The Hidden Link Between Sleep and Dementia: How Better Rest Can Improve Lives

“Sleep problems in dementia patients are not only common but also contribute to a faster progression of cognitive decline and increased burden on caregivers.”

Sleep is essential for everyone, but for those living with dementia, it is vital for better health and quality of life. Addressing sleep problems in dementia care is a crucial step toward improving life for both patients and caregivers.

Dementia and Sleep

Sleep is critical for brain health and well-being, but it is often a struggle for people with dementia. Dementia, a condition that affects memory, thinking, and daily life, is frequently complicated by other health issues like heart disease, diabetes, and anxiety. On top of these challenges, sleep problems such as insomnia and sleep apnea are common, making life even harder for patients and their caregivers. 

Addressing sleep issues is key to improving the lives of people with dementia and easing the burden on their support systems. Recognizing this need, researchers Upasana Mukherjee, Ujala Sehar, Malcolm Brownell, and P. Hemachandra Reddy from Texas Tech University Health Sciences Center conducted an extensive review. Published in Aging, Volume 16, Issue 21, their work aims to update healthcare professionals on these issues and promote new practices in dementia care.

The Study: Update on Sleep and Dementia’s Connection

Sleep deprivation in dementia comorbidities: focus on cardiovascular disease, diabetes, anxiety/depression and thyroid disorders” is a comprehensive review that explores the connections between sleep disturbances, dementia, and related conditions like heart disease, diabetes, and anxiety.

The review emphasized how untreated sleep issues can worsen cognitive decline, demonstrating that sleep health is not just a symptom of dementia but an integral part of its progression.

The Challenge: Why Sleep Problems are Overlooked but Critical

People with dementia often face significant sleep disruptions. They might wake up multiple times during the night, feel excessively sleepy during the day, or move around at night. This lack of restorative sleep worsens memory loss and confusion. For example, untreated sleep apnea reduces oxygen flow to the brain, further harming cognitive function. Meanwhile, caregivers experience immense stress and burnout from managing sleepless nights and restless behavior.

Despite these profound effects, many dementia treatment strategies fail to adequately address sleep issues, treating them as secondary problems rather than main components of care. Understanding the relationship between sleep and dementia is critical for designing effective interventions.

The Breakthrough: How Improving Sleep Can Transform Dementia Care

The study highlighted that sleep problems are deeply linked to the progression of dementia rather than being merely side effects. Conditions like cardiovascular disease and diabetes often worsen these disturbances, creating a cycle where poor health accelerates cognitive decline.

The findings showed that improving sleep quality can bring significant benefits. One solution is addressing sleep apnea, which not only improves sleep quality but also enhances brain function and lowers the risk of related health issues such as heart disease. Non-drug therapies such as structured bedtime routines, light therapy, and anxiety management have shown promise in improving sleep for dementia patients. Cognitive-behavioral therapy for insomnia has been especially effective in managing chronic sleep issues. These interventions not only improve brain health but also reduce caregiver stress, promoting a healthier and more supportive environment for everyone involved.

The Future of Dementia Care

Integrating sleep care into dementia treatment is the way forward. Addressing sleep disturbances together with other health conditions like diabetes and anxiety can have a profound impact. Personalized approaches, such as setting up calming bedtime routines and improving sleep environments, can make a real difference. Future research should focus on refining these strategies and equipping caregivers with better tools to manage sleep challenges. 

Conclusion

Sleep disturbances are more than just a symptom of dementia. They are a major factor driving this condition’s progression and affecting quality of life. By prioritizing sleep health in dementia care, memory loss can be slower, day-to-day well-being can be improved, and burden on caregivers can be reduced. Holistic care approaches that address both sleep and overall health hold the key to improving quality of life for dementia patients and their families.

Click here to read the full research paper in Aging.

Aging is indexed by PubMed/Medline (abbreviated as “Aging (Albany NY)”), PubMed CentralWeb of Science: Science Citation Index Expanded (abbreviated as “Aging‐US” and listed in the Cell Biology and Geriatrics & Gerontology categories), Scopus (abbreviated as “Aging” and listed in the Cell Biology and Aging categories), Biological Abstracts, BIOSIS Previews, EMBASE, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).

Click here to subscribe to Aging publication updates.

For media inquiries, please contact [email protected].

Aging’s Commitment to Advancing Research: Sponsoring the “Future of Aging Research Mixer 2024”

Future of Aging Research Mixer
Future of Aging Research Mixer

Aging (Aging-US) was a proud sponsor of the “Future of Aging Research Mixer 2024” hosted by the Aging Initiative at Harvard University on November 15 in Boston. This event united a vibrant community of students, researchers and technologists, all driven by a shared mission: advancing innovations in aging research and longevity science.

Key Highlights from the Future of Aging Research Mixer 2024

The event kicked off with inspiring opening remarks and a keynote by George Church, professor at Harvard Medical School, founding member of the Wyss Institute, and co-founder of over 50 biotech companies. He was joined by Kat Kajderowicz, an MIT PhD student and Principal at age1. Together, they highlighted the interdisciplinary nature of aging research and its immense potential to drive transformative advancements.

Jesse Poganik, HMS Instructor in Medicine and Executive Co-Director of the Biomarkers of Aging Consortium, discussed the evolution of aging science and the critical role biomarkers play in understanding aging processes and assessing the effectiveness of interventions aimed at slowing or reversing age-related changes.

Alex Colville, co-founder and general partner at age1, explained how venture capital can accelerate innovation in longevity biotechnology. He shared career advice for aspiring researchers and paid tribute to his mentor, Dr. David Sinclair, a pioneer in aging research.

These talks highlighted the importance of mentorship, interdisciplinary collaboration, and investment in driving progress in the aging research field.

Empowering Future Aging Science Leaders

A majority of the attendees were students from Boston-area universities including Harvard, MIT, UMass and BU. These future scientists, entrepreneurs, and innovators engaged in meaningful discussions about research, career paths, and publishing in academic journals. Many expressed interest in journals like Aging (Aging-US) and sought advice on how to publish their work.

The “Future of Aging Research Mixer 2024” showcased the passion, collaboration, and innovation within the aging research community. Through its sponsorship, Aging (Aging-US) reaffirmed its commitment to fostering a vibrant network of talent and supporting the voices of young, passionate researchers. Initiatives like this inspire the next generation of scientists and entrepreneurs, driving sustained growth and transformative impact in the field.

