarker categories. Multinomial logistic regression tested risk factors including age, sex, education, APOE4, family history of dementia, cognitive function, vascular risk indices (high systolic blood pressure, body mass index (BMI), high cholesterol, physical inactivity, ever smoked, blood pressure medication, diabetes, prior cardiovascular disease, atrial fibrillation and white matter lesion (WML) volume), and three vascular-related composite scores, to predict five ATN subgroups; ROC curve models estimated their added value in predicting pathology. Results Age, APOE4, family history, BMI, MMSE and white matter lesions (WML) volume differed between ATN biomarker groups. Prediction of Alzheimer’s disease pathology (versus normal AD biomarkers) improved by 7% after adding family history, BMI, MMSE and WML to a ROC curve that included age, sex and APOE4. Risk composite scores did not add value. Conclusions ATN-defined Alzheimer’s disease biomarker status prediction among cognitively healthy individuals is possible through a combination of constitutional and cardiovascular risk factors but established dementia composite risk scores do not appear to add value in this context.

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Biobank-wide association scan identifies risk factors for late-onset Alzheimer’s disease and endophenotypes

10.1101/468306 ◽

2018 ◽

Cited By ~ 3

Author(s):

Donghui Yan ◽

Bowen Hu ◽

Burcu F. Darst ◽

Shubhabrata Mukherjee ◽

Brian W. Kunkle ◽

...

Keyword(s):

Risk Factors ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Family History ◽

Late Onset ◽

Association Studies ◽

Risk Scores ◽

Genome Wide Association Studies ◽

High Cholesterol ◽

Multiple Traits

AbstractDense genotype data and thousands of phenotypes from large biobanks, coupled with increasingly accessible summary association statistics from genome-wide association studies (GWAS), provide great opportunities to dissect the complex relationships among human traits and diseases. We introduce BADGERS, a powerful method to perform polygenic score-based biobank-wide scans for disease-trait associations. Compared to traditional regression approaches, BADGERS uses GWAS summary statistics as input and does not require multiple traits to be measured on the same cohort. We applied BADGERS to two independent datasets for Alzheimer’s disease (AD; N=61,212). Among the polygenic risk scores (PRS) for 1,738 traits in the UK Biobank, we identified 48 significant trait PRSs associated with AD after adjusting for multiple testing. Family history, high cholesterol, and numerous traits related to intelligence and education showed strong and independent associations with AD. Further, we identified 41 significant PRSs associated with AD endophenotypes. While family history and high cholesterol were strongly associated with neuropathologies and cognitively-defined AD subgroups, only intelligence and education-related traits predicted pre-clinical cognitive phenotypes. These results provide novel insights into the distinct biological processes underlying various risk factors for AD.

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Cardiometabolic risk factors predict executive function scores in high-risk individuals

Innovation in Aging ◽

10.1093/geroni/igab046.2448 ◽

2021 ◽

Vol 5 (Supplement_1) ◽

pp. 651-651

Author(s):

Joshua Gills ◽

Megan Jones ◽

Anthony Campitelli ◽

Sally Paulson ◽

Erica Madero ◽

...

Keyword(s):

