Conditions: Obesity
Keywords: Pharmacological Obesity Management Individualized
Allocation: RANDOMIZED | Intervention model: PARALLEL
Enrollment: 193
Healthy volunteers: no

Brief summary:
The researchers are trying to identify the specific characteristics (phenotypes) that may be useful to help select the right medication for weight loss.

Detailed description:
All participants will be phenotype and participants will randomized to randomly assigned medications vs phenotype guided medications for obesity. All participants will receive a standard intense lifestyle intervention.All participants will be seen at 4 and 12 weeks. At the 12-week visit, participants will be unblinded to their "obesity-related phenotype" and they could contact their physician to continue a FDA-approved medication as part of clinical care. Study team will prospectively follow the patients' weight, waist circumference and use of obesity medications every 3 months for 1 year.

Arms:
arm 1: Phenotype-guided pharmacotherapy, which includes Phentermine-Topiramate, Liraglutide, Naltrexone/bupropion or Phentermine plus Exercise arm 2: Randomly assigned pharmacotherapy, which includes Phentermine-Topiramate, Liraglutide, Naltrexone/bupropion or Phentermine

Interventions: intervention 1: Phentermine-Topiramate intervention 2: Liraglutide intervention 3: Naltrexone/bupropion intervention 4: Phentermine
Intervention descriptions: intervention 1: Extended Release at dose of 7.5/46 mg oral daily intervention 2: dose of 3 mg subcutaneous daily intervention 3: Oral naltrexone extended-release/bupropion extended-release at dose of 32/360 mg oral daily (divided in 2 tables in morning and 2 tablets in evening) intervention 4: 15-37.5 mg oral daily

Protocol document:
Prot_SAP_001.pdf: 
 
 
Individualized Pharmacological Approach to 
Obesity Management based on Obesity 
Phenotypes: A Randomized Clinical Trial 
(PHENO-MEDs trial) 
 
NCT03374956 
 
18MAY2020 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 1 of 28 
 
PROTOCOL  18May2020 
Individualized Pharmacological Approach to Obesity Management based on Obesity Phenotypes: A Randomized 
Clinical Trial (PHENO-MEDs trial) 
Co-Principal Investigators:    
• 
Andres Acosta M.D., Ph.D., Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, 
Rochester, MN;  
• 
Michael Camilleri, M.D., Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, 
Rochester, MN 
 
Co-Investigator:    
• 
Phillip Schulte, Ph.D., Division of Biomedical Statistics & Informatics, Department of Health Sciences Research, 
Mayo Clinic, Rochester, MN.   
• 
Duane Burton, M.S. Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, 
Rochester, MN   
• 
Manpreet Mundi, M.D., Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, Mayo 
Clinic, Rochester, MN   
• 
John D. Port M.D., Ph.D. Department of Diagnostic Radiology, Mayo Clinic, Rochester, MN. 
• 
Maria Daniela Hurtado Andrade, Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, 
Mayo Clinic, Rochester, MN   
Research Fellow:  
• 
Gerardo Calderon, M.D., Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, 
Rochester, MN 
• 
Daniel Gonzalez-Izundegui, M.D., Division of Gastroenterology and Hepatology, Department of Medicine, Mayo 
Clinic, Rochester, MN 
• 
Maria Laura Ricardo-Silgado, Division of Gastroenterology and Hepatology, Department of Medicine, Mayo 
Clinic, Rochester, MN 
• 
Angel A Campos-Rodriguez Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, 
Rochester, MN 
 
Coordinator:    
 
• 
MN   
• 
Irene Busciglio, B.S. Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, 
Rochester, MN   
• 
Linh Tran, Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, Rochester, MN 
• 
Megan Schaefer, Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, 
Rochester, MN 
IRB approved: 17-003449 
 
 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 2 of 28 
 
Individualized Pharmacological Approach to Obesity Management based on Obesity Phenotypes: A Randomized 
Clinical Trial (PHENO-MEDs trial) 
Table of Contents 
ABSTRACT 
3 
BACKGROUND 
5 
TREATMENT FOR OBESITY: 
5 
PHARMACOTHERAPY 
6 
PHENTERMINE-TOPIRAMATE EXTENDED RELEASE: 
6 
LORCASERIN (BELVIQ®): THE SECOND MEDICATION APPROVED BY THE FDA IN 2012 FOR CHRONIC WEIGHT MANAGEMENT IS LORCASERIN[ 
7 
ORAL NALTREXONE EXTENDED-RELEASE/BUPROPION EXTENDED-RELEASE 
7 
LIRAGLUTIDE (SAXENDA®) 
7 
PHARMACOGENOMICS 
8 
PRELIMINARY DATA 
9 
GASTROINTESTINAL TRAITS (PHENOTYPES) ASSOCIATED WITH OBESITY 
9 
OBESITY PHENOTYPES TO PREDICT WEIGHT LOSS RESPONSE: 
9 
HYPOTHESIS AND AIMS 
17 
SIGNIFICANCE 
17 
RESEARCH PLAN 
18 
STUDY DESIGN: 
18 
RANDOMIZATION AND ALLOCATION 
18 
SELECTION PARTICIPANTS 
19 
ANTHROPOMETRICS AND PHENOTYPE STUDIES 
19 
STANDARD OF CARE: 
22 
INTENSE LIFESTYLE INTERVENTION AND BEHAVIORAL TREATMENT 
22 
PHARMACOTHERAPY FOR OBESITY 
22 
GENERAL PRINCIPLES OF STATISTICAL ANALYSES 
24 
ANTICIPATED RESULTS AND SIGNIFICANCE: 
25 
POTENTIAL PITFALLS, PRECAUTIONS TAKEN, AND ALTERNATIVE STRATEGIES: 
25 
REFERENCE: 
26 
 
 
 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 3 of 28 
 
ABSTRACT  
Introduction: Obesity prevalence continues to increase worldwide[7] and, in the United States, 69% of adults are 
overweight or obese[8]. Despite advances in understanding of aspects of obesity pathophysiology, weight loss with 
current treatments including diet, exercise, medications, endoscopy and surgery is highly variable [9]. However, there 
are usually great responders to each therapy, specifically “responders” to medications can lose as much weight and with 
less side effects than bariatric surgery. These individuals – the responders – can benefit from significant weight loss 
(>15% total body weight loss) which is known to reduce all-cause cardiovascular mortality and morbidity. With the 
current approach with pharmacotherapy, less than 35% of patients will lose more than 10% of body weight. Additionally, 
the high variability in weight loss response has resulted in a poor market penetrance by new medications, devices and 
surgery. Clearly the one-treatment-fits all approach is not working and obesity management beyond diet and behavioral 
therapy continues to be a hit-or-miss intervention. One approach has been advocated where physicians select 
pharmacotherapy based on potential side effect and patient comorbidities [10], instead of choosing the right drug for 
the right patient based on its pathophysiology. To achieve the goal of individualizing treatment for obesity, it is essential 
to identify the best responders to each intervention, and hence maximize their weight loss.  Recently, we acquired 
preliminary data to identify predictors of weight loss using gastrointestinal and behavioral traits (phenotypes) [3]. 
Obesity can be sub-classified based on specific phenotypes in satiation (21%), gastric capacity (15%), behavioral 
(13%), gastric sensorimotor (11%) factors and others (40%)[3]. This obesity sub-classification may stratify patients for  
weight loss  pharmacotherapy or bariatric endoscopy [3, 11-13]. Using this classification, the effect on weight loss of 
Phentermine-topiramate ER [3], and exenatide 5µg [11]  can be enhanced, and the marked effect of Liraglutide 3mg on 
gastric emptying suggests it may be even more efficacious in patients with baseline acceleration of gastric emptying  
[11]. However, the results with Phentermine-topiramate ER [3], and exenatide 5µg [11] were determined in post-hoc 
analysis and each study was done independently. Thus, the identification of the obesity phenotype at baseline to guide 
obesity pharmacotherapy has not yet been tested and the outcome is unknown in the clinical setting. Thus, there is a 
critical need to study the weight loss outcome using obesity phenotypes to guide therapy for obesity.  
We hypothesize that the identification of the obesity phenotype at baseline to guide obesity pharmacotherapy 
will enhance the weight loss response rate (i.e. percentage of patient with weight loss higher than 10% at 12 weeks).  
Aim: To compare the weight loss response to phenotype-guided pharmacotherapy vs. control therapy (not guided by 
baseline phenotype) in patients with obesity and an abnormal obesity-related phenotype. 
-Sub-aim 1: to study the effect of phenotype-guided pharmacotherapy in brain blood flow and gut mucosal changes.  
Methods:  
Design: In a 12 week, randomized, double-blinded, active controlled, with open-label extension trial of 250 participants 
with obesity; we will compare the weight loss response rate to obesity-phenotype-guided pharmacotherapy 
(intervention) vs. non-phenotype guided (randomly selected) pharmacotherapy (control) in patients with obesity and an 
abnormal obesity-related phenotype. 
  
