In the late 17th century physician-philosopher John Locke published An Essay Concerning Human Understanding, which suggested that the mind was a blank slate at birth and that all behaviors could be attributed to the environment, past or present, they were exposed to. From that point forward, the nature versus nurture debate, i.e. whether behavior is the result of a person’s environment (past or present) or their genes, has raged on.
Adherence to physical activity and dietary change are no exceptions to this debate. For example, a Spanish study on over 1000 individuals attempting to eat healthier attributed their lack of success to environmental barriers (e.g. nature) such as irregular work ours (29.7%), lack of willpower (29.7%) and lack of appealing, healthy food items (21.3%).  With respect to exercise, an Australian study on nearly 900 adults found that of those were classified as inactive (n=198), the reasons most often selected for the lack of physical activity were also related to environmental barriers such as lack of time (50%), nobody to exercise with (20.7%), or lack of money (16.2%), though none of the available selections included a role for genetics. 
- Exercise adherence is relatively poor, as nearly 50% of individuals who start an exercise program will drop-out be the 6-month mark. Most people attribute environmental barriers such as lack of time, money, or person to exercise with as the reasons they aren’t physically active. Genetic influences on exercise adherence or the tendency to be physically active are rarely considered.
- There are over 70 different genes associated with athletic performance and response to exercise. Studies evaluating how families respond to exercise show a 2.5-times larger difference in response between families than within families. Additionally, studies looking at how individuals respond to resistance training show a wide range of results, with some getting worse, e.g. non-responders, and some getting huge gainzZz, e.g. extreme responders. Genetics likely play a significant role in exercise outcomes and adherence to exercise.
- Research into genetic determinants of exercise adherence is in its early stages. The current evidence has developed some potential targets for future research, but there haven’t been any slam-dunk associations found just yet.
Physical inactivity is a major health problem worldwide and is the fourth greatest global risk factor for mortality according to the World Health Organization (WHO), behind high blood pressure, tobacco use, and elevated blood sugar. It predisposes individuals to a wide variety of chronic diseases, including cardio-cerebrovascular disease, metabolic disease, musculoskeletal disorders, frailty, and many others. Despite these risks, most Americans are inactive with only 26% of men, 19% of women, and 20% of adolescents self-report meeting current recommendations for exercise.  When physical activity is directly measured using sophisticated FitBit-like devices, less than 5% of individuals are actually meeting these recommendations. 
The 2018 Physical Activity Guidelines for Americans recommend the following minimum targets:
- 150 to 300 minutes per week of moderate-intensity aerobic physical activity, OR;
- 75 to 150 minutes per week of vigorous-intensity aerobic physical activity, AND;
- Resistance training of moderate or greater intensity involving all major muscle groups on 2 or more days per week.
Regular participation in physical activity, including resistance training, has well-documented benefits for numerous health outcomes, diseases, and risk of premature death. [14, 15] Even small changes, such as taking an additional 2000 steps per day (about 20 minutes of brisk walking) reduces the risk of having a cardiovascular event by 10% and reduces the risk of having elevated blood sugar by 25%. [22, 23] Resistance training appears to provide additional benefit, as there is a 23% reduction in all-cause mortality in individuals who resistance train 2-3 times per week.  This is an example of dose-response effect, where larger doses of training volume produce larger improvements in health outcomes. 
While it is relatively easy to point out the benefits of regular exercise, it can be far more difficult to promote long-term adherence to this behavior. For example, most studies report that ~50% of people who start an exercise program will dropout within 6 months even if they’re part of a study where they receive instruction, supervision, and other incentives to participate. [25, 26] As it turns out, behavior change is complex, with a number of biological, psychological, and social factors contributing to adherence. Let’s focus on the biology and take a look at the genetic influences of exercise adherence. First up, a quick review on genetics to make sure we’re all on the same page.
The human body is comprised of cells, each containing identical genetic information. This genetic information is called the genome, which is contained within 46 chromosomes in most cases. The chromosomes are made up of DNA, or deoxyribonucleic acid. DNA is a double-helix structure typically residing in the cell’s nucleus, but also in the mitochondria, termed mitochondrial DNA. It contains genetic information that is stored in a code of four chemical bases, called nucleotides: adenine (A), guanine (G), cytosine (C), and thymine (T). Specific sequences of nucleotides contained within a chromosome are known as genes, which we inherit from our parents.
While 99% of human DNA is the same between individuals, small variations in DNA can make big differences. The most common type of genetic variation in humans are known as single nucleotide polymorphisms, or “snips” more commonly. Each SNP is a difference in a single DNA nucleotide, e.g. a cytosine (C) might be replaced with a thymine (T) in a piece of DNA.