Risk Factors ◽

Alzheimer’S Disease ◽

Blood Pressure ◽

Alzheimer's Disease ◽

Executive Function ◽

High Risk ◽

Cardiometabolic Risk ◽

Density Lipoprotein ◽

Cardiometabolic Risk Factors ◽

Walking Test

Abstract Alzheimer’s disease (AD) is expected to triple by 2050, affecting 16 million Americans. As a result, it is essential to combat this alarming increase in cognitive impairment through early detection. Cardiometabolic risk factors have shown to be associated with higher risk of AD. The purpose of this study was to determine if cardiometabolic risk factors could predict executive function scores in a high-risk population. Fifty (60.9±8.8 years) high-risk adults (classified by the Australian National University Alzheimer’s Disease Risk Index) were enrolled in this study. Participants completed a 6-minute walking test, venous blood draw, blood pressure measurement, and the digit coding symbol test (DCS). Results were examined through a multiple linear regression with DCS as the dependent variable and age, sex, total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), glucose, 6-minute walking test, systolic blood pressure (SBP), and diastolic blood pressure (DBP) as predictor variables. The model explained 42% of the variance of DCS (p = .04) with SBP (45%; p = .003) as a significant predictor. LDL (p = .087) and DBP (p = .123) accounted for 24% and 22% of the variance for this model, respectively. These results suggest cardiometabolic risk factors predict executive function values in high-risk individuals. Higher SBP was significantly associated with lower DCS scores indicating SBP as a valuable tool for practitioners when evaluating cognitive decline. Further research should expand sample size and track values longitudinally to substantiate these claims.

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What is Alzheimer’s disease?

10.1093/oso/9780190098124.003.0002 ◽

2021 ◽

pp. 11-18

Author(s):

Andrew E. Budson ◽

Maureen K. O’Connor

Keyword(s):

Risk Factors ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Family History ◽

Lumbar Puncture ◽

Amyloid Plaques ◽

Pet Scan ◽

Brain Cells ◽

Special Circumstances ◽

The Brain

Alzheimer’s is a disease in which amyloid plaques build up in the brain. The plaques damage brain cells, the cells develop tangles, and the tangles destroy the cells. Alzheimer’s disease begins silently and progresses through very mild, mild, moderate, and severe stages. Age, being a woman, and family history are risk factors for the disease. Tests using a lumbar puncture or PET scan can help to confirm the diagnosis of Alzheimer’s disease, but they are only used in special circumstances. Lastly, you can reduce your risk of developing Alzheimer’s disease by eating a Mediterranean-style diet, engaging in aerobic exercise, and staying socially active.

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Associations between vascular risk factors and subsequent Alzheimer’s disease in older adults

Alzheimer s Research & Therapy ◽

10.1186/s13195-020-00690-7 ◽

2020 ◽

Vol 12 (1) ◽

Author(s):

Hyewon Lee ◽

Kiwon Kim ◽

Yeong Chan Lee ◽

Soyeon Kim ◽

Hong-Hee Won ◽

...

Keyword(s):

Risk Factors ◽

Alzheimer’S Disease ◽

Blood Pressure ◽

Older Adults ◽

Alzheimer's Disease ◽

Clinical Guidelines ◽

Density Lipoprotein ◽

Vascular Risk Factors ◽

Lipoprotein Cholesterol ◽

Vascular Risk

Abstract Background The clinical guidelines related to the primary prevention of Alzheimer’s disease (AD) have focused on the management of vascular risk factors. However, the link between vascular risk factors and AD in older adults remains unclear. This study aimed to determine the association between vascular risk factors and subsequent AD in 178,586 older adults (age ≥ 65 years). Methods Participants were recruited from 2009 through 2010 and followed up for 6 years. We assessed various vascular risk factors (total cholesterol [TC], low-density lipoprotein cholesterol [LDL-C], high-density lipoprotein cholesterol [HDL-C], triglycerides [TG], fasting glucose [FG], systolic blood pressure [SBP], diastolic blood pressure [DBP], pulse pressure [PP], and body mass index [BMI]) and their association with AD incidence, categorizing each vascular factor using current clinical guidelines. Results AD was observed in 6.0% of participants at follow-up. All lipid profiles (TC, LDL-C, HDL-C and TG) were positively associated with the risk of AD. SBP and PP were in negative associations with AD, and DBP was positively associated with AD. BMI exhibited a negative association with AD incidence. We found no significant association between FG and AD risk. The sex difference was observed to have effects on vascular risk factors. Conclusions In this study, we comprehensively investigated the association between eight vascular risk factors and the risk of incident AD. Our findings suggest that multiple vascular risk factors are related to the development of AD in older adults. These results can help inform future guidelines for reducing AD risk.

