Indicators of amyloid burden in a population-based study of cognitively normal elderly

Mielke, Michelle M.; Wiste, Heather J.; Weigand, Stephen D.; Knopman, David S.; Lowe, Val J.; Roberts, Rosebud O.; Geda, Yonas E.; Swenson-Dravis, Dana; Boeve, Bradley F.; Senjem, Matthew L.; Vemuri, Prashanthi; Petersen, Ronald C.; Jack, Clifford R.

doi:10.1212/wnl.0b013e31826e2696

Cited by 152 publications

(163 citation statements)

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“…We previously identified risk factors associated with an increased risk of MCI. [1][2][3][4][5][6][7][8][9][10][11][12][13] The present analyses demonstrate the predictive importance of these risk factors when incorporated into multivariable models and suggest that there are variables that quantify MCI risk differently for men and women. The risk scores obtained from these multivariable models can be used to stratify CN individuals according to their risk of MCI.…”

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confidence: 53%

“…[1][2][3] Analyses of MCSA data have identified several factors associated with the risk of MCI including age, education, sex, APOE genotype, 4 parkinsonism, 5 diabetes, [6][7][8] depressive symptoms, 9 cardiovascular disease, 10,11 stroke, 12 and slow gait. 13 In the present study, we focused on developing an algorithm that uses these variables to predict the risk of transitioning from cognitively normal (CN) to MCI.…”

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confidence: 99%

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Predicting the risk of mild cognitive impairment in the Mayo Clinic Study of Aging

et al. 2015

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Objective: We sought to develop risk scores for the progression from cognitively normal (CN) to mild cognitive impairment (MCI). Methods:We recruited into a longitudinal cohort study a randomly selected, population-based sample of Olmsted County, MN, residents, aged 70 to 89 years on October 1, 2004. At baseline and subsequent visits, participants were evaluated for demographic, clinical, and neuropsychological measures, and were classified as CN, MCI, or dementia. Using baseline demographic and clinical variables in proportional hazards models, we derived scores that predicted the risk of progressing from CN to MCI. We evaluated the ability of these risk scores to classify participants for MCI risk. Conclusions:We have developed MCI risk scores using variables easily assessable in the clinical setting and that may be useful in routine patient care. Because of variability among populations, validation in independent samples is required. These models may be useful in identifying patients who might benefit from more expensive or invasive diagnostic testing, and can inform clinical trial design. Inclusion of biomarkers or other risk factors may further enhance the models. As clinicians and researchers strive to identify individuals at the highest risk of dementia in the earliest possible stages, understanding the predictors of mild cognitive impairment (MCI) is crucial because individuals with MCI have an increased risk of developing dementia. A method that predicts an individual's risk of developing MCI, particularly one that is brief, inexpensive, and noninvasive, is essential for risk stratification at the population level and would enhance the design and conduct of interventional trials.Estimates of the prevalence and incidence of MCI have been published from the prospective population-based Mayo Clinic Study of Aging (MCSA), designed to examine cognitive changes among individuals initially without dementia.

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confidence: 53%

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confidence: 99%

Predicting the risk of mild cognitive impairment in the Mayo Clinic Study of Aging

et al. 2015

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“…This finding in normal population is not new and has been reported by others authors. [22][23][24] Age has been suggested as the explanation, and accordingly, our healthy 11 C-PIBpositive subject was aged 70 years.…”

Section: Discussionmentioning

confidence: 96%

Amyloid Imaging With 11C-PIB in Patients With Cognitive Impairment in a Clinical Setting

Jiménez-Bonilla¹,

Banzo²,

Arcocha-Torres³

et al. 2016

Clinical Nuclear Medicine

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“…Thus, APOE4 has been consistently shown in many studies to be associated with a significant increase in Aβ deposition or a greater proportion of amyloid-positive individuals in normal elderly (Reiman et al, 2009;Hinrichs et al, 2010;Morris et al, 2010;Rowe et al, 2010;Villemagne et al, 2011;Jagust et al, 2012;Kantarci et al, 2012;Mathis et al, 2012;Mielke et al, 2012;Fleisher et al, 2013). Thus, across studies in cognitively normal elderly, 35 to 49% of APOE4 carriers are 11 C-PIBpositive while they are 9 to 37% amongst non carriers (see Table 1).…”

