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Kassab A, Rizk N, Prakash S. The Role of Systemic Filtrating Organs in Aging and Their Potential in Rejuvenation Strategies. Int J Mol Sci 2022; 23:ijms23084338. [PMID: 35457154 PMCID: PMC9025381 DOI: 10.3390/ijms23084338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 04/05/2022] [Accepted: 04/08/2022] [Indexed: 11/26/2022] Open
Abstract
Advances in aging studies brought about by heterochronic parabiosis suggest that aging might be a reversable process that is affected by changes in the systemic milieu of organs and cells. Given the broadness of such a systemic approach, research to date has mainly questioned the involvement of “shared organs” versus “circulating factors”. However, in the absence of a clear understanding of the chronological development of aging and a unified platform to evaluate the successes claimed by specific rejuvenation methods, current literature on this topic remains scattered. Herein, aging is assessed from an engineering standpoint to isolate possible aging potentiators via a juxtaposition between biological and mechanical systems. Such a simplification provides a general framework for future research in the field and examines the involvement of various factors in aging. Based on this simplified overview, the kidney as a filtration organ is clearly implicated, for the first time, with the aging phenomenon, necessitating a re-evaluation of current rejuvenation studies to untangle the extent of its involvement and its possible role as a potentiator in aging. Based on these findings, the review concludes with potential translatable and long-term therapeutics for aging while offering a critical view of rejuvenation methods proposed to date.
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Affiliation(s)
- Amal Kassab
- Biomedical Technology and Cell Therapy Research Laboratory, Department of Biomedical Engineering, Faculty of Medicine, McGill University, 3775 University Street, Montreal, QC H3A 2BA, Canada
| | - Nasser Rizk
- Department of Biomedical Sciences, College of Health Sciences-QU-Health, Qatar University, Doha 2713, Qatar
| | - Satya Prakash
- Biomedical Technology and Cell Therapy Research Laboratory, Department of Biomedical Engineering, Faculty of Medicine, McGill University, 3775 University Street, Montreal, QC H3A 2BA, Canada
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Wu L, Xie X, Liang T, Ma J, Yang L, Yang J, Li L, Xi Y, Li H, Zhang J, Chen X, Ding Y, Wu Q. Integrated Multi-Omics for Novel Aging Biomarkers and Antiaging Targets. Biomolecules 2021; 12:39. [PMID: 35053186 PMCID: PMC8773837 DOI: 10.3390/biom12010039] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 12/17/2021] [Accepted: 12/19/2021] [Indexed: 12/12/2022] Open
Abstract
Aging is closely related to the occurrence of human diseases; however, its exact biological mechanism is unclear. Advancements in high-throughput technology provide new opportunities for omics research to understand the pathological process of various complex human diseases. However, single-omics technologies only provide limited insights into the biological mechanisms of diseases. DNA, RNA, protein, metabolites, and microorganisms usually play complementary roles and perform certain biological functions together. In this review, we summarize multi-omics methods based on the most relevant biomarkers in single-omics to better understand molecular functions and disease causes. The integration of multi-omics technologies can systematically reveal the interactions among aging molecules from a multidimensional perspective. Our review provides new insights regarding the discovery of aging biomarkers, mechanism of aging, and identification of novel antiaging targets. Overall, data from genomics, transcriptomics, proteomics, metabolomics, integromics, microbiomics, and systems biology contribute to the identification of new candidate biomarkers for aging and novel targets for antiaging interventions.
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Affiliation(s)
- Lei Wu
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China; (L.W.); (X.X.); (T.L.); (L.Y.); (J.Y.); (L.L.); (Y.X.); (H.L.); (J.Z.)
- School of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi’an 710021, China; (J.M.); (X.C.)
| | - Xinqiang Xie
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China; (L.W.); (X.X.); (T.L.); (L.Y.); (J.Y.); (L.L.); (Y.X.); (H.L.); (J.Z.)
| | - Tingting Liang
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China; (L.W.); (X.X.); (T.L.); (L.Y.); (J.Y.); (L.L.); (Y.X.); (H.L.); (J.Z.)
- School of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi’an 710021, China; (J.M.); (X.C.)
| | - Jun Ma
- School of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi’an 710021, China; (J.M.); (X.C.)
| | - Lingshuang Yang
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China; (L.W.); (X.X.); (T.L.); (L.Y.); (J.Y.); (L.L.); (Y.X.); (H.L.); (J.Z.)
| | - Juan Yang
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China; (L.W.); (X.X.); (T.L.); (L.Y.); (J.Y.); (L.L.); (Y.X.); (H.L.); (J.Z.)
