a randomized controlled trial

학위논문(박사) -- 서울대학교대학원 : 의과대학 의과학과, 2021.8. 최형진.Background - Since lifestyle modification is the cornerstone of the obesity treatment, digital therapeutics (DTx) became one of the compelling and easily accessible treatment modalities. Objective - This research proposes to validate the treatment efficacy, understand behavioral changes by eating behavioral analysis, identify the predictive digital phenotypes for engagement and clinical outcomes, and examine genetic precision medicine of a novel digital therapeutic for obesity (dCBT-O). Method – This was an open-label, active-comparator, randomized controlled trial. Seventy female participants with body mass index (BMI) scores above 24kg/m² and no clinical problems besides obesity were randomized into experimental and control groups. The experimental group (dCBT-O group; 45 participants) was connected with a therapist intervention using a digital healthcare service that provided daily feedback and assignments for 8 weeks. The control group (25 participants) also used the digital healthcare service but practiced self-care without therapist intervention. Regarding the validating treatment efficacy, the primary outcomes of this study were objectively measured: weight in kg as well as other body compositions at 0, 8, and 24 weeks. Also, several eating behavioral phenotypes were assessed by buffet test-meal and food diary in app to examine the healthy behavioral change. Regarding the predictors for treatment efficacy, multidimensional digital phenotypes within time-series data were analyzed by elastic net regression method and obesity-related SNPs were genotyped from dCBT-O group. Result – Both weight (–3.1%, SD 4.5, vs –0.7%, SD 3.4; p = 0.036) and fat mass (–6.3%, SD 8.8, vs –0.8%, SD 8.1; p = 0.021) reduction at 8 weeks in the dCBT-O group were significantly higher than in the control group. Applying the machine learning approach, sixteen types of digital phenotypes (i.e., lower intake of high calorie food and evening snack, higher interaction frequency with mentors) predicted engagement rates, thirteen different digital phenotypes (i.e., lower intake of high calorie food and carb, higher intake of low calorie food) predicted the short-term weight change, and eight measures of digital phenotypes (i.e., lower intake of carb and evening snack, higher motivation) predicted the long-term weight change. The dCBT-O was also successful in promoting healthy eating behaviors that led to physiological and psychological adjustment for the metabolic mechanisms and consequences of healthy eating behavior. Lastly, CETP and APOA2 SNPs were significantly associated with the change in BMI (p = 0.028 and p = 0.005, respectively) at 24 weeks and eating behavioral phenotypes (p = 0.007 for healthy diet diversity and p = 0.036 for healthy diet proportion, respectively), the clinical efficacy markers of this study. Conclusion – These findings confirm that the multidisciplinary approach via digital modalities enhances the clinical efficacy of digital-based interventions for obesity. Moreover, it contributes to better understand the mechanisms of human eating behavior related to weight control. This line of research may shed light on the development of advanced prevention and personalized digital therapeutics.비만은 대표적인 생활습관 질병으로 알려져 있다. 따라서, 효과적인 비만 치료를 위해서는 다차원적인 치료적 접근이 중요시되는데, 디지털 치료제(Digital Therapeutics; DTx)는 이러한 접근에 최적화 되어있다. 본 연구의 목적은 새로 개발한 비만 디지털 치료제의 효과를 임상적 지표들과 섭식 행동 표현형들의 변화를 기반으로 검증하며, 치료적 순응도와 효과성을 예측할 수 있는 디지털 표현형들과 유전형들을 탐색하는 것이다. 본 연구에서는 BMI 24 이상, 기타 임상적인 증상을 보이지 않는 70명의 2-30대 여성들을 대상으로 대조군 대비 비만 디지털 치료제군(Digital Therapeutic for Obesity; dCBT-O군)에 1:2 비율의 무작위배정 임상시험을 시행하였다. dCBT-O군의 비만 치료는 임상심리학 전공 및 디지털 헬스케어 전문가가 8주 동안 진행하였으며, 24주차에는 치료 후 경과에 대한 평가를 실시하였다. 비만 디지털 치료제 효과 검증의 주요 지표는 체중을 비롯한 다양한 신체 계측 지표들의 변화이다. 이차 지표는 뷔폐실험과 모바일 어플리케이션 내 식단기록에서 수집된 섭식행동 표현형들을 기반으로 건강한 섭식행동 변화이다. 치료 순응도 및 효과 예측 인자들을 발굴하기 위해서는 다차원적인 시계열 디지털 표현형들을 머신러닝 기법으로 분석하였다. 그리고, 치료 반응 수준을 예측하는 유전형들을 찾기 위해 단일염기다형(Single Nucleotide Polymorphisms; SNP) 분석을 시행하였다. 본 연구의 주요 결과로 첫째, 8주간 치료 직후 dCBT-O군의 체중 변화가 대조군의 체중 변화에 비해 유의미하게 감량하였으며, 치료 종료 후 24주차도 체중이 감량 및 유지되었다. 둘째, dCBT-O군의 섭식행동이 대조군의 섭식행동에 비해 유의미하게 건강한 섭식행동으로 증진되었다. 셋째, 머신러닝 분석의 결과 16가지 디지털 표현형들이 치료적 순응도를 예측하고, 13가지 디지털 표현형들이 단기적인 치료효과를 예측하며, 8가지 디지털 표현형들이 장기적인 치료효과를 예측하였다. 마지막으로, CETP와 APOA2 SNP 유전형들이 신체계측 변화와 섭식행동변화와 유의미한 상관을 보였다. 본 연구는 디지털 기술을 활용한 다학제적인 접근이 비만 디지털 치료제의 임상 효과를 향상시킨다는 것을 보여준다. 또한 다차원적인 분석을 통해 체중 조절과 관련된 인간의 섭식 행동의 메커니즘을 더 잘 이해하는 데 기여한다. 본 연구는 첨단 예방의학과 정밀의학을 위한 디지털 치료제 개발에 중요한 패러다임을 제시할 것이다.Chapter 1. Introduction 1 Part I. Validating the treatment efficacy and finding its predictive markers: development of a dCBT-O 6 Part II. Eating behavioral analysis using buffet test-meal and food diary in app: understanding human eating behavior change by dCBT-O 8 Part III. Digital phenotyping using machine-learning analysis: identifying a predictive model for engagement in application and clinical outcomes of dCBT-O 11 Part IV. Genetic analysis for predicting the clinical responses: genetic precision medicine of dCBT-O 14 Chapter 2. Method 19 Chapter 3. Results 40 Chapter 4. Discussion 75 Perspectives A. Main issues related to DTx for obesity and eating behavior problems 91 Perspectives B. Limitations of DTx being applied in the clinics 96 Perspectives C. Future perspectives and recommendations 96 Chapter 5. Conclusion 99 Bibliography 100 Abstract in Korean 118 Acknowledgement 120박

