Personalized Interventions May Improve Cognition, Reduce Alzheimer Dementia Risk


Study results suggest that adherence to individually tailored interventions, including behavioral, dietary, pharmacologic, educational, and other recommendations can have a positive impact on cognition and reduce risk in patients across the clinical spectrum who have a family history of Alzheimer disease.

Dr Richard Isaacson

Richard Isaacson, MD, director, Alzheimers Prevention Clinic, Weill Cornell Memory Disorders Program

Richard Isaacson, MD

The therapeutic treatment of Alzheimer disease (AD) has proven to be extremely challenging. Amid numerous failed attempts to prevent disease progression and reduce the risk of disease development, the use of personalized, multidomain interventions have emerged as a promising new paradigm.

Study results published in Alzheimer’s & Dementia suggest that adherence to individually tailored interventions, from improved diet and exercise to optimized blood pressure and blood sugar control, may improve cognition as well as reduce risk scores for AD in those at risk of developing AD dementia.1 The results place extra emphasis on the importance of early intervention and good adherence, with data demonstrating that higher compliance in patients across the spectrum, from cognitively normal to those with mild cognitive impairment (MCI) due to AD, resulted in significantly better improvement in cognition than that seen in historical cohorts.

“We envision a day when individualized AD risk factor management may be applied for care to tens of millions of patients at risk for AD dementia,” lead author Richard Isaacson, MD, director of the Alzheimer’s Prevention Clinic, Weill Cornell Memory Disorders Program at Weill Cornell Medical College/New York-Presbyterian Hospital, and colleagues wrote. “From a practical clinical perspective, there is ample evidence to support recommending established lifestyle changes known to benefit overall brain health. However, important challenges remain for researchers, clinicians, patients, and health policy decision-makers on how best to evaluate—both objectively and ethically—any new information, findings, and knowledge that promote and/or maintain brain health.”

Isaacson told NeurologyLive that these findings can be viewed “really, as a bright light in the field of Alzheimer disease prevention and risk reduction,” noting that this cohort included individuals age 25 to 86. While participants had a family history of AD, those included in the trial were from across the clinical spectrum, ranging from those with no cognitive impairment or subjective cognitive decline and those with preclinical disease, to those with MCI due to AD or mild AD dementia.

“This study was very unique because it included, really for the first time, patients across the entire clinical spectrum of AD—primary, secondary, and tertiary prevention,” Isaacson told NeurologyLive. “The other part about this study that was unique was that we included a wide variety of ages. Our minimum age requirement was 25 years old. Most people are unaware that AD begins in the brain decades—20, 30, possibly more years—before symptoms…It was our goal to enroll people across all age ranges.”

The study ultimately included 154 individuals who requested a clinical consultation for AD prevention. Participants were given individualized interventions inclusive of education, pharmacologic, and nonpharmacologic approaches (mean recommendations per patient, 21) based on individual risk factors, and were evaluated every 6 months with continual refinements to each patient’s interventions. Change in the intervention cohorts was compared with matched historical cohorts from the National Alzheimer’s Coordinating Center (NACC; N = 38,836) and the Rush University Memory and Aging Project (N = 3289) datasets.

The basis for the individualized clinical approach was built from the group’s prior work from 2018.2 The recommendations included patient education/genetic counseling, various pharmacological approaches, including medical management of hypertension, diabetes, and vitamin deficiency, nonpharmacological approaches, including personalized recommendations for diet, exercise, and sleep, as well as interventions related to vascular risk, cognitive engagement/training, stress, and general medical care.

Patients were grouped by clinical stage, with those who were asymptomatic to having subjective cognitive decline included in the prevention group, (n = 119) while those with MCI due to AD or mild AD dementia were included in the early treatment group (n = 35). Participants were ultimately sub-stratified by compliance, with those adhering to 60% or more of the recommended interventions deemed high-compliance, while those who adhered to less than 60% of interventions deemed as low-compliance.

Among those in the prevention cohort, those in both the higher- (n = 65) and lower-compliance (n = 54) groups showed significant improvements on the primary outcome measure, which was change in modified Alzheimer's Prevention Initiative Cognitive Composite (m-APCC) score (4.6 points [95% CI, 3.09—6.19, P <.0001] and 4.5 points [95% CI, 2.24—6.84, P =.0002], respectively). No significant differences were observed between the groups. Among those in the early treatment cohort, higher-compliance patients (n = 15) improved by 4.8 points (95% CI, —1.06 to –10.67; P =.1073)on the m-APCC, while the lower-compliance group (n = 20) worsened significantly by 6.0 points (—10.83 to –1.20; P =.0148), with a significant difference between the high-compliance and low-compliance subgroups (P =.0007).

Compared to the historical control cohorts, the higher-compliance prevention subgroup improved by 3.1 points (95% CI, 1.14—5.09; P =.0012) and 4.9 points (95% CI, 2.55—7.25; P <.0001) points more than what was observed in the NACC and Rush cohorts, respectively. The lower-compliance prevention group improved by 2.9 points (95% CI, 0.74—5.06; P =.0088) and 4.0 points (95% CI, 1.26—6.74; P =.0055) more points than the NACC and Rush cohorts, respectively.