Baseline Phenotype: All 250 participants will be phenotype:  
a) The DEXA scan (dual energy x-ray absorptiometry) will measure body composition.  
b) Resting energy expenditure:  
c) Gastric emptying (GE) of solids by scintigraphy 
d) Appetite (hunger level) by visual analog score fasting and after standard meal for GE and prior to Satiation test  
e) Satiation by ad-libitum buffet meal to measure total caloric intake and macronutrient distribution in the chosen 
food 
f) Satiety will be measured in length of time of fullness at Ad-libitum meal  
g) Self-administered questionnaires assessing affect, physical activity, attitudes, body image, and eating behavior; 
h) Plasma gastrointestinal hormones (Total and active Ghrelin, GLP-1, CCK, PYY and bile acids) by RIA 
i) 
Targeted Metabolomics 
j) 
Blood DNA stored 
k) Stool sample stored   
l) 
Saliva samples stored 
m) Flexible sigmoidoscopy and biopsies of left colon for mRNA, DNA, protein studies 
n) Pseudo-continuous arterial spin labeling (pCASL) functional brain MRI study paradigm 
 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 4 of 28 
 
Medication selection by a non-study pharmacist will be randomized and double blinded (physician, study team and 
participant) according to the FDA-approved medicine suggested by the phenotype or to another FDA-approved medicine 
not suggested by the phenotype.   
Follow-up: All participants will be seen at 4 and 12 weeks (+/- 4 days) (current standard of practice). All participants will 
receive standard intense lifestyle interventions, which consists of one visit with CRTU registered dietitian. At 10 weeks 
(+/- 2 weeks) of treatment, participants will have a repeat flexible sigmoidoscopy and a pCASL functional brain MRI 
study paradigm. At the 12-week visit, participants will be unblinded to their “obesity-related phenotype” and they could 
contact their physician to discuss continuation of a FDA-approved medication as clinically indicated and recommended 
by their physician. Study team will prospectively follow the patients’ weight and waist circumference, as well as any 
pharmacotherapy followed for obesity every 3 months for 1 year.  
Primary endpoint: Total Body Weight Loss, kg (defined as weight changed from baseline to 12 weeks) in the obesity 
phenotype-guided pharmacotherapy (intervention) vs. the randomly assigned pharmacotherapy (control) group.  
The secondary end points will be percentage of responders (defined as number of participants who loss 5% or more of 
total body weight) compared to baseline in the obesity phenotype guided pharmacotherapy (intervention) group vs. 
standard of care at 4 and 12 weeks; percentage of responders with at least 10 and 15% at 12 weeks, and 10% at 6 
months and 12 months; percentage of responders at 5%, 10% and 15%; percentage of responders within each obesity-
phenotype group at 4 and 12 weeks; side effects of medications; changes in blood flow in the brain areas, and 
transcriptomic changes in colonic mucosa. In the open-label extension, we will assess the total body weight loss at 24 
and 52 weeks in both groups.  
Sample size assessment: In order to account for dropouts and to detect an effect size in weight loss between groups of 
interest (intervention vs. control) we propose a randomized, double-blinded, active controlled trial of 250 participants 
with obesity to compare effects of Intervention compared to Control in weight loss. In our recent pilot study [with 
Liraglutide 3.0 mg vs. placebo], the SD for the overall weight change (pre-post) observed was 2.8kg. Using this SD, we 
have estimated the differences between groups that could be detected with approximately 80% power (2-sided α level 
of 0.05) for main effects.  The analysis will involve an ANCOVA models, with the response being actual weight change; 
the covariates to be considered include gender, and weight at baseline.  We noticed a 20% withdrawal rate during the 
study, thus, we extended the enrolled number to aim to have 200 participants complete the study. 
Significance: Our study individualizes obesity treatment to maximize pharmacotherapy outcome based on phenotyping 
obesity at baseline. 
 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 5 of 28 
 
BACKGROUND 
 
Obesity prevalence continues to increase worldwide[7] and, in the United States, 69% of adults are overweight 
or obese[8]. Estimated costs to the healthcare system are more than $550 billion annually. Increased severity of obesity 
correlates with a higher prevalence of the associated co-morbidities. Likewise, obesity increases the risk of premature 
mortality [14]. Obesity affects almost every organ system in the body and increases the risk of numerous diseases 
including type 2 diabetes mellitus, hypertension, dyslipidemia, cardiovascular disease, and cancer. It is estimated that a 
man in his twenties with a BMI over 45 will have a 22% reduction (13 years) in life expectancy.  
Despite advances in understanding of aspects of obesity pathophysiology, weight loss with current treatments 
including diet, exercise, medications, endoscopy and surgery is highly variable [9]. However, there are usually great 
responders to each therapy, specifically “responders” to medications can lose as much weight and with less side effects 
than bariatric surgery. These individuals – the responders – can benefit from significant weight loss (>15% total body 
weight loss) which is known to reduce all-cause cardiovascular mortality and morbidity. For example, the high dose of 
extended release (ER) phentermine-topiramate was associated with an average weight loss of 9.8%; only 48% of 
patients lost more than 10% of body weight, whereas 30% of patients lost less than 5% body weight [4]. Additionally, the 
high variability in weight loss response has resulted in a poor market penetrance by new medications, devices and 
surgery. Clearly the one-treatment-fits all is not working and obesity management continue to be a hit-or-miss 
intervention. Leaving physicians to select pharmacotherapy based in potential side effect and patient comorbidities [10], 
instead of choosing the right drug for the right patient based on its pathophysiology. Thus, it is essential to identify the 
responders to each intervention, to maximize their weight loss.  Recently, we made significant progress to identify 
predictors of weight loss using gastrointestinal and behavioral traits [3]. 
Treatment for obesity:  
The 2013 Obesity Guidelines suggest that to achieve weight loss, an energy deficit is essential. Reducing dietary energy 
intake below that required for energy balance can be achieved through a reduction of daily calories to 1200-1500 for 
women, and 1,500-1800 for men (kilocalorie levels are usually adjusted for the individual’s body weight and physical 
activity levels); or estimation of individual daily energy requirements and prescription of an energy deficit of 500 kcal/d 
or 750 kcal/d. Recommendations for young children through adolescence vary in order to support normal growth and 
development occurring during these years.  The Academy of Nutrition and Dietetics Evidence Analysis Library 
recommends no fewer than 900 kcal/day for 6-12 year olds who are medically monitored and no fewer than 1200 
kcal/day for 13-18 year olds (Academy of Nutrition and Dietetics Weight Management Position Paper which provides an 
overview of a nutrition assessment: http://www.eatrightpro.org/resource/practice/position-and-practice-
papers/position-papers/weight-management).  Evidence supports greatest long-term success with an individualized, 
structured meal plan in place. A registered dietitian nutritionist can play an important role in designing the nutrition 
intervention tailored to address each patient’s unique needs and circumstances, taking into consideration factors such 
as insulin resistance. Any diet program that meets this required energy deficit is appropriate to adopt, and comparative 
trials have shown no long-term superiority between different macronutrient composition or elimination diets. 
Furthermore, it is important to adhere to a balanced diet that provides a variety of items from all food groups and limits 
potentially harmful food ingredients like added sugars, sodium and alcohol. Additionally, guidelines recommend limiting 
or avoiding liquid calories (i.e. sodas, juices, alcohol, etc.). And, finally, the meal plan should be designed in such a way 
that the individual is likely to follow it. 
Along with the prescription for a reduced calorie diet, a comprehensive lifestyle intervention program should prescribe 
increased aerobic physical activity (such as brisk walking) for ≥150 min/week (equal to ≥30 min/d most days of the 
week), and a goal of >10,000 steps per day. Higher levels of physical activity, approximately 200 to 300 min/wk., are 
recommended to maintain the weight lost or minimize weight regain in the long term (>1 year) [15]. The diet and 
physical activity can be in combination with a hospital/university or commercial behavior program; these are 
comprehensive lifestyle interventions that usually provide structured behavior strategies to facilitate adherence to diet 
and activity recommendations. These strategies include regular self-monitoring of food intake, body weight, physical 
activity, and food cravings. These same behaviors are recommended to maintain lost weight, with the addition of 
frequent (i.e., weekly or more frequent) monitoring of body weight[16]. 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 6 of 28 
 
 
 
Figure 1. Effects of phentermine plus 
topiramate on bodyweight. Patients with at 
least 5% and at least 10% weight loss. [4] 
Pharmacotherapy  
In addition to diet, exercise and behavioral modification, pharmacotherapies should be considered as an adjunct to 
lifestyle changes in patients who have been unable to lose and maintain weight with diet and exercise alone. They 
should also be considered in people whose history or clinical circumstances require expedited weight loss. Medication 
should not be used alone, but in combination with an intensive lifestyle program. 
Pharmacotherapy for the treatment of obesity can be considered if a patient has a body mass index (BMI) ≥ 30 kg/m2 or 
a BMI ≥ 27 kg/m2 with weight-related co-morbidities such as hypertension, type 2 diabetes, dyslipidemia and obstructive 
sleep apnea[16]. Medical therapy should be initiated with dose escalation based on efficacy and tolerability to the 
recommended dose.  An assessment of efficacy and safety at least monthly for the first three months and then at least 
every three months. In patients who have cardiovascular disease, guidelines recommend against prescribing 
sympathomimetic agents such as phentermine and phentermine/topiramate extended release (ER).  Lorcaserin and 
orlistat are safer alternatives.  In patients with T2DM, the guidelines suggest antidiabetic agents that promote weight 
loss such as glucagon-like peptide (GLP-1) analogs which reduce hyperglycemia in addition to the first-line agent for 
T2DM, metformin[17]. 
Medication / 
dose 
Clinical data 
Mean weight 
change 
from baseline after 
1 year 
Weight loss after 1 year 
(Proportion of participants)  
References 
>5% 
>10% 
>15% 
Orlistat  
120 mg TID 
Clinical data from three 
trials 
−6.0 to 10.3  Kg vs 
−2.6 to 6.1 Kg with 
placebo 
36–67% 
(vs.16–
43.6%) 
17 - 38.9  
(vs. 8.8 – 
24.8) 
NA 
[18-20] 
Phentermine/  
topiramate ER 
15 mg/92 mg 
QD 
1‐year trial, people with 
obesity (BMI ≥35 kg/m2) 
−10.9% vs −1.6% 
with placebo 
70% 
(vs.21%) 
48%  
(vs. 7%) 
NA 
[21] 
Lorcaserin  
10 mg BID  
2‐year trial, people with 
obesity or overweight 
and ≥1 comorbidity 
−5.8% vs −2.5% with 
placebo 
47% 
(vs. 23%) 
22.6  
(vs. 7.7) 
NA 
[6] 
Naltrexone/ 
bupropion SR 
32 mg/360 mg  
Four 56‐week trials, 
people with obesity and 
≥1 comorbidity 
−5.4% vs −1.3% with 
placebo (COR‐I) 
42% 
(vs. 17%) 
28.3  
(vs. 5.7) 
13.5  
(vs. 2.4) 
[1] 
Liraglutide  
3.0 mg QD 
56‐week trial, people 
with obesity or 
overweight and ≥1 
comorbidity 
−7.4% vs −3.0% with 
placebo 
62% 
(vs. 34%) 
33.1% 
(vs. 
10.6%) 
14.4%  
(vs. 3.5%) 
[22] 
 
