Mois : juin 2024

In Nature Aging, researchers have published the creation of a new clock that uses multiple metrics to evaluate biological aging.

What’s worth measuring?

Multiple metrics have been used to measure aging. The most commonly known in the literature are the epigenetic clocks, such as GrimAge and PhenoAge, but those are not the only sources of information. For many decades, people have been attempting to build clocks based on physical analysis in rodents [1] and people [2], an effort that continues to this day [3].

Some clocks are meant to estimate biological age [4], while others are built around determining how likely it is that an organism will die within a certain timeframe [5]. The latter are often correlated with markers of specific risks, such as cardiovascular risks, but are more geared towards predicting all-cause mortality.

Many methylation-based clocks are built around clinical features, but these researchers have decided to go straight to the source instead, focusing on clinical clocks, which directly measure clinical metrics intead of epigenetic one. Becaue the number of metrics that can be derived from any one individual is very large, this team prioritized focusing on combining them into principal components (PCs), which are often used to analyze large data sets.

Proving the concept

After removing incomplete information, this study used data from just under 1,800 people in the 1999-2000 cohort of the widely referenced NHANES database, and they tested it on just over 2,000 people in the 2001-2002 NHANES cohort to demonstrate its validity. Starting with 165 clinical parameters, the team was able to use an algorithm to compress them into 18 PCs that the team could use to predict all-cause mortality, calculating men and women separately. They used this prediction as their basis for a clock that estimates biological age (PCAge), which, unsurprisingly, was closely correlated with chronological age.

People with lower PCAge estimates had longer telomeres, faster walking speed, and better cognitive performance than people with higher estimates but the same chronological age. Compared to the ASCVD, a widely used measurement of estimating cardiovascular risk, PCAge was found to be a better predictor of mortality and was less sensitive to noise in the data. The researchers also found that PCAge was more useful in predicting survival than the PhenoAge clock.

The researchers were also able to group people into five broad categories based on this data: healthy agers, people with three distinct severity levels of metabolic disorders, and people with multimorbidities. As expected, the healthy aging group had the lowest PCAge compared to chronological age. People who lived to be centenarians, also as expected, had lower PCAges than other people in their cohort who did not live that long.

One of the PCs used in this study, PC2, was found to be the most correlated with healthy aging. When they unpacked this PC back into its components, they found that its strongest elements involved metrics related to fat mass, leading the researchers to suggest that healthy weight maintenance and healthy aging are strongly linked.

PC4 was also found to be very strongly significant, and this PC was comprised of such factors as kidney function, glucose metabolism, and inflammation. People with untreated kidney disease, as measured by the albumin-to-creatinine ratio, also scored worse on PC4’s other components; people with treated disease had much better outcomes than the untreated group. This finding, according to the researchers, underscores the need for early detection and proper prescription of drugs that treat this particular ailment.

The researchers also used their methodology to analyze the effects of caloric restriction, as conducted by the CALERIE trial. Unsurprisingly, they found that caloric restriction was associated with reduced biological age.

An easier clock

Being made of so many measurements, PCAge is hard to derive in the clinic. Therefore, the researchers used the same cohorts to develop a simpler clock, LinAge, which uses standard blood biomarkers along with basic information about patients that is readily available in any medical setting. LinAge was found to be a better predictor of mortality than chronological age, ASCVD, and the chronic frailty scale, and it performed slightly better than PhenoAge in predicting mortalty as well. Despite being trained on 20-year follow-up data, LinAge was found to be effective in determining mortality 25 years away in an earlier NHANES cohort.

The researchers note that they cannot determine the causality of the interventions they suspect to be effective; confounding factors may be at play. However, the clock they have created appears to be accurate and can be quickly derived from simple blood tests and clinical data. They see their tool as being “to geroscience what clinical risk scores are to traditional primary prevention.”

Aging clocks are not replacements for disease-specific risk markers or differential diagnosis. They differentiate subjects who are aging well from those who are aging poorly, helping us to define the former and pointing to interventions to help the latter.

Literature

[1] Ingram, D. K. (1983). Toward the behavioral assessment of biological aging in the laboratory mouse: concepts, terminology, and objectives. Experimental aging research, 9(4), 225-238.

[2] Comfort, A. (1969). Test-battery to measure ageing-rate in man. The Lancet, 294(7635), 1411-1415.

[3] Ferrucci, L., Gonzalez‐Freire, M., Fabbri, E., Simonsick, E., Tanaka, T., Moore, Z., … & de Cabo, R. (2020). Measuring biological aging in humans: A quest. Aging cell, 19(2), e13080.

[4] Horvath, S. (2013). DNA methylation age of human tissues and cell types. Genome biology, 14, 1-20.

[5] Lu, A. T., Binder, A. M., Zhang, J., Yan, Q., Reiner, A. P., Cox, S. R., … & Horvath, S. (2022). DNA methylation GrimAge version 2. Aging (Albany NY), 14(23), 9484.