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A Novel Score for Predicting Alzheimer’s Disease Risk from Late Life Psychopathological and Health Risk Factors

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18041802 ◽

2021 ◽

Vol 18 (4) ◽

pp. 1802

Author(s):

Javier Santabárbara ◽

Juan Bueno-Notivol ◽

Darren M. Lipnicki ◽

Concepción de la Cámara ◽

Raúl López-Antón ◽

...

Keyword(s):

Risk Factors ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

High Risk ◽

Risk Index ◽

Late Life ◽

Health Concern ◽

Risk Scores ◽

Risk Of Death ◽

Dementia Risk

With the increasing size of the aging population, dementia risk reduction has become a main public health concern. Dementia risk models or indices may help to identify individuals in the community at high risk to develop dementia. We have aimed to develop a novel dementia risk index focused on the late-life (65 years or more) population, that addresses risk factors for Alzheimer’s disease (AD) easily identifiable at primary care settings. These risk factors include some shown to be associated with the risk of AD but not featured in existing indices, such as hearing loss and anxiety. Our index is also the first to account for the competing risk of death. The Zaragoza Dementia and Depression Project (ZARADEMP) Alzheimer Dementia Risk Score predicts an individual´s risk of developing AD within 5 years. The probability of late onset AD significantly increases in those with risk scores between 21 and 28 and, furthermore, is almost 4-fold higher for those with risk scores of 29 or higher. Our index may provide a practical instrument to identify subjects at high risk of AD and to design preventive strategies targeting the contributing risk factors.

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Modifiable risk factors moderate the relationship between beta-amyloid and cognition in midlife

10.1101/229062 ◽

2017 ◽

Author(s):

Lindsay R. Clark ◽

Rebecca L. Koscik ◽

Samantha L. Allison ◽

Sara E. Berman ◽

Cynthia M. Carlsson ◽

...

Keyword(s):

Risk Factors ◽

Alzheimer’S Disease ◽

Blood Pressure ◽

Alzheimer's Disease ◽

Depressive Symptoms ◽

Verbal Learning ◽

Beta Amyloid ◽

Modifiable Risk Factors ◽

Pittsburgh Compound B ◽

The Relationship

ABSTRACTAlthough evidence suggests a relationship between elevated beta-amyloid and cognitive decline, approximately 30% of older adults with positive markers of amyloid remain cognitively healthy. Our objective was to test if the presence of modifiable risk factors (i.e., central obesity, hypertension, and depressive symptoms) moderated the relationship between amyloid and longitudinal cognitive performance. Data were from 207 adults (140 females; age range=40-70) enriched for Alzheimer’s disease risk (73% parental history of Alzheimer’s disease) enrolled in the Wisconsin Registry for Alzheimer’s Prevention study. Participants completed at least three neuropsychological evaluations and one biomarker visit ([C11]Pittsburgh Compound B PET scan or lumbar puncture). Participants were characterized as high or low on beta-amyloid using cutoffs developed for [C11]Pittsburgh Compound B-PET distribution volume ratio or CSF amyloid beta 1-42 values. Participants were also coded as high or low risk on obesity (waist circumference > 102 cm for males or 88 cm for females), hypertension (systolic blood pressure ≥ 140 mm Hg or diastolic blood pressure ≥ 90 mm Hg), and depressive symptoms (Center for Epidemiologic Studies of Depression scale ≥ 16). Linear mixed effects regression models examined three-way interactions between modifiable risk factor status x beta-amyloid status x visit age on longitudinal Verbal Learning & Memory and Speed & Flexibility factor scores. Results indicated that the relationship between beta-amyloid and Verbal Learning & Memory decline was moderated by the presence of hypertension at baseline (p = .02), presence of hypertension at all visits (p = .001), and presence of obesity at all visits (p = .049). Depressive symptoms did not moderate the association between beta-amyloid and longitudinal Verbal Learning & Memory (p = .62) or Speed & Flexibility (p = .15) performances. In this at-risk for Alzheimer’s disease cohort, modifiable risk factors of hypertension and obesity moderated the relationship between beta-amyloid and cognitive decline. Identification and modification of these risk factors in late middle age may slow the effect of amyloid on the progression of cognitive symptoms.

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