Mois : avril 2024

Scientists have discovered that frequently interrupting prolonged sitting with physical activity, such as short walks or squats, can help control glucose levels in overweight and obese males [1].

Don’t just sit there!

Prolonged sitting is the curse of modern times. It has been associated with various health problems, such as diabetes, poor heart health, weight gain, depression, dementia, and cancer. In overweight and obese people, sedentary lifestyle prevents calorie burning. It is a well-known recommendation to interrupt prolonged sitting with bouts of physical activity [2], but the actual effects of type, duration, and intensity of exercise remain an open question, especially in young individuals.

In this study by Finnish and Chinese scientists, the authors analyzed the effects of various kinds of sitting-interrupting activity in overweight and obese men. While various types of exercise can differ in energy expenditure, in this study, experiments were intentionally isocaloric – that is, involving similar caloric expenditure. The specific outcome the researchers monitored was the dynamic of glucose levels (glycemic control), which is something many obese people struggle with. Failing to maintain glycemic control can quickly lead to diabetes.

The study was relatively small, with 18 participants in total, but it had an interesting design. Each participant performed four different experiments with a seven-day washout period between them. Diets were standardized during the whole study.

SIT, ONE, WALK, SQUAT

The first experiment involved sitting for 8.5 hours. The participants were allowed to use their computers or read. The resulting average energy expenditure was 1,014.6 kcal. Standardized bathroom breaks were arranged and accounted for so that they did not contaminate the results. In their paper. The researchers dubbed this setting SIT.

In the second experiment, dubbed ONE, the sitting was only interrupted once after one hour by a 30-minute-long walk on a treadmill at 4 km (2.5 miles) per hour. In the third experiment, WALK, there were 10 interruptions, each one involving a short 3-minute walk. In both ONE and WALK, the average energy expenditure was measured at 1,123 kcal. Finally, the fourth setting was called SQUAT and, as you probably guessed, involved squatting: ten 3-minute-long interruptions in total, with the average energy expenditure of 1,120 kcal.

ONE resulted in a significant improvement in glucose control, reaching an AUC (area under curve) of 9.2 mmol/L/hour as opposed to 10.2 in SIT. More interestingly, the two other types of activity brought about an even more substantial improvement in glucose control (7.9 mmol/L/hour for both WALK and SQUAT).

Muscle activation matters

Why were WALK and SQUAT twice as effective in lowering glucose levels as ONE despite equaling it in energy expenditure? The researchers might have an answer. In addition to CGMs (continuous glucose monitors) and accelerometers, the participants wore special shorts laced with electrodes, enabling the scientists to perform EMG (electromyography) on various groups of muscles. WALK and SQUAT showed a much stronger signal of acute dynamic muscle activation, albeit in different muscles (quadriceps and glutes, respectively).

“Our data,” the authors conclude, “suggests that frequent interruptions to prolonged sitting, as opposed to a single bout of activity, are more effective in enhancing aEMG (average EMG amplitude) in the specific muscle groups engaged in the interruption activity, leading to a more favorable glycemic response.”

Further analyzing their data, the researchers found that activity duration was not associated with the efficacy of glycemic control. Previous studies suggest a possible explanation. When active, muscles uptake glucose, but only up to a certain threshold [3]. “Muscle cells,” the researchers write, “may reach their maximum capacity for glucose uptake within a defined timeframe, rendering additional muscle activity less effective in further lowering glucose response.”

To put things into perspective, the attenuation of glucose levels achieved during the experiments was not drastic, but it nevertheless might be helpful for trying to keep glucose in check. This research adds yet another good reason to frequently interrupt prolonged sitting with physical activity. Another recent study found that even 1- or 2-minute bouts of activity were associated with reduced mortality risk.