Scientists have found that older people currently retain more youthful abilities than people who were the same age did in previous decades [1].

How miserable are we?

Recent decades have seen leaps in average life expectancy. However, those mostly stem from successes in curbing childhood mortality and infectious diseases. The gains in later life have been more modest, despite all the advances modern medicine has made. Moreover, some research suggests that while people live longer on average, they also spend an increasingly bigger part of their lives with chronic diseases – in other words, increases in lifespan do not translate into longer healthspan [2].

However, some evidence contradicts the idea that we’re just being kept alive for longer in a miserable, disabled state. A new study by an impressive team of scientists from Columbia University, University of New South Wales, World Health Organization, and University College London seems to suggest otherwise. This study is currently published as a preprint and is under review by Nature.

Big differences, especially in cognition

The researchers utilized two large cohort studies from the UK and China: the English Longitudinal Study on Ageing (ELSA) and the China Health and Retirement Longitudinal Study (CHARLS). Both studies have collected massive amounts of health data on participants from different age cohorts.

While most studies in this field have focused on the burden of disease or severe disability, the researchers constructed instead a composite index of intrinsic capacity, “comprising subdomains of cognitive, locomotor, sensory and psychological capacity and a further subdomain labelled vitality, which may represent underlying age-related biological changes and energy balance.”

What they found was that more recent cohorts had much higher levels of intrinsic capacity at the same age. This capacity expectedly declined with time, but the rate of decline was attenuated in more recent cohorts, suggesting slower aging.

The cohort studies from which this data was derived had not run long enough to directly compare distant cohorts: for instance, it was impossible to directly compare the intrinsic capacities of the 1950 (year of birth) cohort and of the 1930 cohort at the same ages.

Where such direct comparisons were possible, they produced hope-inspiring results. For instance, in ELSA, the intrinsic capacity of the 1950 cohort at age 68 was significantly higher than that of the 1940 cohort at age 62. As the researchers note, this comes close enough to validating the popular saying “70 is the new 60.”

The biggest improvements were between the most recent (1950) cohort and the 1940 cohort. “If these directly observed trends were extrapolated to compare the earliest with the most recent cohort,” the authors write, “the improvements would be significantly greater than those we could observe directly.” Among individual metrics, the largest improvement was in cognition.

Whether those trends are equally valid for both sexes remains a question, as the researchers were unable to perform direct cross-gender comparisons. However, within-gender trajectories were largely similar to those found in the overall analyses.

Does this square with previous research?

The researchers admit that interpreting their results is hard due to the numerous factors at play and that those results seem to contradict previous research, which has found that increases in longevity are accompanied by increased prevalence of chronic conditions in older age. The authors then hypothesize at length about possible reasons for that.

For instance, they suggest that the increased prevalence of chronic diseases at a certain age “is likely driven, at least in part, by people who would have previously died from a condition such as heart disease now surviving into older ages.” Not only is modern medicine increasingly better at keeping people with chronic conditions alive, but it can often ensure a reasonably full, active life.

Thus, today, the same disease can be less debilitating than a decade or two ago. There have also been improvements in detection: some chronic diseases that are routinely diagnosed today might have been overlooked more often in the past, creating an impression of lower disease burden.

Variance of measures used across different studies and periods might also be a factor. For example, the researchers note, a common question used to determine the burden of disability is how easy it is for the respondent to use a phone. However, phones today are very different from phones 20 years ago, and using them requires different abilities.

While this study presents a hefty reason for optimism, it also has many limitations, and its findings will have to be validated by future studies, using additional cohorts and designs.

Our research suggests there have been significant improvements in functioning in more recent cohorts of older people in both England and China. Within ELSA, more recent cohorts entered older ages with higher levels of intrinsic capacity, and subsequent declines were less steep than for earlier cohorts. Improvements were seen in all subdomains. Trajectories were similar for males and females and largely consistent across both countries.

Literature

[1] Beard, J., Katja, H., Si, Y., Thiyagarajan, J., & Moreno-Agostino, D. (2024). Is 70 the new 60? A longitudinal analysis of cohort trends in intrinsic capacity in England and China.

[2] Garmany, A., Yamada, S., & Terzic, A. (2021). Longevity leap: mind the healthspan gap. NPJ Regenerative Medicine, 6(1), 1-7.

Researchers have published a method of rescuing cells from damaged mitochondria and cellular senescence, potentially alleviating major aspects of aging.

Bad mitochondria must be consumed

A core part of autophagy involves selective autophagy receptors (SARs), which build the autophagosomes in which the organelles are consumed [1]. Mitophagy is a subset of autophagy that refers to the consumption of mitochondria. When these tiny power plants become damaged and dysfunctional, they need to be cleared and replaced, and failure to do this drives age-related diseases [2]. Mitochondrial autophagy is primarily spurred by the PINK1/Parkin pathway, which has been extensively studied [3]. PINK1 on the surface of damaged mitochondria leads to the formation of downstream targets, which spur SAR activity through multiple biochemical pathways [4].

