A roundup of genetic research reveals how variability and lifestyle intervention make exercise programming much more complex than “One size fits all.”
Imagine this science fiction scenario: While preparing your client for a set of back squats, the Training Scene Investigators (TSI) interrupt with a spot check. After your client has undergone a DNA mouth swab, a quick noninvasive laser muscle biopsy and a family history interview, the agents issue a comprehensive report.
“We found fibers—fast-twitch fibers—indicating the appropriateness of your exercise selection. DNA analysis confirms the existence of the D phenotype of the ACE gene, which shows responsiveness to strength training. However, there is a genetic predisposition for back and neck injury. This evidence indicates that the single-leg bench squat might be a more appropriate exercise than the back squat. Given that your client consumes a diet rich in antioxidants, the inflammatory risks that could influence the genetic expression of the back injury gene are low” (Hartvigsen et al. 2009; Bland 1999; Thompson & Binter-Macleod 2006; Boyle 2010).
Obviously the above scenario exists well into the future, but other than the laser biopsy, the scene is an extrapolation of current genetic research within the performance, fitness, health and nutrition communities. While study findings have yet to produce immediate practical applications—such as reliable tests that can confirm the efficacy of our training programs—the information now available may force fitness professionals to explore a broad path to programming.
More than 250 genes relevant to health and fitness have been identified since the Human Genome Project’s completion in the late 1990s (Bray et al. 2008). These range from genes affecting cardiovascular endurance and muscle strength to genes related to heart rate regulation, body composition, blood pressure, and metabolic factors such as glucose and blood lipid utilization (Bray et al. 2009). Along with the identification of exercise-related genetic characteristics, or phenotypes, there is now scientific evidence that responsiveness to different kinds of exercise training is heritable, indicating that individuals with specific genetic profiles may be very responsive to a particular exercise modality and nonresponsive to another (Roth 2007).
Strength and conditioning, track and swimming coaches have understood the need for different types of training for years without knowing the genetics involved, and it’s no mystery that anaerobic/sprinter physiologies and aerobic/endurance physiologies are different. Basic exercise science delineates the distinctions between the two. What has been missing from exercise programming is the acknowledgement that it’s not just athletes who have these specific phenotypes; everyone has them.
Newer research underscores the inherent aspects of individual metabolic responses and the need to dig deeper into our clients’, athletes’ and class participants’ genetic tendencies in order to better help people reach their health and fitness goals. Genetic research studies have shown widely varying responses to different protocols, implying a need for diverse training modalities. The challenge for fitness professionals is to be acutely aware of these possibilities.
Individuals can be dominant in either aerobic or anaerobic physiologies or fall somewhere in between. The aerobic individual is more suited to endurance programming, while the anaerobic person is better suited to activities requiring strength and speed. The two physiologies are differentiated by the speed of muscle fiber contractions, the type of fuel used and the way oxygen is used (Wilmore 1994). Aerobic-dominant physiologies are characterized by slow-twitch contractions (type I muscle fibers), use fat or blood lipids for fuel during work and utilize a higher number of mitochondria to process oxygen for long-term activity. Anaerobic-dominant physiologies are characterized by fast-twitch, more powerful contractions (type IIa and type IIb muscle fibers), use glucose or blood sugar for fuel during work and have fewer mitochondria to deliver oxygen for energy. As a consequence, the latter group depends primarily on internal chemical reactions to keep fueling muscle fiber contractions (Bouchard, Malina & Perusse 1997).
Research on these starkly different metabolic processes has shown fairly dramatic variability, mostly accounted for by genetic differences. Before we reached our current understanding of the genetic influences on exercise, outliers in the studies were probably not noticed or were cast off because they didn’t fit the bell curve. Now that we have a deep and growing understanding of the existence of specific health- and performance-related genes, we can theoretically bring those outliers back into a relevant discussion and apply the results to the wide range of outcomes we see in our clients and athletes.
The following studies on muscle gain, cardiorespiratory improvement and weight gain show how variances in results might affect exercise programming.