Phentermine-Topiramate Extended Release: When low-dose, controlled-release, phentermine was combined with the 
glutamatergic and GABA-ergic antiepileptic topiramate in a large phase 
III study (more than 1400 participants on treatment arms with different 
doses), subjects lost 10.2 kg on15/92 mg combination therapy vs. 1.4 
kg on placebo over 56 weeks [21]. The most common adverse events 
were dry mouth, paresthesias, constipation, insomnia, dizziness, and 
dysgeusia. Depression- and anxiety-related adverse events were also 
observed. The medication had favorable effects on glycemia, including 
prevent progression to diabetes, improvements in lipids, blood 
pressure, sleep apnea, and quality of life measures. There was also, as 
previously noted, a small but consistent increase in pulse rate [23]. The 
overall rate of adverse effects decreased in weeks 56–108 compared to 
weeks 0–56; among which dry mouth, constipation and paresthesias 
were the most prevalent There were 19 pregnancies carried to term 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 7 of 28 
 
during these studies none of which resulted in congenital abnormalities [23-25]. 
In July 2012, the FDA voted for approval of phentermine (3.75–15mg/d) plus extended release topiramate (23–92mg/d) 
as an adjunct to diet and physical activity for treatment of obesity among adult individuals with BMI≥30kg/m2 or 
BMI≥27kg/m2 with at least one obesity-related comorbid condition. The drug will carry a warning of potential increased 
risk for orofacial clefts in neonates exposed to topiramate during the first trimester of gestation and will be subject to a 
Risk Evaluation and Mitigation Strategy (REMS) that will restrict prescribing to trained clinicians, will require effective 
contraception and monthly pregnancy tests for reproductive age women, and will restrict dispensing to specific mail-
order pharmacies. The company is also required to carry a long-term cardiovascular outcomes trial. No randomized 
pediatric studies have as yet been reported. Noteworthy, the high dose of PhenTop was associated with a mean weight 
loss of 9.8%; however, only 48% of patients lost >10% of their body 
weight, and 30% of patients lost <5% of their body weight (Figure 1). 
The high variability of weight loss response to treatment with 
PhenTop is unclear.   
Lorcaserin (Belviq®): The second medication approved by the FDA in 
2012 for chronic weight management is lorcaserin[26]. It is a 
serotonin receptor agonist thought to reduce food intake and 
increase satiety by selectively activating receptors on anorexigenic 
POMC neurons in the hypothalamus.  At the recommended dose, 
lorcaserin selectively binds to 5-HT2C receptors instead of 5-HT2A 
and 5-HT2B receptors, which are associated with hallucinations and 
cardiac valve insufficiency respectively [27].  The recommended 
dose of lorcaserin is 10 mg twice daily.  The medication should be 
discontinued if ≥ 5% weight loss is not achieved after 12 weeks 
(Figure 2)[6].  
Oral naltrexone extended-release/bupropion extended-release (NBSR; Contrave®, Mysimba™) is available as an 
adjunct to a reduced-calorie diet and increased physical activity in adults with an initial body mass index (BMI) of 
≥30 kg/m2 (i.e. obese) or a BMI of ≥27 kg/m2 (i.e. overweight) in the presence of at least one bodyweight-related 
comorbidity, such as type 2 diabetes mellitus, hypertension or dyslipidemia. In 56-week phase III trials in these patient 
populations, oral naltrexone ER/bupropion ER 32/360 mg/day was significantly more effective than placebo with regard 
to percentage bodyweight reductions from baseline and the proportion 
of patients who achieved bodyweight reductions of ≥5 and ≥10 % 
(table 1)(figure 3)[1, 28, 29]. Significantly greater improvements in 
several cardiometabolic risk factors were also observed with 
naltrexone ER/bupropion ER versus placebo, as well as greater 
improvements in glycated hemoglobin levels in obese or overweight 
adults with type 2 diabetes. Naltrexone ER/bupropion ER was generally 
well tolerated in phase III trials, with nausea being the most common 
adverse event (table 2) [28, 29]. Thus, naltrexone ER/bupropion ER 
32/360 mg/day as an adjunct to a reduced-calorie diet and increased 
physical activity is an effective and well-tolerated option for chronic 
bodyweight management in obese adults or overweight adults with at 
least one bodyweight-related comorbidity.  
Noteworthy, the high dose of NBSR was associated with a mean weight 
loss of 8.1%; however, only 34% of patients lost >10% of their body 
weight, and 62% of patients lost <5% of their body weight. The high variability of weight loss response to treatment with 
NBSR is unclear.  
Liraglutide (Saxenda®) is a glucagon-like peptide-1 (GLP-1) analogue with 97% homology to human GLP-1, a gut derived 
incretin hormone[26]. Liraglutide was approved in 2010 for the treatment of type 2 diabetes at doses up to 1.8 mg daily.  
In phase III studies many patients on liraglutide for diabetes lost weight in a dose-dependent manner [30] and the 
 
Figure 3. Effects of naltrexone/bupropion 
SR on bodyweight. Categorical weight loss 
in week 28 in completers populations. 
***P < 0.001 for NB32 vs. Placebo [1] 
Figure 2: Effects of Lorcaserin on Body weight. 
The proportions of patients who lost 5% or 
more or 10% or more of their 
baseline body weight at 1 year are shown [6]. 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 8 of 28 
 
 
Figure 4 shows the proportions of patients who lost at 
least 5%, more than 10%, and more than 15% of their 
baseline body weight. Data shown are the observed 
means for the full-analysis set (with LOCF). [2]. 
efficacy was similar in patients with obesity without diabetes [22]. The FDA approved liraglutide in 2014 as Saxenda at 
3.0 mg dose for chronic weight management in patients with obesity.  Weight loss is mediated by reduced energy intake 
by reducing appetite, increasing satiety and delaying gastric emptying [11, 31]. Liraglutide is administered as a 
subcutaneous injection once daily.  It is initiated at 0.6 mg daily for one week with instructions to increase by 0.6 mg 
weekly until 3.0 mg is reached.  Slower dose titration is 
effective in managing gastrointestinal side effects.  The 
medication should be discontinued if a patient has achieved ≤ 
4% weight loss at 16 weeks. 
The average weight loss in a large NEJM-published trial [2] of 
liraglutide was ~8% of body weight; 33% of participants lost 
>10% and 14.4% lost >15% of body weight.   However, 36.8% 
of patients did not respond to treatment with liraglutide 
(figure 4). The reason for the high variability of weight loss 
response to treatment with liraglutide is unclear.  
Pharmacogenomics  
Pharmacogenomics (PGx) is a new field in individualized 
medicine generally concerned with genetic polymorphisms in 
drug-metabolizing enzymes, transporters, receptors, and 
drug targets that explain inter-individual variation in drug 
efficacy and toxicity [41].  PGx has the potential to improve clinical outcomes by using an individual’s genotype to inform 
personalization and optimization of drug therapy. A large number of PGx variants with demonstrated clinical utility are 
known and have been incorporated into drug labeling by the US Food and Drug Administration (FDA) [2].  As the 
availability of high throughput genomics technology becomes more widespread and the associated cost of genetic 
testing more economical, opportunities for patients to have precision genomic information to guide healthcare decisions 
is expected to increase. Integration of genetic data into the clinical decision making process has the potential to 
significantly advance the practice of precision medicine and in the case of PGx, ultimately affect every patient.  Mayo 
Clinic’s Individualized Medicine Clinic (within the Center for Individualized Medicine) has established a 
Pharmacogenomics Testing Service. Largely an interest for “otherwise healthy” patients, or those self-reporting 
medication struggles, these patients can be referred for testing and/or consultation/evaluation by a PGx expert 
pharmacist who will help facilitate a PGx laboratory test in partnership with the referring physician. The PGx pharmacists 
can also assist with interpretation of the results—given the newness of the field and level of exposure to PGx testing 
across physicians.  Though single gene PGx testing has long been used at Mayo Clinic in certain, focused departments for 
diagnostic or therapeutic reasons, the clinical evidence is expanding to implicate a greater number of genes and 
medications, laboratories are creating panel tests that cover more genes at a lesser cost than previous single gene tests.  
The clinical value of these tests is now becoming more broadly understood. Prescribers who believe their patients have 
medication metabolism issues can currently tap into the PGx Testing Service by ordering PGx gene tests for diagnostic 
purposes and requesting a PGx e-consult or patient face to face consult with the PGx pharmacist for results 
interpretation assistance. Additionally, a limited number of pilots offering clinical PGx testing primarily for predictive 
reasons are offered with the Center for Individualized Medicine.  The value of the service includes utilization of PGx 
testing as a tool for assisting health care providers improve the medication experience of their patients. Patients may 
also benefit from understand their own PGx variations and the relevance of their results and other family members. The 
service is also assisting providers in this new and growing field, by providing expertise and support to help prescribers 
tailor medications for their patients--adjusting current mediations according to the patient’s genetic variations and/or 
providing valuable information for future prescribing events.   
 
