Appetite is a combination of hunger response and satiety. Many scientific studies have been undertaken to identify genomic variations that contribute to these aspects of eating. What we have discovered is that it is a complex interaction between many systems:

• Brain neurotransmitters (dopamine & serotonin)
• Intestinal peptides
• Signals from fat cells
• Appetite hormones

All components of this network require coordination in central sensing mechanisms of the brain in order to create your response.

Insulin resistance is a state where the body requires greater and greater amounts of insulin in order to drive down blood sugar levels. It is usually associated with diabetes or the pre-diabetic state.

Studies have demonstrated that some individuals actually possess a greater predisposition towards insulin resistance and this predisposition can be predicted based on genetic variations. Individuals that carry greater risk tend to have higher, though frequently normal, fasting blood sugar levels and insulin levels. These higher fasting blood glucose levels also promote accelerated rates of aging in the body. Individuals with a greater propensity towards insulin resistance often report greater difficulty losing weight than others that follow similar diets despite aggressive adherence to the diet.

Dairy genes relate to the processing of the sugar and the fat in dairy products.

Lactose is a sugar found in milk. Some individuals have deficiencies in the enzyme or lack the enzyme lactase that is required to fully digest the sugar. The actual gene involved is LCT but the MCM6 is a regulator of the LCT expression. Variants of the MCM6 gene only indicate a PROPENSITY toward lactose intolerance.

Certain genotypes will also express a greater propensity toward weight gain and obesity when consuming high fat dairy

Gluten is a mixture of proteins found in wheat and related grains. It is also found in many food preparations because it provides elasticity and chewiness to many prepared foods. There is a difference between allergy and sensitivity, these genes relate to potential for developing allergy. See the section relating to grain sensitivity for more information. These genetics related to gluten are based on predisposition and are only suggestive of susceptibility to developing reactions to gluten in foods. This is not a diagnostic test.

Glutamic acid decarboxylase is an enzyme responsible for the conversion of glutamate into GABA. GAD1 is only present in the brain and helps us to convert the excitatory neurotransmitter, glutamate, into the inhibitory neurotransmitter GABA.

The GAD1 genes relate to the handling of glutamic acid containing foods and the potential for creation of an imbalance between excitatory and inhibitory neurotransmitters in the brain. Certain variations can lead to decreased activity of this enzyme and a tendency toward higher glutamate and lower GABA levels in the brain. This can lead to anxiety, agitation, and difficulty sleeping.

Many grains are high in glutamic acid and frequently people will misinterpret a negative response to grains as a negative response to gluten. When these variations are significant and the symptoms are expressed, it is important to reduce exposure to glutamic acid and make sure that B6 levels remain healthy since it is required for the enzyme to work optimally

Many people perceive that snacking behaviors and the inability to stop eating sweets are willpower based. While this may be true at times, much of the drive toward snacking and sweets is coded in our DNA. The snacking gene variations that we analyze have been applied in clinical practice for several years and there is an extremely high correlation between genetic variations and client reported snacking behaviors. The same holds true for sweets, there are genes that code for perception of sweet taste where each person can have a different perception of sweetness based on their gene variations.

There are also genes that code for the way our brains respond when we taste something sweet.

Carbohydrates are frequently praised or villainized in dietary recommendations, but the one aspect that we have identified in the genomic data is that there is no right answer that fits every person.

Carbohydrates are a very individualized component of the diet and using the current scientific literature and our experience with genomics in clinical practice, the relevant and highest impact genes have been identified.

This is especially relevant when it comes to ideal body composition as some people will do better on lower carbohydrate intake while others tend to burn fat in the flame of a carbohydrate.

Be mindful of the fact that much of this response can be modified through epigenetics. Review your past experience and your food preferences with your coach.

Primary fats of the human diet: .Saturated fats (SFA) .Monounsaturated fats (MUFA) .Polyunsaturated fats (PUFA)

Depending on the source of the advice, you will hear about which ones are good for you and which ones are bad. The problem with this advice is two-fold; first, fats are a macronutrient that our bodies require for optimal health so there is no strict classification of good and bad. Second, there are significant individual differences in how each person responds to the different types of fat.

When using genetic variations to provide guidance on fat intake, it is important to understand that many of the studies used did not differentiate the types of fat. This section provides guidelines for planning the ideal percentage of calories from fat in your daily diet

Saturated fats (SFA) represent one of the most debated aspects of human nutrition today. Various studies go back and forth regarding whether it is healthy or not healthy. The Atkins and Paleo movements have brought saturated fat into the forefront of discussions.

