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Relationship: 2205

Title

A descriptive phrase which clearly defines the two KEs being considered and the sequential relationship between them (i.e., which is upstream, and which is downstream). More help

Decrease, Cell proliferation leads to Decrease, Growth

Upstream event

The causing Key Event (KE) in a Key Event Relationship (KER). More help

Decrease, Cell proliferation

Downstream event

The responding Key Event (KE) in a Key Event Relationship (KER). More help

Decrease, Growth

Key Event Relationship Overview

The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes.Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE. More help

AOPs Referencing Relationship

AOP Name	Adjacency	Weight of Evidence	Quantitative Understanding	Point of Contact	Author Status	OECD Status
Uncoupling of oxidative phosphorylation leading to growth inhibition via decreased cell proliferation	adjacent	Moderate	Moderate	You Song (send email)	Open for citation & comment	WPHA/WNT Endorsed
Mitochondrial ATP synthase antagonism leading to growth inhibition (1)	adjacent			You Song (send email)	Under development: Not open for comment. Do not cite
Mitochondrial complex III antagonism leading to growth inhibition (1)	adjacent			You Song (send email)	Under development: Not open for comment. Do not cite
Uncoupling of oxidative phosphorylation leading to growth inhibition via glucose depletion	adjacent			You Song (send email)	Under development: Not open for comment. Do not cite	Under Development
Excessive reactive oxygen species leading to growth inhibition via oxidative DNA damage	adjacent			You Song (send email)	Under development: Not open for comment. Do not cite
Excessive reactive oxygen species leading to growth inhibition via protein oxidation and cell cycle disruption	adjacent			You Song (send email)	Under development: Not open for comment. Do not cite
Excessive reactive oxygen species leading to growth inhibition via fatty acid oxidation and reduced cell proliferation	adjacent			You Song (send email)	Under development: Not open for comment. Do not cite
Increase in reactive oxygen species leading to growth inhibition via oxidative DNA damage and cell cycle disruption	adjacent	High	Moderate	You Song (send email)	Under development: Not open for comment. Do not cite	Under Development
Increase in reactive oxygen species leading to growth inhibition via lipid peroxidation and decreased cell proliferation	adjacent	High	Moderate	You Song (send email)	Under development: Not open for comment. Do not cite	Under Development
Increase in reactive oxygen species leading to growth inhibition via protein oxidation and decreased cell proliferation	adjacent	High	Moderate	You Song (send email)	Under development: Not open for comment. Do not cite	Under Development

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) that help to define the biological applicability domain of the KER.In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER. More help

Term	Scientific Term	Evidence	Link
zebrafish	Danio rerio	High	NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help

Sex	Evidence
Unspecific	High

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER. More help

Term	Evidence
Embryo	High

Key Event Relationship Description

Provides a concise overview of the information given below as well as addressing details that aren’t inherent in the description of the KEs themselves. More help

This key event relationship describes reduced cell proliferation (cell growth, division or a combination of these) leading to reduced tissue, organ or individual growth.

Evidence Collection Strategy

Include a description of the approach for identification and assembly of the evidence base for the KER. For evidence identification, include, for example, a description of the sources and dates of information consulted including expert knowledge, databases searched and associated search terms/strings. Include also a description of study screening criteria and methodology, study quality assessment considerations, the data extraction strategy and links to any repositories/databases of relevant references.Tabular summaries and links to relevant supporting documentation are encouraged, wherever possible. More help

Update - non-endorsed (by You Song, 05/10/2026)

The evidence for this KER was collected through a manual review of the published literature, without the use of AI-based tools. Canonical knowledge on the dependence of tissue and organism size on cell number was taken from the review literature (Conlon and Raff, 1999). Studies reporting both cell proliferation and growth in the same experimental system were identified for empirical support; because cell proliferation is typically measured in vitro and growth in vivo, few such studies exist (Bestman et al., 2015). Literature on mathematical models describing the relationship between cell proliferation and tissue growth was reviewed for quantitative understanding (Binder et al., 2008; Mosca et al., 2018; Jarrett et al., 2018). No formal study quality assessment was performed.