 
 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 9 of 28 
 
Figure 5: Potential application of medications and 
devices directed at phenotypes associated with 
obesity. Rx, therapy; ER, extended release; GLP-1, 
glucagon-like peptide 1. Adapted from Camilleri and 
Acosta, GIE, 2016 [5] 
PRELIMINARY DATA 
Gastrointestinal traits (phenotypes) associated with obesity: Recently we published the characterized gastrointestinal 
functions, satiation and satiety, in 509 participants across the normal weight to obesity spectrum. We found that obesity 
is associated with decreased satiation (higher caloric intake before feeling full, measure by volume to fullness [VTF] 
p=0.038), large fasting gastric volume (GV, p=0.03), accelerated gastric emptying (GE) T1/2 (solids: p<0.001; liquids: 
p=0.011), and lower postprandial peak plasma levels of PYY (p=0.003). In addition, principal components (PC) analysis 
identified latent dimensions (LDs) accounting for ~81% of OW-OB variation and sub-classifies obesity (figure 5) in 
satiation (21%), gastric capacity (15%), behavioral (13%), 
gastric sensorimotor (11%) factors and others (40%)[3]. 
This obesity sub-classification may predict weight loss 
response to pharmacotherapy and bariatric endoscopy 
[3].   
Obesity phenotypes to predict weight loss response: 
Thus far, we validated the applicability of obesity-related 
gastrointestinal quantitative traits in two randomized 
clinical trials [3, 11]. In a single-center, randomized, 
parallel-group, double-blind, placebo-controlled, 14-day 
study, we evaluated the effects of Phentermine-
topiramate-ER (PhenTop) (7.5/46mg, orally, daily) on GE, 
GV, satiation, satiety, and fasting and postprandial gut 
hormones in 24 obese adults using validated assays. 
PhenTop is approved for the treatment of obesity. 
However, its effects on gastric functions, satiation, satiety 
and relevant gut hormones are unknown. PhenTop was 
associated with reduced food intake at buffet meal (mean 
Δ 260kcal, p=0.032) and delayed GE solids (mean Δ GE4h 
6%, p=0.03; and Δ GE T½ 19min, p=0.057). There were no 
significant differences in GV, satiation, GE of liquids and 
GI hormones. Patients on PhenTop had greater mean weight loss of 1.4kg than placebo (p=0.03). Weight loss on 
PhenTop was significantly associated with kcal intake at a prior satiety test.  We concluded that PhenTop reduces food 
intake and delays GE of solids, suggesting central as well as peripheral 
mechanisms of action in inducing weight loss and that a prior satiety 
test predicts weight loss with PhenTop (Figure 6) [3]. 
In another placebo-controlled trial, we studied the effect of exenatide, 
5µg, SQ, twice daily for 30 days, on GE, satiety, satiation and weight 
loss in 20 obese participants with accelerated GE. Exenatide had a very 
significant effect on GE of solids (p<0.001) and reduced calorie intake at 
a buffet meal by an average 130kcal compared to placebo. The average 
weight loss was 1.3kg for exenatide and 0.5kg for the placebo group. 
We concluded from this relatively short duration study that exenatide 
reduces food intake and delays GE of solids; and that a prior 
accelerated gastric emptying test predicts weight loss with exenatide 
[11]. 
In a recent retrospective analysis, we have identified that the best 
responders to the intragastric balloon therapy are those individuals 
with an accelerated gastric emptying (p<0.001) and the greater delay in 
gastric emptying after intragastric balloon placement (p<0.001)[13].  
We recently completed a prospective, randomized clinical trial with 
liraglutide, a long-acting GLP-1 receptor agonist, is approved for 
treatment of obesity. The objective was to compare effects of 
liraglutide and placebo over 16 weeks on gastric motor functions, 
Figure 6: Body weight change by prior 
satiety test. Association of change in body 
weight (in response to randomized treatment 
with placebo or PhenTop) and kcal intake at 
prior ad-libitum meal. This is shown (p=0.029) 
for the drug* treatment interaction.[3] 
-3
-2
-1
0
1
2
Body Weight Change, kg
< 900 kcal
> 900 kcal
  Placebo    Phen-Top ER
*p=0.029 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 10 of 28 
 
satiation, satiety and weight in obese patients. This study was a randomized, double-blind, placebo-controlled trial of 
subcutaneous liraglutide, 3mg, with standardized nutritional and behavioral counseling at Mayo Clinic, Rochester, MN. 
Forty adult, otherwise healthy local residents with BMI ≥30kg/m2 were randomized between December 2015 and 
September 2016. Liraglutide or placebo was escalated by 0.6mg/day each week for 5 weeks and continued until week 
16. At baseline and after 16 weeks’ treatment, we measured weight, gastric emptying of solids (GES, primary endpoint), 
gastric volumes, satiation, and satiety. GES was also measured at 5 weeks. Statistical analysis compared treatment 
effects using ANCOVA (with baseline measurement as covariate). Effect of liraglutide on GES T1/2 at 5 and 16 weeks in 
the liraglutide group was analyzed by paired t-test. Seventeen participants were analyzed in the liraglutide group (n=19 
randomized) and 18 in the placebo group (n=21 randomized). Compared to placebo, liraglutide retarded GES at 5 
(p<0.0001) and 16 (p=0.025) weeks, caused significant weight loss and increased satiation. In 16 weeks, the total body 
weight loss for the liraglutide group was 6.1±2.8 kg (SD) compared to 2.2±5 kg control group (p=0.0096). There was 
tachyphylaxis to GES effects of liraglutide from 5 to 16 weeks’ treatment. At 5 and 16 weeks, GES T1/2 correlated with Δ 
weight loss on liraglutide (all p<0.02). Nausea was the most common adverse event in the liraglutide group (63.2%) 
compared to placebo (9.5%). Our results suggests that Liraglutide, 3.0mg, significantly delays GES after 5 and 16 weeks’ 
treatment; effects on weight loss are associated with absolute value of GES T1/2 on liraglutide [32]. 
Quantitative traits - phenotypes are associated with higher BMI, distinguish obesity phenotypes, and may predict 
response to obesity pharmacotherapy and endoscopic devices [3]. However, the tests of quantitative GI traits are 
currently limited to a few research/academic centers. Thus, we 
have developed a novel and simple diagnostic-blood-test that 
predicts weight loss in obesity. The diagnostic test is based on an 
algorithm that combines candidate gene variants (SNPs), 
metabolites and metabolic peptides. We recently completed the 
analysis of 102 patients with obesity, matched for gender, age and 
BMI. These individuals were non-diabetic and were in not 
medications for weight loss. Based on the profile of each patient we 
were able to validate the main groups in obesity in 1) abnormal 
satiation, 2) rapid return to hunger, 3) behavioral eating (identified 
by questionnaire) and 4) abnormal energy expenditure; plus a 
“mixed” group.  Once these variables were tested, we first created a 
combined logit regression model using stepwise variable selection 
to identify variables that are significantly associated with each of 
the phenotypic classes. The result included a combination 14 
metabolites (amino-compounds, neurotransmitters and fatty acids), 
no candidate gene or metabolic peptide were included/make the 
cut (The 14 metabolites are knowingly not disclosed per MCV/legal 
request - Mayo IP disclosure No. 2017-040 and DR16-520 – 
unpublished/confidential). Figure 7 shows the sub-classification 
prediction accuracy of this combined model and an ROC analysis 
showed that this model has >0.90 AUC for all four classes. Next, we 
set out to derive binary classification models that can predict 
whether a patient belongs to one group over the others. As 
preliminary data, we derived Bayesian covariate predictors for abnormal satiation, behavioral eating, and abnormal 
energy expenditure (detailed models not shown here for lack of space). These models yielded an ROC AUC of 0.9414, 
0.9668, and 0.8775. These data suggested that the serum metabolite levels hold all the information needed to predict 
obesity subclasses. We propose to develop a novel targeted panel-based blood assay using the metabolites in these 
models (both integrated model and independent binary models) and validate them against an independent cohort. We 
will also extend our statistical analysis to develop a binary model for predicting whether a patient has rapid return to 
hunger phenotype. 
Quantitative traits are associated with higher BMI, distinguish obesity phenotypes, and may predict response to 
obesity pharmacotherapy and endoscopic devices (Figure 5) [3]. However, these results were determined 
retrospectively and each of them was done independently. Thus, the identification of the obesity phenotype at baseline 
Figure 7: Diagnostic test for Obesity 
Phenotypes that predict weight loss response to 
interventions. ROC curves for each main group: 
Blue line: abnormal satiation, Orange line: rapid 
return to hunger, and Green line: abnormal 
energy expenditure (unpublished – confidential) 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 11 of 28 
 
to guide obesity pharmacotherapy has not been tested yet and the outcome is unknown in the clinical setting. Thus, 
there is a critical need to do a prospective randomized study to evaluate the weight loss outcome using obesity 
phenotypes to guide therapy for obesity.  
 
PRELIMINARYA DATA FOR SUB-AIM 1:  
The heterogeneity of human obesity has confounded our ability to translate research findings to 
understand the mechanisms underlying obesity pathophysiology. Thus, we hypothesized that our 
pathophysiological classification will assist in the elucidation the uniqueness among obesity phenotype and to 
address this hypothesis, we decided to conduct a series of studies aiming to further characterize each phenotype 
in depth, and identify unique biological perturbations underpinning each phenotype. In all the measurements 
described below, there were no differences in weight, BMI, age or gender among the different groups, unless 
otherwise noted. 
 