The genetic code contained within DNA is important for virtually all cellular functions including survival, maturation, making hormones, and more. When a cell receives a signal to do something, e.g. a hormone or growth factor binding to a receptor, the cell springs responds by making a protein that ultimately helps carry out the cellular function. The genetic code for these active proteins is packed within the cell’s DNA. The process to go from DNA to functional protein is complex, but can be summarized in the following three steps:
- Cells are stimulated by a physiological signal, which in-turn drives the activation of DNA transcription factors. Transcription is the process of producing RNA, or ribonucleic acid, from the specific DNA code. RNA is slightly different than DNA chemically, but contains a copy of the genetic code contained in the DNA. This takes place in the cell’s nucleus typically.
- The RNA moves from the cell’s nucleus into the cytoplasm where it is then translated into protein. The genetic code that originated in the cell’s DNA has thus been transcribed to RNA and translated into a protein.
- The protein may undergo further modifications before ultimately altering cell function.
Additionally, there is quite a bit of cellular turnover in the human body as old cells die off and are replaced. During this process, all the cell’s DNA is exactly copied, e.g. each base is precisely copied in exactly the same location. Errors in this process are known as mutations, which happen relatively infrequently considering the entire human genome is about 3 billion bases long and there are about 37 trillion cells in your body. Fortunately, most of these mutations occur in regions of the DNA that don’t have any impact on the cell’s function, structure, or survival. 
So, now that we have a basic understanding of genetics, what do we know about genes and exercise? At present, we have data on how a person’s inherited genes affect the following exercise outcomes:
- Aerobic Fitness- The Health, Risk Factors, exercise Training, and Genetics (HERITAGE) study looked at parents and adult offspring from 130 families who were all placed on a standardized 20-week aerobic exercise program. The study found that there was over a 2.5 times greater variance in VO2max development between families than within families, which suggests a substantial genetic component. After controlling for age and sex, the authors estimated that ~47% of the VO2max response in an individual was due to genetics. [31, 32]
- Muscular Strength and Size- Data from twin studies suggests up to 50% to 60% of the difference in muscle mass and strength may be due to genetic factors without clear gender influences. [33 -35] In particular, variants in the genes IL15, ACE, ACTN3, and IGF1 have all been associated with genetic determinants of muscular strength and size. [36–40]
- Body Composition- Certain variations in the fat mass and obesity-associated gene (FTO) has been associated with increased BMI, increased body fat, and a below-average fat mass reduction in response to exercise. [1, 3] Increasing the volume of physical activity seems to reduce the risk of obesity in those with the high-risk variants of the FTO gene based on a meta-analysis of over 200,000 adults and nearly 20,000 children. 
- Tendency to be Physically Active- In studies performed on twins, concordance is the probability that both twins will have a particular trait, e.g. the tendency to be physically active in this case, provided that one of the twins has the trait. For example, a trait with 100% concordance would result in both twins displaying the same trait every time one twin displayed the trait. In European twins, the concordance for participation in vigorous physical activity is ~80%. [28 –30]
There is relatively little data on the influence of genetics on adherence. A previous study looked at single nucleotide changes – either an insertion (I) or deletion (D)- in the angiotensin-converting enzyme (ACE) gene. It was found that those with two copies of the insertion (I) tended to adhere better than those with two copies of the deletion (D). Those with the two I copies also tended to get better results, e.g. higher VO2max and lower body fat. Importantly, these genetic changes were not correlated to VO2max, BMI, body fat, or serum lipid levels, which suggests that the increased adherence to the exercise generated the improved results rather than having a genetic predisposition to respond better to exercise. 
So, there’s already some data suggesting adherence may be influenced by genetics. Let’s take an in-depth look at the 2014 article, Genetic factors in exercise adoption, adherence, and obesity, by Herring et al.
The purpose of this paper was to assess the role of genetic and non-genetic predictors of adherence to physical activity by using data from the Training Interventions and Genetics of Exercise Response (TIGER) Study. The TIGER study originally recruited 3,773 students from the University of Houston, age 18-35 years. All subjects were sedentary, e.g. they had exercised for less than 30 minutes per week for the previous 30 days. Additionally, they were not actively limiting calorie intake.
Of the original 3700+ subjects, 885 individuals (333 males, 552 females) provided genetic samples for analysis, as described below. Unfortunately, the racial/ethnic distribution of this particular cohort is unknown. However, the TIGER study at large was 29.1% Caucasian, 22.9% Hispanic, 28.1% African American, 7.5% Asian, 3.9% Asian Indian, 0.2% Native American, and 8.4% other. There were substantial ethnic disparities in overweight and obesity rates, but these were similar overall to national averages (Figure. 1).