Beyond the event, the Aging Initiative at Harvard University strengthens the community through ongoing programs like journal clubs, guest lectures, and informal lunches with professors. These initiatives encourage skill-building, idea-sharing, and mentorship, preparing students for impactful careers in aging science.

Why We Support Aging Research

Aging (Aging-US) was founded in 2008 by visionary scientists—the late Dr. Mikhail (Misha) Blagosklonny, the late Dr. Judith Campisi, and Dr. David Sinclair—with a clear mission: to create a journal by scientists, for scientists, so the researchers can publish their ideas, theories (sometimes unconventional) and studies on the rapidly developing aging field. Since then, we have remained dedicated to advancing the understanding of aging and age-related diseases, including cancer, a leading health challenge in today’s aging world.

Supporting initiatives like the Aging Initiative at Harvard University and events such as the “Future of Aging Research Mixer 2024” is central to our mission. By supporting young researchers, we strive to drive meaningful advancements in the field and ensure it receives the recognition and resources it deserves. We are deeply committed to supporting initiatives that empower scientists and promote collaboration, mentorship, and innovation.

Sponsoring this initiative is more than an investment—it’s a commitment to the future of aging science and a healthier, longer life for all.

As we look to the future, we are inspired by the passion and talent within this growing field. Together, through continued collaboration and investment, we can shape a world where aging research leads to healthier and longer lives.

Aging is indexed by PubMed/Medline (abbreviated as “Aging (Albany NY)”), PubMed CentralWeb of Science: Science Citation Index Expanded (abbreviated as “Aging‐US” and listed in the Cell Biology and Geriatrics & Gerontology categories), Scopus (abbreviated as “Aging” and listed in the Cell Biology and Aging categories), Biological Abstracts, BIOSIS Previews, EMBASE, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).

Click here to subscribe to Aging publication updates.

For media inquiries, please contact [email protected].

How AI and Longevity Biotechnology are Revolutionizing Healthcare for Healthier, Longer Lives

“The integration of artificial intelligence (AI), biomarkers, ageing biology, and longevity medicine stands as a cornerstone for extending human healthy lifespan.”

Imagine a future where we not only live longer but stay healthy throughout those extra years. Thanks to recent breakthroughs in biotechnology and artificial intelligence (AI) in healthcare, this vision is closer to becoming a reality.

Advancements in Aging Research

Aging research has made significant progress in recent years by combining disciplines like biology, technology, and medicine to tackle the challenges of extending healthspans and reducing age-related diseases. While people today live longer than ever before, extending our “healthspan”—the years we stay active and illness-free—remains challenging. AI and health biomarkers (biological indicators of our body’s condition) are now key tools in the pursuit of longer, healthier lives.

In a recent paper, led by corresponding authors Yu-Xuan Lyu from Southern University of Science and Technology Shenzhen; Alex Zhavoronkov from Insilico Medicine AI Limited, Masdar City, Abu Dhabi; Morten Scheibye-Knudsen and Daniela Bakula from the Center for Healthy Aging, University of Copenhagen, along with numerous other collaborators, the transformative potential of AI in aging research was explored. The research paper, titled “Longevity biotechnology: bridging AI, biomarkers, geroscience and clinical applications for healthy longevity,” was published as the cover paper in Aging’s Volume 16, Issue 20.

The Study: A New AI-Powered Approach to Aging

The work summarizes insights from the 2023 Aging Research and Drug Discovery Meeting. Researchers from renowned institutions explored how AI, biomarkers, and clinical applications can work together to enhance longevity. This fusion, termed “longevity biotechnology,” promises to transform healthcare from reactive treatments to proactive, preventive measures focused on staying healthy as we age.

The Challenge: Targeting Multiple Health Conditions with Longevity Biotechnology

Traditional aging research often targets single diseases, but most elderly individuals experience multiple chronic conditions. Addressing this complex challenge requires identifying biological markers that indicate aging and predicting health risks before diseases manifest.

The Breakthrough: AI in Biomarker Discovery for Aging

The study highlights how AI can accelerate the discovery of biomarkers, allowing scientists to understand aging at the cellular level. By using machine learning to identify unique patterns, researchers can estimate biological age, discover potential treatments, and evaluate the impact of lifestyle changes on health. This personalized approach enables healthcare providers to create prevention and treatment plans suited to each person’s unique health needs.

The Future of Healthcare: Preventive, AI-Driven Longevity Treatments

Currently, healthcare often focuses on managing diseases as they arise. However, these AI-driven tools could bring about a shift to preventive healthcare. Instead of waiting for age-related illnesses, clinicians could use AI insights to address aging’s root causes, improving health before issues arise.

While the promise of AI in healthcare is significant, the research team emphasizes that further investment is needed to make these AI-driven approaches accessible and accurate. With continued advancements, longevity biotechnology could become a standard part of healthcare, offering a new way to maintain vitality and well-being as we age.

Conclusion

Longevity biotechnology represents a groundbreaking shift, with AI and biomarkers helping us envision a future of healthier, longer lives. This approach brings us closer to understanding and managing the aging process, making extended healthspans a real possibility.

Click here to read the full research paper in Aging.

Aging is indexed by PubMed/Medline (abbreviated as “Aging (Albany NY)”), PubMed CentralWeb of Science: Science Citation Index Expanded (abbreviated as “Aging‐US” and listed in the Cell Biology and Geriatrics & Gerontology categories), Scopus (abbreviated as “Aging” and listed in the Cell Biology and Aging categories), Biological Abstracts, BIOSIS Previews, EMBASE, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).

Click here to subscribe to Aging publication updates.

For media inquiries, please contact [email protected].

Exploring Baseline Variations and Mechanical Loading-Induced Bone Formation in Young-Adult and Aging Mice through Proteomics

Bone mass declines with age, and the anabolic effects of skeletal loading decrease. While much research has focused on gene transcription, how bone ages and loses its mechanoresponsiveness at the protein level remains unclear.

Researchers Christopher J. Chermside-Scabbo, John T. Shuster, Petra Erdmann-Gilmore, Eric Tycksen, Qiang Zhang, R. Reid Townsend, Matthew J. Silva from Washington University School of Medicine and Washington University in St. Louis, MO, share their findings which underscore the need for complementary protein-level assays in skeletal biology research.

On October 12, 2024, their research paper was published as the cover of Aging (listed by MEDLINE/PubMed as “Aging (Albany NY)” and “Aging-US” by Web of Science), Volume 16, Issue 19, entitled, “A proteomics approach to study mouse long bones: examining baseline differences and mechanical loading-induced bone formation in young-adult and old mice.”