Hungry Brain Phenotype – Abnormal Satiation: The sensation of satiation, which leads to the termination of a 
meal[33], requires close coordination between the brain and the gut[34, 35]. These “stop eating signals” are 
mainly driven by the distention of the stomach, and vagal nerve afferents, transmitting the sensation to the 
hypothalamus to induce satiation and stop the meal[34, 36]. Previously, we have shown that individuals with 
obesity consumed more calories prior to reaching ‘usual’ fullness – for every 5 units of BMI increase, 
participants consumed 50 calories more[37]. Here, we showed that patients with a hungry brain phenotype 
consumed significantly more calories (62% more) to reach satiation, thus determining their unique phenotype. 
Interestingly, individuals without the hungry brain obesity phenotype consumed similar calories to historical 
normal weight controls[37]. The prevalence of hungry brain obesity was 28% in the new cohort (n=46/165) and 
42% in the previously published[37] cohort of patients completing the phenotype test (n=68/163).  
These participants completed a well-validated “nutrient-drink test”, another feeding paradigm, that 
identifies different degrees of the sensation of fullness. During a nutrient drink test, participants with hungry 
brain obesity consumed 107 calories more calories to reach volume to “usual” fullness (VTF) (p<0.05) and 241 
calories more calories to reach ‘maximal’ fullness – maximal tolerated volume (MTV)(p<0.001) compared to 
individuals with the non-hungry brain obesity (Supplemental table 1). Thus, the hungry brain obesity phenotype 
may have a deficiency in the mechanisms that mediate the “stop eating” signals.  
To further investigate and to understand this association, we performed brain MRI in patients, using 
pseudo-Continuous Arterial Spin Labeling (pCASL) MRI sequence to study the hypothalamic function of 
individuals with and without the hungry brain obesity phenotype, and lean controls (patient demographics 
Supplemental table 3).   The patients were scanned at 4 time points - i.e., at baseline, after drinking 240ml of 
Ensure (VTF), after reaching maximal tolerable volume (MTV) of Ensure representing peak fullness and 30 
minutes after reaching MTV (MTV+30). There was no difference in hypothalamic blood flow at any time point 
in patients with obesity (n=22) compared to lean (n=7) controls (Figure 2H) or in a control area, which was 
frontal lobe white matter that is considered unrelated to food regulation and therefore represents an area where, 
theoretically, blood flow would be stable at all four time points (Figure 2 G, I). In patients with hungry brain 
obesity (n=8), the average blood flow within the right side of the hypothalamus was consistently lower at all 
four time points and significantly lower at MTV (p=0.02), compared to patients with non-hungry brain obesity 
(n=14)(Figure 2 A-F, J). These findings are consistent with previous observations of obesity in animal models 
and humans associated with hypothalamic injury[38], neuronal plasticity[39] and/or gliosis[40].  


Andres Acosta MD, PhD 
Mayo Clinic 
Page 12 of 28 
 
 Figure 2. Hungry 
brain phenotype assessed by Pseudo-Continuous Arterial Spin Labeling (pCASL) MRI sequence. The 
blood flow to the  right hypothalmus, region of interest, shown in red and blue circles for non-hungry brain and 
hungry brain, respectively, visible by T2 MRI imaging (A, D), pCASL imaging at baseline (B, E) and at 
maximal fullness (MTV) (C,F).  Quantitated blood flow at baseline, volume to usual fullnes (VTF), MTV, and 
30 minutes after reaching MTV (MTV+30) was compared between groups for the right anterior frontal white 
matter, a control area (G, I), and the right hypothalamus (H,J). Green triangles= lean; purple diamonds= “all” 
obesity; red circles=NHB; blue-squares=HB. *p<0.05.  
 
 
 
 


Andres Acosta MD, PhD 
Mayo Clinic 
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Hungry Gut Phenotype – Abnormal Satiety: From a physiological perspective, the sensation of satiety or 
persistent fullness[33] is mainly driven by communication of the gut with the brainstem and the 
hypothalamus[34, 36, 41].  Factors regulating satiety, which is usually recorded via subjective 100 mm visual 
analog scales, include gastric emptying and gastrointestinal satiety peptides, and these variables are 
reproducible and objective measurements of satiety[37, 42, 43]. Therefore, rapid gastric emptying was selected 
as a surrogate for abnormal satiety in assessment of the hungry gut phenotype, as it is an objective, reproducible 
test. The prevalence of hungry gut obesity was 28% in the new cohort (n=46/165) and 34% in the previously 
published[37] cohort (n=56/164). In female participants with hungry gut obesity, gastric emptying T1/2 (GE) was 
accelerated by 30% for solids (p<0.001) and by 22% for liquids (p=0.01) compared to non-hungry gut obesity. 
In male participants with hungry gut obesity, GE T1/2 was accelerated by 38% for solids (p<0.001) and 33% for 
liquids (p=0.05) compared to non-hungry gut obesity. The observation is of clinical relevance as gastric 
emptying is correlated with the caloric consumption in the next meal[43] and with the sensation of persistent 
fullness[34, 44]. Interestingly, this observation both elucidates and builds upon our previous findings that “all” 
obesity experiences rapid gastric emptying compared to lean controls; demonstrating only a subgroup of obesity 
experience this pathophysiological abnormality that alters satiety[37, 42, 43].  
The pathophysiology underlying the hungry gut phenotype might be secondary to an abnormal negative 
feedback of gastrointestinal satiety hormones, Glucagon-like peptide 1 (GLP-1), and Peptide YY (PYY), 
secreted from L-type enteroendocrine cells of the ileum and colon. Enteroendocrine (EE) cells are real-time 
nutrient, bile and microbiota sensors that regulate food intake, brain-gut communication, gastrointestinal 
motility, and glucose metabolism. EE cell function can be studied indirectly by measuring plasma levels of 
hormones such as GLP-1 or PYY, and less frequently EE cells are studied as part of whole intestinal tissue. We 
have examined the characteristics of the EE cells in participants with or without the hungry-gut obesity 
phenotype in mucosal biopsies obtained during unsedated flexible sigmoidoscopy. Both mucosal biopsies and 
blood were collected from previously phenotyped participants (demographics in Supplemental table 4 and 5). 
There was no difference in plasma fasting or 15, 45 and 90 minutes postprandial gastrointestinal peptides 
PYY3-36 or GLP-1 concentration (Figure 3A, E) nor in colonic mucosal GCG mRNA expression (Figure 3C) 
in obesity compared to healthy weight controls; though PYY mRNA expression was significantly increased in 
‘all’ obesity compared to lean (Figure 3G; p=0.04). However, participants with the hungry gut obesity 
phenotype, defined by accelerated GE, had significantly lower plasma concentration of GLP-1 (AUC p=0.007) 
and PYY (AUC p=0.03) when compared with non-hungry gut obesity (Figure 3B, F). Furthermore, participants 
with hungry gut obesity had decreased mRNA expression of GLP-1 (p=0.01) and PYY (p=0.04) in colonic 
mucosa when compared to non-hungry gut obesity (Figure 3D, H). The observed reductions in mucosal 
expression and circulating levels of GLP-1 and PYY are consistent with reduced negative feedback that 
normally results in slow gastric emptying and reduced signaling to the hypothalamus, thereby reducing the 
hypothalamic-mediated sensation of fullness in this phenotype. These observations also suggest the importance 
of the EE cells, of the distal gut in food intake regulation, in addition to their role in direct communication with 
luminal nutrients, toxins and microbiota.    
 
 
 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 14 of 28 
 
 
Figure 3. Hungry gut phenotype characterized by comparing plasma concentration and colonic mucosal gene 
expression of gastrointestinal satiety hormones, Glucagon-like peptide-1 (GLP-1, GCG), and Peptide YY3-36 
(PYY). Comparisons are made between lean versus “all” obesity, as well as between the Hungry gut-obesity 
phenotype (HG), and the non-hungry gut obesity phenotype (NHG). Plasma concentrations during fasting (-15 
minutes) and at 15, 45 and 90 minutes postprandially for GLP-1 (A, B) and PYY (E, F) were investigated. 
Normalized mRNA expression of GCG (GLP-1) (C,D), and PYY (G, H) was measured at baseline from colonic 
mucosal tissue.   
 
 
 
 


Andres Acosta MD, PhD 
Mayo Clinic 
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Emotional Hunger Phenotype - Hedonic Behavior: Obesity is often regarded as a behavioral disease, in which 
patient’s emotions drive obesogenic behavior in search of reward through compensatory mechanisms[45]. Here 
we report that there is a sub-group within obesity possessing a strong psychological component, potentially 
predisposing them to obesity, thus, we have labeled this sub-group as the emotional hunger phenotype. The 
prevalence of emotional hunger obesity was 34% in the new cohort (n=56/165) and 27% in the previously 
published[37] cohort (n=44/164). Additionally, individuals with the emotional hunger obesity phenotype are 
characterized as having higher levels of symptoms of anxiety (p<0.001), symptoms of depression (p<0.001), 
emotional restraint –TEFQ21 (30% higher, p=0.04), emotional eating (Disinhibition on the Eating Inventory, 
p=0.007) and lower levels of self-esteem (p=0.002) and body image (P<0.001) when compared to non-
emotional eating obesity phenotypes. This emotional hunger group is likely acquiring most of their calories 
from emotional eating, cravings and reward-seeking behaviors, despite having appropriate sensations of 
satiation and satiety – normal homeostatic eating behavior. Identifying this phenotype validates decades of 
eating behavior research, which describes a hedonic eating behavior, mechanistically different that the 
“homeostatic” eating behavior[46]. 
While an interesting, and somewhat expected finding, the questionnaires remain a subjective 
measurement of emotional eating. The Nucleus accumbens is an important brain structure in the reward 
response system[47] and previously reported to be highly associated with obesity[48, 49].   Indeed, deep brain 
stimulation of the nucleus accumbens is attempted as a treatment for obesity[50]. For this reason we utilized 
pCASL MRI, to study the relationship between perfusion of nucleus accumbens and the emotional hunger status 
(See cohort demographics in Supplemental table 6). There was no difference in blood flow in the nucleus 
accumbens or in the anterior frontal white matter control area, in obesity compared to lean controls (Figure 4 A-
G, I). In contrast, in the emotional hunger obesity phenotype (n=6) there was increased blood flow in the left 
nucleus accumbens at all 4 time points: baseline (p=0.06), VTF (p=0.21), MTV (p=0.07), and significantly 
higher at MTV+30 (p=0.015) compared to the non-emotional eating phenotypes (n=14) (Figure 4 A-F, H, J). 
Although the right side nucleus accumbens showed similar trends (i.e., higher flow in all time points), none of 
the differences were statistically significant. Our MRI findings support the unique nature of the phenotype, and 
the importance of our classification in identifying patients with abnormal emotional eating behavior. 
 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 16 of 28 
 