Sedentary behavior has become a significant global public health concern, with interrupting prolonged sitting being recognized as an effective strategy for promoting health. Recent research suggests that frequent, brief bouts of physical activity are more beneficial than longer, less frequent interruptions in improving glycemic control. By examining muscle activity patterns during interruptions, our study offers a promising physiological explanation for the effectiveness of frequent interruptions in managing glucose responses. Importantly, we found that increased intensity of lower limb muscle activation during multiple breaks leads to a more significant reduction in glucose response compared to a single break. This insight sheds light on the importance of elevated muscle activity, particularly during frequent sit-to-activity transitions, as a potential mechanism for improved glycemic control when interrupting prolonged sitting. It provides valuable guidance for designing intervention strategies aimed at promoting health through increased muscle activity.

Literature

[1] Gao, Y., Li, Q. Y., Finni, T., & Pesola, A. J. (2024). Enhanced muscle activity during interrupted sitting improves glycemic control in overweight and obese men. Scandinavian Journal of Medicine & Science in Sports, 34(4), e14628.

[2] Hwang, C. L., Chen, S. H., Chou, C. H., Grigoriadis, G., Liao, T. C., Fancher, I. S., … & Phillips, S. A. (2022). The physiological benefits of sitting less and moving more: opportunities for future research. Progress in cardiovascular diseases, 73, 61-66.

[3] Brewer, P. D., Habtemichael, E. N., Romenskaia, I., Mastick, C. C., & Coster, A. C. (2014). Insulin-regulated Glut4 translocation: membrane protein trafficking with six distinctive steps. Journal of Biological Chemistry, 289(25), 17280-17298.

Researchers have published the results of a study in Aging Cell, finding some evidence that type 2 diabetes causes accelerated aging.

Later-generation clocks only

This paper begins with explanations of Type 2 diabetes and epigenetic clocks, noting that principal component (PC) versions of clocks may give stronger results because they filter out noise. These researchers eschew first-generation clocks entirely, focusing on GrimAge and PhenoAge along with DunedinPACE, which solely measures age acceleration.

Previous studies have found associations between Type 2 diabetes and aging: One study found that DunedinPACE, which was trained on Western participants, has also found accelerated aging to be associated with diabetes in Taiwanese people [1]. An earlier study by the same researchers found connections between diabetes and aging as measured by other clocks as well [2]. Most importantly, a previous study has found evidence for a causal connection: that it’s diabetes that accelerates aging [3]. These researchers sought to more firmly prove this connection.

A robust cohort

This study used data from the Chinese National Twin Registry (CNTR). A total of 535 pairs of twins (380 pairs identical), including 157 pairs that had both baseline and 4- or 5-year follow-up data (95 pairs identical), were included. These participants were measured for such diabetes-related metrics as fasting glucose and HbA1c along with potential confounders, such as smoking, education, BMI, alcohol consumption, and exercise. This wealth of data allowed the researchers to conduct both cross-sectional and longitudinal analyses.

On average, the participants were 50 years old, and 10% of them had glycemic markers that categorized them as having type 2 diabetes. Among the participants that had follow-up data, almost 12% had type 2 diabetes at baseline and 17% had it at follow-up.

In the cross-sectional study, the researchers found that a couple of measurements related to diabetes, as expected, were strongly associated with age accleration as measured by all three clocks, most notably PhenoAge: people with excess HbA1c had an extra three years of aging on average, according to this clock. Fasting glucose also had a very strong association. Diabetes, itself, was less strongly associated, and did not reach statistical significance in any of the clocks.

A direct longitudinal study did not reveal much additional information. However, a cross-lagged study, which compared measurements at follow-up and at baseline, revealed that people with higher fasting glucose, higher HbA1c, or higher triglyceride and glucose (TyG) indices at baseline were likely to have higher age acceleration according to DunedinPACE at follow-up. The TyG index was associated with higher acceleration according to GrimAge at followup.

Limited, but relevant, evidence

When the analysis was broken down into individual strata, the associations were found to be significant only in men and in people with lower levels of education. This stratification, however, decreases the number of people in these subgroups, which therefore have less statistical power.