In the early treatment cohort, higher-compliance patients improved by 10.3 points (5.99—14.61, P <.0001) and 5.3 points (0.20—10.40, P =.0428) more than the NACC and Rush cohorts, while the lower-compliance subgroup did not differ compared with either the NACC (P =.9820) or Rush cohorts (P =.1115).

“Both groups had significant improvements from baseline to 18 months,” Isaacson told NeurologyLive. “In the prevention group—meaning primary prevention and secondary prevention or preclinical Alzheimer&mdash;whether you followed greater than 60% or less than 60% of the recommendations, both groups had significant benefits when compared to a natural history control cohort. However, when somebody was already diagnosed with MCI due to Alzheimer disease, only the patients who followed greater than 60% of the recommendations had significant improvement.”

The secondary outcomes included the change in 2 AD risk scales (the Australian National University—AD Risk Index [ANU-ADRI], and the Cardiovascular Risk Factors, Aging and Incidence of Dementia [CAIDE]), and 2 cardiovascular risk scores (the American College of Cardiology/American Heart Association [ACC/AHA] and the Multi-Ethnic Study of Atherosclerosis [MESA]), as well as risk biomarkers.

At 6 months on ANU-ADRI, the higher-compliance prevention group decreased by 2.8 points (95% CI, 1.76—3.75; P <.0001) and the lower-compliance group decreased by 1.2 points (95% CI, 0.01—2.35; P =.0480), while the early treatment groups decreased by 5.9 (95% CI, 1.73—10.11; P =.0060) and 3.9 (95% CI, 0.52—7.27; P =.0240) points in the higher- and lower-compliance groups, respectively.

At 18 months, CAIDE scores for the prevention group decreased by 0.1 (95% CI, −0.14 to −0.25; P =.6053) and 0.0 (95% CI, −0.26 to −0.33; P =.8247) in the higher- and lower-compliance groups, respectively, and 0.9 (95% CI, 0.19—1.53; P =.0120) and 0.7 (95% CI, 0.14—1.35; P =.0170) in the higher- and lower-compliance early treatment groups, respectively.

For ACC/AHA cardiovascular risk at 18 months, the prevention group decreased by 3.8 (95% CI, 3.05—4.49; P <.0001) and 2.8 (95% CI, 2.06—3.60, P <.0001) in the higher- and lower-compliance groups, respectively, while the higher-compliance early treatment group decreased by 10.4 (95% CI, 4.54—16.30; P =.0006) and the lower-compliance group decreased by 13.0 (95% CI, 8.20—17.78; P <.0001).

Likewise, at 18 months for MESA, the higher- and lower-compliance prevention groups decreased by 1.7 (95% 1.39—1.99; P <.0001) and 1.4 (95% CI, 1.17–1.64; P <.0001), respectively, while the early treatment groups decreased by 2.7 (95% CI, 1.37—3.95; P <.0001) and 2.7 (95% CI, 0.73—4.68; P =.0076) in the higher- and lower-groups, respectively.

While a number of biomarker changes were observed, none were significantly correlated with either change in m-APCC or change in CogAging in all patient groups, save for cystatin C, for which a worsening of 0.1 mg/L corresponded to greater improvement in CogAging by 1.2 years (P =.0227).

Notably, the key limitation of the study was the lack of a concurrent, randomized control group, though the investigators clarified that this may have not been possible because well-informed participants actively enrolled in an AD risk reduction study may seek out and make lifestyle and/or other behavioral changes that impact outcomes, and the infeasibility to withhold treatment from a nonintervention randomized control group.

Isaacson said that the key finding of the study which he and his colleagues found “truly surprising” was the improvement in cognition over 18 months for patients in the early treatment cohort who were highly compliant. “I think most people in the field would ask, ‘Well, is that really possible?’ And it was,” he said.

Isaacson and colleagues concluded that with these findings, it is their hope that international funding agencies and foundations will look to these data as the basis for the adoption of comparative effectiveness research as an opportunity going forward.

With no available treatments for those with MCI due to AD, Isaacson noted that the findings provide physicians with some tools in an area in which they’ve often struggled to aid their patients.

“Individualized clinical management—assessing risk factors, blood pressure control, getting to lower targets…getting blood sugar under control, exercising regularly, the list goes on and on&mdash;is a way to really optimize cognition,” Isaacson said.


1. Isaacson RS, Hristov H, Saif N, et al. Individualized clinical management of patients at risk for Alzheimer's dementia. Alzheimer’s Dement. Published online October 30, 2019. doi: 10.1016/j.jalz.2019.08.198.

2. Isaacson RS, Ganzer CA, Hristov H, et al. The clinical practice of risk reduction for Alzheimer’s disease: a precision medicine approach. Alzheimer’s Dement. 2018; 14: 1663—1673. doi: 10.1016/j.jalz.2018.08.004

Related Videos
Michael Levy, MD, PhD
Michael Kaplitt, MD, PhD
Michael Kaplitt, MD, PhD
video 4 - "Amyloid Cascade Hypothesis of Alzheimer’s Disease"
Video 3 - "Amyloid Precursor Protein and Amyloid Beta Species in Alzheimer’s Disease"
Svetlana Blitshteyn, MD, FAAN, director and founder of Dysautonomia Clinic
© 2024 MJH Life Sciences

All rights reserved.