 
Figure 4. Emotional Hunger phenotype assessed by Pseudo-Continuous Arterial Spin Labeling (pCASL) 
MRI sequence. The blood flow to the  left nucleus accumbens, region of interest, shown in red and blue circles 
for non-emotional hunger and emotional hunger, respectively, visible by T2 MRI imaging (A, D), pCASL 
imaging at baseline (B, E) and at maximal fullness (MTV) (C,F).  Quantitated blood flow at baseline, volume to 
usual fullness (VTF), MTV, and 30 minutes after reaching MTV (MTV+30) was compared between groups for 
the left anterior frontal white matter, a control area (G, I), and the left nucleus accumbens (H,J). Green 
triangles= lean; purple diamonds= “all” obesity; red circles=NEH; blue-squares=EH. *p<0.05.  
 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 17 of 28 
 
HYPOTHESIS AND AIMS 
The unique quantitative data garnered in our preliminary studies led to the overall hypothesis that weight loss with 
pharmacological agents may be individualized, based on the baseline abnormality in obesity phenotype of each patient.  
Thus, each baseline trait could be targeted by pharmacological actions of specific obesity medications.  
Hypothesis: We hypothesize that the identification of the obesity phenotype at baseline to guide obesity 
pharmacotherapy will enhance the weight loss response rate (i.e. percentage of patient with weight loss higher than 
10% at 12 weeks).  
 
Aim: In a 12 week, randomized, double-blinded, active controlled trial, with open-label 9-month extension of 250 
participants with obesity; we will compare the weight loss response rate to obesity-phenotype-guided pharmacotherapy 
(intervention) vs. non-phenotype guided (randomly selected) pharmacotherapy (control) in patients with obesity and an 
abnormal obesity-related phenotype.  
-Sub-aim 1: to study the effect of phenotype-guided pharmacotherapy in brain blood flow and gut mucosal changes.  
 
SIGNIFICANCE 
This proposal addresses a significant unmet public health need: the development of effective management 
approaches to treat obesity based in individual phenotypes. Currently, there are several safe and effective FDA-
approved medications and devices for the treatment of obesity. Unfortunately, the response to obesity treatment 
(medicines, devices or surgery) is highly variable. Obesity phenotypes can be used to predict weight loss response to 
pharmacotherapy and devices. Thus, it essential that we understand the predictors of response to each intervention for 
obesity to be able to select the right tool for the right patient with minimal or no side effects – Individualized approach 
for obesity.  
 
 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 18 of 28 
 
RESEARCH PLAN 
Study Design:  
 In a 12 week, randomized, double-blinded, 
active controlled trial, with 9 month open-
label extension  of 250 participants with 
obesity; we will compare the weight loss 
response rate to obesity-phenotype-guided 
pharmacotherapy (intervention) vs. non-
phenotype guided (randomly selected) 
pharmacotherapy (control) in patients with 
obesity. All 250 participants will be 
phenotyped and the medication selection 
will be randomly and double blinded (to 
physician, study team and participant) to the 
FDA-approved medicine suggested by the 
phenotype or to another FDA-approved 
medicine not suggested by the phenotype. A 
computer generated randomization 
schedule generated by the study 
statistician’s office will be submitted to the 
Mayo Clinic CCaTS Research Pharmacy. 
Allocations will be concealed. This study will 
be blinded until data are transmitted to the 
statistician for data lock.   All participants 
will receive a standard intense lifestyle 
intervention, which consists of 1 visit with 
registered dietitian. The phenotypic studies 
include (all performed in same day in the 
following order): Fasting blood collection, 
resting energy expenditure, gastric emptying 
with meal for breakfast, behavioral questionnaires, and buffet meal test for lunch. Blood will be collected assessment of 
metabolomic biomarkers, gastrointestinal hormones, and DNA (blood and buccal swab). Stool samples for microbiome 
and bile acid. Saliva samples for assessment of metabolomic biomarkers. Participants will return to the CRTU to pick up 
medication based on the randomization and a personal fitness tracker. All participants will be seen at 4 and 12 weeks 
(+/- 4 days) (current standard in practice). Participants will keep a medication diary, which will have to be returned on 
the 12-week visit. A saliva, stool and fasting blood sample, and DEXA will be done at the 12-week visit. At the 12-week 
visit, participants will be unblinded to their “obesity-related phenotype” and they could contact their physician to 
continue a FDA-approved medication as part of clinical care. Study team will prospectively follow the patients’ weight, 
waist circumference and use of obesity medications every 3 months for 1 year. In a sub-study, 40 participants will 
complete at baseline and at 10 weeks (+/- 2 weeks), a flexible sigmoidoscopy and a pCASL functional MRI; with the 
intention to study the effects of pharmacotherapy in gut mucosa and brain blood flow changes at baseline and after 
treatment.  
Randomization and Allocation  
A computer generated randomization schedule generated by the study statistician’s office will be submitted to the Mayo 
Clinic CCaTS Research Pharmacy. Randomization will be based on guiding pharmacotherapy based on the phenotype or 
randomly as current standard of care. Allocations will be concealed. This study will be blinded until data are transmitted 
to the statistician for data lock. All subjects will be given a verbal explanation of the study, provided time to read and 
study the written consent form and its information, given opportunities to ask questions and a copy of the consent form.  
Participants will be informed of their right to withdraw from the study at any time without prejudice to their clinical 
management now or in the future. Consent will be sought by one of the medical doctor investigators or the study 
coordinator, and consent will be documented by the participant’s signature on the consent form. Mayo’s Institutional 
FIGURE 8: STUDY DESIGN - Randomized clinical trial to identify 
weight loss responders to obesity pharmacotherapy 
 


Andres Acosta MD, PhD 
Mayo Clinic 
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Review Board will approve the process and protocol. All the members of multidisciplinary team for weight management 
(i.e. physicians, coordinators, clinical assistants, registered dietitians will remain blinded).  
Selection Participants 
 
We plan to study a cohort of 200 patients with obesity (BMI>30 kg/m2) and an abnormal obesity-related 
phenotype. Participants will be recruited from the Mayo Clinic Weight Management and Nutrition Clinic when they are 
offered a medication for weight loss as standard of care for obesity; from our gastroenterology clinics; from our previous 
existing database of more than 1000 participants with obesity and from advertising and Mayo Clinic classifieds. Two 
hundred and fifty participants that agree to pharmacotherapy treatment will be invited to participate in the phenotypic 
assessment of their obesity, that will guide (or not) the pharmacotherapy.   
Inclusion criteria 
• 
Adults with obesity (BMI >30Kg/m2); these will be otherwise healthy individuals with no unstable psychiatric 
disease and controlled comorbidities or other diseases.  
• 
Age: 18-75 years.   
• 
Gender: Men or women. Women of childbearing potential will have negative pregnancy tests before each 
radiation exposure.  
• 
Participant must have an abnormal phenotype based on testing done in visit 2. 
 
Exclusion criteria 
a) Abdominal bariatric surgery 
b) Positive history of chronic gastrointestinal diseases, or systemic disease that could affect gastrointestinal 
motility, or use of medications that may alter gastrointestinal motility, appetite or absorption, e.g., orlistat, 
within the last 6 months.  
c) Significant untreated psychiatric dysfunction based upon screening with the Hospital Anxiety and Depression 
Inventory (HAD), and the Questionnaire on Eating and Weight Patterns (binge eating disorders and bulimia). If 
such a dysfunction is identified by an anxiety or depression score >11 or difficulties with substance or eating 
disorders, the participant will be excluded and given a referral letter to his/her primary care doctor for further 
appraisal and follow-up.  
d) Hypersensitivity to any of the study medications. 
e) No contraindications to the FDA-approved medications: Phentermine-Topiramate Extended Release; 
Phentermine; Oral naltrexone extended-release/bupropion extended-release (NBSR; Contrave®, Mysimba™); 
and Liraglutide (Saxenda®). 
f) Participants who meet the following criteria:  
a. No match to any phenotype based upon 90th and 75th percentile criteria; or 
b. Matches 2 or more phenotype based upon 90th percentile criteria; or  
c. No match to phenotype based on 90th percentile criteria and 2 or more match to phenotype based upon 
75th percentile criteria  
g) Sub Study specific exclusion criteria 
a. Any contraindications to MRI  
b. Claustrophobia  
 
