Research Blog

Cigarette Smoke and Muscle Degradation


Exposure to cigarette smoke causes muscular degradation, especially in oxidative (aerobic) muscle fibers. Understanding the mechanism of this muscle degradation will aid in providing treatment to those suffering from COPD.

A competitive athlete is wary of cigarette smoke because of its established negative pulmonary effects.  However, recent research has found that cigarette smoke also causes muscle degradation. A team of researchers from the University of California, San Diego is searching for possible biological mechanisms by which cigarette smoke affects muscle.

People suffering from smoking-induced chronic obstructive pulmonary disease (COPD) exhibit changes independent from the pulmonary system in their muscles. These changes include loss of muscle strength and mass, receding capillaries in the muscle, muscle transition from oxidative fibers to glycolytic fibers and impaired muscle energy metabolism.

To assess the biological pathway that links cigarette smoke exposure with muscle degradation, the researchers exposed mice to cigarette smoke for 8 and 16 weeks (TNF-alpha Mediated Reduction in PGC-1alpha may Impair Skeletal Muscle Function After Cigarette Smoke Exposure, 2009, Kechun Tang, et al.).  The soleus and extensor digitorum longus (EDL) muscles were then analyzed.  Because the EDL is composed of glycolytic muscle fiber it showed, as the researchers expected, a smaller change in oxidative associated enzymes and cytokines as a result of cigarette smoke. In the soleus, aerobic oxidative fibers were converted to anaerobic glycolytic fibers. The decrease in capillary density in the soleus can be seen in the figure below.

Reduced soleus and EDL capillarity in mice exposed to cigarette smoke for 8 and 16 weeks bouts.  Measured in capillary number/sq mm.

Cigarette smoke was found to increase levels of the inflammatory cytokine TNF-alpha. The transcriptional co-factor PGC-1alpha has been shown to control capillarity density in the muscle fiber through the angiogenic factor VEGF. TNF-alpha was found to mediate the levels of PGC-1 in vitro. Therefore, mediating the inflammatory cytokine TNF-alpha may result in normal expression of the co-factor PGC-1alpha providing COPD patients with a means of combating the muscular degradation associated with cigarette smoke. As the figure below demonstrates, TNF-alpha levels were raised significantly with cigarette smoke exposure. This elevation in TNF-alpha saw a major decrease in the VEGF transcription factor PGC-1alpha in the oxidative heavy soleus muscle.

Demonstrates the decrease in PGC-1alpha with the increase in TNF-alpha following cigarette smoke exposure in mice after 8 and 16 weeks.

In summary, cigarette smoke exposure causes muscular degradation in addition to the adverse pulmonary effects. Athletes, therefore, can expect to see damage to both their pulmonary and muscular systems as a result of exposure to cigarette smoke.  Cgarette smoke is found to elevate levels of inflammatory cytokine TNF-alpha which lowers the transcription factor PGC-1alpha. TNF-alpha may be a target for patients with chronic obstructive pulmonary disease.

Napping and Diabetes Risk

obese or fat or overweight man napping hispanic

Nighttime sleep and daytime nap duration are associated with type 2 diabetes risk. In addition to unaccounted socioeconomic and lifestyle factors this association may arise from sleep deprivation's influence on glucose metabolism.

A several studies have found links between type 2 diabetes risk and sleep patterns. In 2005, a study found that men, but not women, who reported a short sleep duration (≤5 hours of sleep a night) or difficulty maintaining or initiating sleep were more likely to suffer from new diabetes in a 12 year follow-up (High incidence of diabetes in men with sleep complaints or short sleep duration: a 12-year follow-up study of a middle-aged population, 2005; Malton L, Broman JE, Hetta J). This study found that women were more prone to develop new diabetes if they reported sleeping for 9 or more hours a night. The study subjects were between the ages of 45 and 65.

The relationship between sleep and diabetes risk was further complicated by a 2009 study that looked at nighttime sleep, daytime napping and diabetes risk independently of each other (Day Napping and Short Night Sleeping Are Associated With Higher Risk of Diabetes in Older Adults, 2009, Qun Xu, et al.).  The study found that those who reported an hour or more of napping a day were more likely to be diagnosed with new diabetes in a 7-year follow-up medical diagnosis. To be included in the study participants had to be healthy and non-obese. Those who reported an hour or more of napping had a higher BMI and reported less physical activity. However, the association between daytime napping and diabetes risk persisted after statistical adjustment for the BMI and physical activity variables.

Like the study published in 2005, nighttime sleep duration influenced diabetes risk as well. However, daytime napping added a twist to the results.  Participants who reported less than seven hours of nighttime sleep were found to have an increase in diabetes risk. The relationship between sleep and diabetes risk was nonlinear for those reporting less than seven hours of sleep. Here is the twist: participants who reported more than nine hours of nighttime sleep had an increased risk of diabetes onset only if they reported daytime napping in excess of an hour.

