by Corie Edwards, ND

Using a patient’s genetic code to both treat and prevent disease is nothing new.  However, practitioners are now finding that genetic testing can act as an excellent clue for patients who may not respond to traditional treatment. These patients may have unique reactions to medications, high blood pressure or history of stroke at a young age, or who struggle losing weight.  Genome-wide association studies have found several genes that are linked to increased body mass index (BMI) and blood sugar dysregulation. Knowing a patient’s phenotype for weight gain can be the key to unlocking the mystery of a patient’s health.

Genetic testing is on the rise as research identifies significant connections between certain allelic variations in the genetic code and disease states.  Through improved understanding of medical conditions on a deeper level, it is now possible to relate the uniqueness of each patient to an informative test result.

Genetic testing identifies individual potential biochemical interactions, and allows practitioners to develop targeted treatment plans.  As more significant, clinically useful information is becoming available, medicine is at the cusp of a new way to work with patients.

Genome wide association studies have identified several key genes involved in increased BMI and blood sugar dysregulation.  These include human fat mass gene (FTO), Melanocortun 4 Receptor (MC4R), Fatty Acid Binding Protein 2 (FABP2), Beta-2 Adrenergic Receptor (ADRB2), and SH2B adaptor Protein 1 (SH2B1).

Genes that encode for cell receptors that respond to the body’s messages of satiety can affect a person’s weight.  The FTO gene has been found to have a strong correlation with increased risk for high BMI.

In a 2007 study, “A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity,” the authors found a significant association between weight, BMI, and the FTO risk allele in over 38,000 participants1. It was determined that adults who have two copies of the risk allele weighed an average of 6.6 pounds more and had a 1.7-fold increased risk of developing obesity when compared with those not carrying a risk allele1.

Studies have shown that FTO is highly expressed in adipose tissue and in hypothalamic areas that are involved in food intake regulation, suggesting this risk may result in a preference for high-calorie foods or low feelings of satiety2.

Another gene mutation that affects appetite control is MC4R which encodes for a receptor that is found in the hypothalamus.  The MCR4 risk allele has been linked to obesity, diminished insulin response in the brain, altered eating behaviors, and is believed to impair MC4R function3.

SH2B1 encodes for a signaling transducing adaptor protein that responds to leptin and insulin.  Patients with a risk allele in this gene can have an altered form of the adapter protein that impairs insulin and leptin signaling resulting in increased appetite and associated weight gain4-9.

Another gene that works via cell signaling is the ADRB2, which encodes for a receptor located on cells of various tissues including liver and fat cells10. Research suggests that mutations in the ADRB2 gene may be important risk factors for the development of obesity, and may affect how an individual’s weight changes in response to exercise or a carbohydrate rich diet11-13. Women in particular who have this risk allele could benefit from lower carbohydrate intake11.

Some studies suggest that the ADRB2 variant may lower the rate of fat metabolism during workout recovery phase although this is currently not conclusive11.  However, some genetic mutations that affect obesity, such as FABP2, may have nothing to do with cell signaling.  The FABP2 protein helps in fat transportation and absorption, specifically in mobilizing fat from the small intestine into circulation for downstream deposit and storage in fat cells and the liver. FABP2 variants result in increased absorption and transportation of fats in the body14-16. This variant has also been linked to type 2 diabetes mellitus risk in certain ethnic populations16-18. Controlling the amount and types of fat, particularly saturated fat, is critical to working successfully with this variant. 

Case Study

A 39 year old female presents to clinic with concerns of inability to lose weight 11 months after the birth of her second child.  The patient has a history of being overweight on and off since early childhood, but for the majority of her adult life, she had been able to maintain a healthy BMI through diet and exercise. Her current health history is unremarkable other than occasional low back pain that she has struggled with for approximately 15 years.

The patient’s current diet is paleo for 10 months with no weight loss.  She exercises five to seven days a week, 30 minutes a day, at moderate intensity with the main goal of preventing an increase in back pain.  She was on no pharmaceutical medications, but took a multi-vitamin, probiotic, fish oil, and vitamin C, 500 milligrams. Review of systems was unremarkable. Physical exam was unremarkable.

Tests ordered included:

  • Complete blood count (CBC)
  • Comprehensive metabolic panel
  • Thyroid panel (free T4, free T3, and TSH)
  • Genetic testing looking for genetic markers related to weight management and nutritional deficiencies.

Results of these tests revealed no anemia present, though the MVC was on the upper range of normal at 94 fl/red cell indicating a tendency towards low B12 or folate levels.  Triglycerides, TSH, T3, T4, and fasting blood sugar levels were within normal range.

The genetic testing revealed the patient had risk alleles for three out of the five genetic markers associated with an increased BMI: FTO, ADRB2, and SH2B1.   The nutritional deficiencies panel also revealed that the patient was positive for three risk alleles associated with vitamin D deficiency (VDR, NADSYN1/DHCR7, and CYP2R1) and the risk allele for vitamin B12 deficiency (FUT2 ).  Follow up testing for serum vitamin D levels was preformed and a vitamin D deficiency was confirmed.

Does your patient:

  • Gain weight on a low carb diet?