- School of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi’an 710021, China; (J.M.); (X.C.)
| | - Longyan Li
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China; (L.W.); (X.X.); (T.L.); (L.Y.); (J.Y.); (L.L.); (Y.X.); (H.L.); (J.Z.)
| | - Yu Xi
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China; (L.W.); (X.X.); (T.L.); (L.Y.); (J.Y.); (L.L.); (Y.X.); (H.L.); (J.Z.)
| | - Haixin Li
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China; (L.W.); (X.X.); (T.L.); (L.Y.); (J.Y.); (L.L.); (Y.X.); (H.L.); (J.Z.)
| | - Jumei Zhang
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China; (L.W.); (X.X.); (T.L.); (L.Y.); (J.Y.); (L.L.); (Y.X.); (H.L.); (J.Z.)
| | - Xuefeng Chen
- School of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi’an 710021, China; (J.M.); (X.C.)
| | - Yu Ding
- Department of Food Science and Technology, Institute of Food Safety and Nutrition, Jinan University, Guangzhou 510632, China
| | - Qingping Wu
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China; (L.W.); (X.X.); (T.L.); (L.Y.); (J.Y.); (L.L.); (Y.X.); (H.L.); (J.Z.)
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Martens DS, Thijs L, Latosinska A, Trenson S, Siwy J, Zhang ZY, Wang C, Beige J, Vlahou A, Janssens S, Mischak H, Nawrot TS, Staessen JA. Urinary peptidomic profiles to address age-related disabilities: a prospective population study. THE LANCET. HEALTHY LONGEVITY 2021; 2:e690-e703. [PMID: 34766101 PMCID: PMC8566278 DOI: 10.1016/s2666-7568(21)00226-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 called for innovation in addressing age-related disabilities. Our study aimed to identify and validate a urinary peptidomic profile (UPP) differentiating healthy from unhealthy ageing in the general population, to test the UPP predictor in independent patient cohorts, and to search for targetable molecular pathways underlying age-related chronic diseases. METHODS In this prospective population study, we used data from participants in the Flemish Study on Environment, Genes and Health Outcomes (FLEMENGHO), done in northern Belgium from 1985 to 2019, and invited participants to a follow-up examination in 2005-10. Participants were eligible if their address was within 15 km of the examination centre and if they had not withdrawn consent in any of the previous examination cycles (1985-2004). All participants (2005-10) were also invited to an additional follow-up examination in 2009-13. Participants who took part in both the 2005-10 follow-up examination and in the additional 2009-13 follow-up visit constituted the derivation dataset, which included their 2005-10 data, and the time-shifted internal validation dataset, which included their 2009-13 data. The remaining participants who only had 2005-10 data constituted the synchronous internal validation dataset. Participants were excluded from analyses if they were incapacitated, had not undergone UPP, or had either missing or outlying (three SDs greater than the mean of all consenting participants) values of body-mass index, plasma glucose, or serum creatinine. The UPP was assessed by capillary electrophoresis coupled with mass spectrometry. The multidimensional UPP signature reflecting ageing was generated from the derivation dataset and validated in the time-shifted internal validation dataset and the synchronous validation dataset. It was further validated in patients with diabetes, COVID-19, or chronic kidney disease (CKD). In FLEMENGHO, the mortality endpoints were all-cause, cardiovascular, and non-cardiovascular mortality; other endpoints were fatal or non-fatal cancer and musculoskeletal disorders. Molecular pathway exploration was done using the Reactome and Kyoto Encyclopedia of Genes and Genomes databases. FINDINGS 778 individuals (395 [51%] women and 383 [49%] men; aged 16·2-82·1 years; mean age 50·9 years [SD 15·8]) from the FLEMENGHO cohort had a follow-up examination between 2005 and 2010, of whom 559 participants had a further follow-up from Oct 28, 2009, to March 19, 2013, and made up the derivation (2005-10) and time-shifted internal validation (2009-13) datasets. 