THE STUDY

In this study, the tibias of young-adult and old mice were analyzed using proteomics and RNA-seq techniques, while the femurs were examined for age-related changes in bone structure. A total of 1,903 proteins and 16,273 genes were detected through these analyses. Multidimensional scaling demonstrated a clear separation between the young-adult and old samples at both the protein and RNA levels. Furthermore, 93% of the detected proteins were also identifiable by RNA-seq, and the abundance of these shared targets showed a moderately positive correlation. Additionally, differential expression analysis revealed 183 age-related differentially expressed proteins and 2,290 differentially expressed genes between young-adult and old bone samples.

Proteomic and RNA-seq analyses were conducted on paired tibias from young-adult and old mice to study age-related differences and the effects of mechanical loading on bone formation. The results showed distinct differences in protein and gene expression between the two age groups. Many of the significantly upregulated and downregulated proteins and genes in old bone have been associated with bone phenotypes in genome-wide association studies (GWAS). The study also identified age-related differentially expressed proteins and genes involved in bone phenotypes and aging processes. Integrated analysis with GWAS data revealed eight targets that may be relevant to human disease, including Asrgl1 and Timp2. Furthermore, co-expression analysis identified an age-related module indicating baseline differences in TGF-beta and Wnt signaling. Baseline age-related differences in ECM/MMPs and TGF-beta signaling were detected in both the proteome and transcriptome. Following mechanical loading, the proteome showed distinct pathway, protein class, and process enrichments, with temporal differences observed between young-adult and old mice.

Overall, the findings provide valuable insights into the molecular mechanisms underlying age-related changes and the response to mechanical loading in mouse long bones.

DISCUSSION

This study aimed to compare the proteome and transcriptome of tibias from young-adult and old mice under baseline conditions and analyze changes in the bone proteome in response to mechanical loading. The researchers successfully developed a proteomics method to detect protein-level changes in cortical bone and used it to perform proteomic and RNA-seq analyses on tibias from both young-adult and old mice. They observed a moderately positive correlation between the proteome and transcriptome in bone tissue. Age-related differences were detected at both the protein and RNA levels, with altered TGF-beta signaling and changes in extracellular matrix (ECM) and matrix metalloproteinases (MMPs) protein and transcript levels in old bones. The researchers identified Tgfb2 as the most reduced Tgfb transcript in old bone, predominantly expressed by osteocytes. Proteomic analysis of the loading response showed modest changes compared to age-related differences, with fewer protein-level changes in old bones. The findings suggest that proteomics is a valuable tool for studying bone biology and can provide insights into protein-specific changes in aging.

The data obtained from the analysis were subjected to various statistical and data exploration techniques. Differential expression analysis was performed to compare protein abundance between different groups. Total RNA was extracted from the bones using TRIzol, and its integrity and concentration were measured. The bones were also processed for paraffin sectioning and RNA in situ hybridization.

Overall, the study involved the collection and analysis of bone samples from female mice to investigate age-related changes and loading responses in the skeletal system.

Click here to read the full research paper in Aging.

Aging is indexed by PubMed/Medline (abbreviated as “Aging (Albany NY)”), PubMed CentralWeb of Science: Science Citation Index Expanded (abbreviated as “Aging‐US” and listed in the Cell Biology and Geriatrics & Gerontology categories), Scopus (abbreviated as “Aging” and listed in the Cell Biology and Aging categories), Biological Abstracts, BIOSIS Previews, EMBASE, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).

Click here to subscribe to Aging publication updates.

For media inquiries, please contact [email protected].

How Single Housing Impacts Growth and Lifespan in African Turquoise Killifish

“[…] our results suggest that sharing housing with others in early life might influence whole-life attributes, potentially leading to specific life history traits beyond the typical relationship between the growth rate and lifespan.”

In this research, Chika Takahashi, Emiko Okabe, Masanori Nono, Saya Kishimoto, Hideaki Matsui, Tohru Ishitani, Takuya Yamamoto, Masaharu Uno, and Eisuke Nishida from the RIKEN Center for Biosystems Dynamics Research (BDR) in Hyogo, Japan; Brain Research Institute, Niigata University in Niigata, Japan; Research Institute for Microbial Diseases at Osaka University in Osaka, Japan; Kyoto University in Kyoto, Japan; and RIKEN Center for Advanced Intelligence Project (AIP), explored the effects of housing density during the juvenile stage on whole-life traits, including growth, fecundity, and lifespan, in African turquoise killifish. Their research paper was published on the cover of Aging (listed by MEDLINE/PubMed as Aging (Albany NY) and as Aging-US by Web of Science), Volume 16, Issue 18, entitled, “Single housing of juveniles accelerates early-stage growth but extends adult lifespan in African turquoise killifish.”

THE STUDY

A study on African turquoise killifish examined the impact of housing density on juvenile growth. Newly hatched fish were kept in different densities ranging from 1 to 40 fish per tank. It was found that lower housing densities resulted in faster growth, with fish in single housing growing significantly larger than those in group housing. Additionally, single-housed fish reached sexual maturity earlier compared to group-housed fish at higher densities. Comparisons between group-housed and single-housed fish showed that housing conditions in the juvenile stage did not affect the appearance changes during sexual maturation. 

As the fish progressed to middle-aged adults, the rate of increase in body length slowed down, while body weight continued to increase. Differences in body weight between group-housed and single-housed fish persisted into old age, suggesting potential differences in body composition. Surprisingly, single-housed fish had a longer mean adult lifespan compared to group-housed fish, contradicting the commonly held belief that faster growth leads to shorter lifespan. Lower housing densities during the juvenile stage were also found to extend adult lifespan, further challenging the inverse correlation between growth rate and lifespan. These findings suggest that lower housing densities promote accelerated growth in the juvenile stage of African turquoise killifish.

The study also found that single-housed fish had a longer adult lifespan compared to group-housed fish. This led to the suspicion that the egg-laying period of single-housed fish might also be longer. To investigate this, the researchers conducted weekly monitoring of the number of eggs laid until the old adult stage. In group-housed fish, the number of eggs laid was high for the first two weeks, followed by a medium level for the subsequent five weeks, and then decreased. In contrast, single-housed fish showed a medium level of egg-laying for the first nine weeks, followed by a decrease. The cumulative number of live embryos was found to be lower in single-housed fish compared to group-housed fish. These findings suggest that while the number of eggs laid is not very high, single-housed fish have a longer egg-laying period than group-housed fish.