Section: Apoe4 and Amyloid Deposition / Amyloid Pet Imagingmentioning

confidence: 94%

Neuroimaging biomarkers for Alzheimer's disease in asymptomatic APOE4 carriers

Chételat

Fouquet

2013

Revue Neurologique

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Abstract:Introduction. The E4 allele of the apolipoprotein E (APOE4) is the major known genetic risk factor for AD, with a dramatic increase in the risk of developing AD as the number of APOE4 alleles increases from 0 to 2. For this reason, asymptomatic APOE4 carriers as a group offer a great opportunity to seek for the presence of early biomarkers for AD. The present article reviews neuroimaging studies on APOE4 carriers, focusing on cognitively normal individuals and on the main neuroimaging biomarkers for AD, i.e. atrophy with structural MRI, hypometabolism with FDG-PET, and amyloid deposition with amyloid-PET imaging.State of art. There is a great number of studies on the effect of APOE4 on brain structures, and they tend to show significant atrophy in APOE4 carriers compared to non carriers especially in regions susceptible to AD pathology such as the hippocampus. However, results are rather discrepant which suggests that the effect of APOE4 on brain structure is subtle. As for FDG-PET metabolism, the few studies show decreased metabolism, again especially in AD-sensitive regions such as posterior associative parietal areas, with a dose-dependent effect (i.e. worsening as the number of APOE4 alleles increases). Finally, there is a unanimous and major effect of APOE4 on amyloid deposition with an increase in Aβ load as the number of APOE4 alleles increases and a decrease in the age of predicted amyloid-positivity in APOE4 carriers. This graded effect of APOE4 on atrophy, hypometabolism, and amyloid deposition is consistent with multimodal neuroimaging studies suggestive of a predominant effect of APOE4 on amyloid rather than tau-related injury and on brain metabolism rather than brain structure. Neuroimaging studies also suggest that APOE4 effects may be mediated by both Aβ-dependent and Aβ-independent pathological processes. This contradicts the view that Aβ pathology is a necessary upstream event to neuronal injury in AD. Perspectives and conclusion. Future studies would tell whether the mechanisms and sequences evidenced in carriers is comparable to those found in non carriers, but it is likely that APOE4 not only influences the risk for AD, but also modulates the physiopathological cascade. Altogether, APOE4 carriers offer a great opportunity to investigate brain changes in the asymptomatic stages of AD and to further our understanding of the physiopathology of the disease, although precaution is needed for interpretation in AD at large. Etat des connaissances. De très nombreuses études ont évalué les effets de l'APOE4 sur la structure cérébrale. Les résultats sont très divergents, même s'ils suggèrent dans l'ensemble un effet subtile dans le sens d'une diminution de volume dans les régions les plus sensibles à la MA telles que l'hippocampe. Les rares études en TEP-FDG indiquent une baisse du métabolisme là encore dans les régions altérées précocement dans la MA comme le cortex associatif pariétal postérieur, avec un effet dose-dépendant (i.e. fonction du nombre d'allèles APOE4). Enfin, l'effet sur les d...

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Indicators of amyloid burden in a population-based study of cognitively normal elderly

Cited by 152 publications

References 34 publications

Predicting the risk of mild cognitive impairment in the Mayo Clinic Study of Aging

Predicting the risk of mild cognitive impairment in the Mayo Clinic Study of Aging

Amyloid Imaging With 11C-PIB in Patients With Cognitive Impairment in a Clinical Setting

Neuroimaging biomarkers for Alzheimer's disease in asymptomatic APOE4 carriers

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