Test for FABP2

  • Always feel hungry, crave high calories foods and often over eat?

Test for FTO, MC4R, SH2B1

  • Lose less weight than their diet/exercise partners?

Test for MC4R, ADRB2

  • Have trouble regulating blood sugar?

Test for SH2B1, ADRB2

Patient Protocol

The treatment plan was compiled based on the patient’s presenting symptoms, physical exam results, and laboratory test results.  Genetic testing revealed that this patient has trouble feeling full after a meal and prone to crave high calorie foods and to over eating.  In addition, she was less likely to lose weight in response to medium to high intensity exercise.  SH2B1 result revealed that this patient was prone to both insulin and leptin resistance.

The patient was recommended intermittent fasting in which she ate during an eight hour period each day.  Her diet was changed to emphasize high fiber and high protein, with an abstinence from dairy and gluten.  Exercise was switched to 30 minutes of yoga a day.  Increased supplementation was recommended, vitamin D was prescribed in the form of calcitriol, and B12 in the form of injections.

After four months of the prescribed treatment plan, the patient reported improved weight loss with an average of 4-5 pounds a month for a total of 23 pounds lost.  Serum vitamin D levels were increased to low normal range, and MCV was reduced to an optimal level of 90 fl/red cell.  The patient reported an increase in both mood and energy level.

Additionally, the patient found the changes easy to integrate into her lifestyle, and seeing results significantly increased her level of motivation.  The personalized treatment plan helped the patient achieve her desired weight of 150 pounds without severe calorie restriction.

As the new field of gene based medicine unfolds, knowing which genes to test can be a challenge.  A general guideline is to select genes for which there are robust genome wide association studies and from which there are actionable treatment considerations.  Genetic testing can be a powerful tool in helping to prevent as well as treat disease.  It can at times give the provider clues on how to treat patients who respond differently to the usual treatment protocols.  And, most importantly, it can help the provider formulate targeted treatment plans that maximize benefits while minimizing unnecessary recommendations.

References

  1. Frayling TM, Timpson NJ, Weedon MN, Zeggini E, Freathy RM, et al. (2007) A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 316: 889–894.
  2. Den Hoed M et al. Postprandial responses in hunger and satiety are associated with the rs9939609 single nucleotide polymorphism in FTO. Am J Clin Nutr. 2009;90:1426–1432
  3. Qi L et al. The common obesity variant near MC4R gene is associated with higher intakes of total energy and dietary fat, weight change and diabetes risk in women. Human Mol Genetics. 2008;17:3502-3508
  4. Duan C et al. Disruption of the SH2-B gene causes age-dependent insulin resistance and glucose intolerance. Mol Cell Biol 2004;24:7435–7443
  5. Ren D et al. Identification of SH2-B as a key regulator of leptin sensitivity, energy balance, and body weight in mice. Cell Metabolism. 2005;2:95–104
  6. Ren D et al. Neuronal SH2B1 is essential for controlling energy and glucose homeostasis. J Clin Invest 2007;117:397–406
  7. Li M et al. Differential role of SH2-B and APS in regulating energy and glucose homeostasis. Endocrinology. 2006;147: 2163–2170
  8. Bochukova EG et al. Large, rare chromosomal deletions associated with severe early onset obesity. Nature. 2010;463:666–670
  9. Walters RG et al. A new highly penetrant form of obesity due to deletions on chromosome 16p11.2. Nature. 2010;463:671–675
  10. Wachter SB et al. Beta-adrenergic receptors, from their discovery and characterization through their manipulation and beneficial clinical application. Cardiology. 2012;112:104-112
  11. Corbalán MS et al. The 27Glu polymorphism of the β2-adrenergic receptor gene interacts with physical activity influencing obesity risk among female subjects. Clin Genet. 2002;61:305-307
  12. Macho-Azcarate et al. Gln27Glu polymorphism in the beta2 adrenergic receptor gene and lipid metabolism during exercise in obese women. Int J Obesity. 2002;26:1434-1441
  13. Martínez JA et al. Obesity risk is associated with carbohydrate intake in women with the Gln27Glu β2-adrenoreceptor polymorphism. J Nutr. 2003;133:2549-2554
  14. Baier LJ et al. An amino acid substitution in the human intestinal fatty acid binding protein is associated with increased fatty acid binding, increased fat oxidation, and insulin resistance. J Clin Invest.1995;95:1281-1287
  15. Almeida JC et al. The Ala54Thr polymorphism of the FABP2 gene influences the postprandial fatty acids in patients with type 2 diabetes. J Clin Endocrin Met. 2010;95:3909-3917
  16. Levy E et al. The polymorphism at codon 54 of the FABP2 gene increases fat absorption in human intestinal explants. J Biol Chem. 2001;276:39679-39684
  17. Marín C et al. The Ala54Thr polymorphism of the fatty acid-binding protein 2 gene is associated with a change in insulin sensitivity after a change in the type of dietary fat. Am J Clin Nut. 2005;82:196-200
  18. McColley SP et al. A high fat diet and the Thr54 polymorphism of FABP2 reduces plasma triglyceride-rich lipoproteins. Nutr Res. 2011;31:503-508