🧬 Aging Wiki

Senescence in tissue samples of humans with age-related diseases: A systematic review

6 min read

⚠️ Auto-extracted by Claude on 2026-06-25 — body claims are sourced exclusively from the published abstract (PubMed PMID 33819674) and Crossref metadata; full text is behind a paywall (ScienceDirect) with no PMC or Europe PMC open-access copy. Quantitative specifics from the body of the review (per-disease marker data, forest plots, individual study designs) are not available and have NOT been inferred. Do not rely on any claims beyond those explicitly sourced to the abstract. gap/no-fulltext-access

Tuttle et al. 2021 — Senescence in Human Age-Related Disease Tissues: Systematic Review

Systematic review. doi:10.1016/j.arr.2021.101334 · PMID 33819674. Published Ageing Research Reviews 2021; 68:101334 (epub April 2, 2021). Authors: Tuttle CSL and Luesken SWM (Royal Melbourne Hospital, University of Melbourne), Waaijer MEC (Leiden University Medical Center, Netherlands), Maier AB (Royal Melbourne Hospital; Vrije Universiteit Amsterdam; National University of Singapore). Funded by NHMRC (Australia). Full text not OA; verified against abstract + Crossref metadata only.

TL;DR

Tuttle et al. performed the first (to publication date) systematic review of evidence for senescent cells in human tissue samples obtained from people with age-related diseases. Searching three databases through September 2019 and screening 12,590 articles, they included 103 studies spanning 9 organ systems and 27 age-related diseases. The heart and respiratory system were the most investigated. Senescence was detected using 27 different markers, of which p16INK4a was the most commonly applied (used across 23 of 27 pathologies surveyed). The headline conclusion is that senescence marker expression is elevated in diseased human tissue, but that marker selection is inconsistent across tissue types — limiting cross-study comparisons. gap/no-fulltext-access — per-disease quantitative estimates, effect sizes, individual study quality ratings, and the specific disease list are available only in the full text.

Background and Scope

Senescent cells accumulate with age and have been implicated in multiple age-related pathologies via the Senescence-Associated Secretory Phenotype (SASP) — a proinflammatory, tissue-remodeling secretome 1. Prior reviews had summarized senescence biology in model organisms, but a structured survey of the human disease-tissue evidence base was lacking.

This review addresses two related questions:

  1. In which age-related diseases is there direct histological or molecular evidence of elevated senescence markers in human tissue?
  2. Which markers are being used, and how consistently?

Methods (Abstract-derived)

  • Databases searched: PubMed, Web of Science, EMBASE
  • Search period: Inception to 29 September 2019
  • Keywords: Terms related to ‘senescence’, ‘age-related diseases’, ‘biopsies’
  • Screening: 12,590 articles retrieved → 103 included
  • Inclusion criteria: Not explicitly stated in abstract; implied requirement for human tissue samples from patients with age-related conditions plus senescence marker measurement

Results (Abstract-derived)

Scope of coverage

DimensionCount
Organ systems covered9
Age-related diseases covered27
Studies included103
Senescence markers identified27 distinct markers

Most investigated organ systems

  1. Heart — 27 of 103 articles (~26%)
  2. Respiratory system — 18 of 103 articles (~17%)

The cardiovascular and respiratory dominance likely reflects the high disease burden, tissue accessibility (cardiac biopsies, bronchoalveolar lavage, lung resections), and independent interest in cardiac fibrosis and COPD as senescence-driven conditions.

Marker landscape

p16INK4a (CDKN2A) is the most frequently applied marker, appearing in 23 of 27 age-related pathologies surveyed — underscoring its status as the de-facto primary human senescence marker 2 3. However, the use of 27 distinct markers with inconsistent cross-tissue deployment means that studies using different markers in the same tissue cannot be directly compared, a major limitation of the literature as a whole.

Headline conclusion

“This review demonstrates that a higher expression of senescence markers are observed within disease pathologies. However, not all markers to detect senescence have been assessed in all tissue types.”

