An integrative machine-learning meta-analysis of high-throughput omics data identifies age-specific hallmarks of Alzheimer’s disease DOI Creative Commons
Maxim N. Shokhirev, Adiv A. Johnson

Ageing Research Reviews, Journal Year: 2022, Volume and Issue: 81, P. 101721 - 101721

Published: Aug. 25, 2022

Alzheimer's disease (AD) is an incredibly complex and presently incurable age-related brain disorder. To better understand this debilitating disease, we collated performed a meta-analysis on publicly available RNA-Seq, microarray, proteomics, microRNA samples derived from AD patients non-AD controls. 4089 originating tissues blood remained after applying quality filters. Since progression in correlates with age, stratified large dataset into three different age groups: < 75 years, 75-84 ≥ 85 years. The proteomics datasets were then combined integrated datasets. Ensemble machine learning was employed to identify genes proteins that can accurately classify as either or control. These predictive inputs subjected network-based enrichment analyses. ability of genes/proteins associated pathways the Molecular Signatures Database diagnose also tested. We separately identified microRNAs be used make diagnosis predicted gene targets most analysis. following key themes emerged our bioinformatics analyses: cell death, cellular senescence, energy metabolism, genomic integrity, glia, immune system, metal ion homeostasis, oxidative stress, proteostasis, synaptic function. Many results demonstrated unique age-specificity. For example, terms highlighting senescence only earliest intermediate ranges while majority relevant death appeared youngest patients. Existing literature corroborates importance these hallmarks AD.

Language: Английский

Measuring biological age using omics data DOI
Jarod Rutledge, Hamilton Oh, Tony Wyss‐Coray

et al.

Nature Reviews Genetics, Journal Year: 2022, Volume and Issue: 23(12), P. 715 - 727

Published: June 17, 2022

Language: Английский

Citations

301

Aging Hallmarks and the Role of Oxidative Stress DOI Creative Commons
Edio Maldonado, Sebastián Morales, Fabiola Urbina

et al.

Antioxidants, Journal Year: 2023, Volume and Issue: 12(3), P. 651 - 651

Published: March 6, 2023

Aging is a complex biological process accompanied by progressive decline in the physical function of organism and an increased risk age-related chronic diseases such as cardiovascular diseases, cancer, neurodegenerative diseases. Studies have established that there exist nine hallmarks aging process, including (i) telomere shortening, (ii) genomic instability, (iii) epigenetic modifications, (iv) mitochondrial dysfunction, (v) loss proteostasis, (vi) dysregulated nutrient sensing, (vii) stem cell exhaustion, (viii) cellular senescence, (ix) altered communication. All these alterations been linked to sustained systemic inflammation, mechanisms contribute timing not clearly determined yet. Nevertheless, dysfunction one most important contributing process. Mitochondria primary endogenous source reactive oxygen species (ROS). During ATP production elevated ROS together with antioxidant defense. Elevated levels can cause oxidative stress severe damage cell, organelle membranes, DNA, lipids, proteins. This contributes phenotype. In this review, we summarize recent advances emphasis on production.

Language: Английский

Citations

207

Biomarkers of aging DOI Open Access

Hainan Bao,

Jiani Cao, Mengting Chen

et al.

Science China Life Sciences, Journal Year: 2023, Volume and Issue: 66(5), P. 893 - 1066

Published: April 11, 2023

Language: Английский

Citations

197

Advances and Utility of the Human Plasma Proteome DOI
Eric W. Deutsch, Gilbert S. Omenn, Zhi Sun

et al.

Journal of Proteome Research, Journal Year: 2021, Volume and Issue: 20(12), P. 5241 - 5263

Published: Oct. 21, 2021

The study of proteins circulating in blood offers tremendous opportunities to diagnose, stratify, or possibly prevent diseases. With recent technological advances and the urgent need understand effects COVID-19, proteomic analysis blood-derived serum plasma has become even more important for studying human biology pathophysiology. Here we provide views perspectives about developments possible clinical applications that use mass-spectrometry(MS)- affinity-based methods. We discuss examples where proteomics contributed valuable insights into SARS-CoV-2 infections, aging, hemostasis offered by combining with genetic data. As a contribution Human Proteome Organization (HUPO) Plasma Project (HPPP), present PeptideAtlas build 2021-07 comprises 4395 canonical 1482 additional nonredundant detected 240 MS-based experiments. In addition, report new Extracellular Vesicle 2021-06, which five studies 2757 extracellular vesicles blood, 74% (2047) are common PeptideAtlas. Our overview summarizes advances, impactful applications, ongoing challenges translating utility precision medicine.

