Submitted:
15 March 2024
Posted:
18 March 2024
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Abstract
Keywords:
Introduction
Specific Aims and Hypotheses
Materials and Methods
Study Design
Setting and Recruitment
Participants
Inclusion Criteria
Exclusion Criteria
Screening
Randomization and Blinding
MCNS Intervention
MCNS Control
Weight Loss Intervention
Weight Loss Control
Monitoring Participant Adherence to the Administered Interventions
Data collection and Measures
Procedures and Training
Measures
| Measure | Screening | Baseline | 3-month | 6-month | 12-month |
|---|---|---|---|---|---|
| Demographics | x | ||||
| Medical history | x | ||||
| Anthropometry | |||||
| Height (cm) | x | ||||
| Weight (kg) | x | x | x | x | x |
| Blood pressure (mmHg) | x | x | x | x | x |
| Pulse (BPM) | x | x | x | x | x |
| Biological samples | |||||
| Blood | x | x | x | x | |
| Urine | x | x | x | x | |
| Cerebral hemodynamics | |||||
| Fasted | x | x | x | x | |
| Post-prandial | x | x | x | x | |
| Cognitive assessments | |||||
| Auditory Verbal Learning Test (AVLT) | x | x | x | x | |
| Controlled Oral Word Association Test (COWAT) | x | x | x | x | |
| Single Digit Modalities Test (SDMT) | x | x | x | x | |
| Stroop Interference Test | x | x | x | x | |
| Trails Making Test (A) | x | x | x | x | |
| Trails Making Test (B) | x | x | x | x | |
| NIH Toolbox (NIH-TB) | x | x | x | x | |
| Dietary | |||||
| Multi-pass 24-hour recall | x | x | x | x | |
| Questionnaires | |||||
| 36-Item Short Form Health Survey (SF-36) | x | x | x | x | |
| Adult Eating Behavior | x | x | x | x | |
| Center for Epidemiologic Studies Depression Scale (CES-D) | x | x | x | x | |
| Cognitive & Leisure Activity Scale (CLAS) | x | x | x | x | |
| Community Healthy Activities Model Programs for Seniors (CHAMPS) | x | x | x | x | |
| Factors Influencing Food Choice (FCQ) | x | x | x | x | |
| General Nutrition Knowledge Survey | x | x | x | x | |
| Sarason Social Support (SSQSR) | x | x | x | x | |
| Self-Regulation of Eating Behavior (SREBQ) | x | x | x | x | |
| Stigmatizing Situations Inventory | x | x | x | x | |
| Three-Factor Eating (TFEQ) | x | x | x | x | |
| Weight-Striving Stress Scale | x | x | x | x | |
| Yale Food Addiction Scale | x | x | x | x |
- Cognitive function (primary outcome). Assessments of cognitive function were derived from performance on well-established neuropsychological tests and the NIH-Toolbox cognitive module. All cognitive assessments were completed at baseline, 3 months, 6 months, and 12 months at 30 minutes postprandial. Five standardized scores from five tests were obtained and summed to yield a composite executive function z-score as the primary outcome. These tests include: Controlled Oral Word Association Test (COWAT),[70,71] Single Digit Modalities Test (SDMT),[72] Stroop Interference Test (Stroop),[73] Trails Making Test (TMTA, B).[74,75] The Auditory Verbal Learning Test (AVLT): Total Learning and Delayed Recall[76] and the NIH Toolbox (NIH-TB) will also be administered and were considered secondary outcomes. A detailed overview of the cognitive assessments is presented in Table 2. All cognitive assessments were audiotaped for quality control and proper coding of verbal tasks and were reviewed by a member of the research team.
| TEST | DOMAIN(S) ASSESSED | DESCRIPTION |
| Primary Outcomes | ||
| COWAT | Controlled response generation | Examines phonemic verbal fluency and response generation. Participants verbalize during 1-minute periods as many words as possible that begin with particular letters (e.g., H, O). The restriction of response set requires executive control and executive function for controlled response production. |
| SDMT | Working memory, focused attention, processing speed | Widely used and well standardized test speed and accuracy in the coding symbols associated with specific numbers is a highly sensitive tests of brain dysfunction. The final score is the total number of correctly entered symbols in 90 seconds. |
| Stroop | Executive inhibitory control, focused attention | Assesses the extent of slowing created by attentional interference created by the demand of naming colors that are discordant with the printed word of a different color. The score on the Color-Word interference trial is compared with scores on color word reading and color naming in the absence of interference. For each of the 3 tasks, scores are based on the number of colors correctly named in 45 seconds, with these scores computed to yield a Stroop Interference z-score. |
| TMT-A | Attention, speed of processing | Involves the use of a pencil to connect a series of numbers in ascending order that are distributed over a sheet of paper as quickly as possible. Completion time provides the performance measure that is converted to a z-score. |
| TMT-B | Attention and executive control – inhibition (set switching, processing speed) | Similar to Trail A, except that alternation of an ascending sequence between numbers and letters distributed over the page is required (e.g., 1-A-2-B…). The number-letter sequence is connected by pencil. Completion time provides the performance measure that is converted to a z-score. |
| Additional Outcomes | ||
| AVLT | Learning and memory | The AVLT is a verbal learning and memory test. A list of 15 words is presented to the participant over five trials with recall assessed immediately following each trial. Recall for these words is assessed after presentation of an interference list B after the five trials. Delayed recall of the first 15 word list is then assessed after a 15-minute interval. |
| NIH-TB | Fluid and crystalized cognitive function | The cognitive module of the NIH-TB was developed to assess fluid and crystalized cognitive functions via computerized (IPAD) administration. It takes 30-45 minutes to complete and contains seven primary tasks (Flanker Inhibitory Control and Attention Test, Dimensional Change Card Sort Test, List Sorting Test, Pattern Comparison Processing Speed Test, Picture Sequence Memory Test, Picture Vocabulary Test, and Oral Reading Test). |
- 2.