Anthropometrics and phenotype studies  
Anthropometrics Measurements: will be taken of hip-waist ratio, height, weight, blood pressure, pulse at baseline, 
randomization day and week 12.  
Phenotype studies at baseline: 
Participants will attend the Mayo Clinic Clinical Research and Trials Unit after an 8-hour fasting period, and the following 
validated quantitative traits (phenotypes) will be measured at baseline:  
o) The DEXA scan (dual energy x-ray absorptiometry) will measure body composition.  
p) Resting energy expenditure: was assessed by indirect calorimetry with a ventilated hood (Parvo Medics, Sandy, 
UT). 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 20 of 28 
 
q) Gastric emptying (GE) of solids by scintigraphy: The primary endpoint is gastric half-emptying time (GE t1/2) [3, 
51, 52]. 
r) Appetite (hunger level) by visual analog score fasting and after standard meal for GE and prior to the Satiation 
test [3]. 
s) Satiation will be measure by ad-libitum buffet meal to measure total caloric intake and macronutrient 
distribution in the chosen food. Satiation will be reported in calories consumed at fullness (satiation) [3]. 
t) Satiety by visual analog score postprandial after standard meal for GE and after to the Ad-libitum meal test for 
every 30 minutes for 2 hours [3]. Satiety will be measured in length of time of fullness. 
u) Self-administered questionnaires assessing affect, physical activity levels, attitudes, , body image, and eating 
behavior; details of each questionnaire are provided below. 
v) Samples collection, handling and storage: Samples were collected after an overnight fast (of at least 8 hours) in 
the morning. Plasma was preserved following standard guidelines and protein degradation inhibitors, kalikrein 
and DPP-IV inhibitors were added to preserve the samples. Samples are stored at -80ºC in the PI’s laboratory.  
a. Plasma gastrointestinal hormones (Total and active Ghrelin, GLP-1, CCK, PYY and bile acids) by 
radioimmunoassay, measured fasting, and 15, 45, and 90 minutes postprandial, with the primary endpoint 
being the peak postprandial level (test should be done simultaneously to GE).  
b. Targeted Metabolomics:  We will perform quantitative, targeted metabolomics of salient classes of 
compounds in plasma and saliva samples using mass spectrometry.  These assays are well-established, 
validated, and routinely performed in the Mayo Clinic Metabolomics Core Laboratory.   Amino acids plus 
amino metabolites will be quantified in plasma by derivatizing with 6-aminoquinolyl-N-hydroxysuccinimidyl 
carbamate according to Waters MassTrak kit.  A 10-point calibration standard curve will be used for 
quantification of unknowns using a triple-stage quadrupole mass spectrometer (Thermo Scientific TSQ 
Quantum Ultra) coupled with an ultra-performance liquid chromatography (UPLC) system (Waters Acquity 
UPLC). Data acquisition will be performed using multiple-reaction monitoring (MRM). Concentrations of 42 
analytes in each sample are calculated against their respective calibration curves with a measurement 
precision of < 5%.  Essential nonesterified fatty acid (NEFA) concentrations,  such as myristic, palmitic, 
palmetoleic palmitoelaidic, stearic, oleic, elaidic, linoleic, linolenic and arachidonic, will be measured against 
a six-point standard curve by LC/MS/MS, underivatized after extraction from plasma via negative 
electrospray ionization (ESI) and multiple reaction monitoring conditions. This technique was developed to 
replace the GC/MS method where NEFAs required methylation before analysis. This technique reduces the 
uncertainty as to whether the methylation step increases FFA concentrations by inadvertently hydrolyzing 
other lipid classes.   Intra CV is < 3% for all analytes.  
c. Blood DNA. 
w) Stool will be collected and stored to study microbiome, short chain fatty acids and bile acids.  
x) Saliva will be collected by passive drooling using a Saliva Collection aid from SalivaBio (State college, PA). Saliva 
sample will be stored at -80C for metabolomics and GI peptides testing.  
 
Sub-study at baseline and 10 weeks 
• 
Flexible Sigmoidoscopy visit: 
1. After an overnight fasting, participants will come to the CRTU in Charlton 7. 
2. Flexible sigmoidoscopy: It will be performed in the CRTU with a prior tap water enema by the CRTU 
nurse. Using standard biopsy forceps, 24 mucosal biopsies will be obtained each from the left colon 
(descending, sigmoid and rectum; 8 mucosal biopsies for each).  
• 
Standard EE-cell immunohistochemistry: Tissues and sorted cells will be processed by standard 
clinical methods as published previously [53, 54].  
• 
Flow cytometry - Fluorescence-activated cell sorting (FACS)[55]:  
• 
Purified EE-cells from each group (healthy, obesity without hungry gut and obesity with hungry gut) 
will be sorted to validate the cell counts, cell morphology, DNA, total RNA content, mRNA 
expression and protein concentration of GLP-1 and PYY. mRNA will be extracted from the EE-cells as 
described previously[56]. Protein will be studied as described previously by Dr. LaRusso [57]. 
Supernatants and lysates will be assayed for active GLP-1 and/or total PYY by ELISA (Millipore, USA). 
RNA and protein will be stored for further studies. Collected tissue will be used for Standard EE-cell 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 21 of 28 
 
immunohistochemistry, Flow cytometry - Fluorescence-activated cell sorting (FACS). EE cells sorted 
will be used for RNA, IHC and protein. 
• 
 
 
• 
Pseudo-continuous arterial spin labeling (pCASL) MRI visit 
1. After overnight fasting, participants will be provided a 300 kcal breakfast (breakfast granola bar and 
protein shake).  
2. Partipants will report to the Charlton LN or any other Mayo Clinic MRI facility four hours later and 
complete the MRI patient safety screening form 
3. pCASL MRI: (3 Tesla MRI scanner):  will be performed three times during the nutrient drink test 
(baseline, after reaching maximal fullness and 30 minutes after maximal fullness). A single experienced 
radiologist (JDP) will be blinded to the timing of the scans performed all the ROI analyses and the 
groups. 
4. Nutrient Drink test: using Ensure, Abbott Labs, Abbott Park, IL will be done as described previously [3]. 
The main outcomes will be volume to usual fullness (VTF), maximal tolerated volume (MTV) and 30 
minutes post-MTV. 
 
Participants, who are not compensated for participating in the study, will be compensated for completing each visit of 
the sub-study.  
 
Studies at 12-week visit:  
• 
Saliva, stool and fasting blood sample will be collected and stored. Stool will be used to measure microbiome, 
short chain fatty acids and bile acids (as above). Fasting saliva and blood will be used to GI hormones and 
metabolomics (as above).  
• 
 The DEXA scan (dual energy x-ray absorptiometry) (as above).  
• 
 Behavioral questionnaires 
 
Questionnaires to Assess GI Symptoms and Behavioral Disorders 
    Participants will complete a series of questionnaires (all included in the APPENDIX): Weight management 
Questionnaire (Mayo Clinic®) and the Hospital Anxiety and Depression Inventory [HAD [58]] to appraise the contribution 
of affective disorder. 
 
Behavioural Questionnaires 
a. AUDIT-C Alcoholism Screening Test [59] - The AUDIT-C is a 3-item alcohol screening questionnaire that reliably 
identifies participants who are hazardous alcohol drinkers or have active alcohol use disorders. This score will be used in 
screening by the study physician/nurse coordinator. The AUDIT-C is scored on a scale of 0-12. Each AUDIT-C question has 
5 answer choices. Points allotted are: a=0 points; b=1 point; c=2 points; d=3 points; e=4 points. In men, a score of 4 or 
more is considered positive, optimal for identifying hazardous drinking or active alcohol use disorders. In women, a 
score of 3 or more is considered positive (same as above).   
b.   Eating Disorders Questionnaire - The Questionnaire on Eating and Weight Patterns-Revised [60], is a valid measure of 
screening for eating disorders which has been used in several national multi-site field trials. Respondents are classified 
as binge eating disorder, purging bulimia nervosa, non-purging bulimia nervosa, or anorexia nervosa. We have used this 
instrument to screen for eating disorders in obese populations. 
c.   Body Image Satisfaction  - The Multidimensional Body-Self Relations Questionnaire [61, 62]provides a standardized 
attitudinal assessment of body image, normed from a national body-image survey. Items are rated on a 5-point scale, 
ranging from 1=Definitely Disagree to 5=Definitely Agree. In this study, we will use one of the sub-scales, the Body Areas 
Satisfaction Scale, which measures feelings of satisfaction with discrete aspects of physical appearance (e.g., face, 
weight, hair). Cronbach’s  values range from .70 to .89 [62]. 
d.   Eating Behaviors  -  The Weight Efficacy Life-Style Questionnaire [WEL [63]] is a 20-item eating self-efficacy scale 
consisting of a total score and five situational factors: negative emotions, availability, social pressure, physical 
discomfort, and positive activities. Subjects are asked to rate their confidence about being able to successfully resist the 
urge to eat using a 10-point scale ranging from 0=not confident to 9=very confident.  