Qualifying Factors That Predict Weight Loss Success Within Diet Interventions

Evidence-based diet strategies lead to weight loss for some, while for others, the same diet approach could result in trivial weight loss or even in weight gain. This prompts the underlying research question: what factors predict that a given diet strategy will be efficacious for some, but not for others? This research was a secondary analysis of clinical weight loss studies to determine which factors influence an individual’s weight loss success for three diet intervention strategies: low-carbohydrate, low-fat, and low-calorie. A combination of physiological, psychological, behavioral, and dietary factors was evaluated for each diet study. Multiple linear regression and logistic regression models were used to estimate significance of variables and to what extent they influence weight loss. For the low-carbohydrate group, race, body fat percentage, and fasting glucose at baseline were the most significant predictors (p \u3c 0.05). For the low-fat group, income, leptin, education, low-density lipoprotein, and dietary adherence at baseline were the most significant predictors (p \u3c 0.05). For the low-calorie group, age, eating behavior, total sugar consumption, and leptin at baseline (p \u3c 0.05) were the most significant predictors. Completion status was the most important predictor of weight loss regardless of diet type. Understanding which of these individual physiological, behavioral, and environmental factors interact with specific dietary strategies to influence weight loss can be used to inform personalized approaches to diet interventions that are more likely to lead to successful weight loss and reduction of cardiometabolic disease risk

A laboratory-based study of mood and eating behavior in overweight children

Loss of control over eating refers to the sense that one cannot control what or how much one is eating. Loss of control eating is prevalent among overweight children and is associated with psychosocial impairment. Self-report data suggest that pediatric loss of control eating may be related to the experience of aversive emotions, with investigators theorizing that loss of control eating is a maladaptive means of alleviating negative mood. However, these data need to be substantiated using more objective methodology. The current study utilized a feeding laboratory paradigm to further explore the relation between mood and eating in 46 overweight girls with: LOC+; n = 23) and without: LOC-; n = 23) loss of control eating problems. Girls underwent two separate experimental mood manipulations during which they viewed either a sad or neutral film segment. Following each mood induction, girls ate ad libitum from a multi-item meal. LOC+ girls did not consume more food, as measured in either kilocalories or grams, after a sad mood induction relative to a neutral mood induction. However, LOC+ girls consumed a greater percentage of kilocalories from fat after a sad mood induction relative to a neutral mood induction. Negative mood on the day of the sad mood induction significantly predicted the likelihood of LOC+ girls reporting loss of control during the subsequent test meal. Contrary to expectation, there was a trend towards an interactional effect of loss of control status and mood condition on food intake in grams, such that LOC- participants tended to consume a larger volume of food in the sad condition relative to the neutral condition, whereas LOC+ girls ate a similar volume of food regardless of mood condition. Mood improvements subsequent to the sad condition test meal were observed in the full sample. Results suggest that emotional eating episodes in children reporting loss of control eating problems may be best characterized by a subjective sense of loss of control as opposed to consumption of large amounts of food. Interventions addressing affect regulation and coping in at-risk youth may help minimize the negative sequelae associated with pediatric loss of control eating

