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INFLUENCE OF OBESITY-RELATED GENOTYPE ON WEIGHT LOSS SUCCESS AND BODY COMPOSITION CHANGES WHILE
PARTICIPATING IN A 3-MONTH EXERCISE AND WEIGHT LOSS PROGRAM: PRELIMINARY FINDINGS
A Coletta1, B Sanchez1, A O'Connor1, R Dalton1, S Springer1, M Koozehchian1, Y P Jung1, S Simbo1, M Cho1, C Goodenough1, A Reyes1, E Galvan1, K Levers1, L Wilkins2,
C Rasmussen1 and R Kreider1. 1Exercise & Sport Nutrition Lab, Texas A&M University, College Station, TX and 2Functional Genetics, Interleukin Genetics, Waltham, MA.
Abstract
Purpose
This study examined whether genotype of some obesity-related
genes (FABP2, PPARG, ADRB2-79, ADRB2-46, ADRB3) influences success to different diets while participating in an exercise program. 40 sedentary women (41±13 yrs, 35.8±7.9 kg/m2)
were matched according to genotypes favoring carbohydrate
restricted and less restricted diets. Diets were 1,500 kcal/d with
20:35:45 and 30:25:45 percentages of C:F:P. Participants performed a circuit style resistance-exercise program (4 d/wk) and
a walking program (10,000 steps/d, 3 d/wk). Body weight and
DEXA body composition measures were obtained at 0, 4, 8, &
12, wks, analyzed by MANOVA, and are presented as changes
from baseline after 12 wks. An overall Wilks' Lambda
time x genotype trend was observed (p=0.08) with no time x diet
effects (p=0.57). Univariate analysis revealed significant differences between true (T) and false (F) matched genotype groups
in fat mass (T: -3.81±2.5, F: -1.92±3.2 kg; p=0.013), fat free
mass (T:-0.76±1.8, F: -2.16±2.3; p = 0.042) and body fat
(T: -2.15±2.3, F: 0.01±2.1 %; p=0.002) with no differences in
changes in body weight (T: -4.33±3.6, F: -3.91±3.9 kg, p=0.36).
These preliminary findings suggest that women participating in
a diet and exercise program may experience greater improvements in body composition when diet type is aligned with their
genetic profile. Supported by Curves International (Waco, TX) &
Interleukin Genetics (Waltham, MA)
To determine if use of the selected genetic profile for personalized nutrition is effective in promoting weight loss and improvements in body composition
Rationale
Obesity is attributed to an interaction among physiological, metabolic, behavioral, social, and genetic factors.1 Countless genes
related to obesity have been identified through Genome Wide
Association Studies.2-5 The use of genetic profiling to predict
clinical outcomes is used frequently in oncology and is helpful
for determining optimal treatment.6 Regarding weight management, the use of genetic profiling for personalized nutrition is
relatively new. Five variants among the following four candidate
genes, PPARG, FABP2, PPARG, ADRB2, and ADRB3, have
demonstrated a significant relationship between response to
diet/exercise interventions and changes in body weight.7 Thus
the aforementioned candidate genes may serve as an effective
genetic profile for weight loss. A previous investigation retrospectively assessed this genetic profile in response to a diet
and exercise intervention and found significant changes in
weight favoring true genotype match to diet and exercise intervention.8 Further research is warranted with use of this genetic
profile in a weight loss intervention.
Methods & Procedures
Results




Significant differences in change in fat mass (FM), fat free
mass (FFM), and body fat percentage (BF%) favoring true
genotype match (p < 0.05) FM: T: -3.81±2.5, F: -1.92±3.2 kg (p = 0.013) FFM: T:-0.76±1.8, F: -2.16±2.3 (p = 0.042) BF%: T: -2.15±2.3, F: 0.01±2.1 % (p = 0.002) Conclusions & Applications

Preliminary findings suggest that overweight/obese women
participating in a diet and exercise program may experience
greater improvements in body composition when following a
diet that aligns with their genotype.

Preliminary findings support use of the selected genetic profile for diet matching and personalized nutrition in weight
management of overweight/obese women.
Participants
 40 sedentary women (41±13 yrs, 35.8±7.9 kg/m2)
 Participants were informed of experimental procedures and
signed a consent statement in adherence with the human
subject guidelines of Texas A&M University.
 Review of results from a standard medical exam and medical history was performed by a research RN for clearance to
participate in study.
Diet Groups
 Prospective matching to diet based on genotype. Half true
genotype matches to diet group, half false genotype
matches to diet group.
 1500 kcal per day, 20% kcal CHO, 35% kcal fat, 45% kcal
protein
 1500 kcal per day, 30% kcal CHO, 25% kcal fat, 45% kcal
protein
Exercise
 Curves® exercise program consisted of a 30-min resistance

based circuit interspersed with calisthenic exercises or Zumba
4 days per week.
10,000 steps per day , 3 days per week (days participants
were not exercising on the circuit)
Acknowledgements and Funding
www.exerciseandsportnutritionlab.com
Supported by Curves International (Waco, TX) & Interleukin
Genetics (Waltham, MA)
Measures
 Body weight and DEXA body composition was measured at
baseline, 4, 8, and 12 weeks References
Statistical Analysis
1.
Data were analyzed by MANOVA with repeated measures, using
IBM SPSS for Windows version 22.0 software (Chicago, IL). Data is
presented as changes from baseline after 12 weeks for true genotype match versus false genotype match to diet. 2.
3.
4.
Results
5.


Time x genotype trend (p = 0.08) was observed with no time
x diet effect (p 0.57) No difference in change in body weight (T: -4.33±3.6,
F: -3.91±3.9 kg, p = 0.36) 6.
7.
8.
Kotsis V SS, Papakatsika s, Rizos Z, Gianfranco P. Mechanisms of obesityinduced hypertension. Hypertension Research. 2010;33:386-393.
Willer CJ, et al. Genetic Investigation of Anthropometric Traits Consortium.
Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nat Genet. 2009;21(1):25-34.
Thorleifsson G, et al. Genome-wide association yields new sequence variants at seven loci that associate with measures of obesity. Nat Genet.
2009;41(1):18-24.
Speliotes EK, et al. Association analyses of 249,796 individuals reveal 18
new loci associated with body mass index. Nat Genet. 2010;42(11):937948.
Fox CS, et al. Genome-wide association for abdominal subcutaneous and
visceral adipose reveals a novel locus for visceral fat in women. PLoS
Genet. 2012;8(5).
Mutch DM TM, et al. Adipose gene expression prior to weight loss can
differentiate and weakly predict dietary responders. PLoS One. 2007;2
(12):e1344.
The science behind the weight management genetic test.
www.inherenthealth.com/media/4759/wm_scientific%20summary.pdf
Dopler-Nelson M PP, Kornman K, Gardner C. Genetic phenotypes predict
weight loss success: the right diet does matter. AHA Abstracts. 2010:79-80.