In plain terms: human disease tissues consistently show elevated senescence marker expression versus healthy controls or younger comparators, but the field lacks a standardized multi-marker panel applied uniformly — making it impossible to directly compare senescence burden across diseases or tissues from the existing literature.

Significance

This systematic review provides the most comprehensive pre-2020 synthesis of the human tissue senescence evidence base across age-related diseases. Together with cross-sectional aging surveys (e.g., idda-2020-senescent-markers-human-tissues), it establishes that:

  1. Senescent cells are a measurable feature of human age-related disease tissue — not merely a mouse-model artifact.
  2. The heart and lungs have the deepest evidence base; other organs are comparatively understudied.
  3. Marker standardization is the field’s primary methodological gap — 27 different markers with heterogeneous cross-tissue coverage prevents meta-analytic synthesis.

The review’s 2019 literature cutoff means it predates the dasatinib+quercetin human biopsy trials (Hickson 2019; Justice 2019), the SenNet consortium’s multi-organ single-cell work, and the multi-marker protein-level methodology introduced by Cherqui et al. 2025 cherqui-2025-senescence-burden-organs.

Limitations

  • Abstract-only access for this wiki entry. Per-disease marker quantification, individual study designs, quality assessment, and the full disease list are in the full text behind the paywall. gap/no-fulltext-access
  • Literature search cutoff September 2019. The review misses the dasatinib+quercetin senolytic human trials (Hickson 2019 published November 2019; Justice 2019 contemporaneous), the IDO inhibitor work, and all post-2019 multi-omics human senescence papers.
  • Marker heterogeneity. The authors themselves identify inconsistency across studies as a primary limitation. A systematic review of heterogeneous markers cannot produce pooled effect estimates.
  • Disease-tissue vs. healthy-aging distinction. By design, the review focuses on patients with age-related diseases — not normal aging populations. Cross-sectional age stratification within healthy donors (as in Idda 2020 1) is a complementary, not overlapping, evidence type.
  • No per-disease quantitative synthesis. Without a standardized marker and a meta-analytic pooling strategy, the review is essentially a catalog rather than an effect-size estimate.

Cross-references

  • cellular-senescence — primary hallmark page; this review provides the broadest human disease-tissue survey of senescence marker prevalence
  • sasp — SASP is the proposed mechanism linking senescent cell accumulation to the age-related pathologies surveyed here
  • p16-rb-pathway — p16INK4a is the most-used marker across the 27 pathologies in this review
  • p21 — p21CIP1 is one of the 27 markers surveyed; cross-tissue usage relative to p16 not determinable from abstract alone
  • idda-2020-senescent-markers-human-tissues — complementary cross-sectional IHC survey of normal aging (not disease) across 10 organs; Idda 2020 and this review together bracket the human evidence: normal aging accumulation + disease-tissue burden
  • cherqui-2025-senescence-burden-organs — more recent multi-marker single-cell quantification in mouse + human PBMCs; post-dates this review’s search cutoff

Footnotes

Footnotes

  1. idda-2020-senescent-markers-human-tissues · n=5 donors/organ/age-group · observational (cross-sectional IHC) · model: human FFPE tissue arrays; 10 organs; 3 age groups · gold OA PMC7093180; complementary normal-aging cross-sectional data ↩ ↩2

  2. krishnamurthy-2004-ink4a-arf-aging-biomarker · doi:10.1172/JCI22475 · PMID 15520862 · Krishnamurthy J et al. · J Clin Invest 2004;114(9):1299–1307 · in-vivo (rodent multi-tissue) · Ink4a/Arf as multi-tissue aging biomarker; one of the primary papers establishing p16INK4a as the field-standard marker ↩

  3. ressler-2006-p16-human-skin-biomarker · doi:10.1111/j.1474-9726.2006.00231.x · PMID 16911562 · Ressler S et al. · Aging Cell 2006;5(5):379–389 · observational · model: human skin biopsies stratified by age · p16INK4a as robust in-vivo biomarker of cellular aging in human skin; key validation paper for p16 as human marker ↩

Graph View

Backlinks