Nutrient intake in college students in a Midwestern regional university compared to the recommended dietary guidelines

The prevalence of obesity is problematic in the United States. The objectives of the present study were to determine the extent of obesity in students studying at Eastern Michigan University and to evaluate their diet quality. Body Mass Index (BMI) of students (19-30 years, n=100) was measured from self-reported heights and weights as a benchmark of their weight category. Intakes of total energy (kilocalories), macronutrients and key micronutrients were assessed from three-day food diaries maintained by participants and compared with the Dietary Reference Intake Standards. Results indicated that 4% of EMU students were underweight, 52% were within a normal weight range, 28% were overweight, and 16% were obese. No linear relationships existed between BMI and energy intake. Consumption of most nutrients, except sodium were within the Recommended Dietary Guidelines. Since 44% of students at EMU are overweight or obese, a health promotion campaign aimed at weight control is warranted

Gut-brain interactions affecting metabolic health and central appetite regulation in diabetes, obesity and aging

The central aim of this thesis was to study the effects of gut microbiota on host energy metabolism and central regulation of appetite. We specifically studied the interaction between gut microbiota-derived short-chain fatty acids (SCFAs), postprandial glucose metabolism and central regulation of appetite. In addition, we studied probable determinants that affect this interaction, specifically: host genetics, bariatric surgery, dietary intake and hypoglycemic medication.First, we studied the involvement of microbiota-derived short-chain fatty acids in glucose tolerance. In an observational study we found an association of intestinal availability of SCFAs acetate and butyrate with postprandial insulin and glucose responses. Hereafter, we performed a clinical trial, administering acetate intravenously at a constant rate and studied the effects on glucose tolerance and central regulation of appetite. The acetate intervention did not have a significant effect on these outcome measures, suggesting the association between increased gastrointestinal SCFAs and metabolic health, as observed in the observational study, is not paralleled when inducing acute plasma elevations.Second, we looked at other determinants affecting gut-brain interactions in metabolic health and central appetite signaling. Therefore, we studied the relation between the microbiota and central appetite regulation in identical twin pairs discordant for BMI. Second, we studied the relation between microbial composition and post-surgery gastrointestinal symptoms upon bariatric surgery. Third, we report the effects of increased protein intake on host microbiota composition and central regulation of appetite. Finally, we explored the effects of combination therapy with GLP-1 agonist exenatide and SGLT2 inhibitor dapagliflozin on brain responses to food stimuli

The associations between sugar sweetened beverage intake, satiety, and metabolic health in minority youth

Non-Hispanic Black (NHB) and Hispanic children are at an increased risk of obesity and metabolic disease in the United States. Increasingly obesity is viewed as a multifaceted phenotype, beyond simply excess body weight. Research indicates that homeostatic mechanisms as well as hedonic systems are altered in obese individuals. The objective of this study was to examine how sugar sweetened beverage (SSB) intake, a highly modifiable dietary behavior, impacts both metabolic health and hedonic perceptions. This study is made up of three cross sectional analyses: the first two are secondary analyses of data from the University of Southern California, and the third was preformed at the University of Texas at Austin. The first examined the relationship between SSB intake, perceived hunger and satiety, and endocrine biomarkers in overweight and obese NHB and Hispanic adolescents (14-17 y). SSB intake of two servings or more per day was associated with decreased satiety and suppressed ghrelin compared to subjects that consumed one or less servings of SSB. The second examined the association between SSB intake, visceral fat accumulation (VAT), and cortisol awakening response (CAR) in a similar sample of 60 overweight and obese NHB and Hispanic adolescents (14-17y). SSB intake of two servings or more was associated with increased VAT and increased CAR compared to subjects that consumed one or less servings of SSB. The third examined the effect of SSB intake on reward pathways in the brain using functional magnetic resonance imaging (fMRI), as well as how free-living dietary and dietary intake at an ad libitum meal impacts hunger and metabolic biomarkers in 41 overweight and obese Hispanic children (7-10 y). Although analysis of the fMRI data was uninterruptable, increased hunger and decreased satiety at an ad libitum meal was related to added sugar intake greater than 10% of the subject’s daily calories. In adolescents, SSB intake is associated with decreased feelings of fullness and an unfavorable metabolic profile. In young children, added sugar intake is associated with appetite independent of homeostatic factors.Nutritional Science