While the identical twin pairs eliminated the possibility of different genetic factors leading to different outcomes, the researchers note that their relatively small number, particularly in the group that had both baselines and follow-ups, also hampered this study’s statistical power. However, they were able to come to multiple conclusions, two of the most notable being that DunedinPACE is uniquely sensitive to glycemic metabolism and that these results are not affected by blood cell composition.

In total, while this study provides solid evidence that diabetes accelerates epigenetic aging regardless of confounders, it is still not fully proven, and further research should be conducted to verify this evidence. However, diabetes is still strongly related to early death through a variety of well-known morbidities, such as cardiovascular disease [4].

Literature

[1] Lin, W. Y. (2023). Epigenetic clocks derived from western samples differentially reflect Taiwanese health outcomes. Frontiers in Genetics, 14, 1089819.

[2] Lo, Y. H., & Lin, W. Y. (2022). Cardiovascular health and four epigenetic clocks. Clinical Epigenetics, 14(1), 73.

[3] Kong, L., Ye, C., Wang, Y., Hou, T., Zheng, J., Zhao, Z., … & Wang, T. (2023). Genetic evidence for causal effects of socioeconomic, lifestyle, and cardiometabolic factors on epigenetic-age acceleration. The Journals of Gerontology: Series A, 78(7), 1083-1091.

[4] Palmer, A. K., Gustafson, B., Kirkland, J. L., & Smith, U. (2019). Cellular senescence: at the nexus between ageing and diabetes. Diabetologia, 62, 1835-1841.

The authors of a recent paper published in GeroScience used an alternative statistical test to reanalyze data from the Interventions Testing Program and identified additional life‑extending compounds [1].

The crucial step of data analysis

A typical biological experiment can be divided into three stages: planning, executing, and results analysis. The last part can be done in multiple ways, such as by using different statistical methods to focus on different outcomes.

The authors of a recent paper decided to use the data from The National Institute on Aging’s Interventions Testing Program (ITP) and reanalyze it. This program, which we have covered previously, is “a multi-institutional study investigating diets and dietary supplements purported to extend lifespan and delay disease and dysfunction.”

For the third stage of their experiment, the analysis, the ITP scientist used the log-rank test combined with the Allison-Wang test. The log-rank test “assumes an effect on mortality hazard independent of age.” The Allison-Wang test tests for the “effects on maximum lifespan.” So far, the ITP has tested 48 drugs, and the log-rank test analysis identified 12 that appear to positively impact lifespan.

The way the log-rank test is constructed makes it “most sensitive to interventions with consistent effects on mortality through the lifespan.” However, if an intervention affects mortality only through a limited period, such as the early stages of life, this test might not be able to identify it.

To remedy this, the authors of this paper used the Gehan-Breslow-Wilcoxon (Gehan) test to reexamine ITP survival data. The Gehan test shows more sensitivity in cases where age-specific effects can be observed, especially if those effects are at early ages [2]. The authors also note that while ITP researchers have used the Gehan test several times, it hasn’t been used systematically. Using the Gehan test allowed the authors to find six additional interventions that affect lifespan in mice.

Sex-specific lifespan extension drugs

When ITP data was reanalyzed with the Gehan test, some of the compounds that hadn’t shown a statistically significant impact on mouse lifespan with the log-rank test now appeared to show statistical significance and vice versa. What’s more, the effect appeared to be sex-specific.

According to the Gehan test, female lifespan was significantly increased by caffeic acid phenethyl ester (CAPE), leading to a median lifespan extension of 5%, and green tea extract prolonged the female median lifespan by 7%. CAPE has anti-inflammatory, antioxidant, and anticancer properties [3], and green tea extract has potent antioxidant properties [4].

On the other hand, according to the Gehan test, different compounds significantly extended lifespan only in males. One of them was the diabetes drug metformin, which increased the median lifespan of males by 8%. Similarly, a median lifespan increase of 7% in males was seen for both enalapril and 17-DMAG, which was considered statistically significant using the Gehan test. 17-DMAG is a compound with an anti-tumor, anti-inflammatory, and neuroprotective function [5], and enalapril is a drug used for blood pressure management.