It is likely that unaccounted for socioeconomic or lifestyle factors explain most of the associations between sleep and diabetes risk. However, some evidence points to potential biological mechanisms that may play a role in the link between sleep deprivation and type 2 diabetes (Reduced Sleep Duration or Quality: Relationships With Insulin Resistance and Type 2 Diabetes, 2009; Esra Tasali, Rachel Leproult, Karine Spiegel). In a study with 11 healthy young male subjects, sleep deprivation was shown to increase glucose intolerance and insulin resistance.  Following breakfast after sleep deprivation, glucose levels were higher despite similar levels of insulin secretion. The graphs below show the results of the study.

The line graphs above show the difference in glucose and insulin levels following 4-hours in bed (sleep deprivation) and 12 hours in bed (baseline).  Note the shaded area showing elevated glucose levels following breakfast after sleep deprivation.

The brain utilizes up to 50% of the body's total glucose. Therefore, a "tired" brain resulting from sleep deprivation significantly impacts the body's glucose metabolism.

Other factors affected by sleep play a role in glucose metabolism. During sleep debt, the levels of glucose regulating hormones such as growth hormone and cortisol are altered. Inflammatory markers known to be predisposed to insulin resistance have been shown to appear from a lack of sleep. Obstructive sleep apnea has been shown to influence several glucose regulators. As the image below shows, obstructive sleep apnea and other factors provide a positive-feedback loop that results in diabetes.

obstructive sleep apnea diabetes insulin resistance

Positive-feedback loop linking diabetes, OSA, sleep and glucose regulators.

VEGF Expression

VEGF Protein


VEGF is a growth factor that has been linked to both curing and causing numerous diseases. Its expression through exercise may provide insight on its role in the human body.

Vascular endothelial growth factor (VEGF) is plays a major role in many physiological functions and has disease implications. VEGF is a key regulator of angiogenesis, the process of building new blood vessels. In a previous research blog post, Controlling Alzheimer's Risk, it was mentioned that increased VEGF in the brain leads to a decreased risk of Alzheimer's. VEGF counters the loss of the brain's blood vessels that results from natural aging. However, the past decade has seen a flurry of debate regarding VEGF's role in cancer.  

Cancer patients have been found to have increased levels of VEGF around their tumors. VEGF inhibitors are suppressed by malignant cells. This allows new blood vessels to penetrate through the developing tumor. Thus, VEGF suppressors have been a focus of several cancer-treating drugs. Their performance in cancer patients has shown mixed results. In some trials the anti-VEGF drugs have, in concert with chemotherapy, decreased tumors. Other trials have found that anti-VEGF drugs make the tumor more potent.

VEGF upregulation, an increase in cellular VEGF receptors, has been linked to brain edema, tumors, anti-inflammatory diseases and age-related macular degeneration, the leading cause of blindness.

VEGF levels fluctuate with the menstrual cycle is essential for embryonic development.  VEGF is necessary for postnatal development. Partial VEGF inhibition in neonatal mice resulted in stunted growth, increased mortality and impaired organ function, notably the liver (VEGF is required for growth and survival in neonatal mice. 1999: HP Gerber, et al.).  

In a developed human when is VEGF expressed? VEGF is expressed during hypoxia, oxygen suppression, and exercise. However, the mechanism of VEGF expression differs between exercise and hypoxia. A study published in 2010 offers insight into exercise's mechanism of VGEF expression (Exercise-induced VEGF transcriptional activation in brain, lung and skeletal muscle, 2010, Kechun Tang, et al.).

In this study, mice were subject to an hour of exercise on a treadmill and two hours in 6% oxygen. VGEF expression was measured  with transcriptors, mRNA and the actual protein. VGEF levels rise in response to exercise in the brain, lungs and skeletal muscle, but not the liver or heart. Results can be seen in the graph below.

 One hour of exercise signals an increase in transcriptional-regulated VEGF gene expression in brain and lung.  Mice were subjected to a 1-h exercise bout (24 M/min, 10° incline) before the collection of non-skeletal muscle organs and measurement of VEGF transcriptional activity, mRNA and protein levels compared to non-exercised (Resting) mice.

In contrast, hypoxia resulted in higher protein expression in the brain only. Additional differences can be seen in the areas of the brain that saw elevated VEGF expressed. VEGF expression in exercised mice was elevated in the hippocampus only. Mice subjected to hypoxia saw expression elevated in the hippocampus, frontal cortex and striatum.

Exercise increases VGEF protein level in the hippocampus only.  Trends can be observed between Luciferase, mRNA and VEGF level.

