Core Neuropsychological Measures for Obesity and Diabetes Trials: Initial Report

ATN blood biomarkers are related to digital cognitive assessment in type 1 diabetes

INTRODUCTION

Associations between amyloid-tau-neurodegeneration (ATN) plasma biomarkers and cognition have not been characterized in adults with type 1 diabetes (T1D).

METHODS

Using data from participants in the Glycemic Variability and Fluctuations in Cognitive Status in Adults with T1D (GluCog) study (N = 114), we evaluated associations between phosphorylated tau (pTau)181, pTau217, β-amyloid 42/40 ratio, glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) and self-administered digital cognitive tests, adjusting for age, sex, education, comorbidities (e.g., kidney disease), and glycemic indices.

RESULTS

Higher concentrations of pTau181 and GFAP were associated with slower responses on working memory tasks (pTau181: β = 0.261; p = 0.007; GFAP: β = 0.175, p = 0.036), and higher β-amyloid 42/40 ratio was associated with better vocabulary (β = 0.260, p = 0.009).

Discussion

Digital cognitive performance was associated with several ATN plasma biomarkers in T1D adults. Prospective studies are needed to understand the utility of these biomarkers in T1D.

Highlights

There is an increase in life expectancy for individuals with type 1 diabetes (T1D).Few studies investigate the relationship between T1D and neurodegeneration.We characterize the relation between ATN plasma biomarkers and cognitive function.Digital cognitive performance was associated with plasma biomarkers in T1D adults.

Episodic future thinking improves intertemporal choice and food choice in individuals with higher weight: A systematic review and meta-analysis

Episodic future thinking (EFT) strengthens self-regulation abilities by increasing the perceived value of long-term reinforcements and reducing impulsive choice in delay discounting tasks. As such, EFT interventions have the potential to improve dietary and eating-related decision-making in individuals with obesity or binge eating symptoms, conditions associated with elevated delay discounting. Here, we meta-analyzed evidence from 12 studies that assessed whether EFT interventions improve delay discounting and real-world food choice compared to control interventions. Included studies involved 951 adults with overweight or obesity (body mass index [BMI] ≥25). There were no studies involving participants with binge eating disorder. EFT intervention pooled effects were significant, improving delay discounting with a medium effect, g = 0.55, p < 0.0001, and subsequent food choice outcomes with a small effect, g = 0.31, p < 0.01. Notably, our review is the first to analyze mechanisms of effect in this population, demonstrating that improvements were greater when temporal horizons of EFT episodes were aligned with delay discounting tasks and more distant horizons predicted far-transfer to subsequent dietary and eating-related choices. Our findings thus show that EFT is an effective intervention for individuals with higher weight at risk of adverse health consequences.

Dynamic associations between glucose and ecological momentary cognition in Type 1 Diabetes

Type 1 diabetes (T1D) is a chronic condition characterized by glucose fluctuations. Laboratory studies suggest that cognition is reduced when glucose is very low (hypoglycemia) and very high (hyperglycemia). Until recently, technological limitations prevented researchers from understanding how naturally-occurring glucose fluctuations impact cognitive fluctuations. This study leveraged advances in continuous glucose monitoring (CGM) and cognitive ecological momentary assessment (EMA) to characterize dynamic, within-person associations between glucose and cognition in naturalistic environments. Using CGM and EMA, we obtained intensive longitudinal measurements of glucose and cognition (processing speed, sustained attention) in 200 adults with T1D. First, we used hierarchical Bayesian modeling to estimate dynamic, within-person associations between glucose and cognition. Consistent with laboratory studies, we hypothesized that cognitive performance would be reduced at low and high glucose, reflecting cognitive vulnerability to glucose fluctuations. Second, we used data-driven lasso regression to identify clinical characteristics that predicted individual differences in cognitive vulnerability to glucose fluctuations. Large glucose fluctuations were associated with slower and less accurate processing speed, although slight glucose elevations (relative to person-level means) were associated with faster processing speed. Glucose fluctuations were not related to sustained attention. Seven clinical characteristics predicted individual differences in cognitive vulnerability to glucose fluctuations: age, time in hypoglycemia, lifetime severe hypoglycemic events, microvascular complications, glucose variability, fatigue, and neck circumference. Results establish the impact of glucose on processing speed in naturalistic environments, suggest that minimizing glucose fluctuations is important for optimizing processing speed, and identify several clinical characteristics that may exacerbate cognitive vulnerability to glucose fluctuations.

Glycemic Variability and Fluctuations in Cognitive Status in Adults With Type 1 Diabetes (GluCog): Observational Study Using Ecological Momentary Assessment of Cognition

BACKGROUND

Individuals with type 1 diabetes represent a population with important vulnerabilities to dynamic physiological, behavioral, and psychological interactions, as well as cognitive processes. Ecological momentary assessment (EMA), a methodological approach used to study intraindividual variation over time, has only recently been used to deliver cognitive assessments in daily life, and many methodological questions remain. The Glycemic Variability and Fluctuations in Cognitive Status in Adults with Type 1 Diabetes (GluCog) study uses EMA to deliver cognitive and self-report measures while simultaneously collecting passive interstitial glucose in adults with type 1 diabetes.

OBJECTIVE

We aimed to report the results of an EMA optimization pilot and how these data were used to refine the study design of the GluCog study. An optimization pilot was designed to determine whether low-frequency EMA (3 EMAs per day) over more days or high-frequency EMA (6 EMAs per day) for fewer days would result in a better EMA completion rate and capture more hypoglycemia episodes. The secondary aim was to reduce the number of cognitive EMA tasks from 6 to 3.

