Ying, K., Paulson, S., Reinhard, J. ...
· bioinformatics
· Division of Genetics, Department of Medicine, Brigham and Women\\\'s Hospital and Harvard Medical School
· biorxiv
Open scientific competitions have successfully driven biomedical advances but remain underutilized in aging research, where biological complexity and heterogeneity require methodological innovations. Here, we present the results from Phase I of the Biomarkers of Aging Challenge, ...
Open scientific competitions have successfully driven biomedical advances but remain underutilized in aging research, where biological complexity and heterogeneity require methodological innovations. Here, we present the results from Phase I of the Biomarkers of Aging Challenge, an open competition designed to drive innovation in aging biomarker development and validation. The challenge leverages a unique DNA methylation dataset and aging outcomes from 500 individuals, aged 18 to 99. Participants are asked to develop novel models to predict chronological age, mortality, and multi-morbidity. Results from the chronological age prediction phase show important advances in biomarker accuracy and innovation compared to existing models. The winning models feature improved predictive power and employ advanced machine learning techniques, innovative data preprocessing, and the integration of biological knowledge. These approaches have led to the identification of novel age-associated methylation sites and patterns. This challenge establishes a paradigm for collaborative aging biomarker development, potentially accelerating the discovery of clinically relevant predictors of aging-related outcomes. This supports personalized medicine, clinical trial design, and the broader field of geroscience, paving the way for more targeted and effective longevity interventions.
Longevity Relevance Analysis
(5)
The paper addresses the development and validation of biomarkers of aging, which is directly related to understanding and potentially mitigating the biological processes of aging. By leveraging a unique dataset and focusing on predictive models for aging-related outcomes, it contributes to the field of geroscience and personalized medicine. The findings indicate important advances in biomarker accuracy, which could have significant implications for aging research. However, while the work is important, it does not represent a major breakthrough that would transform the field, hence the score of 5.
Ludger J E Goeminne, Anastasiya Vladimirova, Alec Eames ...
· Cell metabolism
· Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
· pubmed
Aging is a complex process manifesting at molecular, cellular, organ, and organismal levels. It leads to functional decline, disease, and ultimately death, but the relationship between these fundamental biomedical features remains elusive. By applying elastic net regularization t...
Aging is a complex process manifesting at molecular, cellular, organ, and organismal levels. It leads to functional decline, disease, and ultimately death, but the relationship between these fundamental biomedical features remains elusive. By applying elastic net regularization to plasma proteome data of over 50,000 human subjects in the UK Biobank and other cohorts, we report interpretable organ-specific and conventional aging models trained on chronological age, mortality, and longitudinal proteome data. These models predict organ/system-specific disease and indicate that men age faster than women in most organs. Accelerated organ aging leads to diseases in these organs, and specific diets, lifestyles, professions, and medications influence organ aging rates. We then identify proteins driving these associations with organ-specific aging. Our analyses reveal that age-related chronic diseases epitomize accelerated organ- and system-specific aging, modifiable through environmental factors, advocating for both universal whole-organism and personalized organ/system-specific anti-aging interventions.
Longevity Relevance Analysis
(5)
The paper addresses the root causes of aging by developing organ-specific aging models based on plasma proteome data, which is relevant to longevity research. It explores how accelerated organ aging correlates with diseases and suggests modifiable factors that could influence aging rates, aligning with the goal of understanding and potentially mitigating aging processes. The findings are significant and contribute to the field, but they do not represent a major breakthrough or transformative work, hence the score of 5.
Vassiliki Nikoletopoulou
· The EMBO journal
· Department of Fundamental Neurosciences, University of Lausanne, Lausanne, Switzerland. vassiliki.nikoletopoulou@unil.ch.
· pubmed
The selective turnover of mitochondria via autophagy, known as mitophagy, is a major quality control mechanism safeguarding eukaryotic cells, including highly specialized neurons in the mammalian brain. A new resource by Rappe et al (2024) now provides a spatiotemporal landscape ...
The selective turnover of mitochondria via autophagy, known as mitophagy, is a major quality control mechanism safeguarding eukaryotic cells, including highly specialized neurons in the mammalian brain. A new resource by Rappe et al (2024) now provides a spatiotemporal landscape of mitophagy changes during mouse brain aging at unprecedented resolution, encompassing different cell types and subregions, and revealing unanticipated, context-specific dynamics.
Longevity Relevance Analysis
(5)
The paper addresses mitophagy, a critical cellular process related to mitochondrial quality control, which is essential for understanding the aging process and its implications for longevity. By providing insights into the dynamics of mitophagy in the aging mouse brain, it contributes to the broader understanding of cellular mechanisms that could influence lifespan and age-related diseases. However, while the findings are important, they do not represent a major breakthrough or transformative work in the field, hence the moderate impact score.
Renjia Zhao, Heyang Lu, Huangbo Yuan ...
· GeroScience
· State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and School of Life Science, Fudan University, Songhu Road 2005, Shanghai, China.
· pubmed
Individual's aging rates vary across organs. However, there are few methods for assessing aging at organ levels and whether they contribute differently to mortalities remains unknown. We analyzed data from 45,821 adults in the UK Biobank, using plasma proteomics and machine learn...
