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Molecular Nutrition In Health, Well-Being & Longevity — Dr. Courtney Millar, Ph.D. — Marcus Institute For Aging Research, Hebrew SeniorLife / Harvard Medical School


Dr. Courtney Millar, Ph.D. (https://www.marcusinstituteforaging.org/who-we-are/profiles/courtney-millar-phd) is an Assistant Scientist at the Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, and Instructor in Medicine, Harvard Medical School and Beth Israel Deaconess Medical Center.

Dr. Millar is a research scientist devoted to improving health and well-being of older adults through dietary interventions and her current research aims to test the ability of anti-inflammatory dietary strategies that promote both physical and emotional well-being in older adults.

Dr. Millar received her PhD in molecular nutrition at the University of Connecticut, where she developed a deep understanding of the relationship between dietary bioactive components and metabolic disease.

Dr. Millar’s post-doctoral fellowship focused on training related to conducting both nutritional epidemiological analyses and clinical interventions.

Moreover, among the 37 druggable genes supported by at least two pieces of genetic evidence, we have identified 28 drugs targeting MPL, CA4, TUBB, and RRM1, although neither in clinical trials nor reported previously have the potential to be repurposed for slowing down brain aging. Specifically, four drugs, namely, avatrombopag, eltrombopag, lusutrombopag, and romiplostim, which are typically used for thrombocytopenia, act as agonists for MPL. As mentioned above, MPL is a thrombopoietin receptor and has been linked to platelet count and brain morphology in the GWAS catalog. Notably, platelet signaling and aggregation pathway is enriched using the 64 MR genes. It is worth noting that platelet count decreases during aging and is lower in men compared to women (84). A recent study of platelets has also revealed that platelets rejuvenate the aging brain (85). Schroer et al. (86) found that circulating platelet-derived factors could potentially serve as therapeutic targets to attenuate neuroinflammation and improve cognition in aging mice (86). Park et al. (87) reported that longevity factor klotho induces multiple platelet factors in plasma, enhancing cognition in the young brain and decreasing cognitive deficits in the aging brain (87). Leiter et al. (88) found that platelet-derived platelet factor 4, highly abundant chemokine in platelets, ameliorates hippocampal neurogenesis, and restores cognitive function in aged mice. These findings suggest that the aforementioned drugs may enhance the expression of MPL, leading to increased platelet count and potentially contributing to a delay in brain aging. It is important to note that determining the significant tissue(s) for gene prioritization can be challenging. Although brain tissues may be more biologically relevant for brain aging, circulating proteins have the capability to modulate brain aging as well (89, 90). Six drugs (cladribine, clofarabine, gallium nitrate, gemcitabine, hydroxyurea, and tezacitabine) are inhibitors of RRM1, whereas 12 drugs (brentuximab vedotin, cabazitaxel, crolibulin, indibulin, ixabepilone, paclitaxel, plinabulin, podofilox, trastuzumab emtansine, vinblastine, vinflunine, and vinorelbine) are inhibitors of TUBB. Most of these drugs targeting RRM1 and TUBB are antineoplastic agents used in cancer treatment. In addition, six drugs (acetazolamide, brinzolamide, chlorothiazide, methazolamide, topiramate, and trichlormethiazide) are inhibitors of CA4 and most of them are used for hypertension.

There are a few limitations to this study: (i) The accurate estimation of brain age is hindered by the lack of ground-truth brain biological age and discrepancies between brain biological age and chronological age in supposedly healthy individuals. The estimated brain age derived from MRI data includes inherent biases (91). Although our model has shown better generalization performance compared to other models, there is always an expectation for a more accurate brain age estimation model that can deliver more robust outcomes for clinical applicants (3, 91). (ii) Potential data bias may affect the findings of this comprehensive study. For instance, the brain age estimation model and GWAS summary statistics primarily relied on cohorts of European white individuals, potentially overlooking druggable targets that would be effective in individuals of non-European ancestry. Validation using genomic and clinical data from more diverse populations could help remedy this limitation. (iii) Validation on independent discovery and replication cohorts would enhance the reliability of the identified genes as drug targets for the prevention of brain aging. Although we maximized statistical power using the UKB data as a large discovery cohort, the absence of a discovery-replication design is unavoidable. As large-scale datasets containing both MRI and genome-wide genotypes were not widely available, we used a combination of GWAS for BAG, MR with xQTL, colocalization analysis, MR-PheWAS, and the existing literature to carefully identify genetic targets that are supported by evidence for their involvement in brain aging. With the availability of more comprehensive proteomics platforms and the inclusion of more diverse non-European ancestry populations in studies, it is likely to replicate and validate our results. (iv) Brain aging is a complex process involving numerous potential causes, such as aging of cerebral blood vessels (92), atrophy of the cerebral cortex (93), etc. These causes may overlap and interweave, undergoing considerable changes during brain aging (48). Although our study demonstrates the utility of systematically analyzing GWAS alongside extensive brain imaging information and xQTL analysis to enrich the identification of drug targets, there remains a need for machine learning or statistical methods to address the various risk factors associated with brain aging. Fine-grained analysis is a must to comprehend the individualized causes and trajectories of brain aging, enabling the identification of effective drug targets and the use of precision medications for the purpose of slowing down or even preventing brain aging. There is also an increasing need for comprehensive studies spanning different tissues and organs to evaluate tissue-or organ-specific effects of targets, enabling the systematic prevention or treatment of human aging. (v) This study did not explore adverse effects of the rediscovered antiaging drugs. This is particularly important because healthy aging individuals should be encouraged to consider the potential risks associated with taking medications or supplements for slowing down aging as these interventions may have unintended negative consequences for both individuals and society. Alternatively, it is worthwhile to explore nonpharmacological interventions/digital therapies that can help preserve mental and physical fitness in people during aging.