Strength research has shown that individual responses to similar training protocols vary dramatically, even at the cellular level. Hubal et al. (2005) found that participant responses to 12 weeks of resistance training ranged from no change in muscle size to a 59% increase. In 2007, Bamman et al. also observed a wide range of responses to strength training, with top responders experiencing a 58% gain, middle responders showing a 28% increase and bottom responders seeing no changes. Growth factors and other muscle-stimulating hormones showed comparable variability between responders and nonresponders (Bamman et al. 2007).
In a later report by the same researchers, Petrella et al. (2008) determined that one subtle factor contributing to the disparity in results was the number of satellite cells surrounding the muscle fibers. Satellite cells are stem cells that circulate through the bloodstream and respond to areas of need by providing cellular substances that stimulate the genetic material in muscle cells (Zammit 2008). For example, satellite cells help repair muscle tissue after resistance training and assist in healing cuts or scrapes to the skin. These cells surround the muscle fibers or tissues in need of regeneration, infuse the areas with genetic material and are a key factor in muscle growth from resistance training.
In the study by Petrella et al., best responders started with an average of 21 satellite cells per 100 fibers, and that number increased to 30 per 100 by week 16. Nonresponders averaged 10 per 100 at the start and showed no change, even though these subjects followed the same exercise protocol.
There was similar variability in the cardiorespiratory training results from the Heritage Family Study, which examined improvements in maximal oxygen consumption and the body’s ability to effectively transport oxygen to working muscles (Roth 2007). Subjects performed 20 weeks of cardiovascular training designed to improve metabolic risk factors and aerobic capacity. By training’s end, oxygen transportation to the muscles had improved by an average of 400 milliliters per minute (ml/min) among study subjects. However, training responses varied dramatically. Instead of a fairly even improvement of 400 ml/min, results ranged from 0 ml/min to >1,000 ml/min. These results cast doubts on the efficacy of the training for all populations.
Research has also shown variability in blood pressure, heart rate and high-density lipoprotein (HDL) cholesterol measurements in response to exercise. The HDL and blood pressure numbers were quite striking, with many individuals actually showing a decrease in HDL levels instead of the expected increase in the artery-scrubbing “good” cholesterol, and some high blood pressure sufferers showing no response to exercise (Roth 2007).
Even weight gain under sedentary conditions is dramatically different from individual to individual. In the Heritage Family Study, 12 pairs of twins were subjected to 84 days of overfeeding by 1,000 calories per day over a 100-day period. Subjects maintained a sedentary lifestyle during this time. Average weight gain was 17.86 pounds, but results ranged from 9.48 pounds to 29.32 pounds. Abdominal fat variability was also dramatic, with one individual showing no increase and the worst showing a 200% increase (Contreras 2011; Bouchard, Malina & Perusse 1997).
The variations in the strength and cardiovascular results discussed above are in line with research estimates that 10%–15% of North Americans are highly dominant in aerobic physiology, 10%–15% are highly dominant in anaerobic physiology and the remaining population is dispersed across varying percentages in the fast- and slow-twitch compendium (Bouchard, Malina & Perusse 1997).
What do these metabolic genetic studies mean to fitness professionals? If we are passionate advocates for an exclusive modality such as strength training, high-intensity intervals, triathlon training or even a particular group exercise class, slightly more than a third of our participants may not be getting an optimal workout for their phenotype. Exercise participants may not even be getting the full health benefits we’ve come to associate with exercise.
The findings on sedentary weight gain may be startling for our industry, which is primarily concerned with increasing strength and endurance in an effort to help people lose weight. As fitness professionals we may not be able to delude ourselves into thinking that everything can be cured with the right diet and exercise program. There may indeed be individual circumstances that require additional intervention, which is why it’s important to be part of an allied medical health team.
