HAPPCAP-AD (Human-APPlication Combined Approach for Prevention of Alzheimer's Disease) (HAPPCAP-AD)

Currently, Alzheimer's disease (AD) has no cure putting prevention-strategies in the forefront for impeding the public health and personal consequences of this devastating disease. Seven major potentially modifiable risk factors show consistent association with AD (midlife type 2 diabetes [T2D], midlife hypertension, midlife obesity, physical inactivity, depression, smoking, and low educational attainment), with combined population-attributable risk of 30%1. A recent extensive literature review of randomized control trials on single lifestyle interventions for AD yielded negative results. The multidomain preDIVA2,3 (Prevention of Dementia by Intensive Vascular Care) and MAPT4,5 (Multidomain Alzheimer Prevention Trial) studies raised concerns regarding the multidomain approach. The multidomain lifestyle model approach of the FINGER6,7 study (Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability) brought some optimism after it presented positive results; several replication trials around the world have been launched8. However, 1) all trials focus on the elderly, 2) the impact of midlife risk factors on dementia risk is stronger than late life, and 3) the neurodegenerative changes in AD begin decades before its clinical manifestations9. A recent study showed that 2 or more cardiovascular risk factors in midlife (but not late life) predicted amyloid aggregation10. Main goals: To examine the feasibility and provide pilot data on effectiveness of a novel "real-life" personalized 18-months intervention for prevention of cognitive decline in middle-aged individuals (age 40-65-year-old) at high AD risk due to AD parental family history. We will implement an approach "diary-monitoring" ("Risk factors log" which will filled daily by participants, using the REDCap (Research Electronic Data Capture) software's survey) with study team guidance. We hypothesize that daily risk-factors documentation in personal "Risk factors log" will increase participant's engagement in the intervention and will enable the study team to accumulate health information, in order to improve support and counselling for improvement of risk factors. In addition to examining the feasibility of our approach, we will explore its effectiveness in both improving risk factors values, as well as improving cognitive function by comparing the HAPPCAP-AD intervention group to "control group". Last, our study will lay the foundations for a strong long-term large-scale preventive intervention in the future. We will compare this group to a partially passive control.

To examine the feasibility and provide pilot data on effectiveness of a novel "real-life" personalized 18-months intervention for prevention of cognitive decline in middle-aged individuals (age 40-65-year-old) at high AD risk due to AD parental family history. We will implement an approach "diary-monitoring" ("Risk factors log" which will filled daily by participants, using the REDCap (Research Electronic Data Capture) software's survey) with study team guidance. We hypothesize that daily risk-factors documentation in personal "Risk factors log" will increase participant's engagement in the intervention and will enable the study team to accumulate health information, in order to improve support and counselling for improvement of risk factors. In addition to examining the feasibility of our approach, we will explore its effectiveness in both improving risk factors values, as well as improving cognitive function by comparing the HAPPCAP-AD intervention group to "control group". Last, our study will lay the foundations for a strong long-term large-scale preventive intervention in the future. We will compare this group to a partially passive control.

At 6 months and 12months the study team will communicate with the participants by phone to inquire about risk factors data, propose alternative activities, and provide positive reinforcement and feedback

At baseline, participants in the intervention group will be asked to fill a daily "risk-factor diaries" ("Risk factors log" using the REDCap (Research Electronic Data Capture) software's survey). In the "Risk factors log", participants will need to answer shortly questions about their specific unbalanced risk factor. In addition, during the 18-months intervention period, the study team will communicate with the participants' every 3-4 weeks by phone. Before each phone call, participants' "Risk factors log" data since previous phone call will be analyzed. The team will propose alternative activities, and provide positive reinforcement and feedback.

At baseline, participants in the intervention group will be asked to fill a daily "risk-factor diaries" ("Risk factors log" using the REDCap (Research Electronic Data Capture) software's survey). In the "Risk factors log", participants will need to answer shortly questions about their specific unbalanced risk factor. In addition, during the 18-months intervention period, the study team will communicate with the participants by phone every 3-4 weeks to inquire about risk factors data. Before each phone call, participants' "Risk factors log" data since previous phone call will be analyzed. The team will propose alternative activities, and provide positive reinforcement and feedback.

"Risk factors log" response rate will be measured as an adherence to the intervention surrogate (response rate will be calculated as the number of submitted daily "Risk factors logs" divided by number of days in the study)

For participants with less than 150 minutes of weekly physical activity at baseline , percentage of relative change between weekly physical activity time (in minutes) values at baseline and 18 months (will be calculated as {([time at 18 months/ time at base line]-1)*100}.

For participants with BMI greater than 25 kg/m2 at baseline, percentage of relative change between BMI (BMI values at baseline and 18 months (will be calculated as {([BMI at 18 months/ BMI at base line]-1)*100}.

For participants who smoke at baseline, percentage of relative change between number of smoked cigarettes (number of smoked cigarettes at baseline and 18 months (will be calculated as {([number of smoked cigarettes at 18 months/ number of smoked cigarettes at base line]-1)*100}.

For participants with hypertension at baseline (worse than 125/85 mm Hg), percentage of relative change between systolic blood pressure (in mm Hg at baseline and 18 months (will be calculated as {([systolic blood pressure at 18 months/ systolic blood pressure at base line]-1)*100}.

For participants with unbalanced diabetes at baseline, percentage of relative change between HBA1C% (at baseline and 18 months (will be calculated as {([HBA1C% at 18 months/ HBA1C% at base line]-1)*100}.

For participants with unbalanced depression at baseline, percentage of relative change between number of participants with depression according to their CES-D (Center for Epidemiologic Studies Depression Scale) questionnaire total score (at baseline and 18 months (will be calculated as {([CES-D total score at 18 months/ CES-D total score at base line]-1)*100}.

The influence of study intervention on global cognitive function will be assessed by calculating the changes in global cognitive function using a Z score between baseline and after 18 month (this is an exploratory aim since this is a pilot study). (Global cognition z score was obtained by averaging the domains [memory, language, executive function, attention] z scores) Higher Z score represent better global cognitive function

The influence of study intervention on memory domain will be assessed by calculating the changes in memory function using a Z score between baseline and after 18 month (this is an exploratory aim since this is a pilot study). Higher Z score represent better memory function

The influence of study intervention on language domain will be assessed by calculating the changes in language function using a Z score between baseline and after 18 month (this is an exploratory aim since this is a pilot study). Higher Z score represent better language function

The influence of study intervention on executive function domain will be assessed by calculating the changes in executive function domain using a Z score between baseline and after 18 month (this is an exploratory aim since this is a pilot study). Higher Z score represent better executive function domain function

The influence of study intervention on attention domain will be assessed by calculating the changes in attention domain using a Z score between baseline and after 18 month (this is an exploratory aim since this is a pilot study). Higher Z score represent better attention function

Inclusion Criteria: • Age 40-65 at enrollment to the study Family history of AD-All subjects recruited will have at least 1 parent diagnosed with AD (as specified below) All participant will be MHS (Maccabi Health System) members Participants must have at least two of the seven risk factors for AD (1. Smoking; 2. type 2 diabetes [T2D]; 3. Hypertension; 4. obesity/ overweight; 5. low physical inactivity; 6. low educational attainment/ mental activity; 7. depression) No dementia diagnosis Hebrew fluency Exclusion Criteria: Previously diagnosed dementia• Any condition expected to limit the adherence to suggested intervention for 18 months Any significant neurologic or psychiatric disease

Participants will sign if they agree that their data will be shared anonymously with other AD/ cognition/ other studies