However, much previous research into mitophagy has been done in models of intense mitochondrial stress. This research team has also done work demonstrating that a lack of mitophagy is a driver of cellular senescence [5], and this paper builds on that work, elaborating on a pathway fundamental to mitophagy and a small molecule that encourages it.

Mitophagy in human cells

These researchers used a genetically engineered human cell line that expresses a fluorescent reporter compound when mitophagy is conducted, along with a separate reporter that offers real-time information [6]. They then exposed these cells to ionizing radiation to drive them into senescence, according to well-established biomarkers and a halting of the cell cycle. Interestingly, this did not stop autophagy as a whole; in fact, general autophagy was increased, which is in line with previous research [7].

However, mitophagy was greatly suppressed with radiation-induced senescence, which still held true on a different group of cells driven senescent through hydrogen peroxide. Pre-senescent human dermal fibroblasts (HDFs) derived from older people also had reduced mitophagy compared to their younger counterparts.

Mitochondrial superoxide, unlike other reactive oxygen species (ROS), was found to be significantlly downregulated in radiation, hydrogen peroxide exposure, and natural aging. This superoxide is one method by which mitochondria are encouraged to be consumed in mitophagy [8]. The researchers discovered that this was attributable to mitochondrial fusion: instead of being consumed, the mitochondria were fusing together in cells.

This process was amenable to chemical intervention. Exposing cells to paraquat, which encourages superoxide production, also encouraged mitophagy. Targeting the cells with the well-known mitochondrial ROS scavenger mitoquinone (MitoQ) discouraged mitophagy, and exposing HDFs to MitoQ over 11 days drove them into senescence. Rather than being entirely negative, therefore, some ROS are clearly required for proper mitochondrial function.

Multiple other elements were found to be related to this superoxide-induced mitophagy, including the PINK1/Parkin pathway and the autophagy receptor p62. Knocking down p62 suppressed autophagy in proliferating HDFs.

Potential treatments

The researchers investigated whether NAD precusors, including nicotinamide and NR, along with the well-known compound rapamycin could rescue mitophagy, and they found positive results for all of these compounds. Some of the markers associated with senescence were recovered, but it did not restore the cells’ ability to proliferate. NAD precursors were able to encourage mitophagy even in cells that had p62 knocked down.

The researchers then performed a long series of experiments involving p62 and various mutant forms. They found that one particular small molecule, STOCK1N-57534, strongly encouraged p62 to oligomerize, which encouraged mitophagy. Most importantly, applying STOCK1N-57534 to the HDFs derived from older people restored much of their function, decreasing senescence markers and increasing the motility and activity of these cells and their mitochondria.

The researchers clearly believe that they have discovered a potential approach to age-related diseases of mitochondria and senescence. However, this is only a cellular study. Preclinical work in animals will need to be done before this small molecule, or any derivative, can be considered for the clinical trial process.

Literature

[1] Conway, O., Akpinar, H. A., Rogov, V. V., & Kirkin, V. (2020). Selective autophagy receptors in neuronal health and disease. Journal of molecular biology, 432(8), 2483-2509.

[2] Sedlackova, L., & Korolchuk, V. I. (2019). Mitochondrial quality control as a key determinant of cell survival. Biochimica et Biophysica Acta (BBA)-Molecular Cell Research, 1866(4), 575-587.

[3] Onishi, M., Yamano, K., Sato, M., Matsuda, N., & Okamoto, K. (2021). Molecular mechanisms and physiological functions of mitophagy. The EMBO journal, 40(3), e104705.

[4] Lazarou, M., Sliter, D. A., Kane, L. A., Sarraf, S. A., Wang, C., Burman, J. L., … & Youle, R. J. (2015). The ubiquitin kinase PINK1 recruits autophagy receptors to induce mitophagy. Nature, 524(7565), 309-314.

[5] Korolchuk, V. I., Miwa, S., Carroll, B., & Von Zglinicki, T. (2017). Mitochondria in cell senescence: is mitophagy the weakest link?. EBioMedicine, 21, 7-13.

[6] Sun, N., Yun, J., Liu, J., Malide, D., Liu, C., Rovira, I. I., … & Finkel, T. (2015). Measuring in vivo mitophagy. Molecular cell, 60(4), 685-696.

[7] Young, A. R., Narita, M., Ferreira, M., Kirschner, K., Sadaie, M., Darot, J. F., … & Narita, M. (2009). Autophagy mediates the mitotic senescence transition. Genes & development, 23(7), 798-803.

[8] Kataura, T., Otten, E. G., Rabanal‐Ruiz, Y., Adriaenssens, E., Urselli, F., Scialo, F., … & Korolchuk, V. I. (2023). NDP52 acts as a redox sensor in PINK1/Parkin‐mediated mitophagy. The EMBO Journal, 42(5), e111372.