Even research into nutrition genetics—a field known as nutrigenomics—identifies the need for more individual consideration (Roth 2007). People with food allergies or sensitivities are classic examples of the nutrigenomic expression of genes. Celiac disease and gluten sensitivities are extreme examples, as sufferers either become very sick or display symptomatic responses such as stomach distress or fatigue upon consuming substances that contain wheat and gluten (Bland 1999).
Some of our commonly held beliefs are being challenged as the nutrigenomic field progresses. At one point, everyone with hypertension was encouraged to limit sodium (or salt) intake. Now, researchers estimate that only 30%–50% of individuals with high blood pressure are salt-sensitive and the rest have no need to restrict sodium (Bland 1999). On the flip side of the salt equation, recent research identified a specific gene in hypertensive individuals that indicated a more favorable response to reduced sodium intake (Sun et al. 2010).
Fat intake restriction is also under scrutiny. Scientists estimate that 50% of blood cholesterol level variances can be explained by genetics, with the remaining 50% explained by nutrition and other lifestyle factors. One study actually found that 41% of a group placed on a low-fat diet to reduce levels of low-density lipoproteins (LDL)—the so called “bad cholesterol” that promotes artery clogging—actually saw their LDL levels increase (Bland 1999).
Research has also identified genetic-inheritance factors that make certain individuals more sensitive to sugars—especially fructose and lactose, which are not properly absorbed in the intestinal tract and can cause a variety of inflammatory conditions (Bland 1999). Given the preponderance of high-fructose sugar in our foods and the large quantities of dairy products in our food supply, these negative effects may continue to occur (Pollan 2006).
Weight loss response to specific diets also appears to have a genetic component. At the request of a genetic testing company, Stanford University researchers compared the responses of different nutrition genotypes to low-carbohydrate (Atkins™), low-fat (Ornish), very low fat (LEARN) and balanced (Zone™) diets. Individuals on a genotype-appropriate diet shed more than twice the percentage of body weight lost by those on a diet not matched to their genotype. Weight loss differences were even greater when individuals who were trying to follow a diet with the lowest possible level of carbohydrate or fat were matched correctly. Improvements in clinical measures related to weight loss (e.g., blood triglyceride levels) paralleled the weight loss differences (Fox 2010).
As shown by the above studies, kinesiogenomics (the study of genetics in the field of kinesiology) and nutrigenomics have opened up exciting but mysterious trails for health and fitness professionals. Even more relative to the genetics discussion is the field of epigenetics—the study of external influences that can change genetic response.
Heritage Family Study researchers documented that approximately 50% of VO2max results could be explained through direct genetic factors, while the remaining 50% were attributable to nongenetic factors such as environment and exercise habits (Roth 2007). Environmental aspects are considered epigenetic effects on the surface, but the impact goes deeper than that. Epigenetic studies have revealed long-term and heritable influences on genes other than inherited gene code sequences. Those influences are caused by external factors that change organic molecules chemically attached to genes. What makes these chemical attachments important is that they can make genes more or less active. The process of making genes more active is called gene expression and can determine either positive or negative outcomes (Roth 2007; Francis 2011).
Epigenetics looks at how gene-regulating attachments are emplaced and removed. Sometimes attachments and detachments occur more or less at random, like mutations, but epigenetic changes have also been shown to occur because of the food we eat, the pollutants we are exposed to, our social interactions or even the type of exercise we do on a regular basis.
Animal studies have demonstrated that diet can affect not just body weight and glucose response but even coat color in the offspring of animals whose diets are manipulated (Roth 2007; Francis 2011; Church 2007). In limited human studies, researchers have found correlations between dietary pattern and epigenetic inheritance in traits such as birth weight, body type, cardiovascular disease and even mental health (Roth 2007; Francis 2011; Church 2007).
Epigenetic gene expression can also be more direct, as shown by the dramatic increase in satellite cells in good responders in the strength training study by Petrella et al. (2008). Good responders had a superior number of satellite cells to begin with; however, the epigenetic effect of training led to an increase in satellite cell numbers (Petrella et al. 2008) and a greater influence on the genetic material of muscle cell fibers (Bamman et al. 2007). Epigenetic alterations can result in other types of positive gene expression, such as longer life, a fitter body, a stronger immune system and even better joint health (Francis 2011).