To investigate the potential reasons behind the reduction in offspring number and longer egg-laying period in single-housed fish, the researchers conducted RNA sequencing analysis of testes or ovaries at four life stages. These stages included the onset of sexual maturity, young adult, mature adult, and middle-aged adult. Interestingly, the analysis revealed that single-housed fish showed higher similarity to group-housed fish at earlier life stages compared to group-housed fish at the same life stage. For instance, in the testes, single-housed fish at stage II exhibited the highest similarity to group-housed fish at stage I. Similarly, in the ovaries, single-housed fish at stage II and III showed higher similarity to group-housed fish at stage I. These findings suggest that the rate of gonadal transcriptional change with life stage progression is slower in single-housed fish compared to group-housed fish.

The researchers identified differentially expressed genes (DEGs) between stage I and stage IV in group- and single-housed fish. In the testes, ribosome-related genes and cilium-related genes were highly enriched in DEGs with higher expression in stage I compared to stage IV, suggesting a link between life stage progression, testes development, and spermatogenesis. In the ovaries, growth-related genes and translation-related genes were highly enriched in DEGs with higher expression in stage I compared to stage IV, indicating a link between life stage progression, ovarian development, oogenesis, and aging. Comparing group-housed and single-housed fish at different stages, there were differences in the PC1 values, suggesting that single-housed fish exhibited slower progression of gametogenesis and gonadal maturation relative to life stage progression compared to group-housed fish.

To further investigate this, the researchers focused on specific genes related to spermatogenic differentiation, oocyte development, oocyte construction, and female gonad development. The expression of these genes showed slower changes with life stage progression in single-housed fish compared to group-housed fish in both the testes and ovaries. This suggests that single-housed fish may have slower rates of gametogenesis and gonadal maturation, leading to a lower proportion of mature sperm and oocytes in their gonads. Overall, the results indicate that, at the transcriptional level, the progression of gonadal maturation and ovarian aging is slower in single-housed fish compared to group-housed fish. This slower progression may explain the medium fecundity and extended egg-laying period observed in single-housed fish.

The liver was chosen for analysis as it plays a central role in organismal metabolic processes. Gene expression profiles of the livers were compared between group- and single-housed fish at two different ages: 7 weeks post-hatching (wph) and 14 wph. Surprisingly, despite the 2-week age difference, the correlation coefficients showed that group- and single-housed fish at 14 wph were highly similar. The researchers identified 1588 age-related differentially expressed genes (DEGs) between the two age groups. Hierarchical clustering based on the expression changes of these age-related genes demonstrated that the expression profiles of group- and single-housed fish were similar at 14 wph.

IN CONCLUSION

In summary, juvenile single housing in African turquoise killifish promotes faster growth, longer egg-laying periods, and extended lifespans compared to group housing. These findings challenge traditional assumptions about the relationship between growth and lifespan and shed light on the impact of early-life environmental conditions on overall life history.

Overall, the experiments involved maintaining and rearing the fish, measuring their body length and weight, analyzing RNA sequencing data, measuring lifespan, and counting the number of eggs laid. Statistical analysis was conducted to assess significant differences between groups.

Click here to read the full research paper in Aging.

Aging is indexed by PubMed/Medline (abbreviated as “Aging (Albany NY)”), PubMed CentralWeb of Science: Science Citation Index Expanded (abbreviated as “Aging‐US” and listed in the Cell Biology and Geriatrics & Gerontology categories), Scopus (abbreviated as “Aging” and listed in the Cell Biology and Aging categories), Biological Abstracts, BIOSIS Previews, EMBASE, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).

Click here to subscribe to Aging publication updates.

For media inquiries, please contact [email protected].

The Cell Rejuvenation Atlas: Unveiling Rejuvenation Strategies through Network Biology

Researchers introduce SINGULAR, a cell rejuvenation atlas that provides a unified analysis framework to study the effects of rejuvenation strategies at the single-cell level.

Researchers Javier Arcos Hodar, Sascha Jung, Mohamed Soudy, Sybille Barvaux, and Antonio del Sol from CIC bioGUNE-BRTA and University of Luxembourg introduce SINGULAR, a cell rejuvenation atlas that provides a unified analysis framework to study the effects of rejuvenation strategies at the single-cell level. On September 9, 2024, their research paper was published on the cover of Aging (listed by MEDLINE/PubMed as “Aging (Albany NY)” and “Aging-US” by Web of Science), Volume 16, Issue 17, entitled, “The cell rejuvenation atlas: leveraging network biology to identify master regulators of rejuvenation strategies.”

THE RESEARCH

Various strategies, including lifestyle changes, gene therapies, and surgical procedures, have shown promise in improving aging markers and increasing lifespan in model organisms. These interventions often have limitations, however, such as not achieving comprehensive functional improvement across tissues or facing challenges in clinical translation. To address these limitations, the researchers characterized and compared rejuvenation interventions at different biological levels. The paper introduces SINGULAR, a cell rejuvenation atlas that provides a unified analysis framework to study the effects of rejuvenation strategies at the single-cell level. By examining gene regulatory networks, intracellular signaling, cell-cell communication, and cellular processes, the atlas identifies master regulators and common targets across immune cells. SINGULAR has the potential to inform future advancements in human age reversal and aid in the selection of drugs that mimic the effects of rejuvenation interventions.

RESULTS

The authors propose a unified multiscale analysis pipeline for characterizing and comparing the effects of rejuvenation interventions. This process begins by filtering low-quality cells, normalizing expression profiles, and identifying optimal cell clustering. The data is then analyzed at various biological levels, including differential gene expression, transcriptional regulatory networks, signaling cascades, and intercellular communication.

Nine previously published single-cell RNA-seq datasets from different rejuvenation interventions were collected and analyzed, revealing technical variability that highlights the need for a standardized data processing pipeline. The analysis showed heterogeneous gene expression responses across different cell types and organs. Systemic interventions had consistent effects on multiple organs, while metformin had minimal impact. Interestingly, exercise produced the largest transcriptional effects in the liver, artery, and spinal cord, even though it primarily targets muscles.

Transcriptional regulatory networks (TRNs) were reconstructed to explore the regulatory mechanisms behind these gene expression changes. The TRNs, which averaged 72 genes, were highly hierarchical, indicating the presence of ‘master regulators’ that explain significant portions of gene expression changes.

