Effects of Divalproex Sodium on Food Intake, Energy Expenditure, and Posture Allocation

The purpose of the proposed study is to identify the mechanisms responsible for the weight gain associated with Depakote treatment, and to identify methods to prevent and treat weight gain in people taking Depakote. Both sides of the energy balance equation will be measured in a sample of healthy lean and overweight adults. Energy intake will be measured in the Pennington Center's Eating Laboratory, and total daily energy expenditure (TEE) and posture allocation will be measured with the IDEEA™. Questionnaires that assess food cravings and eating attitudes and behaviors will be used to determine if a behavioral phenotype is associated with weight gain in response to Depakote treatment. It is hypothesized that Depakote treatment will result in increased food intake. It is also hypothesized that the time spent engaging in sedentary behavior will increase in response to Depakote treatment. Time spent engaging in, and the energy expended during, physical activity is expected to decrease significantly. Therefore, it is hypothesized that TEE is expected to decrease significantly. The results will be used to identify specific behavioral targets to prevent weight gain during treatment with Depakote. Potential targets include interventions to modify food intake and physical activity. The degree to which each behavior (food intake or physical activity) will be targeted is dependent on the results of this study. For instance, if the majority of the weight gain associated with Depakote treatment is due to changes in food intake, stronger dietary interventions will be suggested. Additionally, changes in endocrine factors (hormones and peptides) will be evaluated during the study to determine if Depakote is associated with an altered endocrine response that affects satiety, food intake, or energy expenditure. If an altered endocrine response is found, these results will be used to identify adjunctive medications or compounds to correct the endocrine response and reduce weight gain. Genomic studies will also be possible, since gene sequencing and gene expression can be analyzed from archived buffy coat samples.

Depakote (Abbott Laboratories, Abbott Park, IL) is an anti-convulsant medication used to treat epilepsy \[1\] and mania associated with bipolar disorder \[2, 3\]. Depakote also is used as a prophylaxis for migraine headache \[4\]. One side effect of Depakote that negatively influences its appeal to health care professionals and consumers is weight gain. It is unknown if changes in energy intake, energy expenditure, or a combination of both are responsible for this side effect. The purpose of the proposed study is to: 1) test if Depakote increases body weight by increasing food intake or decreasing energy expenditure, possibly through changes in posture allocation, and 2) identify methods to prevent and treat weight gain in people taking Depakote. This randomized placebo-controlled trial will measure both sides of the energy balance equation (energy intake and expenditure), and posture allocation (the time spent in active and sedentary behaviors, and the energy cost of these behaviors). Measurement of both total daily energy expenditure (TEE) and posture allocation provides a powerful tool to determine if Depakote decreases energy expenditure by increasing the time spent in sedentary behavior. These data, along with the food intake data, provide a test of the mechanisms responsible for weight gain associated with Depakote, and these data can identify methods to prevent or treat this weight gain.

Divalproex sodium is a co-ordination compound consisting of sodium valproate and valproic acid. The exact mechanism of action of Depakote is unknown, but it is believed to increase brain concentrations of gamma aminobutyric acid (GABA). Similarly, the mechanism by which Depakote increases body weight is not understood. The balance between energy intake and expenditure influences body weight; therefore, Depakote likely alters energy intake, energy expenditure, or both. Alterations in energy intake or expenditure can result from, or be associated with, changes in biological mechanisms, including hormone and peptide levels. To our knowledge, only one study has tested the effects of a compound containing valproic acid on energy intake and expenditure, but this study was small (n = 8), uncontrolled, and used methods to measure energy intake (food records and recall) that were unlikely to detect changes in such a small sample \[5\]. The study proposed herein is the first study to test the effects of Depakote on eating behavior, measured in the laboratory, and energy expenditure and posture allocation, measured with the Intelligent Device for Energy Expenditure and Activity (IDEEA™; MiniSun LLC, Fresno, CA).

In vitro, leptin secretion and mRNA levels in adipocytes decrease in response to valproic acid, and it is believed that altered leptin levels might influence weight gain in people taking compounds containing valproic acid \[6\]. Other researchers have reported that postprandial insulin and proinsulin levels increase in people taking valproic acid, and BMI is positively related to two-hour postprandial levels of insulin, proinsulin, and C-peptide \[7\]. Luef and colleagues indicate that treatment with valproic acid might increase glucose stimulated pancreatic section, which could be related to higher body weight due to two factors that are related to pancreatic beta-cell regulation and insulin secretion. First, valproic acid is a free-fatty acid (FFA) derivative that competes with FFAs for albumin binding, and, second, valproic acid is a GABA agonist. Thus, valproic acid treatment might increase glucose stimulated pancreatic secretion and contribute to weight gain. Evidence from other laboratories suggests that valproic acid treatment in children increases insulin levels and decreases glucose levels, which might stimulate appetite \[8\]. Importantly, Demir and Aysun note that carnitine levels did not correlate with weight gain, suggesting that valproic acid induced weight gain is not due to impairments in beta-oxidation of fatty acids. Carnitine is involved in the transfer of fatty acids into the mitochondria for beta-oxidation. Due to the potential role of FFA and valproic acid in influencing pancreatic beta-cell regulation and insulin secretion, FFA will be measured in the present study at baseline (day 0) and day 21, ½ hour before and one hour after the food intake tests at lunch.

