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.