To demonstrate the practical application of SINGULAR, the study investigated the identification of drugs that could target transcription factor (TF) master regulators and key signaling molecules. Drug-target relationships from DrugBank were analyzed to find drugs that could activate master regulators or mimic the effects of rejuvenation interventions. Interestingly, only 17 out of 239 TFs could be activated by drugs, primarily nuclear receptors, with notable exceptions like AP-1 complex proteins and Trp53. Some of these drugs, such as Curcumin and Vitamin D3, have shown rejuvenating effects on lifespan in model organisms. Key signaling molecules were found to be more druggable, with several drugs targeting specific molecules, though none targeted both genes.

The study aimed to identify master regulators and their downstream effects in rejuvenation interventions. By simulating the activation of transcription factors (TFs) within the network, the researchers quantified the number of genes regulated by each TF. They discovered 493 TFs with non-zero activity across various conditions, though most acted as master regulators in only a few cases. The study also highlighted key differences between TFs involved in aging-related activity changes and those regulating rejuvenation. Notably, the AP-1 complex, consisting of Fos and Jun, emerged as a common master regulator across multiple interventions. The researchers also identified TFs linked to aging and validated their potential rejuvenating effects experimentally. They also explored crosstalk between TFs and signaling pathways, finding negative enrichment of aging gene sets in several integrated networks. Overall, the findings offer valuable insights into the regulatory mechanisms and potential rejuvenating effects of master regulators and signaling molecules involved in rejuvenation interventions.

CONCLUSION

In conclusion, this study employed a unified analysis pipeline, SINGULAR, to compare the effects and mediators of various rejuvenation interventions. Key master regulators, including Arntl, AP-1 complex proteins, NFE2L2, and MAF, were identified as playing crucial roles in rejuvenation. The analysis revealed distinct differences between aging-related transcriptional changes and rejuvenation regulators. Immune and skin cell types were highlighted as potential intervention targets, with the possibility of additive or synergistic effects by targeting non-overlapping master regulators. Some limitations were noted, such as biases in cell type comparisons, reliance on ligand-receptor interactions for cell-cell communication analysis, and the risk of false negatives in differential expression testing. Despite these limitations, SINGULAR offers valuable insights into rejuvenation mechanisms and the identification of agents for anti-aging strategies. It provides a robust framework for understanding the mechanisms behind various interventions and offers a wide range of potential target genes for a comprehensive anti-aging approach.

Click here to read the full research paper in Aging.

Aging is indexed by PubMed/Medline (abbreviated as “Aging (Albany NY)”), PubMed CentralWeb of Science: Science Citation Index Expanded (abbreviated as “Aging‐US” and listed in the Cell Biology and Geriatrics & Gerontology categories), Scopus (abbreviated as “Aging” and listed in the Cell Biology and Aging categories), Biological Abstracts, BIOSIS Previews, EMBASE, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).

Click here to subscribe to Aging publication updates.

For media inquiries, please contact [email protected].

When Does Human Life Truly Begin?

In this fascinating new review, researchers Polina A. Loseva and Vadim N. Gladyshev discuss “The beginning of becoming a human.”

For centuries, the question of when human life commences has perplexed philosophers, theologians, and scientists alike. With the advent of modern reproductive technologies and groundbreaking scientific advancements, this profound inquiry has taken on renewed urgency and complexity. In a fascinating new review paper, researchers Polina A. Loseva and Vadim N. Gladyshev from Harvard Medical School delved into this intricate subject, exploring the multifaceted perspectives that have shaped our understanding of life’s origins. On May 6, 2024, their review was published on the cover of Aging’s Volume 16, Issue 9, entitled, “The beginning of becoming a human.” Below, this article breaks down their chronological review of the various ways life has been defined: movement, fusion, self-sufficiency, uniqueness, and now, aging.

Life Defined by Movement: The Quickening

Historically, the notion of life’s inception was inextricably linked to the first perceptible movements of the fetus within the womb, a phenomenon known as “quickening.” In 18th-century England, this milestone was so pivotal that it could even pardon a pregnant woman sentenced to hanging. However, as our comprehension of embryonic development deepened, it became evident that quickening is an unreliable indicator, as the timing varies widely among individuals and is largely dependent on maternal factors.

Life Defined by Fusion: The Conception Conundrum

Another perspective posits that life begins at the moment of conception, when the egg and sperm fuse, forming a unique genetic entity distinct from its progenitors. However, this definition encounters challenges, as the newly formed zygote lacks a fully assembled nucleus and functional genome initially. Furthermore, the ability to split or combine embryos during the early stages raises philosophical quandaries about the individuality and uniqueness of life.

Life Defined by Self-Sufficiency: Viability and Technological Advancement

As medical technologies advanced, the definition of life’s beginning shifted towards the point at which the fetus could theoretically survive outside the womb, albeit with medical intervention. This threshold, known as “viability,” has been a moving target, continually redefined as neonatal care capabilities improve. However, with the advent of artificial womb systems, this criterion may become increasingly ambiguous.

In the midst of the heated debates surrounding reproductive technologies and embryonic experimentation in the 1980s, the Warnock Committee was tasked with establishing ethical boundaries. Their landmark report introduced the “14-day rule,” a compromise that prohibited the cultivation or experimentation on human embryos beyond 14 days after fertilization. While the rationale behind this specific timeframe was somewhat arbitrary, it struck a delicate balance between scientific progress and ethical considerations.

Life Defined by Uniqueness: The Gastrulation Milestone

Remarkably, the 14-day stage coincides with a pivotal developmental event known as gastrulation, during which the embryo transitions from a single-layered structure to a three-layered disc that prefigures the body plan of a vertebrate organism. This transformation not only establishes the embryo’s anterior-posterior, dorsal-ventral, and left-right axes but also marks the point at which the embryo becomes increasingly resistant to splitting or combining, solidifying its individuality.

As scientific capabilities advanced, the ability to culture human embryos beyond the 14-day threshold became a reality, reigniting discussions about revising the Warnock Committee’s guidelines. Proponents argued that this boundary was arbitrary and that our improved understanding of neural development warranted an extension. Others proposed alternative timeframes, such as 22 days (when the nervous system begins to form) or 28 days (when abortions are typically not performed). Ultimately, the International Society for Stem Cell Research (ISSCR) opted for a case-by-case approach, with individual oversight committees evaluating each experiment’s merits.

