By Mercy Kagoda, MD, MPH
Preventive Medicine Physician, Lotus Integrative Medicine, Santa Monica, CA
Dr. Kagoda reports no financial relationships relevant to this field of study.
- Twelve weeks of high-intensity interval training reversed age-related differences of mitochondrial proteins in participants age 65 to 80 years, and was associated with the greatest increase in gene transcripts for both participants 18 to 30 years of age and 65 to 80 years of age.
SYNOPSIS: High-intensity interval training performed over 12 weeks reversed age-related differences of mitochondrial proteins in adults 65 to 80 years of age, as well as increased insulin sensitivity and VO2 peak, and decreased fat free mass in adults 18 to 30 years of age and 65 to 80 years of age.
SOURCE: Robinson MM, Dasari S, Konopka AR, et al. Enhanced protein translation underlies improved metabolic and physical adaptations to different exercise training modes in young and old humans. Cell Metabolism 2017;25:581-592.
The clinical benefits of exercise are well-accepted for improving various diseases.1,2 However, the changes occurring at the molecular level are not completely understood. Robinson et al contrasted the changes at the physical level with changes at the molecular level.3
A total of 399 participants initially were recruited and sorted into two age groups: 18 to 30 years or 65 to 80 years. Participants were tested over 12 weeks after randomization into three groups: high-intensity interval training (HIIT), resistance training (RT), or combined training (CT). Exclusion criteria included performing structured physical activity of > 20 minutes twice a week, body mass index (BMI) > 32 kg/m2, cardiovascular disease, diabetes, untreated thyroid disease, renal disease, type 2 diabetes or fasting glucose > 110 mg/dL, pregnancy, smoking, implanted medical devices, and numerous classes of medications (insulin sensitizers, insulin, corticosteroids, beta-blockers, peroxisome proliferators activated receptor gamma agonists, tricyclic antidepressants, etc.). Of the 399 initially assessed, 72 (18%) were eligible for the study.
HIIT was undertaken five days per week: three days/week of cycling at > 90% peak oxygen consumption 4 x 4 minutes with three minutes pedaling at no load, and two days/week of treadmill walking for 45 minutes at 70% peak oxygen consumption.
RT was done twice weekly with both upper and lower body exercises (four sets of eight to 12 repetitions).
The CT group first completed a 12-week sedentary period wearing accelerometers to track any structured activity, after which they began activity that included five days/week of cycling at 70% peak oxygen consumption for 30 minutes, and four days of weight lifting but with fewer repetitions than the RT group.
Baseline characteristics of both age groups (18 to 30 years and 65 to 80 years) included BMI, body fat, fasting insulin, and fasting glucose. As expected, the older age group had statistically significantly higher BMI (26.6 ± 3.8 kg/m2 vs. 25.6 ± 3.3 kg/m2), body fat (37.9 ± 6.1% vs. 31.9 ± 4.7%), and fasting glucose (105 ± 8 mg/dL vs. 96 ± 7 mg/dL). However, the fasting insulin concentration between the two groups was similar: 5.5 ± 2.6 ulU/mL for 18 to 30 years, and 4.3 ± 1.8 ulU/mL for 65 to 80 years. Within the two age groups, baseline characteristics of the three exercise groups were similar.
VO2 peak or VO2 max is the maximum volume of oxygen that a body can use during intense exercise. It depends on cardiac output and arteriovenous oxygen difference, and is a measure of cardiorespiratory function. VO2 peak changes at different age groups. VO2 peak can be used to approximate the metabolic equivalent (MET), which is a unit of sitting resting oxygen uptake. Elite endurance athletes have METs of 18, while moderately active young men have a VO2 max that is approximately 12 METs.4 In this paper, VO2 peak was measured indirectly using expired and inspired volumes of carbon dioxide and oxygen on an electronically braked cycle ergometer and not on a graded intensity treadmill walking test. VO2 max indicative of good health and good cardiorespiratory capacity is ≥ 42 mL/kg(-1) min(-1) in men, and ≥ 35 mL/kg(-1) min(-1) in women.5 The authors used a cycle ergometer to measure VO2 peak. Of note, other studies have found that VO2 peak measured using a treadmill tends to be higher (~7%) than cycle values, presumably due to greater muscle mass activation in treadmill testing.5
Body composition was measured with a dual-energy X-ray absorptiometry after an overnight fast.