Andres Acosta MD, PhD 
Mayo Clinic 
Page 22 of 28 
 
e.   Physical Activity Level - The four-item Physical Activity Stages of Change Questionnaire [64]will be utilized to assess 
the physical activity level of participants. Mayo Clinic investigators, led by co-investigator Dr. Clark, have used these 
items to explore the relationship between quality of life and physical activity in an NCI-funded study on long-term lung 
cancer survivors [64]. 
f. Exercise behavior- The Exercise Regulations Questionnaire (BREQ-3)[65] and its subsequent modifications have 
become the most widely used measures of the continuum of behavioural regulation in exercise psychology research. It 
has been used either as a multidimensional instrument giving separate scores for each subscale, or as a unidimensional 
index of the degree of self-determination. 
g. Barriers to Increasing Physical Activity Participation - Barriers to Being Active Quiz, What keeps you from being more 
active?[66]. 
h. Three Factor eating questionnaire is 51-item questionnaire, validated, to assess for emotional eating disorders and 
food cravings.  
i. Bowel Disease Questionnaire  
 
Standard of Care: 
All participants will received standard of care which consists of 1) Intense lifestyle intervention, behavioral evaluation 
and treatment, and a medication as part of the regular clinic management for obesity.  
Intense Lifestyle Intervention and Behavioral Treatment  
All the participants will meet the multidisciplinary team which consists of an Obesity Expert physician and a CRTU 
registered dietitian nutritionist as standard of care in our clinical practice.  These appointments will be scheduled in the 
CRTU. All participants will guided to 1) Nutrition: Reduce dietary intake below that required for energy balance by 
consuming 1200calories per day for women and 1400calories per day for men; 2) Physical Activity: reach the goal of 
10,000 steps or more per day; 3) Exercise: reach the goal of 150 minutes or more of cardiovascular exercise/week; 4) 
Limit consumption of liquid calories (i.e. sodas, juices, alcohol, etc.). All participants will receive a personal fitness 
tracker, where their activity and calories will be tracked. This information will be given in a booklet format.   
Pharmacotherapy for obesity 
Pharmacotherapy for the treatment of obesity can be considered if a patient has a body mass index (BMI) ≥ 30  kg/m2 or 
BMI >27 kg/m2 with a comorbidity such as hypertension, type 2 diabetes, dyslipidemia and obstructive sleep apnea[16]. 
Medical therapy should be initiated with dose escalation based on efficacy and tolerability to the recommended dose.  
We do an assessment of efficacy and safety at 4 weeks. In both groups, medications will be assessed for drug 
interactions and potential side effects as standard of care.  
Medication selection: Once the phenotype tests are completed the results will be filled in an algorithm to assist on the 
decision of the medication selection based on our previous data [3, 5, 11, 13]. The algorithm for phenotype selection will 
be based on the following decision tree (as figure below) 1) Participant will complete the ALL phenotype testing; 2) 
abnormal phenotype will be selected if participant meets criteria for one variable greater or lower than 90% of median 
(values described in table below); 3) if match to two or more abnormal 90% percentile) values, participant will be 
excluded; 4) if no abnormal (< or > 90%) value, the abnormal phenotype will be selected based on the value with < or > 
75%; 5) if there are two or more abnormal values (75% percentile), patient will be excluded; 6) if participants do not 
have any abnormal value (based upon 90% of 75%) will be excluded.      
TEST 
Abnormal result 
Example 
1 
Example 
2 
Example 
3 
Example 
4 
 
Females 
Males 
 
 
 
 
 
 (90%) 
 (75%) 
 (90%)  
 (75%) 
Female 
Male 
Male 
Female 
Satiation                 
(Ad libitum 
> 1065 
kcal 
> 894 kcal 
> 1962 
kcal 
>1376 kcal 1400 kcal 
1000 
kcal 
1100 
kcal 
850 kcal 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 23 of 28 
 
Buffet Meal) 
Satiety                
(Gastric 
emptying SGE 
T1/2) 
< 97 min 
< 101 min 
< 76 min 
< 86 min  
102 min 
80 min 
105 min 
110 min 
Behavioral Traits 
(Questionnaires)  
HADS > 9 
points 
HADS > 7 
points 
HADS > 
10 points 
HADS A > 
7 points 
5 
4 
9 
3 
Energy 
Expenditure 
(Resting EE) 
< 93% 
predicted 
< 96% 
predicted 
< 88% 
predicted 
<94% 
predicted 
102% 
98% 
95% 
92% 
Phenotype 
 
 
 
- 
Ab 
Satiation 
Ab 
Satiety 
Ab Psych 
Ab E.E. 
 
 
 
 
Once the decision is made on the “phenotype-guided” medication, pharmacy will assess whether patient is randomized 
to “intervention” or “control”. Based on the randomization, patient will pick up the prescription for 3 months. 
Phentermine prescribed subjects will be recommended to involve into resistance training routines. During the 3 month 
visit, participants will be offer a prescription to continue the medication (if randomized to the intervention group) or 
switch to the phenotype guided medication (if randomized to the control group). Patients who continue obesity 
pharmacotherapy will be contact every three months for one year to monitor their weight and comorbidities.  


Andres Acosta MD, PhD 
Mayo Clinic 
Page 24 of 28 
 
Control group: Pharmacotherapy for obesity 
Standard of care pharmacotherapy for obesity recommends the following doses and regimen for weight loss: 
- 
Phentermine: 15 mg oral daily 
- 
Phentermine-Topiramate Extended Release (Qsymia®) at dose of 7.5/46 mg oral daily 
- 
Oral naltrexone extended-release/bupropion extended-release (NBSR; Contrave®) at dose of 32/360 mg oral 
daily (divided in 2 tables in morning and 2 tablets in evening) 
- 
Liraglutide (Saxenda®) at dose of 3 mg subcutaneous daily  
 
There is currently no gold-standard or first choice for obesity pharmacotherapy and physicians select the medication to 
use on their patients based on comorbidities, previous experience, safety or adverse events. Thus, in this protocol, the 
FDA-approved medications will be randomly selected. The physician will review the “selection” to assess for potential 
contraindications, adverse events and/or drug-drug interactions per inclusion and exclusion criteria.  
Intervention group: by obesity phenotype guided pharmacotherapy 
Participants in the intervention group will have 4 tests to assess 1) satiation, 2) Satiety/return to hunger, 3) behavioral, 
or 4) energy expenditure. As described on Figure 8 pharmacotherapy will by guide based on the “abnormal” phenotype 
(following algorithm described above). In case of a mixed pattern or multiple abnormal phenotypes, patient will be 
excluded from study and referred to weight management clinic.  
Algorithm diagnostic:  
1. satiation: Phentermine-Topiramate Extended Release (Qsymia®) at dose of 7.5/46 mg oral daily  
2. Satiety/return to hunger:  Liraglutide 3 mg SQ daily 
3. Behavioral/Psychological: Oral naltrexone extended-release/bupropion extended-release (NBSR; Contrave®) at 
dose of 32/360 mg oral daily (divided in 2 tables in morning and 2 tablets in evening); or 
4. Energy expenditure: Phentermine 15 mg daily plus increase physical activity and resistance training.  
 
General Principles of Statistical Analyses  
 
Primary endpoint: Total Body Weight Loss, kg (defined as weight changed from baseline to 12 weeks) in the obesity 
phenotype-guided pharmacotherapy (intervention) vs. the randomly assigned pharmacotherapy (control) group in 
patients with obesity and an abnormal obesity-related phenotype.  
The secondary end points will be percentage of responders (defined as number of participants who loss 5% or more of 
total body weight) compared to baseline in the obesity phenotype guided pharmacotherapy (intervention) group vs. 
standard of care at 4 and 12 weeks; percentage of responders with at least 10 and 15% at 12 weeks, and 10% at 6 
months and 12 months; percentage of responders at 5%, 10% and 15%; percentage of responders within each obesity-
phenotype group at 4 and 12 weeks; side effects of medications, pharmacogenomics role to weight loss,side effect and; 
changes in blood flow in the brain areas, and transcriptomic changes in colonic mucosa.; the performance of the PHENO-
Test in predicting the obesity phenotype and the weight loss outcome based on the  test when comparing phenotype-
guided intervention vs. controls. In the open-label extension, we will assess the total body weight loss at 24 and 52 
weeks in both groups.  
 
Statistical Analyses: We propose a randomized, double-blinded, active controlled trial of 200 participants with obesity 
to compare effects of Intervention compared to controls in weight loss. The analysis will involve an ANCOVA models, 
with the response being actual weight change; the covariates to be considered include gender, and weight at baseline.    
Sample size assessment and power calculation: The detectable effect size in weight loss between groups of interest 
(intervention vs. control) is given in the table below. In our recent pilot study [with Liraglutide 3.0 mg vs. placebo], the 
SD for the overall weight change (pre-post) observed was 2.8kg [32]. Using this SD, we have estimated the differences 
between groups that could be detected with approximately 80% power (2-sided α level of 0.05) for main effects.  Thus, 
the sample size needed is 87 participants per group. In order to account for a maximum dropout rate of 13%, we will 
randomize 100 participants per group. An interim assessment will be done when 50% of the patients have completed 
the study for the purposes of assessing data quality and the power calculation assumptions.  Specifically, that the weight 
change standard deviation is 2.8 and the dropout rate is 10-13%.  No calculation of the treatment difference will be 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 25 of 28 
 
done at this assessment.  Any suggested revision of the power and sample size calculation based on the standard 
deviation or dropout rate will be shared with the investigative team - possibly increasing the planned study 
enrollment.  We have no intention of completing the study with less than the original sample size of 100 per group. In 
the subaim, we will use an ANCOVA to study 20 participants with phenotype-guided pharmacotherapy and compared to 
20 participants randomly assigned pharmacotherapy adjusting for their baseline value as a covariate. Additionally, we 
will study the changes of each drug on treatment compared to baseline using a paired t-test. We noticed a 20% 
withdrawal rate during the study, we propose to extend to 250 participants enrolled and randomized to reach the 100 
participants per group (total of 200 participants) who have completed the study.  
 
 
 
 
 
 
 
 
 
 
Anticipated results and significance:  
Our study individualizes obesity treatment to maximized pharmacotherapy outcome based on phenotyping obesity at 
baseline. 
 
Potential pitfalls, precautions taken, and alternative strategies: 
a. Feasibility - Given high volume of patients interested in weight loss, we are confident we will recruit sufficient 
participants for these studies that involve only noninvasive tests and standard of care treatment. 
b. Statistical power has been addressed with appropriate sample sizes to demonstrate a difference in weight change 
on NBSR with and with phenotype vs. placebo. 
 
 
Mean difference (Δ) of total body weight loss in 
controls group (mean average 6.1 kg) vs. 
intervention group. 
Intervention 
(# of participants) 
Control 
(# of participants) 
Mean difference of 10% [6.7 vs. 6.1kg) 
343 
343 
Mean difference of 20% [7.3 vs. 6.1kg) 
87 
87 
Mean difference of 30% [7.9 vs. 6.1kg) 
39 
39 


Andres Acosta MD, PhD 
Mayo Clinic 
Page 26 of 28 
 
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