Life Defined by Aging: A Paradigm Shift

Intriguingly, recent studies have shed light on an overlooked aspect of embryonic development: the onset of aging. By employing epigenetic clocks and other molecular biomarkers, researchers have discovered that the “ground zero” point of aging coincides remarkably with the 14-day stage, marking the transition from a rejuvenated state to the commencement of the aging process. This finding not only reinforces the significance of this developmental milestone but also prompts a reconsideration of life’s beginnings from the perspective of aging trajectories.

The 14++ Conundrum: Navigating Ethical and Scientific Imperatives

As the debate surrounding the 14-day rule continues to evolve, a paradoxical situation has emerged: the scientific consensus on the beginning of life remains elusive, while the ethical boundaries are subject to ongoing reevaluation and case-by-case determinations. This dichotomy underscores the need for a broader discussion involving not only embryologists but also bioethicists, legal experts, and diverse societal stakeholders.

Rather than seeking a definitive answer to the question of when human life begins, a more holistic approach may be to consider the emergence of different levels of life organization during embryonic development. These levels could encompass the cellular, organismal, and human life levels, each with its own unique characteristics and potential boundaries. By recognizing the complexity and multidimensionality of this process, we may gain a deeper appreciation for the intricate tapestry that weaves together the beginnings of human existence.

Synthetic Embryos: Witnessing the Emergence of Life In Vitro

While the 14-day stage may not represent the ultimate boundary for human life, it emerges as a compelling candidate for the transition to organismal life. At this juncture, the embryo exhibits signs of self/non-self discrimination, with cells organized into layers that prefigure the body plan. Concurrently, the rejuvenation processes conclude, and the aging trajectory commences for the somatic cells. This confluence of events suggests that the 14-day stage marks the emergence of a living organism, even if it may not yet possess all the attributes of a human being.

Recent breakthroughs in the generation of synthetic embryos, or “embryoids,” from pluripotent stem cells have opened up unprecedented opportunities to witness the emergence of organismal life in vitro. By recapitulating the early stages of human development, including gastrulation and the formation of embryonic layers, these synthetic models offer a unique window into the intricate processes underlying the transition from a collection of cells to an organized, living entity.

The Path Forward: Embracing Complexity and Collaboration

As we continue to unravel the enigma of life’s beginnings, it is evident that a multidisciplinary approach is essential. Collaboration among embryologists, bioethicists, legal scholars, and diverse stakeholders will be crucial in navigating the ethical and scientific complexities that arise. By embracing the nuances and respecting the perspectives of various disciplines, we can collectively chart a course that harmonizes scientific progress with ethical considerations, ultimately deepening our understanding of the profound journey that culminates in the emergence of a human being.

Click here to read the full review paper published in Aging.

Aging is an open-access, traditional, peer-reviewed journal that publishes high-impact papers in all fields of aging research. All papers are available to readers (at no cost and free of subscription barriers) in bi-monthly issues at Aging-US.com.

Click here to subscribe to Aging publication updates.

For media inquiries, please contact [email protected].

First Evidence of a Pan-tissue Decline in Stemness During Human Aging

In this new study, researchers provide the first evidence of a pan-tissue decrease of stemness during human aging.

Aging is still shrouded in proverbial darkness. But, some researchers hypothesize that aging may be linked to stem cell exhaustion. Stemness, the ability of a cell to differentiate into various cell types, is an essential characteristic defining the functionality of stem cells. It has been observed that stem cells seem to diminish with age, although the precise role of stem cells in human aging remains to be elucidated. 

“Among the biological pathways associated with aging, we can highlight stem cell exhaustion, which argues that during normal aging, the decrease in the number or activity of these cells contributes to physiological dysfunction in aged tissues [4].”

In a new study, researchers Gabriel Arantes dos Santos, Gustavo Daniel Vega Magdaleno and João Pedro de Magalhães from the Universidade de Sao Paulo, University of Birmingham and the University of Liverpool applied a machine learning method to detect stemness signatures from transcriptome data of healthy human tissues. Their research paper was published on April 4, 2024, and chosen as the cover of Aging’s Volume 16, Issue 7, entitled, “Evidence of a pan-tissue decline in stemness during human aging.”

The Study

In this study, the researchers delve into the intricate relationship between aging and stemness, offering vital insights into this complex interplay. The researchers conducted an in-depth analysis of healthy human tissue samples, assigning “stemness scores” to track the stemness levels across different age groups.

“In this context, detecting stemness-associated expression signatures is a promising strategy for studying stem cell biology.”

This research is the first to provide evidence of a pan-tissue decline in stemness during human aging. It is an important step forward in understanding the cellular mechanisms involved in the aging process and their potential implications for human health.

Methodology & Data Sources

The researchers used the RNA-Seq-based gene expression data from human tissues, downloaded from the Genomics of Ageing and Rejuvenation Lab’s Genomics of Ageing (GTEx) portal. This comprehensive dataset included over 17,000 healthy human tissue samples, spanning an age range of 20 to 79 years.

A machine learning methodology, originally developed by Malta et al., was applied to the GTEx transcriptome data to assign stemness scores to all samples. This advanced machine learning model was trained on stem cell classes and their differentiated progenitors, enabling the researchers to detect stemness signatures from the transcriptome data of healthy human tissues.

Key Findings

The analysis revealed a significant negative correlation between the subject’s age and stemness score in approximately 60% of the studied tissues. Interestingly, the only exception was the uterus, which exhibited increased stemness with age. This finding is particularly noteworthy, as it provides the first evidence of a pan-tissue decline in stemness during human aging. It supports the hypothesis that stem cell deterioration may contribute to the aging process.

The researchers also observed interesting correlations between stemness and other cellular processes. They found that stemness was positively correlated with cell proliferation. However, this relationship was not universal, with some tissues showing exceptions.

In contrast, when they examined the association between stemness and cellular senescence, a negative correlation was observed across the board. This finding suggests that although senescent cells and stem cells are not technically opposite states, they behave in opposite ways at the transcriptomic level within a living organism.

Implications & Future Directions

The findings of this study have far-reaching implications for our understanding of the aging process and its cellular underpinnings. By providing the first evidence of a pan-tissue decline in stemness during human aging, the study adds significant weight to the notion that stem cell deterioration may contribute to human aging.

However, many questions remain. For instance, it is not yet clear whether the loss of stemness contributes to aging or is a consequence of it. Moreover, it is uncertain whether the decline in stemness is due to a direct reduction in the stem cell pool or refers to intrinsic changes in different cells within the tissue.

