Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Dec;15(12):1588-1602.
doi: 10.1016/j.jalz.2019.08.198. Epub 2019 Oct 31.

Individualized clinical management of patients at risk for Alzheimer's dementia

Richard S Isaacson  1 , Hollie Hristov  2 , Nabeel Saif  2 , Katherine Hackett  3 , Suzanne Hendrix  4 , Juan Melendez  5 , Joseph Safdieh  2 , Matthew Fink  2 , Madhav Thambisetty  6 , George Sadek  2 , Sonia Bellara  2 , Paige Lee  7 , Cara Berkowitz  2 , Aneela Rahman  2 , Josefina Meléndez-Cabrero  8 , Emily Caesar  9 , Randy Cohen  10 , Pei-Lin Lu  11 , Samuel P Dickson  4 , Mu Ji Hwang  2 , Olivia Scheyer  12 , Monica Mureb  2 , Matthew W Schelke  13 , Kellyann Niotis  2 , Christine E Greer  14 , Peter Attia  15 , Lisa Mosconi  2 , Robert Krikorian  16
Affiliations

Individualized clinical management of patients at risk for Alzheimer's dementia

Richard S Isaacson et al. Alzheimers Dement. 2019 Dec.

Abstract

Introduction: Multidomain intervention for Alzheimer's disease (AD) risk reduction is an emerging therapeutic paradigm.

Methods: Patients were prescribed individually tailored interventions (education/pharmacologic/nonpharmacologic) and rated on compliance. Normal cognition/subjective cognitive decline/preclinical AD was classified as Prevention. Mild cognitive impairment due to AD/mild-AD was classified as Early Treatment. Change from baseline to 18 months on the modified Alzheimer's Prevention Cognitive Composite (primary outcome) was compared against matched historical control cohorts. Cognitive aging composite (CogAging), AD/cardiovascular risk scales, and serum biomarkers were secondary outcomes.

Results: One hundred seventy-four were assigned interventions (age 25-86). Higher-compliance Prevention improved more than both historical cohorts (P = .0012, P < .0001). Lower-compliance Prevention also improved more than both historical cohorts (P = .0088, P < .0055). Higher-compliance Early Treatment improved more than lower compliance (P = .0007). Higher-compliance Early Treatment improved more than historical cohorts (P < .0001, P = .0428). Lower-compliance Early Treatment did not differ (P = .9820, P = .1115). Similar effects occurred for CogAging. AD/cardiovascular risk scales and serum biomarkers improved.

Discussion: Individualized multidomain interventions may improve cognition and reduce AD/cardiovascular risk scores in patients at-risk for AD dementia.

Keywords: Alzheimer's disease prevention; Alzheimer's prevention clinic; Multi-domain interventions; Personalized medicine; Preclinical Alzheimer's disease.

PubMed Disclaimer

Conflict of interest statement

Declaration of interests

The authors report no conflicts of interest or other relevant disclosures.

Figures

Figure 1:
Figure 1:. Example Biomarker to Intervention Paradigm
NOTE. Each data point collected during the initial clinical intake and evaluation, as well as at each follow-up visit, is used to inform which precision medicine interventions are recommended per participant.
Figure 2:
Figure 2:. Comparison Groups
NOTE. Participants were classified to reflect the different biological phases along the AD continuum (Figure S1) and level of compliance into one of the following four analysis groups: Higher-compliance Prevention, Lower-compliance Prevention, Higher-compliance Early Treatment, and Lower-compliance Early Treatment. Each group was compared to two matched historical control cohorts, NACC and Rush (n=38836 and n=3289, respectively)
Figure 3:
Figure 3:. m-APCC(a) and Cognitive aging(b), NACC comparison(c), and Rush comparison(d)
NOTE: A) Change from Baseline on the m-APCC at 18 months amongst the four diagnosis x compliance groups. B) Change from Baseline on the non-pathological CogAging composite at 18 months amongst the four diagnosis x compliance groups. C) Comparison of change in m-APCC between higher-compliance, lower-compliance, and Rush control (matched for baseline m-APCC and age). D) Comparison of change in m-APCC between higher-compliance, lower-compliance, and NACC control (matched for baseline m-APCC and age)
See this image and copyright information in PMC

References

    1. Sperling RA, Aisen PS, Beckett LA, et al. Toward defining the preclinical stages of Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & dementia: the journal of the Alzheimer’s Association 2011; 7(3): 280–92. - PMC - PubMed
    1. Jack CR Jr., Knopman DS, Jagust WJ, et al. Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. The Lancet Neurology 2010; 9(1): 119–28. - PMC - PubMed
    1. Jack CR Jr., Knopman DS, Jagust WJ, et al. Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. The Lancet Neurology 2013; 12(2): 207–16. - PMC - PubMed
    1. Jack CR Jr., Bennett DA, Blennow K, et al. NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease. Alzheimer’s & dementia: the journal of the Alzheimer’s Association 2018; 14(4): 535–62. - PMC - PubMed
    1. Brookmeyer R, Abdalla N, Kawas CH, Corrada MM. Forecasting the prevalence of preclinical and clinical Alzheimer’s disease in the United States. Alzheimer’s & dementia: the journal of the Alzheimer’s Association 2018; 14(2): 121–9. - PMC - PubMed

Publication types