Due to the likelihood that hormones and peptides influence the weight gain associated with Depakote, blood samples will be archived for later analysis, pending availability of funds. Specifically, a portion of the archives will be used to measure gastric inhibitory polypeptide (GIP) and oxyntomodulin. Oxyntomodulin and GIP will not be assayed immediately because commercially available assay kits are not yet available. Oxyntomodulin has been implicated in the control of food intake and satiety in both humans and animals \[9\], and GIP modulates insulin secretion and might provide new treatments for diabetes \[10\]. Additionally, levels of PYY3-36, glucagon-like peptide-1 (GLP-1), leptin, and ghrelin will be measured. PYY3-36 and GLP-1 are distal gut hormones that have been found to reduce food intake \[9, 11\]. PYY3-36 decreases food intake by 30% when infused into humans \[11\], and obese humans and rodents have attenuated fasting and post-prandial PYY3-36 levels that are likely associated with their obesity \[12\]. GLP-1 also decreases food intake in rodents and man, and it works synergistically with PYY3-36 \[13\]. Leptin reduces food intake \[14\] and increases energy expenditure in humans \[15\], while ghrelin increases food intake and is likely an important regulator of food intake \[16\].

The aforementioned hormones will be sampled ½ hour before and one hour after the start of the food intake tests at lunch on days 0 and 21. The timing of these samples is based on the finding that PYY3-36 and GLP-1 peak one hour after a meal \[17, 18\]. Therefore, we will compare levels prior to meals and the change after the meals between the Depakote and placebo groups. Different pre-meal levels of these hormones and peptides can be correlated with food intake between the groups, and differential change in these hormones in response to the meal will be evaluated between the groups and correlated with food intake.

Two factors that likely affect the amount of weight gain with Depakote treatment are gene sequencing and gene expression. Although these analyses can be costly, DNA material, including RNA, can be archived from whole blood samples and stored for later analysis. This method allows cost to be controlled since analyses can be conducted on a sub-sample of the participants who displayed specific reactions to treatment during the study. For example, genomic studies can be conducted on participants who fall within the lower and upper quartiles of weight gain, or a sub-sample of participants from the placebo and treatment groups. This provides empirical tests of a priori stated hypothesis without the need to endure the costs of running genomic analyses on the entire sample of participants. In the present study, both gene sequencing and gene expression studies will be made possible by archiving blood samples, as outlined in the Methods section. These analyses will depend on the availability of funds and the development of specific testable hypotheses (e.g., weight gain in the Depakote group will be associated with the peroxisome proliferator-activated receptor-gamma gene).

Eligibility Criteria:
Inclusion Criteria:

1. Healthy male or female, age 18 to 54 years
2. 20 \< Body Mass Index (BMI, kg/m2) \< 30
3. Willing to have a blood sample stored for possible future genetic testing

Exclusion Criteria:

1. For females, pregnant or unwilling to use an effective form of contraception while on this study (hormonal methods like birth control pills, implants or shots; barrier methods like condoms or diaphragms with foam; surgical sterilization; or abstinence)
2. For females, use of any other oral contraceptive other than monophasic oral contraceptives
3. For females, irregular menstrual cycles
4. For females, history of partial hysterectomy
5. For females, nursing
6. For females, history of polycystic ovarian syndrome
7. Aspirin use or the refusal to abstain from aspirin use during the study
8. Current or history of urea cycle disorders
9. Tobacco users
10. Use of anti-convulsant medication
11. Use of barbiturates, such as Phenobarbital
12. Use of tranquilizers, such as Xanax and Valium
13. Use of blood thinners, such as Coumadin
14. Use of anti-depressant medication
15. Liver disease or impaired liver function
16. History of pancreatitis
17. Regular (4 or more days per week) consumption of 3 or more alcoholic beverages a day
18. Refusal to abstain from alcohol intake during the study
19. Dietary restraint score \> 14 or disinhibition score \> 12 on the Eating Inventory \[19\]
20. Dislike or allergy to the food used during the food intake tests
21. Unwilling to wear an IDEEA™ during the study
22. Unwilling to wear an accelerometer during the study