- Cerebral hemodynamics. Measures of cerebral blood flow (CBF) and oxygenation were collected at each study visit in fasted and two-to three-hours postprandial states. Microvascular CBF was measured using continuous-wave diffuse correlation spectroscopy (CW-DCS) equipped with a 785 nm laser source and four single-photon avalanche diode detectors, which provided a continuous index of blood flow (BFi).[77,78] A 3D-printed flexible sensing probe was designed with a short source-detector distance of 5 mm for scalp blood flow and two long distances of 25 and 30 mm for cerebral blood flow monitoring, which was connected to the DCS source and detectors and positioned on the subject’s forehead.[79,80,81] The DCS optical data were acquired at 150 MHz. On the opposite forehead, cerebral oxygenation was measured using near-infrared spectroscopy (NIRS), an established method which measures light attenuation due to absorption of hemoglobin to non-invasively monitor hemoglobin oxygen saturation in biological tissues.[82,83] This metric was also used as a surrogate measure of cerebral blood volume (CBV) changes. The NIRS was a battery-operated headband with source-detector distances of 8, 28, and 33 mm, made of 735 and 850 nm LED light sources and photodiode detectors on a flexible printed circuit board, as originally described.[84] The NIRS data were acquired at 266 Hz. Together, DCS and NIRS provide an array of cerebral hemodynamic biomarkers that uniquely characterize brain health and function. Respiratory pattern and EKG was recorded via Biopac. The acquired data were time-synchronized using the devices’ timestamps and common trigger signals.
- 3.
- Fasting duplicate measurements of weight were taken to ±0.1 kg at each study visit. Our standard protocol[85,86] requires the use of the same calibrated scale, and removal of shoes, outer clothing, and heavy items. Brachial systolic and diastolic blood pressure were measured after weight measurements, as an index of the effects of the supplements on cardiometabolic health. Three measurements were performed after a defined rest period, with the last 2 averaged.[86] An automatic blood pressure cuff was used, with cuff sizes based on each subject’s left arm circumference.
- 4.
- Biospecimens. Fasting blood samples (25 ml) were taken at baseline, 6, and 12 months, and processed for storage in our Clinical Laboratory Improvements Amendment (CLIA)-certified laboratory. Because of anticipated changes in blood glucose and insulin sensitivity,[87] HbA1c, fasting plasma glucose and fasting serum insulin levels were measured at each timepoint. Apolipoprotein E4 (ApoE4) genotypes also influence risk of AD and were measured in our core facility.[88,89] Fasting urine samples were also collected in order to evaluate adherence to supplement consumption by assessing catechin metabolites.
- 5.
- Self-reported health outcomes via validated questionnaires. Demographic variables and family history of dementia and AD were assessed at the start of the study and updated as relevant. In addition, health-related quality of life, functional activities, sleep, depression, eating behaviors, activity and activities of daily living were assessed, using NIH-recommended instruments when available.[90,91,92,93,94,95,96] A complete list of questionnaires is included in Table 1.
- 6.
- Dietary adherence. For dietary adherence, we used the multiple-pass interviewer-administered 24-hour dietary recall method.[97] In past studies, we have achieved 90% accuracy relative to gold-standard assessments with this method.[98] Three daily recalls were performed on random days by telephone at screening (to determine if plausible records can be obtained[99]) and these data were used as baseline data for enrollees. Three recalls were collected on random days after each visit at the 3-, 6- and 12-month timepoints. The collected data includes efforts to obtain both general dietary intake information for the period of collection and specific information relevant to this study (e.g., type of chocolate consumed, if any). The records will be analyzed to quantify daily nutrient intakes and intakes of nutrients of particular interest (cocoa polyphenols, DHA+EPA, % adequacy of micronutrients relative to Dietary Reference Intakes), using Nutrition Data System for Research software (Nutrition Coordinating Center, University of Minnesota, Version 2021 or latest). Information will be used to calculate a Healthy Eating Index score[100] and a MIND diet score,[24] which will be used as metrics for adherence to the dietary recommendations of the WL intervention.
Participant Rights and Safety
Power Calculations
Data Management
Statistical Analysis Plan
Cognition (Primary Outcome)
Cerebral Hemodynamics (Secondary Outcomes)
Time-Course Effects and Adherence (Exploratory Outcomes)
Predictors of Cognitive and Cerebral Hemodynamic Responses (Exploratory Outcomes)
Individual Cognitive Functions (Exploratory Outcomes)
Discussion
Funding Sources
Author Contributions
Data Availability Statement
Acknowledgments
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