Language: Английский

Citations

145

Paleoproteomics DOI Creative Commons
Christina Warinner, Kristine Korzow Richter, Matthew J. Collins

et al.

Chemical Reviews, Journal Year: 2022, Volume and Issue: 122(16), P. 13401 - 13446

Published: July 15, 2022

Paleoproteomics, the study of ancient proteins, is a rapidly growing field at intersection molecular biology, paleontology, archaeology, paleoecology, and history. Paleoproteomics research leverages longevity diversity proteins to explore fundamental questions about past. While its origins predate characterization DNA, it was only with advent soft ionization mass spectrometry that became truly feasible. Technological gains over past 20 years have allowed increasing opportunities better understand preservation, degradation, recovery rich bioarchive found in archaeological paleontological records. Growing from handful studies 1990s on individual highly abundant paleoproteomics today an expanding diverse applications ranging taxonomic identification fragmented bones shells phylogenetic resolution extinct species exploration cuisines dental calculus pottery food crusts diseases. More broadly, these opened new doors understanding human–animal interactions, reconstruction environments environmental changes, expansion hominin fossil record through large scale screening nondiagnostic bone fragments, vertebrate record. Even advances, much proteomic still remains unexplored. Here we provide overview history field, summary major methods currently use, critical evaluation current challenges. We conclude by looking future, for which innovative solutions emerging technology will play important role enabling us access unexplored “dark” proteome, allowing fuller can interpretation

Language: Английский

Citations

89

Vitamin D as a Shield against Aging DOI Open Access
Cristina Fantini, Clarissa Corinaldesi, Andrea Lenzi

et al.

International Journal of Molecular Sciences, Journal Year: 2023, Volume and Issue: 24(5), P. 4546 - 4546

Published: Feb. 25, 2023

Aging can be seen as a physiological progression of biomolecular damage and the accumulation defective cellular components, which trigger amplify process, toward whole-body function weakening. Senescence initiates at level consists in an inability to maintain homeostasis, characterized by overexpression/aberrant expression inflammatory/immune/stress responses. is associated with significant modifications immune system cells, decline immunosurveillance, which, turn, leads chronic elevation inflammation/oxidative stress, increasing risk (co)morbidities. Albeit aging natural unavoidable it regulated some factors, like lifestyle diet. Nutrition, indeed, tackles mechanisms underlying molecular/cellular aging. Many micronutrients, i.e., vitamins elements, impact cell function. This review focuses on role exerted vitamin D geroprotection, based its ability shape cellular/intracellular processes drive response protection against infections age-related diseases. To this aim, main paths immunosenescence inflammaging are identified biotargets D. Topics such heart skeletal muscle function/dysfunction, depending status, addressed, comments hypovitaminosis correction food supplementation. research has progressed, still limitations exist translating knowledge into clinical practice, making necessary focus attention aging, especially considering growing number older individuals.

Language: Английский

Citations

56

Proteomic aging clock predicts mortality and risk of common age-related diseases in diverse populations DOI Creative Commons
M. Austin Argentieri, Sihao Xiao, Derrick Bennett

et al.

Nature Medicine, Journal Year: 2024, Volume and Issue: 30(9), P. 2450 - 2460

Published: Aug. 8, 2024

Circulating plasma proteins play key roles in human health and can potentially be used to measure biological age, allowing risk prediction for age-related diseases, multimorbidity mortality. Here we developed a proteomic age clock the UK Biobank (n = 45,441) using platform comprising 2,897 explored its utility predict major disease morbidity mortality diverse populations. We identified 204 that accurately chronological (Pearson r 0.94) found aging was associated with incidence of 18 chronic diseases (including heart, liver, kidney lung, diabetes, neurodegeneration cancer), as well all-cause risk. Proteomic also measures biological, physical cognitive function, including telomere length, frailty index reaction time. Proteins contributing most substantially are involved numerous functions, extracellular matrix interactions, immune response inflammation, hormone regulation reproduction, neuronal structure function development differentiation. In validation study involving biobanks China 3,977) Finland 1,990), showed similar accuracy 0.92 0.94, respectively) compared performance Biobank. Our results demonstrate involves spanning multiple functional categories status, across geographically genetically

Language: Английский

Citations

46

Longitudinal serum proteome mapping reveals biomarkers for healthy ageing and related cardiometabolic diseases DOI Creative Commons
Jun Tang, Yue Liang, Ying Xu

et al.

