Design of a Genetic Score to Predict the Response to a Dietary Intervention in Adults With Metabolic Syndrome
Study Details
Study Description
Brief Summary
The aim of this study is to evaluate whether a genetic score based on genetic variants related to amino acid metabolism could predict the response to a dietary intervention in adults with metabolic syndrome.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
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N/A |
Detailed Description
Metabolic syndrome (MetS) results from the interaction between genetic and environmental factors. Single nucleotide polymorphisms (SNPs) are within the genetic factors. Various SNPs influence amino acid metabolism, and therefore their plasma concentrations. For example, the presence of SNPs such as rs10211524 (SLC1A4), rs9637599 (PPM1K), rs7406661 (ASGR), rs4788815 (TAT), rs199999090, rs11548193 (BCAT2), and rs45500792 (BCKDH), among others, have been related to alterations in the plasma concentration of amino acids. High plasma concentration of amino acids, specifically of branched chain amino acids (BCAA), have a positive association with the presence of different risk factors for MetS including waist circumference, dyslipidemia, blood pressure, glucose concentration and insulin resistance (IR). Moreover, subjects with MetS have a plasma BCAA concentration of up to 34% higher than subjects without MetS.
In the other hand, dietary interventions are among the environmental factors that can prevent MetS. For example, the National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III) in the United States recommends a low saturated fat diet (LSFD) to reduce LDL cholesterol. Although, this recommendation has been suggested to attenuate some of the metabolic abnormalities in individuals with MetS, there is no biological marker that can identify individuals who will respond to a LSFD. Notably, the presence of SNPs could help to identify those individuals. The clinical effects exhibited by SNPs when analyzed individually are generally small. For this reason, it has been sought to evaluate the contributory effects of multiple SNPs by means of a genetic score. The construction of a genetic score could capture the complex relationship between MetS, genetics, and dietary interventions, providing us with a greater understanding of the biochemical and metabolic alterations and responses to available treatments. Furthermore, a genetic score could have a therapeutic value in predicting the response to a dietary intervention in subjects with risk factors for MetS. Predicting the response to a dietary intervention may help implement individualized diets based on the genetic predisposition and clinical characteristics of each individual, showing beneficial effects on anthropometric, clinical and biochemical markers. Likewise, implementing dietary interventions for preventive purposes for complex diseases could minimize public health expenditures.
Adults will be invited to participate through advertising distributed in the City of San Luis Potosí, Mexico. Those interested in participating will be given a short telephone interview to verify that they meet the selection criteria. Then, an appointment will be scheduled to go to the Faculty of Chemical Sciences of the Autonomous University of San Luis Potosí (UASLP). During this visit, participants will be informed of the characteristics of the study, the risks and the benefits expected after the dietary intervention. Those who accept to participate will sign the consent letter. Then a clinical a nutritional assessment will be performed. A blood sample and blood pressure will be taken by a specialist. Anthropometric and body composition measurements will be made. An history of food consumption frequency will be obtained by a nutritionist. The physical activity questionnaire will be carried out (IPAQ long version). The patient will be advised not to change the level of habitual physical activity. Participants will be then assigned a diet for two months following the indications of the National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III) program. The follow-up of the diet will be evaluated by telephone by a nutritionist who will carry out 24-hour reminder questionnaires randomly every 15 days to each participant. After the first visit, participants will start consuming the diet corresponding to their group. The different menus will be delivered and explained to them. A food guide will be given so that they have food exchange options. Patients will be taught to fill the feed log and will be cited in two months.
During the second visit, we will collect a 24-hour dietary record, food logs and we will perform a second clinical and nutritional assessment, including the determination of anthropometric measurements such as weight, waist circumference and body composition, whole blood sample and blood pressure will be taken. The physical activity questionnaire will be carried out (IPAQ long version). Finally, participants will be scheduled within fifteen days for delivery of results and to explain the actions that will be carried out at the end of the study to maintain the continuity of the treatment.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Experimental: Dietary Intervention Participants will be assigned a diet for two months following the indications of the National Cholesterol Education Program Adult Treatment Panel III program. |
Other: ATP III dietary intervention
The dietary intervention will consist of an approximate decrease of 500 kcal from the calories participants habitually consume, with the following macronutrient distribution 15-20% protein, 50-60% carbohydrates, 25-35% fat. Participants will receive recipes with menus for two weeks.