In summary, we present a systematic study for identify genetically supported targets and drugs for brain aging with deep learning-based brain age estimation, GWAS for BAG, analysis of the relation between BAG and brain disorders, prioritization of targets using MR and colorization analysis for BAG with xQTL data, drug repurposing for these targets of BAG, and PheWAS. Our results offer the potential to mitigate the risk associated with drug discovery by identifying genetically supported targets and repurposing approved drugs to attenuate brain aging. We anticipate that our findings will serve as a valuable resource for prioritizing drug development efforts for BAG, shedding light on the understanding of human brain aging and potentially extending the health span in humans.

Summary: A new study reveals that poor sleep in older adults disrupts the brain’s glymphatic system, responsible for clearing harmful waste and toxins. Researchers found that compromised sleep quality leads to dysfunction in this crucial system, potentially increasing risks for memory decline and cognitive impairments.

Using advanced brain imaging in 72 older adults, the research highlighted that poor sleep negatively impacts connections within brain networks linked to memory performance. These insights emphasize the importance of maintaining good sleep hygiene to support brain health and healthy aging.

Longevity snapshot 7 — cellular rejuvenation protects neurons.

Reviewing a Canadian study which uses cellular rejuvenation to protect retinal neurons in a mouse model of multiple sclerosis, preserving the vision of the mice.

Study reviewed:

In this manuscript, Drake et al. describe an aging-like transcriptional signature in retinal ganglion cells during experimental autoimmune encephalomyelitis (EAE) like that of cortical neurons in patients with multiple sclerosis. Partial reprogramming with AAV2-Oct4-Sox2-Kl4 to rejuvenate the transcriptome results in improved RGC survival and visual acuity during EAE.

Artificial Intelligence (AI) is, without a doubt, the defining technological breakthrough of our time. It represents not only a quantum leap in our ability to solve complex problems but also a mirror reflecting our ambitions, fears, and ethical dilemmas. As we witness its exponential growth, we cannot ignore the profound impact it is having on society. But are we heading toward a bright future or a dangerous precipice?

This opinion piece aims to foster critical reflection on AI’s role in the modern world and what it means for our collective future.

AI is no longer the stuff of science fiction. It is embedded in nearly every aspect of our lives, from the virtual assistants on our smartphones to the algorithms that recommend what to watch on Netflix or determine our eligibility for a bank loan. In medicine, AI is revolutionizing diagnostics and treatments, enabling the early detection of cancer and the personalization of therapies based on a patient’s genome. In education, adaptive learning platforms are democratizing access to knowledge by tailoring instruction to each student’s pace.

These advancements are undeniably impressive. AI promises a more efficient, safer, and fairer world. But is this promise being fulfilled? Or are we inadvertently creating new forms of inequality, where the benefits of technology are concentrated among a privileged few while others are left behind?

One of AI’s most pressing challenges is its impact on employment. Automation is eliminating jobs across various sectors, including manufacturing, services, and even traditionally “safe” fields such as law and accounting. Meanwhile, workforce reskilling is not keeping pace with technological disruption. The result? A growing divide between those equipped with the skills to thrive in the AI-driven era and those displaced by machines.

Another urgent concern is privacy. AI relies on vast amounts of data, and the massive collection of personal information raises serious questions about who controls these data and how they are used. We live in an era where our habits, preferences, and even emotions are continuously monitored and analyzed. This not only threatens our privacy but also opens the door to subtle forms of manipulation and social control.

Then, there is the issue of algorithmic bias. AI is only as good as the data it is trained on. If these data reflect existing biases, AI can perpetuate and even amplify societal injustices. We have already seen examples of this, such as facial recognition systems that fail to accurately identify individuals from minority groups or hiring algorithms that inadvertently discriminate based on gender. Far from being neutral, AI can become a tool of oppression if not carefully regulated.