Pre- and post-intervention measurements of insulin sensitivity and muscle biopsies were performed after 72 hours of specific weight maintenance meals consisting of 30% fat, 20% protein, and 50% carbohydrates. The muscle biopsies of the vastus lateralis, one of the quadriceps muscles, were used for analysis of RNA, protein, methylation, and total genes that changed (either up-regulated or down-regulated).
WEB-based Gene Se T Analysis Toolkit (WebGestalt) is a free “functional enrichment analysis web tool.”5 Functional enrichment analysis, also known as gene set enrichment analysis, is a tool used to interpret gene lists or sets. In an analysis of genome scale data, lists of up-regulated or down-regulated genes or proteins are created.6,7 WebGestalt helps “translate the identified gene sets into a better understanding of the underlying biological themes.”8
The statistical analysis test included paired t-test for the before and after (sedimentary followed by combined training), and analysis of variance (ANOVA) to compare the different means from the three groups: HIIT, RT, and CT. Tukey’s procedure was used in conjunction with ANOVA to decrease the number of false positives.
Within the age groups, baseline characteristics were similar. Of the 72 subjects who met the strict inclusion criteria (45 in the younger category and 27 in the older category), 29 of the younger category completed both baseline screening and the training protocol, and 23 of the older category completed both baseline screening and the training protocol. In the younger category, five subjects discontinued training because of moving, medical issues unrelated to the study, lack of time, and incomplete baseline screening. Of the older category, three subjects discontinued training because of medical issues unrelated to the study and loss to follow-up.
1. VO2 peak, skeletal muscle mass, and insulin sensitivity improved with training.
VO2 peak increased in both age groups, with maximal and statistically significant increase in the HIIT groups (~28% vs. ~17% in younger and older, respectively) and CT groups (17% vs. 21% in younger and older, respectively). There was no significant change following RT in both younger and older groups. Fat free mass increased in all age groups, with the greatest increase in RT in the younger group, as expected. Insulin sensitivity, measured as the glucose rate of disappearance, increased in most of the training groups with the exception of older CT. At baseline, there was no difference in insulin sensitivity between the two age groups despite lower mitochondrial respiration in older adults. Fasting insulin and glucose did not change over 12 weeks in any training group.
2. Exercise training in the 65 to 80 years group led to up-regulation of mitochondrial proteins, and an improvement in mitochondrial function.
Mitochondrial function was assessed from mitochondria obtained by muscle biopsy pre- and post-intervention. As expected, at baseline, mitochondrial respiration was lower in older adults. HIIT statistically significantly increased mitochondrial respiration in both age groups +49% vs. +69% in younger and older, respectively. CT statistically significantly increased mitochondrial respiration in only the younger group at +38%. RT did not increase mitochondrial respiration in either group.
3. There was an increase in skeletal muscle gene expression in both age groups.
As expected, at baseline, there were differences in messenger ribonucleic acid (mRNA) in older vs. younger groups, with 267 gene transcripts lower and 166 higher in the older group. Mitochondrial, muscle growth, and insulin signaling genes were down-regulated in the older group. However, HIIT increased insulin signaling, mitochondrial, and muscle growth genes in older adults, and overall HIIT increased the expression of genes in both age groups. Proteins involved with mitochondrial biogenesis and mitochondrial envelope also increased with HIIT. Despite an increase in protein abundance, mRNA was inversely related to mitochondrial and ribosomal protein abundance.
Genes primarily involved in angiogenesis were the most commonly up-regulated across both age groups and all training groups. These genes were 55 in number, and upstream analysis identified them to include angiotensinogen, vascular endothelial growth factor, interleukin-10 receptor subunit, and fibroblast growth factor. Interestingly, skeletal muscle methylation was not affected significantly by 12 weeks of training.