Further research is needed to address these questions, and more robust studies are required to draw more assertive conclusions. It is also crucial to determine which factors drive these changes and which patterns and genes are associated with this process. This will be pivotal in advancing our understanding of stemness aging and its potential implications for human health.

“In conclusion, we provide the first evidence of a pan-tissue decrease of stemness during human aging and report an association between stemness and cell proliferation and senescence. This study also assigned a stemness score to more than 17,000 human samples, and these data can be useful for the scientific community for further studies.”

Click here to read the full research paper published in Aging.

Aging is an open-access, traditional, peer-reviewed journal that publishes high-impact papers in all fields of aging research. All papers are available to readers (at no cost and free of subscription barriers) in bi-monthly issues at Aging-US.com.

Click here to subscribe to Aging publication updates.

For media inquiries, please contact [email protected].

Overcoming Missing Data in the Swedish National Study on Aging

In this new study, researchers compared three multiple imputation strategies for overcoming the missing discrete variable of gait speed in the Swedish National Study on Aging and Care (SNAC).

Missing data in aging studies, especially in the assessment of gait speed (the time it takes individuals to cover a set distance), presents a significant challenge. The elderly are more prone to health and functional issues, which often interfere with data collection efforts. Given that gait speed is a key indicator of functional status and overall health in older individuals, ensuring its availability and accurate measurement is essential for the integrity of aging research.

In a new study, researchers Robert Thiesmeier, Ahmad Abbadi, Debora Rizzuto, Amaia Calderón-Larrañaga, Scott M. Hofer, and Nicola Orsini from Karolinska Institutet, Stockholm University, Stockholm Gerontology Research Center, and Oregon Health and Science University address the systematic challenge of missing gait speed data in aging research and explore the application of multiple imputation (MI), a statistical technique that has emerged as a constructive approach to handle such gaps in data. The team critically examined the implementation strategies, methodologies, and the impact that these missing variables could have on the outcomes of aging studies, thereby offering a framework to manage and interpret incomplete datasets in aging research. On February 14, 2024, their research paper was published in Aging’s Volume 16, Issue 4, entitled, “Multiple imputation of systematically missing data on gait speed in the Swedish National Study on Aging and Care.”

“[…] this study aims to investigate and assess the performance of different MI strategies specifically targeting the systematically missing discrete variable of gait speed in the SNAC [Swedish National Study on Aging and Care] IPDMA [individual participant data meta-analyses] with only four large cohort studies.”

Setting the Context

Before delving into the specifics of the study, it’s crucial to comprehend the broader context. Aging, as a biological process, presents numerous challenges, particularly in healthcare. Addressing these challenges requires comprehensive data to inform clinical diagnosis and prognosis. The Swedish National Study on Aging and Care (SNAC) is one such initiative that aims to provide a holistic view of aging and elderly data.

SNAC was launched in 2001 as an ongoing longitudinal cohort study based on samples of the Swedish elderly population. The study comprises four sites: Kungsholmen, Skåne, Nordanstig, and Blekinge. Each site collects data on health determinants, disease outcomes, functional capacity, and social conditions. SNAC’s diverse data collection has facilitated the development of an innovative Health Assessment Tool integrating indicators of both clinical and functional health in a population aged 60+ years.

SNAC, like any extensive study, faces the issue of missing data. One variable, gait speed, is systematically absent in one study site, Blekinge. This absence poses a significant challenge for researchers. They must decide between using complete data from only three studies, risking information loss and potential bias in combined estimates, or employing multiple imputation (MI) methods to estimate missing values based on observed data.

What is Multiple Imputation?

Gait speed, or the speed at which a person walks, is a simple but powerful indicator of health and functional status in older adults. It can predict the risk of mortality, disability, cognitive decline, and institutionalization. However, measuring gait speed is not always feasible in large-scale epidemiological studies, especially when participants are frail, have mobility limitations, or live in remote areas. This can result in missing data on gait speed, which can bias the estimates of its association with health outcomes and reduce the statistical power of the analyses.

One way to handle missing data on gait speed is to use multiple imputation, a statistical technique that replaces each missing value with a set of plausible values that reflect the uncertainty about the true value. Multiple imputation can reduce bias and increase precision compared to excluding cases with missing data or using a single imputation method. However, there are different ways to perform multiple imputation, and some may be more suitable than others depending on the type and pattern of missing data.

The Study

In the current study, the researchers compared three multiple imputation strategies for dealing with systematically missing data on gait speed in the SNAC. The SNAC consists of four prospective cohort studies that measured gait speed at baseline and follow-up, except for one study that did not measure gait speed at all. The authors simulated 1000 individual participant data meta-analyses (IPDMA) based on the characteristics of the SNAC and evaluated the performance of three multiple imputation strategies: fully conditional specification (FCS), multivariate normal (MVN), and conditional quantile imputation (CQI).

The FCS method imputes each variable separately by using regression models that depend on the other variables in the dataset. The MVN method assumes that the data follow a multivariate normal distribution and imputes all variables simultaneously by using an expectation-maximization algorithm. The CQI method imputes discrete variables by using quantile regression models that preserve the distribution of the original data.

The authors analyzed the imputed datasets with a two-stage common-effect multivariable logistic model that estimated the effect of three levels of gait speed (<0.8 m/s, 0.8-1.2 m/s, >1.2 m/s) on 5-years mortality. They found that all three imputation methods performed relatively well in terms of bias and coverage of the confidence intervals. However, the CQI method showed the smallest bias and the best coverage for both low and high levels of gait speed. The FCS and MVN methods tended to overestimate the effect of low gait speed and underestimate the effect of high gait speed on mortality.

Conclusions

The authors concluded that multiple imputation can be a useful tool for dealing with systematically missing data on gait speed in IPDMA based on the SNAC. They recommended the CQI method as the preferred approach for imputing discrete variables such as gait speed, as it preserves the original distribution and avoids unrealistic values. They also highlighted the importance of reporting the details of the multiple imputation procedure and checking the plausibility of the imputed values.

This study provides valuable insights for researchers who face similar challenges with missing data on gait speed or other discrete variables in aging research. By using appropriate multiple imputation methods, they can improve the validity and reliability of their results and avoid losing valuable information.

Click here to read the full research paper published in Aging.

Aging is an open-access, traditional, peer-reviewed journal that has published high-impact papers in all fields of aging research since 2009. All papers are available to readers (at no cost and free of subscription barriers) in bi-monthly issues at Aging-US.com.