Who Decides What Is Right?

AI forces us to confront profound ethical questions. When a self-driving car must choose between hitting a pedestrian or colliding with another vehicle, who decides the “right” choice? When AI is used to determine parole eligibility or distribute social benefits, how do we ensure these decisions are fair and transparent?

The reality is that AI is not just a technical tool—it is also a moral one. The choices we make today about how we develop and deploy AI will shape the future of humanity. But who is making these decisions? Currently, AI’s development is largely in the hands of big tech companies and governments, often without sufficient oversight from civil society. This is concerning because AI has the potential to impact all of us, regardless of our individual consent.

A Utopia or a Dystopia?

The future of AI remains uncertain. On one hand, we have the potential to create a technological utopia, where AI frees us from mundane tasks, enhances productivity, and allows us to focus on what truly matters: creativity, human connection, and collective well-being. On the other hand, there is the risk of a dystopia where AI is used to control, manipulate, and oppress—dividing society between those who control technology and those who are controlled by it.

The key to avoiding this dark scenario lies in regulation and education. We need robust laws that protect privacy, ensure transparency, and prevent AI’s misuse. But we also need to educate the public on the risks and opportunities of AI so they can make informed decisions and demand accountability from those in power.

Artificial Intelligence is, indeed, the Holy Grail of Technology. But unlike the medieval legend, this Grail is not hidden in a distant castle—it is in our hands, here and now. It is up to us to decide how we use it. Will AI be a tool for building a more just and equitable future, or will it become a weapon that exacerbates inequalities and threatens our freedom?

The answer depends on all of us. As citizens, we must demand transparency and accountability from those developing and implementing AI. As a society, we must ensure that the benefits of this technology are shared by all, not just a technocratic elite. And above all, we must remember that technology is not an end in itself but a means to achieve human progress.

The future of AI is the future we choose to build. And at this critical moment in history, we cannot afford to get it wrong. The Holy Grail is within our reach—but its true value will only be realized if we use it for the common good.

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Copyright © 2025, Henrique Jorge

[ This article was originally published in Portuguese in SAPO’s technology section at: https://tek.sapo.pt/opiniao/artigos/o-santo-graal-da-tecnologia ]

Aubrey de Grey is giving a talk on Twitter this Saturday. You’ll get a chance to ask him questions directly if you attend live: [ https://lu.ma/viva-aubrey](https://lu.ma/viva-aubrey)


Join us for an educational talk with longevity scientist Dr. Aubrey de Grey about the state of longevity research, how to get a COVID-style “war on aging,” and the future of life extension science.

Scientists have recorded the first-ever brain scan of a dying human.

A man suddenly died during a routine brain scan, revealing intriguing insights into what happens in our final moments.

An 87-year-old man undergoing a routine EEG for epilepsy suffered a fatal heart attack. Researchers found that in the 30 seconds before and after his heart stopped, his brain waves resembled those seen during dreaming, memory recall, and meditation.

This suggests that the commonly reported phenomenon of “life flashing before your eyes” may have a neurological basis. However, since this is a single case study, more research is needed to confirm how common this experience may be.

The findings, published by Dr. Ajmal Zemmar and his team, showed a surge in gamma waves — high-frequency neural oscillations linked to memory and consciousness — just before and after death.

These waves are typically observed when people recall memories, adding weight to the idea that the brain may replay key life events in its final moments. While this discovery cannot fully explain the mysteries of death, it offers a fascinating glimpse into the brain’s last activity and opens the door for further research on human consciousness at the end of life.


This innovation, called ALA-CART, helps the immune system better recognize and destroy resistant cancers. The new design not only improves treatment success but also promises fewer side effects.

A Powerful Upgrade to CAR-T Therapy

Researchers at the University of Colorado Anschutz Medical Campus have developed an enhanced version of CAR-T cell therapy designed to improve effectiveness and longevity, particularly against cancer cells that were previously difficult to detect and eliminate.

Sunburns and aging skin are obvious effects of exposure to harmful UV rays, tobacco smoke and other carcinogens. But the effects aren’t just skin deep. Inside the body, DNA is literally being torn apart.

Understanding how the body heals and protects itself from DNA damage is vital for treating genetic disorders and life-threatening diseases such as cancer. But despite numerous studies and medical advances, much about the molecular mechanisms of DNA repair remains a mystery.

For the past several years, researchers at Georgia State University have tapped into the Summit supercomputer at the Department of Energy’s Oak Ridge National Laboratory to study an elaborate molecular pathway called (NER). NER relies on an array of highly dynamic protein complexes to cut out (excise) damaged DNA with surgical precision.