The findings in this study showed that HIIT increased VO2 peak, mitochondrial respiration, fat free mass, muscle strength, and insulin sensitivity in both younger and older age groups. CT had lower improvements in VO2 peak and fat free mass than both HIIT and CT. RT did not increase VO2 peak or mitochondrial function, and fasting insulin and glucose did not change over 12 weeks in any training group. Perhaps with either a longer duration of exercise sessions or increased frequency of sessions in a week, we could expect changes in fasting insulin and glucose.
One of the main strengths of this prospective study is that it spanned both clinical research and basic science research, shedding light on the molecular changes occurring with physiologic changes. For example, angiogenesis was a common factor among the three training groups, and was one of the main 55 gene sets that overlapped in all training groups and ages. Also, since this paper straddled two usually distinct publishing fields, it easily could have been two or even three papers. When presenting results, there is a discussion of prior studies that may be helpful.
Although this study further characterizes the molecular processes that go with various physiologic VO2 peak measurements, the older subjects used are not average 65- to 80-year-old people. The exclusion rate was high, with more than 80% of the initial subjects excluded as described above. It also was not clear if the final participants had any diseases or medical conditions. In clinical practice, how many 65- to 80-year-old patients do not have cardiovascular disease or diabetes or are not taking any of the extensive list of medications that was provided? For the select small number of 65- to 80-year-old patients without any medical conditions and not on any medications, one could consider recommending HIIT after assessing medical safety of physical activity. Although the findings in the older age group have limited generalizability, the younger age group does not. Most 18- to 30-year-olds are similar to those who were studied.
It is not clear why there was a wait time of 72 hours prior to performing the pre- and post-intervention measurements. Pre- and post-metabolic measurements were done after three days of weight maintenance meals (20% protein, 50% carbohydrates, and 30% fat). The percentage of the major food groups is approximate to the percentage of the general public. Perhaps if the measurements were completed within 24 hours, there would have been greater changes.
Interestingly, at baseline, there was no difference in insulin sensitivity between the two age groups despite lower mitochondrial respiration in older adults. The authors suggested that differences in insulin sensitivity could be better explained by adiposity and changes in exercise capacity rather than the functional capacity of mitochondria. Other studies have shown that insulin resistance is associated with decreased efficiency of the mitochondrial respiratory chain. Overall, this was a very good study that provided further understanding of some of the genetic changes that occur with resistance training and HIIT, and why exercise in general is prescribed for continued health as well as particular medical conditions.
- Lawton BA, Rose SB, Elley CR, et al. Exercise on prescription for women aged 40-74 recruited through primary care: Two year randomised controlled trial. BMJ 2008;337:p.a2509.
- Sørensen JB, Skovgaard T, Puggaard L. Exercise on prescription in general practice: A systematic review. Scand J Prim Health Care 2006;24:69-74.
- Robinson MM, Dasari S, Konopka AR, et al. Enhanced protein translation underlies improved metabolic and physical adaptations to different exercise training modes in young and old humans. Cell Metabolism 2017;25:581-592.
- Fletcher GF, Froelicher VF, Hartley LH, et al. Exercise standards. A statement for health professionals from the American Heart Association. Circulation 1990;82:2286-2322.
- Loftin M, Sothern M, Warren B, Udall J. Comparison of VO2 peak during treadmill and cycle ergometry in severely overweight youth. J Sports Sci Med 2004;3:554-560.
- WEB-based Gene SeT AnaLysis Toolkit. Available at: . Accessed Aug. 10, 2017.
- Gene Ontology Consortium. GO Enrichment Analysis. Available at: . Accessed Aug. 10, 2017.
- Wang J, Duncan D, Shi Z, Zhang B. WEB-based gene set analysis toolkit (WebGestalt): Update 2013. Nucleic Acids Res 2013;41:W77-W83.