Evidence Supporting this KER

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help

The overall evidence supporting Relationship 2205 is considered moderate.

Biological Plausibility

Addresses the biological rationale for a connection between KEupstream and KEdownstream. This field can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured. More help

The biological plausibility of Relationship 2205 is considered high.

Rationale: The biological structural and functional relationship between cell proliferation and growth is well established. It is commonly accepted that the size of an organism, organ or tissue is dependent on the total number and volume of the cells it contains, and the amount of extracellular matrix and fluids (Conlon 1999). Impairment to cell proliferation can logically affect tissue and organismal growth.

Empirical Evidence

Provides specific (citable) evidence that supports the idea of a change in the upstream KE (KEupstream) leading to, or being associated with, a subsequent change in the downstream KE (KEdownstream), assuming the perturbation of KEupstream is sufficient. More help

The empirical support of Relationship 2205 is considered low.

Rationale: Because cell proliferation is typically measured in vitro, while growth of an organism is measured in vivo, few studies have measured both in the same experiment. There is one zebrafish study reporting concordant relationship between reduced cell proliferation and embryo growth with some inconsistencies (Bestman 2015).

Uncertainties and Inconsistencies

Addresses inconsistencies or uncertainties in the relationship including the identification of experimental details that may explain apparent deviations from the expected patterns of concordance. More help

In zebrafish embryos exposed to 2,4-DNP, significant growth inhibition (AO), as indicated by whole embryo length, caudal primary (CaP) motor neuron axons and otic vesicle length (OVL) ratio after 21h, somite width and eye diameter after 45h exposure was identified, after 21h, whereas a non- significant reduction in cell proliferation was observed (Bestman 2015).

Known modulating factors

This table captures specific information on the MF, its properties, how it affects the KER and respective references.1.) What is the modulating factor? Name the factor for which solid evidence exists that it influences this KER. Examples: age, sex, genotype, diet 2.) Details of this modulating factor. Specify which features of this MF are relevant for this KER. Examples: a specific age range or a specific biological age (defined by...); a specific gene mutation or variant, a specific nutrient (deficit or surplus); a sex-specific homone; a certain threshold value (e.g. serum levels of a chemical above...) 3.) Description of how this modulating factor affects this KER. Describe the provable modification of the KER (also quantitatively, if known). Examples: increase or decrease of the magnitude of effect (by a factor of...); change of the time-course of the effect (onset delay by...); alteration of the probability of the effect; increase or decrease of the sensitivity of the downstream effect (by a factor of...) 4.) Provision of supporting scientific evidence for an effect of this MF on this KER. Give a list of references. More help

Update - non-endorsed (by You Song, 05/10/2026)

Modulating factor	Details	Effects on the KER	References
Cell size	Cell volume, which can change independently of cell number	An increase in cell size can partly compensate for fewer cells, so a given decrease in proliferation produces a smaller decrease in tissue or organ growth. A decrease in cell size adds to the effect.	Conlon and Raff, 1999
Extracellular matrix and fluid content	Amount of extracellular matrix and fluids in the tissue	Tissue and organ size depend on these components as well as on cell number, so growth can change independently of proliferation.	Conlon and Raff, 1999
Cell death	Rate of cell loss in the tissue	Net cell number depends on the balance between proliferation and cell loss. Increased cell death adds to the effect of reduced proliferation, and decreased cell death can offset it.	Conlon and Raff, 1999
Growth mode of the organism	Animals and plants: growth by cell division and by cell expansion. Unicellular algae: population growth by cell division	In plants, tissue growth results from both cell division and cell expansion, so reduced division can be partly offset by expansion. In unicellular algae, population growth is achieved through cell proliferation, so the relationship is direct.	Mosca et al., 2018 (plants)

Quantitative Understanding of the Linkage

Captures information that helps to define how much change in the upstream KE, and/or for how long, is needed to elicit a detectable and defined change in the downstream KE. More help

The quantitative understanding of Relationship 2205 is moderate.

