Molecular Mechanisms of Exercise Benefits to Insulin Resistant People
Phase: NA
Conditions: Insulin Resistance, Obesity
Sponsor: Mayo Clinic

Study Protocol and Statistical Analysis Plan  
Last update: 12 November 2025 by Kyle Sevits 
 
Introduction  
This section outlines the key statistical considerations for the human studies aspects of 
the grant proposal. For each of our specific aims we provide outlines for the analysis 
plans, along with corresponding rationale for choice of study deign with associated 
sample sizes.  
 
Study Design  
The main study design is that of randomized clinical trial assessing the effects of 3 
months of resistance exercise (RE) training relative to a sedentary control (SC) 
condition in insulin resistant (IR) study volunteers. A total of 48 IR individuals meeting 
inclusion/exclusion criteria as outlined in the application will be enrolled. Baseline 
measures will be obtained after which they will be randomized in a 2:1 ratio to RE 
(n=32) versus SC (n=16). After 3 months, baseline measures will be repeated, with the 
expectation of improvements in measures in the RE-trained arm.  
We will additionally recruit a group of 16 insulin sensitive (IS) individuals, in whom the 
same measures will be obtained, at baseline only.  
 
Rationale for Randomized Trial Design  
Initially it may seem that a single arm study whereby all individuals receive RE training 
would be sufficient to answer the questions of interest; however, by including a 
sedentary control group, if measures increase in the RE-trained group, but not in the SC 
group, we will have more confidence that the training is causative of the changes. It is 
possible that some measures may change over time, for example consequent to 
seasonal effects.  
Rationale for Randomization Ratio  
 
In order to be as efficient in our design, we propose a 2:1 randomization ratio; we 
devote relatively more resources to the RE training arm, as the individuals receiving RE 
training are of primary interest. In addition to learning whether our measures of interest 
change over time in this group (and relative to the sedentary control group), we will seek 
to explore the extent to which changes in some measures relate to others and this will 
benefit from as large a sample size as possible; in contrast there is relatively little to be 
learned from the control group other than to check that there are no changes of 
consequence over the 3 month study time period in this group.  
 
Rationale for Insulin Sensitive Comparator Group  
The premise underlying the proposal is that insulin resistance can to some extent be 
ameliorated by RE training. It is thus important to demonstrate that (i) key measures of 
interest actually do differ in IR people compared to IS people, and (ii) that any changes 
in these measures with RE training do indeed differ in the expected direction – closer to 
those of IR people. Although we do not dramatic changes with only 3 months of training, 
it will be of additional benefit to be able to quantify, even if informally, the proportional 

extent to which improvements can be made in measures relative to the group of IS 
people that we recruit.  
 
Procedures for Randomization and Blinding 
We will create a dynamic randomization allocation algorithm structured to minimize 
imbalance with respect to key baseline variables including age and sex. This will be 
implemented with a web interface in a SAS application with restrictions so that access is 
granted only on a need-to-know basis. The study statistician will be able to monitor 
assignments globally to ensure the algorithm is working appropriately and the study 
coordinator (with a back-up) will be able to log in to access randomization assignment 
for each individual study participant on a prospective basis. All members of the research 
team involved in obtaining any of the measures will be blinded (to the extent possible) to 
the assignment of individuals to study arms. Those study team members involved in 
training will, of course, not be blinded. Randomization assignment data will be merged 
with the rest of the study data according to study identification numbers only as needed 
for analysis, otherwise they will remain separate until the studies are completed. 
 
Statistical Analysis 
Aim 1 - Change in muscle strength 
Endpoint: Δ(1RM normalized to lean mass) = [1RM at 3 months / DEXA lean mass at 3 
months] − [1RM at baseline / DEXA lean mass at baseline]. 
Primary analysis: Two-sample t-test (RE vs SC) on Δ normalized 1RM. 
 
Aim 2 - Change in insulin sensitivity 
Endpoint: Δ(Insulin AUC) where AUC (μIU·min/mL) is computed from time points −20, 0, 
10, 20, 30, 60, 90, 150, 240 min using the trapezoidal rule.  
Primary analysis: Two-sample t-test (RE vs SC) on ΔAUC. 
 
Aim 3 - Change in lean mass 
Endpoint: Δ total lean mass (kg) by DEXA. 
Primary analysis: Two-sample t-test (RE vs SC) on Δ lean mass. 
 
Aim 4 - Change in body fat percentage 
Endpoint: Δ total body fat percentage by DEXA. 
Primary analysis: Two-sample t-test (RE vs SC) on Δ fat %. 
 
Aims 1-4 data will be presented as mean Δ±SD in RE vs SC and p-value.