Precision nutrition : a review of personalized nutritional approaches for the prevention and management of metabolic syndrome

The translation of the growing increase of findings emerging from basic nutritional science into meaningful and clinically relevant dietary advices represents nowadays one of the main challenges of clinical nutrition. From nutrigenomics to deep phenotyping, many factors need to be taken into account in designing personalized and unbiased nutritional solutions for individuals or population sub-groups. Likewise, a concerted effort among basic, clinical scientists and health professionals will be needed to establish a comprehensive framework allowing the implementation of these new findings at the population level. In a world characterized by an overwhelming increase in the prevalence of obesity and associated metabolic disturbances, such as type 2 diabetes and cardiovascular diseases, tailored nutrition prescription represents a promising approach for both the prevention and management of metabolic syndrome. This review aims to discuss recent works in the field of precision nutrition analyzing most relevant aspects affecting an individual response to lifestyle/nutritional interventions. Latest advances in the analysis and monitoring of dietary habits, food behaviors, physical activity/exercise and deep phenotyping will be discussed, as well as the relevance of novel applications of nutrigenomics, metabolomics and microbiota profiling. Recent findings in the development of precision nutrition are highlighted. Finally, results from published studies providing examples of new avenues to successfully implement innovative precision nutrition approaches will be reviewed

Quantitative approaches to energy and glucose homeostasis: machine learning and modelling for precision understanding and prediction

Obesity is a major global public health problem. Understanding how energy homeostasis is regulated, and can become dysregulated, is crucial for developing new treatments for obesity. Detailed recording of individual behaviour and new imaging modalities offer the prospect of medically relevant models of energy homeostasis that are both understandable and individually predictive. The profusion of data from these sources has led to an interest in applying machine learning techniques to gain insight from these large, relatively unstructured datasets. We review both physiological models and machine learning results across a diverse range of applications in energy homeostasis, and highlight how modelling and machine learning can work together to improve predictive ability. We collect quantitative details in a comprehensive mathematical supplement. We also discuss the prospects of forecasting homeostatic behaviour and stress the importance of characterizing stochasticity within and between individuals in order to provide practical, tailored forecasts and guidance to combat the spread of obesity

The effects of carbohydrates on mood and eating behaviour

Some central issues from the literature on the psychophysiological effects of carbohydrate (with protein and fat as comparators) on humans are reviewed and various methodological issues are discussed. From the review chapters the main questions that emerged were: 1. Does carbohydrate, in the form of sucrose alter mood state in humans? 2. Does sucrose increase or delay hunger and subsequent food intake? 3. Does carbohydrate intake in the form of sucrose induce carbohydrate-specific hunger or carbohydrate craving? 4. Can the obese and non-obese regulate nutrient intake physiologically when cognitive cues are held constant? 5. Can humans compensate in the short-term after a sucrose preload? From these central issues a series of experiments was conducted on obese and non- obese adults where it was found that: 1. When administered blind the ingestion of sucrose did not have any significant influence on mood state in either obese or non-obese subjects. This lack of effect suggests a weak relationship between carbohydrate intake and mood, at least when moderate size preloads are given to obese and normal individuals. 2. When cognitive factors are held constant in the laboratory and preloads are administered blind, sucrose can delay hunger and subsequent food intake in both obese and normal-weight subjects in a natural environment. This is taken to be due to physiological regulation in both obese and non-obese individuals. 3. Although the delay in eating suggests some form of physiological regulation, there was no evidence of change in size of the subsequent meal. 4. There was no evidence that carbohydrate in the form of sucrose led to carbohydrate craving or increased hunger for carbohydrate-rich foods in any way. This applies to both obese and non-obese subjects. It is concluded that physiological mechanisms operate effectively in humans when psychological factors are controlled. Compensatory processes, however, do not seem to operate as effectively in the short-term. From these findings it may be argued that the obese are no more or no less responsive to internal signals than normal. It may also be argued that if sugar intake has adverse effects on hunger (i.e. carbohydrate- craving, increased hunger) then such effects are more likely to be caused by psychological factors, rather than to any physiological effects. Although there remains little doubt that nutrients do influence mood and behaviour, improvement in methodology and more elaborate methods of measuring changes in behaviour are required