Individuals were asked to complete at least 30 minutes, but no more than 60 minutes, of aerobic exercise at 65%-85% of their age and gender-specific maximum heart rate along with a 5-minute warm-up and 5-minute cool-down, 3 times per week during an class that earned the students college credit. Subjects were able to self-select from a treadmill, elliptical, stair stepper, and/or exercise bike for each session. Additionally, subjects wore a heart rate monitor during their exercise sessions. Adherence in this study was defined as meeting the prescribed exercise dose, e.g. at least 30 minutes of aerobic exercise 3 times per week for the duration of the 15-weeks of the study.
Exercise duration was recorded in minutes and an average exercise intensity for each session was calculated based on a percent of their heart rate reserve. The heart rate reserve is calculated by subtracting an individual’s age from 220. The average heart rate obtained from an exercise session is then divided by this value to determine the heart rate reserve percentage. Exposure to exercise was quantified by using adding each workout’s Heart Rate Physical Activity Score (HRPAS), which is the product of the heart rate reserve percentage and total minutes exercised, and . For example, say a 30-year-old individual averages a heart rate of 150 beats per minute during each 30-minute exercise session, 3 times per week for 15 weeks. Their heart rate reserve percentage, workout HRPAS, and total HRPAS would be:
- Heart Rate Reserve = 220-30=190 beats per minute
- Heart Rate Reserve Percentage= 150/190= 0.789 or 78.9%
- Workout HRPAS= 78.9% x 30 minutes= 2368
- Total HRPAS= (2368 x 3) x 15= 106,560
The recruited subjects had their genetic information tested using the Ilumina Metabochip, which is a genetic testing kit that identifies over 200,000 potential changes in the DNA sequence. Any changes that were found were run through an open-source analyzing tool called PLINK, which can handle large sets of genetic data at once to point out the differences to researchers. In this study specifically, the researchers focused on 26 potential DNA changes in the following six genes:
- Brain-derived neurotrophic factor (BDNF)– this gene provides instructions for making protein in the central nervous system, e.g. the brain and spinal cord. It promotes survival, growth, and maturation of nerves. Additionally, it actively regulates changes in the synapses, which is where nerve cells communicate with one another. BDNF is also found in areas of the brain involved in regulating behaviors related to eating and body-weight. Exercise has been shown to increase BDNF levels in rats and humans, where it is thought to be responsible for some of the cognitive improvement and positive affect seen with exercise. [11, 12]
- Brain-derived neurotrophic factor, opposite strand (BDNFOS)– this gene’s function is likely similar to BDNF’s, though also likely plays a role in altering how BDNF is expressed, e.g. what functional protein(s) is/are formed from it.
- Dopamine Receptor D2 (DRD2)– this gene is involved with forming a type of dopamine receptor, D2 in this case. While exercise has been shown to increase D2 receptor number and activity in rats, mutations in this gene have been associated with schizophrenia and dystonia, a syndrome that produces spontaneous muscle contractions and abnormal postures. 
- Dopamine Receptor D4 (DRD4)– this gene is involved with forming a type of dopamine receptor, D4, a target for drugs treating schizophrenia and Parkinson disease. Mutations here are also associated with attention-deficit-hyperactivity disorder (ADHD) and the personality trait of novelty seeking.
- 5-Hydroxytryptamine receptor 2A (HTR2A)– this gene encodes for a serotonin receptor. Mutations in this gene are associated with increased risk of schizophrenia and obsessive-compulsive disorder. A recent study demonstrated that variants in this gene are also associated with changes in BMI and food-seeking behavior.  An obesity drug known as lorcaserin (Belviq) that reduces appetite and bodyweight by targeting the HTR2A and HTR2C receptor. 
- 5-Hydroxytryptamine receptor 2C (HTR2C)– this gene also encodes for a serotonin receptor. Mutations in this gene have been associated with overeating and reduced energy expenditure during physical activity in animal models. 
In addition to the genetic analyses described above, subjects received physical examinations at three time points during the study, baseline, 15 weeks, and 30 weeks where body weight, waist and hip measurements, and body fat analysis via both skin-fold (caliper) measurement and DEXA scan, resting heart rate, and blood pressure were obtained. Finally, the subjects completed questionnaires assessing their demographics, medical history, diet, sleep, psychosocial factors, and physical activity at each follow-up.
Over the 7 years this study ran, more than 40,000 exercise sessions were recorded on heart rate monitor. Notably, 84% of exercise sessions were performed at the correct intensity and duration, with an average time spent in the target heart rate zone of 65%-85% maximum heart rate of 30.1 minutes.