Individual's aging rates vary across organs. However, there are few methods for assessing aging at organ levels and whether they contribute differently to mortalities remains unknown. We analyzed data from 45,821 adults in the UK Biobank, using plasma proteomics and machine learning to estimate biological ages for 12 major organs. The differences between biological age and chronological age, referred to as "age gaps," were calculated for each organ. Partial correlation analyses were used to assess the association between age gaps and modifiable factors. Adjusted multivariable Cox regression models were applied to examine the association of age gaps with all-cause mortality, cause-specific mortalities, and cancer-specific mortalities. We reveal a complex network of varied associations between multi-organ aging and modifiable factors. All age gaps increase the risk of all-cause mortality by 6-60%. The risk of death varied from 5.54 to 29.18 times depending on the number of aging organs. Cause-specific mortalities are associated with certain organs' aging. For mental diseases mortality, and nervous system mortality, only brain aging exhibited a significant increased risk of HR 2.38 (per SD, 95% CI: 2.06-2.74) and 1.99 (per SD, 95% CI: 1.84-2.16), respectively. Age gaps of stomach were also a specific indicator for gastric cancer. Eventually, we find that an organ's biological age selectively influences the aging of other organ systems. Our study demonstrates that accelerated aging in specific organs increases the risk of mortality from various causes. This provides a potential tool for early identification of at-risk populations, offering a relatively objective method for precision medicine.
Longevity Relevance Analysis
(5)
The paper is relevant to longevity research as it investigates biological aging at the organ level and its association with all-cause and cause-specific mortality. By identifying how organ-specific aging contributes to mortality risks, it provides insights that could inform strategies for early identification of at-risk populations, which aligns with the goals of precision medicine in the context of aging. However, while the findings are important, they primarily advance understanding rather than directly addressing the root causes of aging or proposing interventions for lifespan extension, which limits its overall impact.
Tyler A U Hilsabeck, Vikram P Narayan, Kenneth A Wilson ...
· Longevity
· Buck Institute for Research on Aging, Novato, CA, 94945, USA.
· pubmed
Dietary restriction (DR) is a potent method to enhance lifespan and healthspan, but individual responses are influenced by genetic variations. Understanding how metabolism-related genetic differences impact longevity and healthspan are unclear. To investigate this, we used metabo...
Dietary restriction (DR) is a potent method to enhance lifespan and healthspan, but individual responses are influenced by genetic variations. Understanding how metabolism-related genetic differences impact longevity and healthspan are unclear. To investigate this, we used metabolites as markers to reveal how different genotypes respond to diet to influence longevity and healthspan traits. We analyzed data from Drosophila Genetic Reference Panel (DGRP) strains raised under AL and DR conditions, combining metabolomic, phenotypic, and genome-wide information. We employed two computational and complementary methods across species-random forest modeling within the DGRP as our primary analysis and Mendelian randomization in human cohorts as a secondary analysis. We pinpointed key traits with cross-species relevance as well as underlying heterogeneity and pleiotropy that influence lifespan and healthspan. Notably, orotate was linked to parental age at death in humans and blocked the DR lifespan extension in flies, while threonine supplementation extended lifespan, in a strain- and sex-specific manner. Thus, utilizing natural genetic variation data from flies and humans, we employed a systems biology approach to elucidate potential therapeutic pathways and metabolomic targets for diet-dependent changes in lifespan and healthspan.
Longevity Relevance Analysis
(5)
The paper investigates the metabolic signatures associated with dietary restriction and their influence on lifespan and healthspan across species, which is directly relevant to longevity research. It explores the genetic variations that affect individual responses to dietary interventions, providing insights into potential therapeutic pathways for enhancing lifespan. The findings contribute to the understanding of the biological mechanisms underlying aging and dietary impacts, making it an important study in the field, though not groundbreaking enough to warrant a higher impact score.
de Lima Camillo, L. P., Sehgal, R., Armstrong, J. ...
· systems biology
· Shift Bioscience, University of Cambridge
· biorxiv
DNA methylation is a critical epigenetic modification that regulates gene expression and plays a significant role in development and disease processes. Here, we present the Cytosine-phosphate-Guanine Pretrained Transformer (CpGPT), a novel foundation model pretrained on over 1,50...
DNA methylation is a critical epigenetic modification that regulates gene expression and plays a significant role in development and disease processes. Here, we present the Cytosine-phosphate-Guanine Pretrained Transformer (CpGPT), a novel foundation model pretrained on over 1,500 DNA methylation datasets encompassing over 100,000 samples from diverse tissues and conditions. CpGPT leverages an improved transformer architecture to learn comprehensive representations of methylation patterns, allowing it to impute and reconstruct genome-wide methylation profiles from limited input data. By capturing sequence, positional, and epigenetic contexts, CpGPT outperforms specialized models when finetuned for aging-related tasks, including chronological age prediction, mortality risk, and morbidity assessments. The model is highly adaptable across different methylation platforms and tissue types. Furthermore, analysis of sample-specific attention weights enables the identification of the most influential CpG sites for individual predictions. As a foundation model, CpGPT sets a new benchmark for DNA methylation analysis, achieving strong performance in the Biomarkers of Aging Challenge, where it placed second overall in chronological age estimation and first on the public leaderboard in methylation-based mortality prediction.
HighlightsO_LICpGPT is a novel foundation model for DNA methylation analysis, pretrained on over 1,500 datasets encompassing 100,000+ samples.
C_LIO_LIThe model demonstrates strong performance in zero-shot tasks including imputation, array conversion, and reference mapping.
C_LIO_LICpGPT achieves state-of-the-art results in mortality prediction and chronological age estimation.
C_LIO_LISample-specific interpretability is enabled through analysis of attention weights.
C_LI
Longevity Relevance Analysis
(5)
The paper presents a novel foundation model, CpGPT, that significantly advances the analysis of DNA methylation, which is closely linked to aging and age-related processes. By demonstrating strong performance in tasks related to chronological age prediction and mortality risk, it contributes to understanding the biological underpinnings of aging. However, while it offers important findings, it does not fundamentally address the root causes of aging or propose mechanisms for lifespan extension, limiting its overall impact to a solid contribution rather than a major breakthrough.