219 were examined once and constituted the synchronous internal validation dataset (2005-10). With correction for multiple testing and multivariable adjustment, chronological age was associated with 210 sequenced peptides mainly showing downregulation of collagen fragments. The trained model relating chronological age to UPP, derived by elastic net regression, included 54 peptides from 17 proteins. The UPP-age prediction model explained 76·3% (r=0·87) of chronological age in the derivation dataset, 54·4% (r=0·74) in the time-shifted validation dataset, and 65·3% (r=0·81) in the synchronous internal validation dataset. Compared with chronological age, the predicted UPP-age was greater in patients with diabetes (chronological age 50·8 years [SE 0·37] vs UPP-age 56·9 years [0·30]), COVID‑19 (53·2 years [1·80] vs 58·5 years [1·67]), or CKD (54·6 years [0·97] vs 62·3 years [0·85]; all p<0·0001). In the FLEMENGHO cohort, independent of chronological age, UPP-age was significantly associated with various risk markers related to cardiovascular, metabolic, and renal disease, inflammation, and medication use. Over a median of 12·4 years (IQR 10·8-13·2), total mortality, cardiovascular mortality, and osteoporosis in the population was associated with UPP-age independent of chronological age, with hazard ratios per 10 year increase in UPP-age of 1·54 (95% CI 1·22-1·95) for total mortality, 1·72 (1·20-2·47) for cardiovascular mortality, and 1·40 (1·06-1·85) for osteoporosis and fractures. The most relevant molecular pathways informed by the proteins involved deregulation of collagen biology and extracellular matrix maintenance. INTERPRETATION The UPP signature indicative of ageing reflects fibrosis and extracellular matrix remodelling and was associated with risk factors and adverse health outcomes in the population and with accelerated ageing in patients. Innovation in addressing disability should shift focus from the ontology of diseases to shared disease mechanisms, in particular ageing-related fibrotic degeneration. FUNDING European Research Council, Ministry of the Flemish Community, OMRON Healthcare.
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Affiliation(s)
- Dries S Martens
- Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium
| | - Lutgarde Thijs
- Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium
| | | | - Sander Trenson
- Division of Cardiology, Sint-Jan Hospital, Bruges, Belgium
| | | | - Zhen-Yu Zhang
- Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Diseases, University of Leuven, Leuven, Belgium
| | - Congrong Wang
- Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium
| | - Joachim Beige
- Martin Luther University of Halle-Wittenberg, Halle (Saale), Germany
| | - Antonia Vlahou
- Systems Biology Center, Biomedical Research Foundation, Academy of Athens, Athens, Greece
| | - Stefan Janssens
- Division of Cardiology, University Hospitals Leuven, Leuven, Belgium
| | - Harald Mischak
- Mosaiques-Diagnostics, Hannover, Germany
- Institute of Cardiovascular and Medical Sciences, Glasgow, UK
| | - Tim S Nawrot
- Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium
- Research Unit Environment and Health, Department of Public Health and Primary Care, University of Leuven, Leuven, Belgium
| | - Jan A Staessen
- Biomedical Sciences Group, Faculty of Medicine, University of Leuven, Leuven, Belgium
- Alliance for the Promotion of Preventive Medicine, Mechelen, Belgium
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Johnson AA, Shokhirev MN, Wyss-Coray T, Lehallier B. Systematic review and analysis of human proteomics aging studies unveils a novel proteomic aging clock and identifies key processes that change with age. Ageing Res Rev 2020; 60:101070. [PMID: 32311500 DOI: 10.1016/j.arr.2020.101070] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 03/23/2020] [Accepted: 04/07/2020] [Indexed: 12/14/2022]
Abstract
The development of clinical interventions that significantly improve human healthspan requires robust markers of biological age as well as thoughtful therapeutic targets. To promote these goals, we performed a systematic review and analysis of human aging and proteomics studies. The systematic review includes 36 different proteomics analyses, each of which identified proteins that significantly changed with age. We discovered 1,128 proteins that had been reported by at least two or more analyses and 32 proteins that had been reported by five or more analyses. Each of these 32 proteins has known connections relevant to aging and age-related disease. GDF15, for example, extends both lifespan and healthspan when overexpressed in mice and is additionally required for the anti-diabetic drug metformin to exert beneficial effects on body weight and energy balance. Bioinformatic enrichment analyses of our 1,128 commonly identified proteins heavily implicated processes relevant to inflammation, the extracellular matrix, and gene regulation. We additionally propose a novel proteomic aging clock comprised of proteins that were reported to change with age in plasma in three or more different studies. Using a large patient cohort comprised of 3,301 subjects (aged 18-76 years), we demonstrate that this clock is able to accurately predict human age.
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