Multi-omics approaches to human biological age estimation

Solovev, Ilya; Shaposhnikov, Mikhail; Moskalev, Alexey

doi:10.1016/j.mad.2019.111192

Cited by 32 publications

(12 citation statements)

References 85 publications

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“…Its application is gaining interest across many disciplines from ageing research to risk assessment (e.g. van der Oost et al, 2003;Suarez and Moyes, 2012;Martyniuk, 2018;Solovev et al, 2020). Transcriptomics is probably the best known 'omics' approach in ecology.…”

Section: Discussionmentioning

confidence: 99%

Urban ecophysiology: beyond costs, stress and biomarkers

Isaksson

2020

Journal of Experimental Biology

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Natural habitats are rapidly declining due to urbanisation, with a concomitant decline in biodiversity in highly urbanised areas. Yet thousands of different species have colonised urban environments. These organisms are exposed to novel urban conditions, which are sometimes beneficial, but most often challenging, such as increased ambient temperature, chemicals, noise and light pollution, dietary alterations and disturbance by humans. Given the fundamental role of physiological responses in coping with such conditions, certain physiological systems such as the redox system, metabolism and hormones are thought to specifically influence organisms’ ability to persist and cope with urbanisation. However, these physiological systems often show mixed responses to urbanisation. Does this mean that some individuals, populations or species are resilient to the urban environmental challenges? Or is something missing from our analyses, leading us to erroneous conclusions regarding the impact of urbanisation? To understand the impact of urbanisation, I argue that a more integrated mechanistic and ecological approach is needed, along with experiments, in order to fully understand the physiological responses; without knowledge of their ecological and evolutionary context, physiological measures alone can be misinterpreted. Furthermore, we need to further investigate the causes of and capacity for individual plasticity in order to understand not only the impact of urbanisation, but also species resilience. I argue that abiotic and biotic urban factors can interact (e.g. pollution with micro- and macronutrients) to either constrain or relax individual physiological responses – and, thereby, plasticity – on a temporal and/or spatial scale, which can lead to erroneous conclusions regarding the impact of urbanisation.

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Section: Discussionmentioning

confidence: 99%

Urban ecophysiology: beyond costs, stress and biomarkers

Isaksson

2020

Journal of Experimental Biology

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“…Even if we could fully understand the mechanisms by which methylation induces or represses transcription, messenger RNAs undergo a great deal of post‐transcriptional processing that may selectively affect what portion of RNA is translated into proteins (Figure 1). Indeed, attempts to create aging and health “clocks” based on transcriptomic data have been only partially successful and have not reached the precision and predictivity of epigenetic clocks, although research in this field is still evolving (Solovev et al, 2020). Beyond protein translation itself, there are many additional factors that influence the aging proteome, including post‐translational protein changes (see Figure 2) such as post‐translational modifications, protein folding, protein aggregation, protein proteolysis (degradation), protein turnover, protein secretory phenotypes, and which proteins are released or shedded into biofluids (López‐Otín et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Even if we could fully understand the mechanisms by which methylation induces or represses transcription, messenger RNAs undergo a great deal of post-transcriptional processing that may selectively affect what portion of RNA is translated into proteins (Figure 1). Indeed, attempts to create aging and health "clocks" based on transcriptomic data have been only partially successful and have not reached the precision and predictivity of epigenetic clocks, although research in this field is still evolving (Solovev et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Proteomics in aging research: A roadmap to clinical, translational research

et al. 2021

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

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“…The challenges of molecular age prediction models include delineating the relationship between the chronological versus the biological age. Multi-omics methods such as combining DNA methylation, mRNA and miRNA markers together could improve the accuracy of age prediction models[129]. Finally, predictive biomarkers and analysis methods will need to be validated prior to implementation into the forensic field.…”

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confidence: 99%

Forensic transcriptome analysis using massively parallel sequencing

Haas

Neubauer

Salzmann

et al. 2021

Forensic Science International: Genetics

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Multi-omics approaches to human biological age estimation

Cited by 32 publications

References 85 publications

Urban ecophysiology: beyond costs, stress and biomarkers

Urban ecophysiology: beyond costs, stress and biomarkers

Proteomics in aging research: A roadmap to clinical, translational research

Forensic transcriptome analysis using massively parallel sequencing

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