Another compound tested by ITP, 1,3‑butanediol (BD), has ketogenic effects, and one of its metabolites is suggested to be responsible for the beneficial effects of a ketogenic diet [6]. According to the new analysis, BD showed a statistically significant lifespan increase (9%) in males. This was not significant when the log-rank test was used, but when female lifespan was analyzed, the log-rank test showed statistical significance even though the median lifespan increase was only 2%. The Gehan test, in this case, didn’t show significance.

Minimizing false negatives

The authors are aware that this secondary analysis might lead to an increase in false positive rates. However, they believe this analysis was important since the survival plots of ITP experiments suggested that some of the compounds’ efficacy might vary with age, and the log-rank test used in the initial analysis might be insensitive to those changes and not identify those compounds. On the other hand, the Gehan test is a good statistical analysis that complements the log-rank test.

The authors also point out that not conducting a test like the Gehan test might lead to false negatives. This is especially important in programs such as the ITP, which aims to identify geroprotective interventions that should be followed up further. If ITP does not identify the compound as a promising candidate, it will most likely not be pursued. Therefore, it is essential to minimize false negative rates.

The researchers also point out that their study showed that some compounds might have a non-uniformly distributed effect on mortality reduction over a lifetime. Some of the identified compounds attenuate mortality during earlier stages of life and might not be geroprotective during later stages. However, they believe the action of these compounds during early life is still important, since this is when aging is already starting to take place. Those compounds can still positively impact pathways that cause aging in this particular period.

The mortality effects of the compounds that these researchers identified are rather small and diminished with age. They discuss the need for more research into the impact of age on pharmacokinetics and pharmacodynamics to understand whether aging leads to a loss in drug efficacy or whether the effect of drugs is limited to certain periods of life for other reasons.

Literature

[1] Jiang, N., Gelfond, J., Liu, Q., Strong, R., & Nelson, J. F. (2024). The Gehan test identifies life-extending compounds overlooked by the log-rank test in the NIA Interventions Testing Program: Metformin, Enalapril, caffeic acid phenethyl ester, green tea extract, and 17-dimethylaminoethylamino-17-demethoxygeldanamycin hydrochloride. GeroScience, 10.1007/s11357-024-01161-9. Advance online publication.

[2] Harrington DP, Fleming TR. A class of rank test procedures for censored survival data. Biometrika. 1982;69(3):553–66.

[3] Taysi, S., Algburi, F. S., Taysi, M. E., & Caglayan, C. (2023). Caffeic acid phenethyl ester: A review on its pharmacological importance, and its association with free radicals, COVID-19, and radiotherapy. Phytotherapy research : PTR, 37(3), 1115–1135.

[4] Strong, R., Miller, R. A., Astle, C. M., Baur, J. A., de Cabo, R., Fernandez, E., Guo, W., Javors, M., Kirkland, J. L., Nelson, J. F., Sinclair, D. A., Teter, B., Williams, D., Zaveri, N., Nadon, N. L., & Harrison, D. E. (2013). Evaluation of resveratrol, green tea extract, curcumin, oxaloacetic acid, and medium-chain triglyceride oil on life span of genetically heterogeneous mice. The journals of gerontology. Series A, Biological sciences and medical sciences, 68(1), 6–16.

[5] Mellatyar, H., Talaei, S., Pilehvar-Soltanahmadi, Y., Barzegar, A., Akbarzadeh, A., Shahabi, A., Barekati-Mowahed, M., & Zarghami, N. (2018). Targeted cancer therapy through 17-DMAG as an Hsp90 inhibitor: Overview and current state of the art. Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie, 102, 608–617.

[6] Han, Y. M., Ramprasath, T., & Zou, M. H. (2020). β-hydroxybutyrate and its metabolic effects on age-associated pathology. Experimental & molecular medicine, 52(4), 548–555.