Epigenetic interventions were used in a study by Dean Ornish, MD, in 2008 to examine lifestyle intervention effects on men who had biomarkers for inactive prostate-cancer tumors. The 3-month study assessed the effects of a lifestyle intervention as opposed to medical or surgical cancer treatments. The intervention included low-fat, whole-food, plant-based nutrition; stress management techniques; moderate exercise; and participation in a psychosocial support group. Using advanced laboratory techniques, the investigators measured the intervention’s effects at the genetic level. Examining prostate biopsy specimens before and after the intervention, they found significant changes in gene activity. Roughly 50 genes associated with cancer suppression became more active, and nearly 500 genes associated with cancer progression became less active. The pattern of change observed in gene activity was consistently and decisively associated with lower risk of cancer development and progression (Katz 2010).
Genetics and epigenetics research recently converged with the discovery of the so-called obesity gene, FTO. When elevated, FTO has been found to increase adiposity through increased appetite, lowered insulin resistance and decreased energy expenditure (Contreras 2011). The good news for individuals with FTO and other genetic predispositions for obesity is that the epigenetic influence of exercise and activity blunted the effects of the gene when daily exercise recommendations were exceeded by 10%–20% (Rampersaud et al. 2008).
Exercise is usually considered a positive epigenetic influence; however, type, amount and frequency determine its efficacy. Overexercising at high intensities produces a large amount of oxidative stress on muscle cells. Overtraining not only fatigues the body, harms muscle tissue and suppresses immune function but can also lead to even more damaging conditions at the cellular level (Tiidus 2008). Genetic caveats for our clients are within our purview, especially vis-à-vis workout intensity, duration and frequency. The knowledge that some genotypes have a greater risk of certain injuries or may experience a negative response to training to exhaustion should add greater perspective to our exercise programming.
Consider Tour de France champion Greg LeMond, who suffered a career-ending condition called mitochondrial myopathy, in which the mitochondria in the muscles could no longer manufacture energy efficiently. The damage was not genetic, but researchers speculated that it could have been induced by long-term, highly intensive training and fierce competition (Bland 1999).
At this time, exercise professionals do not have quick genetic or epigenetic tests that can check clients for anaerobic or aerobic physiology, nutrigenomics requirements, joint genetics or even response to emotional challenges. Despite these limitations, the research on exercise genetics provides a greater appreciation for a unique and individual approach to programming.
At minimum, we can take genetic heritability traits into account in our workout planning and dietary recommendations (in concert with a registered dietitian). We can now accept that a miracle animal protein or vegetarian diet, a strength training program or a long-distance running regimen cannot be dismissed out of hand nor accepted as gospel because of the successes or failures of specific clients. Now, more than ever, our expectations need to be broad-based and accepting.
We also need to recognize that sometimes exercise or a logical dietary recommendation is not the ultimate panacea for society’s ailments. As we saw earlier, certain genetic types did not respond to exercise in studies on hypertension and cholesterol. For these types, movement did not modulate high blood pressure, nor did low-fat diets lower LDL cholesterol. Individuals with these variances may need to be on medication (Roth 2007).
Armed with the knowledge of genetic biodiversity, we can commit to taking more detailed client histories and being keener observers of results. Knowing a client’s athletic history, the history of the client’s parents and even his or her children’s athletic tendencies may help us understand whether the client has genetic tendencies for anaerobic speed, strength or aerobic endurance. If heritable genetic clues are unavailable, we can observe responses to current training modalities. Given that most individuals respond well to a specific training protocol over a 12-week period, key evaluations along the way will provide answers. If a client is making steady progress toward her goals by the 6- to 8-week mark, the program is on a sound footing; if not, you need to adjust the variables.
It behooves us as fitness professionals to remain as open-minded and broadly educated as possible in this exciting and dynamic time, in which genetic research will continue to provide more and more programming solutions for our diverse clientele.