Nature Metabolism, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 13, 2025

The blood proteome contains biomarkers of ageing and age-associated diseases, but such markers are rarely validated longitudinally. Here we map the longitudinal in 7,565 serum samples from a cohort 3,796 middle-aged elderly adults across three time points over 9-year follow-up period. We pinpoint 86 ageing-related proteins that exhibit signatures associated with 32 clinical traits incidence 14 major chronic diseases. Leveraging machine-learning model, pick 22 these to generate proteomic healthy score (PHAS), capable predicting cardiometabolic further identify gut microbiota as modifiable factor influencing PHAS. Our data constitute valuable resource offer useful insights into roles providing potential targets for intervention therapeutics promote ageing. Tang, Yue, Xu colleagues several thousand individuals period

Language: Английский

Citations

2

Proteomics in aging research: A roadmap to clinical, translational research DOI Creative Commons
Ruin Moaddel, Ceereena Ubaida‐Mohien, Toshiko Tanaka

et al.

Aging Cell, Journal Year: 2021, Volume and Issue: 20(4)

Published: March 17, 2021

The identification of plasma proteins that systematically change with age and, independent chronological age, predict accelerated decline health is an expanding area research. Circulating are ideal translational "omics" since they final effectors physiological pathways and because physicians accustomed to use information as biomarkers for diagnosis, prognosis, tracking the effectiveness treatments. Recent technological advancements, including mass spectrometry (MS)-based proteomics, multiplexed proteomic assay using modified aptamers (SOMAscan), Proximity Extension Assay (PEA, O-Link), have allowed assessment thousands in or other biological matrices, which potentially translatable into new clinical provide clues about mechanisms by aging associated deterioration functional decline. We carried out a detailed literature search studies performed different matrices (plasma, serum, urine, saliva, tissues) species multiple platforms. Herein, we identified 232 were age-associated across studies. Enrichment analysis revealed metabolic previously connected both animal models humans, most remarkably insulin-like growth factor (IGF) signaling, mitogen-activated protein kinases (MAPK), hypoxia-inducible 1 (HIF1), cytokine Forkhead Box O (FOXO) pathways, folate metabolism, advance glycation end products (AGE), receptor AGE (RAGE) pathway. Information on these age-relevant proteins, likely expanded validated longitudinal examined mechanistic studies, will be essential patient stratification development treatments aimed at improving expectancy.

Language: Английский

Citations

98

Data mining of human plasma proteins generates a multitude of highly predictive aging clocks that reflect different aspects of aging DOI Creative Commons
Benoit Lehallier, Maxim N. Shokhirev, Tony Wyss‐Coray

et al.

Aging Cell, Journal Year: 2020, Volume and Issue: 19(11)

Published: Oct. 8, 2020

ABSTRACT We previously identified 529 proteins that had been reported by multiple different studies to change their expression level with age in human plasma. In the present study, we measured q‐value and coefficient of these a plasma proteomic dataset derived from 4263 individuals. A bioinformatics enrichment analysis significantly trend toward increased strongly implicated diverse inflammatory processes. literature search revealed at least 64 are capable regulating life span an animal model. Nine (AKT2, GDF11, GDF15, GHR, NAMPT, PAPPA, PLAU, PTEN, SHC1) extend when manipulated mice or fish. By performing machine‐learning modeling 3301 individuals, discover ultra‐predictive aging clock comprised 491 protein entries. The Pearson correlation for this was 0.98 learning set 0.96 test while median absolute error 1.84 years 2.44 set. Using clock, demonstrate aerobic‐exercised trained individuals have younger predicted than physically sedentary subjects. testing clocks associated 1565 Reactome pathways, also show signal transduction immune system especially predicting age. additionally generate multitude predictors reflect aspects aging. For example, regulate models accurately predicts

Language: Английский

Citations

86