A network of government-funded labs has spent the past 15 years searching for a drug that can slow down aging. The results have researchers excited.
First published in 2016, predictors of chronological and biological age developed using deep learning (DL) are rapidly gaining popularity in the aging research community.
These deep aging clocks can be used in a broad range of applications in the pharmaceutical industry, spanning target identification, drug discovery, data economics, and synthetic patient data generation. We provide here a brief overview of recent advances in this important subset, or perhaps superset, of aging clocks that have been developed using artificial intelligence (AI).
David Sinclair PhD is a biologist and Professor of Genetics at Harvard Medical School, co-director of the Paul F. Glenn Center for the Biological Mechanisms of Aging and author of the forthcoming book “Lifespan: The Revolutionary Science of Why We Age — and Why We Don’t Have To”.
This conversation is about the science behind aging and David’s research on the biology of lifespan extension, treating diseases of aging and extending human lifespan.
Continue reading “David Sinclair Is Extending Human Lifespan | Rich Roll Podcast” »
Aging manifests itself through a decline in organismal homeostasis and a multitude of cellular and physiological functions. Efforts to identify a common basis for vertebrate aging face many challenges; for example, while there have been documented changes in the expression of many hundreds of mRNAs, the results across tissues and species have been inconsistent. We therefore analyzed age-resolved transcriptomic data from 17 mouse organs and 51 human organs using unsupervised machine learning3 –5 to identify the architectural and regulatory characteristics most informative on the differential expression of genes with age. We report a hitherto unknown phenomenon, a systemic age-dependent length-driven transcriptome imbalance that for older organisms disrupts the homeostatic balance between short and long transcript molecules for mice, rats, killifishes, and humans. We also demonstrate that in a mouse model of healthy aging, length-driven transcriptome imbalance correlates with changes in expression of splicing factor proline and glutamine rich (Sfpq), which regulates transcriptional elongation according to gene length. Furthermore, we demonstrate that length-driven transcriptome imbalance can be triggered by environmental hazards and pathogens. Our findings reinforce the picture of aging as a systemic homeostasis breakdown and suggest a promising explanation for why diverse insults affect multiple age-dependent phenotypes in a similar manner.
The transcriptome responds rapidly, selectively, strongly, and reproducibly to a wide variety of molecular and physiological insults experienced by an organism. While the transcripts of thousands of genes have been reported to change with age, the magnitude by which most transcripts change is small in comparison with classical examples of gene regulation2,8 and there is little consensus among different studies. We hence hypothesize that aging is associated with a hitherto uncharacterized process that affects the transcriptome in a systemic manner. We predict that such a process could integrate heterogenous, and molecularly distinctive, environmental insults to promote phenotypic manifestations of aging.
We use an unsupervised machine learning approach3 –5 to identify the sources of age-dependent changes in the transcriptome. To this end, we measure and survey the transcriptome of 17 mouse organs from 6 biological replicates at 5 different ages from 4 to 24 months raised under standardized conditions (Fig. 1A). We consider information on the structural architecture of individual genes and transcripts, and knowledge on the binding of regulatory molecules such as transcription factors and microRNAs (miRNAs) (Fig. 1B). We define age-dependent fold-changes as the log2-transformed ratio of transcripts of one gene at a given age relative to the transcripts of that gene in the organs of 4-month-old mice. As expected for models capturing most measurable changes in transcript abundance, the predicted fold-changes (Fig. S1) match changes empirically observed between distinct replicate cohorts of mice (Figs. S2 and S3).
To me cryonics just makes sense. It may not be pretty but, just like open heart surgery, it is one of those things that, without any guarantees, can possibly extend your life [very] substantially. Thus, especially given the alternative, I just can’t quite make sense of the slow rate of adoption evident not only in North America but also across the world. And so I am always happy to discover new books that lay out the scientific argument for cryonics while making it easily digestible and giving it a very personal, human perspective. Since the most recent book, I thoroughly enjoyed on this topic was Frozen to Life: A Personal Mortality Experiment I thought that D.J. MacLennan will make an excellent guest on my podcast. I was not wrong about that.
During our 1 hour conversation with D.j. MacLennan we cover a variety of interesting topics such as: why he decided to write Frozen to Life and who is it for; cryonics as a glass-state time travel; why he chose neuro- rather than full-body preservation; the costs and rate of adoption of cryonics; the culture, conservatism and geography of his home on the Isle of Skye; transhumanism and transcending limitations; the differences between Max More and James Hughes; his fear of death; the promise of chemical brain preservation; mindfulness and meditation; writing a transhumanist take on The Wizard of Oz and potentially on Grim’s Fairy Tales…
As always you can listen to or download the audio file above or scroll down and watch the video interview in full. To show your support you can write a review on iTunes, make a direct donation or become a patron on Patreon.
As published in a recent study, researchers have discovered that neural stem cells are impeded by the invasion of T cells, immune cells that are not normally present in the neural stem cell niche.
The neural stem cell niches
Our brains contain neural stem cells (NSCs); like their name suggests, these cells are responsible for the formation of new neurons within the brain. This process, which continues throughout life, is known as neurogenesis. These stem cells live in particular niches, which contain a panoply of different cell types, including stem cells in different phases of development and multiple types of immune cells. However, the researchers discovered a startling fact: the brains of older mice contain many specific immune cells known as T cells, while the brains of younger mice contain very few – and, as the study explains, this is true for humans as well.
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With that basic research, mankind found the first major clue to the origins of aging and death. They discovered that some cells in our bodies that may never die. These “immortal cells” and the philosophical shift in thinking they engendered, will likely change medicine as we know it.
Different African killifish species vary extensively in their lifespans—from just a few months to several years. Scientists from the Max Planck Institute for Biology of Ageing in Cologne investigated how different lifespans have evolved in nature and discovered a fundamental mechanism by which detrimental mutations accumulate in the genome causing fish to age fast and become short-lived. In humans, mutations accumulate mainly in the genes that are active in old age.
My colleague Nicola Bagalà recently had the opportunity to interview Sergey Young, a board member of XPRIZE and the creator of the $100m Longevity Vision Fund. As you probably know, at the end of May this year XPrize hosted a 2-day workshop to better understand the bottlenecks and opportunities of the longevity industry, and in this interview, Sergey is sharing his vision on what can — and should — be done to accelerate the development of new therapies addressing aging.
We recently had the opportunity to interview Sergey Young, a board member of XPRIZE and the creator of the $100m Longevity Vision Fund.
When did you first become interested in healthy life extension, and why?