Interestingly, exercise produced the same linear relationship between the levels of luciferase transcriptor, VEGF mRNA and VEGF protein across organs suggesting they share a similar cellular mechanism of expression. This may play an impact when looking at the role played by VEGF or VEGF inhibitor in disease treatment.

Please share any thoughts you have on the implications of this research or updates on the medical research being done on VEGF.

Lifestyle Impact on Academic Performance

happy boy with backpack

A healthy lifestyle (participating in daily physical activity, having a healthy nutrition intake, reduced television usage, eating breakfast) appears to aid academic performance.  In addition, a longitudinal study found a link between fitness and academic performance.

There is a lot of conflicting research on the effect students' lifestyle plays on their academic performance. However, two studies published in 2011 found physical activity and a healthy diet play a large role in academic performance.

One of the major problems researchers face when trying to link physical activity or nutrition intake to academic performance is lurking variables. For example, socioeconomic status is a good indicator of academic status. Students from higher socioeconomic strata tend to be more physically fit and nourished. Thus, it is hard to determine cause and effect. Students who are overweight generally have lower self-esteem, another factor in academic performance. Other factors, such as family issues, can simultaneously impact physical fitness, nutrition intake and academic performance. To account for lurking factors, one approach is to do a multivariable longitudinal study, in which the relation between lifestyle and academic performance can only be affected by variables introduced over the course of the longitudinal study. For example, factors such as race, gender and socioeconomic status would remain constant over the course of the longitudinal study.

One longitudinal study used the California Department of Education's physical fitness test, which incorporates aerobic, anaerobic and flexibility components, to track fitness and the California state-wide standardized test to track academic achievement (A Longitudinal Examination of the Link Between Youth Physical Fitness and Academic Achievement, 2011, Rebecca London and Sebastian Castrechini). Two cohorts of students were tracked for four years: one from 4th to 7th grade and a second from 6th to 9th grade. Some interesting observations came out of this study. First, academic success was linked to being white, from an upper socioeconomic class and ability to pass the physical fitness test. Second, the gap in test performance between those who passed the physical fitness test and those who did not became wider over the course of the study. Third, the academic achievement gap between the physically fit and unfit was wider for students from a low socioeconomic background. Fourth, one's ability to pass the physical test was found to be a predictor of academic achievement than BMI.  

Perhaps the most interesting item from the longitudinal study were the academic performance results of those students who passed the initial physical fitness test, but four years later failed the physical fitness test and vice versa. Those who initially passed the physical fitness test, but failed it four years later, were initially on par with the high academic achieving group that passed the physical fitness test both times. Over the four years of the study, this group saw a steady decline to the poor academic achievement seen by the group of students who failed both initial and final physical fitness tests. These results are displayed in the chart below.

Z-score on English Language Arts standardized test as a function of grade and physical fitness.

The other aforementioned study looked at correlations between academic performance, physical activity and nutrition (Relationship of Nutrition and Physical Activity Behaviors and Fitness Measures to Academic Performance for Sixth Graders in a Midwest School District, 2011, Jane Edwards, Lois Mauch, Mark Winkelman). The study looked at 800 sixth graders from Fargo School District in North Dakota. A survey was used to determine daily physical activity, nutritional intake and other lifestyle behaviors. Fitness measures were taken with a mile run, curl-ups, push-ups, height and weight. Academic performance was measured with a reading assessment and math assessment.

Gender and an ability to pay full price for school meals were associated with higher assessment scores. Males did better in math and females did better on reading. Math scores were higher in students who drank more milk and less sweetened beverages (soda, juice), ate breakfast more frequently, had more vigorous physical activity, watched less television, played on sports teams and had better performance on the mile run. Higher reading scores were associated with students who drank less sweetened beverages, had more vigorous and moderate physical activity and watched less television.

One fourth of the students reported spending more than 3 hours a day watching television on school days. In addition, students who had televisions in their bedrooms had higher television usage and spent less time reading.

Only a third of students get the recommended 5 fruits and vegetables a day.

Students who eat breakfast generally have reduced tardiness and better attendance. Breakfast has been shown to increase attention span and memory in students. Students who were obese did not show significant differences in test performance in math or reading. This supports the previous study's conclusion that fitness, not BMI, is a better predictor of academic achievement.  More than four-fiths of students reported getting in at least 20 minutes of physical activity a day, but only one-third reported daily physical activity exceeding an hour. Only a third of the students reported eating 5 fruits or vegetables a day.

In summary, a student's lifestyle plays a role in his or her academic performance. Both studies discussed here suggest that physical activity is linked to better academic performance. Other factors such as eating breakfast, avoiding sweetened beverages, watching less television also appear to play a role in a students success.

If you have personal experience with a healthy lifestyle boosting (or not boosting) academic performance please share it! Please leave your comments on this research.

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