Unfortunately, the raw adherence data for this specific group of TIGER study participants is unknown. Of the original 3,773 participants, only 2,680 had usable data to determine overall adherence. Of these, 2053 (76%) were deemed to be adherent and 627 (24%) were classified as non-adherent. As this study was focused on adherence, no health metrics such as weight loss, body composition change, or other outcomes are available.
Statistically significant non-genetic factors associated with improved adherence include lower BMI, lower waist/hip ratios, smaller waist and hip circumferences, and lighter body weights. Additionally, those with the highest exercise intensity, average heart rate during exercise, and longest exercise durations also were more adherent compared to their peers with lower exercise intensity, average heart rates during exercise, and shorter exercise durations. Of note, baseline measures of cardiorespiratory fitness such as VO2max, resting heart rates, and blood pressure were not associated with exercise adherence. See Table 1 for full results.
Three genes and four total DNA changes showed statistically significant correlations with exercise-related outcomes including adherence, exercise dose, and duration. Specifically, single modifications in the DNA of either serotonin genes, e.g. HTR2A and HTR2C, were associated with increased adherence and duration of exercise. Additionally, a separate DNA change in the HTR2C gene was associated with increased exercise intensity. Finally, a single DNA change was in a dopamine receptor gene, e.g. DRD4, was associated with increased exercise duration.
Despite being statistically significant, the differences seen in these genetic variants are quite small in absolute terms. For example, one of the DNA changes in the HTR2C gene was associated with about a 90 second greater exercise duration at its maximal effect. A similar, yet separate change in the DRD4 gene showed an even smaller increase in exercise duration. Finally, variants in the DRD2, BDNF, and BDNFOS genes were not associated with exercise adherence or other exercise-related outcomes in this study.
This article highlights the complexities when trying to study the impact of nature (genetics) and nurture (environment) on complex human behavior. Overall, the data from the TIGER study provides relatively weak support that genetics play a major role in exercise adherence. However, the way the study was performed didn’t really allow for that to be determined. Let’s take a look at why.
To start, participation in this study was directed through a college-credit-granting course. In other words, participants had to register for the course in order to be included in the study. The reported adherence of 76% is significantly higher than the oft-cited 50% or less seen in other research studies, perhaps because the students felt more compelled to exercise due to the course requirements.
Next, there were 3,773 students recruited throughout the course of the study, but only 2,680 were included in the adherence analysis, with 2053 (76%) being classified as adherent. If we add the 1,113 individuals who were unaccounted for, the adherence rate drops to 54%, which seems more likely. To compound matters, all of the subjects were young, e.g. 18-35 years old, and likely of similar socioeconomic status, as they were all enrolled in college. Moreover, only 855 of the 3,773 subjects were included for genetic testing. It is possible that these sampling biases had something to do with the relatively weak data, which would have had some limited generalizability.
Additionally, the researchers only looked at 26 single nucleotide polymorphisms (SNPs) in 6 genes. This is a relatively restricted view considering there are over 73 different genes associated with increases in fitness and performance.  I would have liked to see a more expanded search for the genetic influence on exercise adherence.
One of the biggest criticisms I have centers around the under-dosed exercise protocol given. To start, there was no recommendation for resistance training as part of the exercise program. Given that the Physical Activity Guidelines for Americans have recommended at least twice weekly resistance training since 2008, two years prior to when this study was registered, and the fact that participants were registered for a college-credit granting course, this is extremely frustrating. On the other hand, the prescription to exercise 3x/wk for at least 30 minutes at 65-85% of maximum heart rate falls into the vigorous intensity exercise classification, which would fall into the acceptable range (75-150 minutes) for vigorous intensity aerobic activity.
The researchers also did not include any of the raw before and after data, e.g. how much weight did people lose, how did their body fat change, what happened to their blood pressure, etc. It would have been great to see how a relatively small increase in physical activity affected these outcomes.
So where does this leave us? I think the totality of the evidence indicates there are substantial genetic influences on response to exercise. For example. Ahtianen et al. found that ina group of nearly 300 subjects, muscle size adaptations to ~6 months of resistance training ranged from a loss of 11% to a gain of 30%, independent of age or sex. Strength adaptations showed a similar heterogeneity, ranging from a loss of 8% to a gain of 60% in the same ~6 months.  This suggests that different people respond differently to a given training program. As suggested in the introduction section, some of this variance is likely attributable to the effect of genetics on training outcomes and, likely, on training adherence.
If we want to get more people exercising in order to reap the health benefits of physical activity, we’ll need to design the program to suit them as an individual, which includes their genetics. Sir William Osler, widely-regarded as the father of modern medicine said it best:
“If there were no individual variability, medicine would have been science not an art.”
Just replace “medicine” with programming. Thanks for reading.
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