METHODS

Baseline cognitive tasks and psychological questionnaires were completed by all the participants (N=20), followed by EMA delivery of brief cognitive and self-report measures for 15 days while wearing a blinded continuous glucose monitor. These data were coded for the presence of hypoglycemia (<70 mg/dL) within 60 minutes of each EMA. The participants were randomized into group A (n=10 for group A and B; starting with 3 EMAs per day for 10 days and then switching to 6 EMAs per day for an additional 5 days) or group B (N=10; starting with 6 EMAs per day for 5 days and then switching to 3 EMAs per day for an additional 10 days).

RESULTS

A paired samples 2-tailed t test found no significant difference in the completion rate between the 2 schedules (t17=1.16; P=.26; Cohen dz=0.27), with both schedules producing >80% EMA completion. However, more hypoglycemia episodes were captured during the schedule with the 3 EMAs per day than during the schedule with 6 EMAs per day.

CONCLUSIONS

The results from this EMA optimization pilot guided key design decisions regarding the EMA frequency and study duration for the main GluCog study. The present report responds to the urgent need for systematic and detailed information on EMA study designs, particularly those using cognitive assessments coupled with physiological measures. Given the complexity of EMA studies, choosing the right instruments and assessment schedules is an important aspect of study design and subsequent data interpretation.

Enhanced sweet taste perception in obesity: Joint analysis of gustatory data from multiple studies

Introduction

While sweet taste perception is a potential determinant of feeding behavior in obesity, the supporting evidence is inconsistent and is typically associated with methodological limitations. Notably, possible associations between sweet taste perception and measures of food reward remain undetermined.

Materials and methods

We conducted a cross-sectional analysis comparing 246 individuals with severe obesity and 174 healthy volunteers using a validated method for taste perception assessment. We included gustatory variables, namely intensity and pleasantness ratings of sour, salt, sweet, and bitter tastants, and taste thresholds assessed by electrogustometry. Reward-related feeding behavior, including hedonic hunger, food addiction, feeding behavior traits, and acceptance of foods and alcohol, was evaluated using self-rated scales for comparison with gustatory measures.

Result

In logistic regressions adjusted for age, gender, educational level, and research center, we found that a greater likelihood of belonging to the obesity group was associated with higher sweet intensity ratings (OR = 1.4, P = 0.01), hedonic hunger, food addiction symptoms, restrained and emotional eating (1.7 < OR ≤ 4.6, all P ≤ 0.001), and lower alcohol acceptance (OR = 0.6, P = 0.0002). Using principal component analysis, we found that while hedonic hunger, food addiction, and emotional eating were strongly interrelated, they were not associated with sweet intensity perception that, in turn, had a closer relationship with alcohol acceptance and restrained eating.

Conclusion

We found that individuals with obesity report higher sweet taste intensity ratings than healthy controls. Furthermore, while psychological measures of reward-related feeding behavior assess a common construct, sweet intensity perception may represent a different obesity-related dimension.

Dietary adaptation for weight loss maintenance at Yale (DAWLY): Protocol and predictions for a randomized controlled trial

Background

Current therapies for obesity treatment are effective at producing short-term weight loss, but weight loss maintenance remains a significant challenge. Here we investigate the impact of pre-intervention dietary fat intake on the efficacy of a dietary supplement to support weight loss maintenance. Preclinical work demonstrates that a vagal afferent pathway critical for sensing dietary lipids is blunted by a high-fat diet (HFD), resulting in a reduced preference for a low-fat emulsion and severe blunting of the dopamine (DA) response to the gastric infusion of lipids. Infusion of the gut lipid messenger oleoylethanolamide (OEA), which is also depleted by HFD, immediately reverses this DA blunting and restores preference for the low-fat emulsion. Studies of OEA supplementation for weight loss in humans have had limited success. Given the strong effect of HFD on this pathway, we designed a study to test whether the efficacy of OEA as a weight loss treatment is related to pre-intervention habitual intake of dietary fat.

Methods/Design

We employed a randomized, double-blind, placebo-controlled trial in which 100 adults with overweight/obesity (OW/OB) were randomized to receive either OEA or placebo daily for 16 months. Following a baseline evaluation of diet, metabolic health, adiposity, and brain response to a palatable an energy dense food, participants in both groups underwent a 4-month behavioral weight loss intervention (LEARN®) followed by a 1-year maintenance period. The study aims are to (1) determine if pre-intervention dietary fat intake moderates the ability of OEA to improve weight loss and weight loss maintenance after a gold standard behavioral weight loss treatment; (2) identify biomarkers that predict outcome and optimize a stratification strategy; and (3) test a model underlying OEA's effectiveness.

Discussion

Focusing on interventions that target the gut-brain axis is supported by mounting evidence for the role of gut-brain signaling in food choice and the modulation of this circuit by diet. If successful, this work will provide support for targeting the gut-brain pathway for weight loss maintenance using a precision medicine approach that is easy and inexpensive to implement.

Clinical Trial Registration

[www.ClinicalTrials.gov], identifier [NCT04614233].

A Neuroeconomics Approach to Obesity

Obesity is a heterogeneous condition that is affected by physiological, behavioral, and environmental factors. Value-based decision making is a useful framework for integrating these factors at the individual level. The disciplines of behavioral economics and reinforcement learning provide tools for identifying specific cognitive and motivational processes that may contribute to the development and maintenance of obesity. Neuroeconomics complements these disciplines by studying the neural mechanisms underlying these processes. We surveyed recent literature on individual decision characteristics that are most frequently implicated in obesity: discounting the value of future outcomes, attitudes toward uncertainty, and learning from rewards and punishments. Our survey highlighted both consistent and inconsistent behavioral findings. These findings underscore the need to examine multiple processes within individuals to identify unique behavioral profiles associated with obesity. Such individual characterization will inform future studies on the neurobiology of obesity as well as the design of effective interventions that are individually tailored.