Bottom line is that saturated fats are needed for healthy human function. Saturated fat makes up 50% of the membrane fats in every cell of our body and is essential for healthy immune function. Our brain is 60% fat and is predominantly saturated fat and cholesterol. Despite this, there can be something to getting too much of a good thing.

Each individual carries genetic variations that can change the way they respond to saturated fats from a health and wellness standpoint. The algorithm used in this profile is based on leading scientific studies into genome wide associations as well as from our extensive experience in applying this in clinical practice.

Even with moderate intake recommendations it is best for most individuals to keep saturated fat intake to less than 10% of total calories.

Polyunsaturated fatty acids (PUFA) have a role in many physiological processes, including energy production, modulation of inflammation, and maintenance of cell membrane integrity. Polyunsaturated fats (PUFAs) include the omega-6 and omega-3s, essential for life and there are health benefits to consuming both in the appropriate ratios.

Research has been focused on omega-6/omega-3 ratios and there is a clear benefit to keeping this ratio at 4:1 or less. While this is the beneficial zone, most people consume these fats in a 10:1 ratio. Many in the industrialized world are reaching levels as high as 25:1. These large ratios in favor of omega-6 are unhealthy and lead to significant inflammation and increased risk for detrimental health effects.

Several GWAS studies have looked at the genetic variations that impact serum levels of PUFAs in the population. Certain variations correlate with rate limiting enzyme activity in the conversion to beneficial forms while others can predict weight loss response to percentages of PUFAs in the diet.

Monounsaturated fatty acids (MUFA) have a long list of studies in the scientific literature supporting the health benefits. Reported health benefits include; decreased inflammation, decreased cancer rates, decreased heart disease, and weight loss.

MUFA is suspected to be the major health benefit of the Mediterranean diet where some traditionally consume as much as 40% of their total calories from olive oil, a major source of MUFA.

MUFA are mainly omega-9 fatty acids but also includes the omega-7 fatty acids. The main sources of MUFA in our diets include; oils, nuts, meats, salmon, and avocado.

MUFA SOURCES: .Olive oil .Macadamia nut oil .Avocado Almonds .Macadamia nuts .Beef .Salmon .Pumpkin seeds .Chicken

Protein is an important macronutrient that provides the amino acid building blocks for structures, enzymes, antibodies, and hormones. There are 20 amino acids that the body uses to create millions of different proteins and of those, ten are considered essential, meaning that we are not able to make them and we must consume them in our diets.

There are many GWAS that look at how our mix of macronutrients can affect our gene expression to create a specific response. Most of these studies have focused on body composition. This means that we can look at certain genetic variations that correlate with an outcome of changing the way certain genes are expressed that relate to obesity, fat storage, and body composition.

Some people will respond better to a diet with a higher percentage of calories from protein, while other do better with a lower percentage. This is a complex network of gene interactions and there are ways to epigenetically shift the expressions of these genes to achieve desired outcomes.

Plant sterols have been reported to lower LDL and triglycerides.

Plant sterols is the term for phytosterols and phytostanols, regardless of biological source. These are cholesterol-like molecules found in all plant foods, with the highest concentrations occurring in vegetable oils. They are absorbed only in trace amounts in normal circumstances, but some individuals possess the genetics to absorb greater amounts. Plant sterols work by inhibiting the absorption of intestinal cholesterol basically through competition for receptors and uptake. This also happens if they get absorbed into our blood stream. This can increase cardiovascular risk.

Generally, the amount of plant sterols taken in through dietary sources are tolerable but excess amounts are a potentially harmful. Supplement sources can come in a variety of forms; sterols, stanols, phytosterols, beta-sitosterol, campesterol and stigmasterol.

In this report, we look at genetic variations and how they tend to affect resting metabolic rate (RMR). RMR is a complex combination of genetics and environment and the genetics can be modified through epigentic influences.

The basal metabolic rate calculators (BMR) are rough estimates and should only be used as guides. In fact, the weight variable in the equation adds even more variability since it is most accurate when using the fat free mass (FFM), and FFM can be very different even for individuals that weigh the same in total body weight.

The BMR calculators are reported in some studies to be as much as 700 kcal off even when using FFM. BMR does not take into account the number of calories burned in daily activity, only resting.