Tissue clocks derived from histological signatures of biological aging enable tissue-specific aging predictions from blood DOI Creative Commons

Ernesto Abila,

Iva Buljan, Yi-Min Zheng

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 15, 2024

Abstract Aging, the predominant risk factor for numerous diseases, manifests in various forms across structure and architecture of tissues human body, offering opportunity to quantify interpret tissue-specific aging. To address this, we present a comprehensive assessment tissue changes occurring during aging, utilizing vast array whole slide histopathological images from Genotype-Tissue Expression Project (GTEx). We analyzed 25,712 40 distinct types 983 individuals, applying deep learning nuanced morphological that undergo with age. developed ‘tissue clocks’—predictors biological age based on images—which achieved mean prediction error 4.9 years were associated telomere attrition, incidence subclinical pathologies, comorbidities. In systematic rates organs, identified pervasive non-uniform aging lifespan, some organs exhibiting earlier (20–40 old) others showing bimodal patterns age-related changes. also uncovered several associations between demographic, lifestyle, medical history factors acceleration or deceleration age, highlighting potential modifiable influenced process at level. Finally, by combining paired histological gene expression data, strategy predict gaps blood samples. This approach was validated external cohorts both healthy individuals those chronic revealing most differentially affected disease contexts. work offers new perspective positioning as an integrator cellular molecular reflect physiological state organs. These findings underscore value imaging tool understanding provide foundation exploration processes age-associated diseases.

Language: Английский

The genetic architecture of multimodal human brain age DOI Creative Commons
Junhao Wen, Bingxin Zhao, Zhijian Yang

et al.

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: March 23, 2024

Abstract The complex biological mechanisms underlying human brain aging remain incompletely understood. This study investigated the genetic architecture of three age gaps (BAG) derived from gray matter volume (GM-BAG), white microstructure (WM-BAG), and functional connectivity (FC-BAG). We identified sixteen genomic loci that reached genome-wide significance (P-value < 5×10 −8 ). A gene-drug-disease network highlighted genes linked to GM-BAG for treating neurodegenerative neuropsychiatric disorders WM-BAG cancer therapy. displayed most pronounced heritability enrichment in variants within conserved regions. Oligodendrocytes astrocytes, but not neurons, exhibited notable WM FC-BAG, respectively. Mendelian randomization potential causal effects several chronic diseases on aging, such as type 2 diabetes AD WM-BAG. Our results provide insights into genetics with clinical implications lifestyle therapeutic interventions. All are publicly available at https://labs.loni.usc.edu/medicine .

Language: Английский

Citations

21
Epigenetic ageing clocks: statistical methods and emerging computational challenges DOI
Andrew E. Teschendorff, Steve Horvath

Nature Reviews Genetics, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 13, 2025

Language: Английский

Citations

3
Artificial intelligence for medicine 2025: Navigating the endless frontier DOI
Jiyan Dai, Huiyu Xu, Tao Chen

et al.

The Innovation Medicine, Journal Year: 2025, Volume and Issue: unknown, P. 100120 - 100120

Published: Jan. 1, 2025

<p>Artificial intelligence (AI) is driving transformative changes in the field of medicine, with its successful application relying on accurate data and rigorous quality standards. By integrating clinical information, pathology, medical imaging, physiological signals, omics data, AI significantly enhances precision research into disease mechanisms patient prognoses. technologies also demonstrate exceptional potential drug development, surgical automation, brain-computer interface (BCI) research. Through simulation biological systems prediction intervention outcomes, enables researchers to rapidly translate innovations practical applications. While challenges such as computational demands, software ethical considerations persist, future remains highly promising. plays a pivotal role addressing societal issues like low birth rates aging populations. can contribute mitigating rate through enhanced ovarian reserve evaluation, menopause forecasting, optimization Assisted Reproductive Technologies (ART), sperm analysis selection, endometrial receptivity fertility remote consultations. In posed by an population, facilitate development dementia models, cognitive health monitoring strategies, early screening systems, AI-driven telemedicine platforms, intelligent smart companion robots, environments for aging-in-place. profoundly shapes medicine.</p>

Language: Английский

Citations

2
The genetic architecture of biological age in nine human organ systems DOI
Junhao Wen, Ye Tian,

Ioanna Skampardoni

et al.

Nature Aging, Journal Year: 2024, Volume and Issue: 4(9), P. 1290 - 1307

Published: June 28, 2024

Language: Английский

Citations

13
Genetically supported targets and drug repurposing for brain aging: A systematic study in the UK Biobank DOI Creative Commons
Yi Fan, Jing Yuan, Judith Somekh

et al.