Click here to subscribe to Aging publication updates.

For media inquiries, please contact [email protected].

Senescence-Related TME Genes as Key Prognostic Predictors in HNSCC

In a new study, researchers aimed to investigate the prognostic significance of senescence-related TME genes in head and neck squamous cell carcinoma (HNSCC) and their potential implications for immunotherapy response. 

Head and neck squamous cell carcinoma (HNSCC) is a prevalent and heterogeneous form of cancer that affects thousands of individuals worldwide. The prognosis for HNSCC patients can vary greatly, depending on factors such as tumor stage and site. The tumor microenvironment (TME) plays a crucial role in tumorigenesis and disease progression, with cellular senescence being a key component. Senescent cells, characterized by cell-cycle arrest, have been shown to have both tumor-suppressive and tumor-promoting effects. However, the prognostic significance of senescence-related TME genes in HNSCC remains poorly understood.

In a new study, researchers Young Chan Lee, Yonghyun Nam, Minjeong Kim, Su Il Kim, Jung-Woo Lee, Young-Gyu Eun, and Dokyoon Kim from Kyung Hee University, Kyung Hee University Hospital at Gangdong, and the University of Pennsylvania aimed to investigate the prognostic significance of senescence-related TME genes in HNSCC and their potential implications for immunotherapy response. They utilized data from The Cancer Genome Atlas (TCGA) to identify two distinct subtypes of HNSCC based on the expression of senescence-related TME genes. The team then constructed a risk model consisting of senescence-related TME core genes (STCGs) and validated its prognostic capability in independent cohorts. Their research paper was chosen as an Aging cover paper and published in Volume 16, Issue 2, entitled, “Prognostic significance of senescence-related tumor microenvironment genes in head and neck squamous cell carcinoma.”

“To the best of our knowledge, this is the first study to offer a comprehensive evaluation of the senescence related TME status by integrating senescence related TME genes through a gene-gene network and clustering. Furthermore, we have introduced a novel risk model that utilizes a selected gene set to predict prognosis and confirmed the expression of STCGs in immune cells at single-cell levels.”

The Study

Identification of Prognostic Senescence-Related TME Genes

To identify prognostic senescence-related TME genes, the researchers screened a total of 7,878 genes in the TCGA-HNSCC dataset. They identified 288 genes that belonged to TME-related genes, tumor-associated senescence (TAS) genes, and immune-related genes. From these genes, they selected 91 prognostic senescence-related TME genes (PSTGs) based on differential expression analysis and Cox regression analysis.

Senescence-Related TME Subtypes and Characterization

Using consensus clustering analysis, the researchers classified the HNSCC samples into two distinct subtypes based on the expression of PSTGs: subtype 1 and subtype 2. The two subtypes exhibited significant differences in clinical and molecular characteristics. Subtype 2 had a higher prevalence of HPV-positive and oropharyngeal cancer cases, while subtype 1 was characterized by a higher proportion of advanced tumor stage and overall stage.

Further analysis revealed distinct differences between the subtypes in terms of genetic alterations, methylation patterns, enriched pathways, and immune infiltration. Subtype 1 had a higher mutation rate in the TP53 gene and exhibited hypomethylation in several CpG sites compared to subtype 2. Additionally, subtype 2 showed higher immune scores, stromal scores, and ESTIMATE scores, indicating a more favorable immune microenvironment.

The two subtypes also displayed differences in survival outcomes. Kaplan-Meier survival analysis showed that subtype 2 had a more favorable overall survival compared to subtype 1. This difference was enhanced in the HPV-positive cohort, suggesting that the senescence-related TME subtypes may have implications for prognosis in specific patient subgroups.

Risk Scoring Based on Senescence-Related TME Status

Using the 91 PSTGs, the researchers constructed a risk scoring model based on the LASSO Cox regression algorithm. They identified 21 STCGs that were associated with either increased risk or protection. The risk scores based on the expression levels of these genes were calculated for each patient, and the patients were classified into high- and low-risk groups.

The prognostic performance of the risk scoring model was tested in independent cohorts, including the TCGA-HNSCC test set, the GSE41613 cohort, and the KHUMC cohort. The high-risk group showed significantly lower overall survival compared to the low-risk group in the TCGA-HNSCC test set and the GSE41613 cohort. Although not statistically significant, the low-risk group demonstrated a trend towards higher overall survival in the KHUMC cohort.

Immunotherapy Response Prediction and Single-Cell Analysis

The team also investigated the immunotherapy response prediction based on the risk model and the expression of STCGs. They found that the low-risk group had higher immunophenoscores and a significantly higher proportion of responders to immunotherapy compared to the high-risk group.

To further evaluate the senescence-related TME characteristics at the single-cell level, the researchers analyzed single-cell transcriptome data from HNSCC tissue. They found that STCGs were enriched in fibroblast, mono/macrophage, and T cell populations, suggesting that these cell types contribute to the senescent features of HNSCC.

Conclusion

In conclusion, the study sheds light on the prognostic significance of senescence-related TME genes in HNSCC. Their findings highlight the heterogeneity of HNSCC and the importance of the senescence-related TME in prognosis and immunotherapy response. The risk scoring model based on STCGs provides a potential prognostic biomarker for HNSCC patients, and the single-cell analysis further elucidates the association between STCGs and specific cell populations within the TME. These findings contribute to a deeper understanding of the complex interplay between senescence and the TME in HNSCC and have implications for precision medicine and personalized treatment approaches. Further research and validation are needed to fully understand the clinical implications of senescence-related TME genes in HNSCC. However, this study provides valuable insights into the role of cellular senescence in tumor progression and the potential for targeting senescence-related pathways in the development of novel therapeutic strategies for HNSCC patients.

“In conclusion, this study comprehensively investigated the prognostic and immunological features of senescence related TME genes in HNSC. By leveraging these senescence related TME genes, we successfully developed a risk model to predict HNSC prognosis and immunotherapy response, which was robustly validated using external transcriptome datasets. These findings provided evidence for the role of senescence in the TME and highlighted the potential of senescence-related biomarkers as promising therapeutic targets.”

Click here to read the full research paper published in Aging.

Aging is an open-access, traditional, peer-reviewed journal that has published high-impact papers in all fields of aging research since 2009. All papers are available to readers (at no cost and free of subscription barriers) in bi-monthly issues at Aging-US.com.

Click here to subscribe to Aging publication updates.

For media inquiries, please contact [email protected].

  • Follow Us