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Outcome Measures
Primary Outcome Measures
- Change in waist circumference [Baseline to 2-month]
Change in waist circumference before and after the dietary intervention (cm)
- Change in serum glucose [Baseline to 2-month]
The concentration of serum glucose will be determined by an autoanalyzer before and after the intervention
- Change in serum HDL cholesterol [Baseline to 2-month]
The concentration of serum HDL-cholesterol will be determined by an autoanalyzer before and after the intervention (mg/dL)
- Change in serum triglycerides [Baseline to 2-month]
The concentration of serum triglycerides will be determined by an autoanalyzer before and after the intervention (mg/dL)
- Change in systolic and diastolic blood pressure [Baseline to 2-month]
The blood pressure will be determined before and after the intervention (mmHg)
Secondary Outcome Measures
- Change in the serum amino acid profile [Baseline to 2-month]
The concentration of the amino acid profile will be determined by HPLC before and after the dietary intervention
- Change in body composition [Baseline to 2-month]
Change in the percentage of fat mass, lean mass and skeletal muscle mass before and after the dietary intervention.
- Change in body weight [Baseline to 2-month]
The change in body weight before and after the dietary intervention.
- Change in serum insulin [Baseline to 2-month]
The concentration of insulin will be determined by ELISA before and after the dietary intervention
- Change in serum leptin [Baseline to 2-month]
The concentration of leptin will be determined by ELISA before and after the dietary intervention
- Change in serum glucagon [Baseline to 2-month]
The concentration of glucagon will be determined by ELISA before and after the dietary intervention
- Change in serum adiponectin [Baseline to 2-month]
The concentration of adiponectin will be determined by ELISA before and after the dietary intervention
- Change of insulin resistance by HOMA index [Baseline to 2-month]
The HOMA index will be calculated as follows: glucose (mg / dl) x insulin (mUI / ml) / 405 before and after the dietary intervention
- Change of Body mass index [Baseline to 2-month]
The body mass index will be calculated before an after the dietary intervention.
Eligibility Criteria
Criteria
Inclusion Criteria:
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Adults (men and women) between the ages of 18 and 60.
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Adults mexican mestizos (parents and grandparents born in Mexico).
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Adults who can read and write.
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Adults willing/able to provide informed consent.
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Adults with obesity (BMI ≥ 30 and ≤ 39 kg / m2).
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Adults with at least one of the metabolic syndrome diagnostic criteria:
Waist circumference: men > 102 cm or women > 88 cm. Hypertriglyceridemia >150 mg/dL High fasting glucose >100 mg/dL High blood pressure ≥ 130/85 mmHg Low HDL-cholesterol: men <40 mg/dL and women < 50 mg/dL
Exclusion Criteria:
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Adults with any type of diabetes.
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Adults with hypertension.
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Adults with kidney disease diagnosed by a medical or with creatinine> 1.3 mg / dL for men and > 1.1 mg / dL for women and / or BUN> 20 mg / dL.
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Adults with acquired diseases that produce obesity and diabetes secondarily.
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Adults who have suffered a cardiovascular event.
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Adults with weight loss > 3 kg in the last 3 months.
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Adults with any catabolic diseases such as cancer and/or AIDS.
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Gravidity status
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Adults who smoke
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Adults in treatment with any medication
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubiran. | Mexico City | Mexico | 14080 |
Sponsors and Collaborators
- Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran
- Universidad Autonoma de San Luis Potosí
Investigators
None specified.Study Documents (Full-Text)
None provided.More Information
Publications
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- Mahendran Y, Jonsson A, Have CT, Allin KH, Witte DR, Jørgensen ME, Grarup N, Pedersen O, Kilpeläinen TO, Hansen T. Genetic evidence of a causal effect of insulin resistance on branched-chain amino acid levels. Diabetologia. 2017 May;60(5):873-878. doi: 10.1007/s00125-017-4222-6. Epub 2017 Feb 10.
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- Teslovich TM, Kim DS, Yin X, Stancáková A, Jackson AU, Wielscher M, Naj A, Perry JRB, Huyghe JR, Stringham HM, Davis JP, Raulerson CK, Welch RP, Fuchsberger C, Locke AE, Sim X, Chines PS, Narisu N, Kangas AJ, Soininen P; Genetics of Obesity-Related Liver Disease Consortium (GOLD), The Alzheimer's Disease Genetics Consortium (ADGC), The DIAbetes Genetics Replication And Meta-analysis (DIAGRAM), Ala-Korpela M, Gudnason V, Musani SK, Jarvelin MR, Schellenberg GD, Speliotes EK, Kuusisto J, Collins FS, Boehnke M, Laakso M, Mohlke KL. Identification of seven novel loci associated with amino acid levels using single-variant and gene-based tests in 8545 Finnish men from the METSIM study. Hum Mol Genet. 2018 May 1;27(9):1664-1674. doi: 10.1093/hmg/ddy067.
- Wang TJ, Larson MG, Vasan RS, Cheng S, Rhee EP, McCabe E, Lewis GD, Fox CS, Jacques PF, Fernandez C, O'Donnell CJ, Carr SA, Mootha VK, Florez JC, Souza A, Melander O, Clish CB, Gerszten RE. Metabolite profiles and the risk of developing diabetes. Nat Med. 2011 Apr;17(4):448-53. doi: 10.1038/nm.2307. Epub 2011 Mar 20.
- FNU-3813-21-22-1