Science Advances, Journal Year: 2025, Volume and Issue: 11(11)

Published: March 12, 2025

Brain age gap (BAG), the deviation between estimated brain and chronological age, is a promising marker of health. However, genetic architecture reliable targets for aging remains poorly understood. In this study, we estimate magnetic resonance imaging (MRI)–based using deep learning models trained on UK Biobank validated with three external datasets. A genome-wide association study BAG identified two unreported loci seven previously reported loci. By integrating Mendelian Randomization (MR) colocalization analysis eQTL pQTL data, prioritized genetically supported druggable genes, including MAPT , TNFSF12 GZMB SIRPB1 GNLY NMB C1RL as aging. We rediscovered 13 potential drugs evidence from clinical trials several strong support. Our provides insights into basis aging, potentially facilitating drug development to extend health span.

Language: Английский

Citations

1
Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning DOI
Junhao Wen, Mathilde Antoniades, Zhijian Yang

et al.

Biological Psychiatry, Journal Year: 2024, Volume and Issue: 96(7), P. 564 - 584

Published: May 6, 2024

Language: Английский

Citations

5
The Genetic Architecture of Biological Age in Nine Human Organ Systems DOI Creative Commons
Junhao Wen, Ye Tian,

Ioanna Skampardoni

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: June 12, 2023

Abstract Understanding the genetic basis of biological aging in multi-organ systems is vital for elucidating age-related disease mechanisms and identifying therapeutic interventions. This study characterized architecture age gap (BAG) across nine human organ 377,028 individuals European ancestry from UK Biobank. We discovered 393 genomic loci-BAG pairs (P-value<5×10 -8 ) linked to brain, eye, cardiovascular, hepatic, immune, metabolic, musculoskeletal, pulmonary, renal systems. observed BAG-organ specificity inter-organ connections. Genetic variants associated with BAGs are predominantly specific respective system while exerting pleiotropic effects on traits multiple A gene-drug-disease network confirmed involvement metabolic BAG-associated genes drugs targeting various disorders. correlation analyses supported Cheverud’s Conjecture 1 – between mirrors their phenotypic correlation. causal revealed potential linking chronic diseases (e.g., Alzheimer’s disease), body weight, sleep duration BAG Our findings shed light promising interventions enhance health within a complex network, including lifestyle modifications drug repositioning strategies treating diseases. All results publicly available at https://labs-laboratory.com/medicine .

Language: Английский

Citations

12
Multi-omics and Multi-organ Aging Clocks Digitize Human Aging DOI Creative Commons
Junhao Wen

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 7, 2025

Abstract Multi-organ biological aging clocks derived from clinical phenotypes and neuroimaging have emerged as valuable tools for studying human disease 1,2,3,4 . Plasma proteomics provides an additional molecular dimension to enrich these 5 Here, we used 2448 plasma proteins 43,498 participants in the UK Biobank develop 11 multi-organ proteome-based age gaps (ProtBAG). We compared them 9 phenotype-based (PhenoBAG 1 ) regarding genetics, causal associations with 525 endpoints (DE) FinnGen PGC, their promise predict 14 categories mortality. highlighted critical methodological considerations generating ProtBAG, including need bias correction 6 addressing protein organ specificity enhance model performance generalizability. Genetic analyses revealed overlap between ProtBAGs PhenoBAGs, shared loci, genetic correlations, colocalization signals. A three-layer network linked PhenoBAG, DE, exemplified by pathway of obesity→renal PhenoBAG→renal ProtBAG holistically understand disease. Combining features across multiple organs improved predictions These findings provide a framework integrating multi-omics biomedicine. All results are publicly disseminated at https://labs-laboratory.com/medicine/

Language: Английский

Citations

0
Artificial Intelligence in Central-Peripheral Interaction Organ Crosstalk: The Future of Drug Discovery and Clinical Trials DOI Creative Commons

Yufeng Chen,

Mingrui Yang, Qian Hua

et al.

Pharmacological Research, Journal Year: 2025, Volume and Issue: unknown, P. 107734 - 107734

Published: April 1, 2025

Drug discovery before the 20th century often focused on single genes, molecules, cells, or organs, failing to capture complexity of biological systems. The emergence protein-protein interaction network studies in 2001 marked a turning point and promoted holistic approach that considers human body as an interconnected system. This is particularly evident study bidirectional interactions between central nervous system (CNS) peripheral which are critical for understanding health disease. Understanding these complex requires integrating multi-scale, heterogeneous data from molecular organ levels, encompassing both omics (e.g., genomics, proteomics, microbiomics) non-omics imaging, clinical phenotypes). Artificial intelligence (AI), multi-modal models, has demonstrated significant potential analyzing CNS-peripheral by processing vast, datasets. Specifically, AI facilitates identification biomarkers, prediction therapeutic targets, simulation drug effects multi-organ systems, thereby paving way novel strategies. review highlights AI's transformative role research, focusing its applications unraveling disease mechanisms, discovering optimizing trials through patient stratification adaptive trial design.

Language: Английский

Citations

0
Long COVID as a Disease of Accelerated Biological Aging: An Opportunity to Translate Geroscience Interventions DOI
Areez Shafqat, Mary Clare Masters, Utkarsh Tripathi

et al.

Ageing Research Reviews, Journal Year: 2024, Volume and Issue: 99, P. 102400 - 102400

Published: June 28, 2024

Language: Английский

Citations

3