Rationale: Multiple mathematical models describing the quantitative relationships between cell proliferation and tissue growth exist for both animals (Binder 2008) and plants (Mosca 2018). There are also numerous models that are specifically developed for predicting tumor growth based on the proliferation rate (Jarrett 2018).

Response-response Relationship

Provides sources of data that define the response-response relationships between the KEs. More help

Update - non-endorsed (by You Song, 05/10/2026)

Tissue, organ, and organism size depend on the total number and volume of cells and on the amount of extracellular matrix and fluids (Conlon and Raff, 1999). A decrease in proliferation therefore reduces growth in proportion to the resulting loss of cell number, modified by changes in cell size and matrix content. This relationship has been formalized in mathematical models of proliferative tissue growth in animals (Binder et al., 2008) and of tissue growth and cell division in plants (Mosca et al., 2018), and numerous models predict tumor growth from the rate of proliferation (Jarrett et al., 2018). These models describe growth as a function of proliferation rate, but they have not been fitted to data on stressor-induced decreases in proliferation, so the precision with which a measured decrease in proliferation predicts a decrease in growth has not been quantified. The only study that measured both events in the same experiment, in zebrafish embryos exposed to 2,4-DNP, showed that growth was significantly inhibited after 21 h while the reduction in cell proliferation was not significant (Bestman et al., 2015), so the relationship cannot be quantified from that study.

Time-scale

Information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). More help

Update - non-endorsed (by You Song, 05/10/2026)

The time-scale of this KER has not been quantified. Growth is the cumulative result of cell divisions, so effects on growth are expected to lag behind effects on proliferation, with the lag depending on the cell-cycle length and growth rate of the system. In the zebrafish study, growth inhibition was detected after 21 h, whereas the reduction in cell proliferation was not yet significant (Bestman et al., 2015). Studies that measure both events at a single time point cannot resolve their temporal order.

Known Feedforward/Feedback loops influencing this KER

Define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits. More help

Update - non-endorsed (by You Song, 05/10/2026)

Modulating factor	Details	Effects on the KER	References
Cell size	Cell volume, which can change independently of cell number	An increase in cell size can partly compensate for fewer cells, so a given decrease in proliferation produces a smaller decrease in tissue or organ growth; a decrease in cell size adds to the effect.	Conlon and Raff, 1999
Extracellular matrix and fluid content	Amount of extracellular matrix and fluids in the tissue	Tissue and organ size depend on these components as well as on cell number, so growth can change independently of proliferation.	Conlon and Raff, 1999
Cell death	Rate of cell loss in the tissue	Net cell number depends on the balance between proliferation and cell loss; increased cell death adds to the effect of reduced proliferation, and decreased cell death can offset it.	Conlon and Raff, 1999
Growth mode of the organism	Growth by cell division and by cell expansion (plants); population growth by cell division (unicellular algae)	In plants, reduced division can be partly offset by cell expansion; in unicellular algae, population growth is achieved through cell proliferation, so the relationship is direct.	Mosca et al., 2018

Domain of Applicability

A free-text section of the KER description that the developers can use to explain their rationale for the taxonomic, life stage, or sex applicability structured terms. More help

Taxonomic applicability

Relationship 2205 is considered applicable to all eukaryotes (both unicellular and multicellular), as growth (or population growth of alga) is well known to be achieved through cell proliferation in animals, plants and some microorganisms.

Sex applicability

Relationship 2205 is considered applicable to both all sexes, as cell proliferation leading to growth is a fundamental process and not sex-specific.

Life-stage applicability

Relationship 2205 is considered applicable to all life stages, as cell proliferation leading to growth is essential for maintaining basic biological processes throughout an organism’s life.

References

List of the literature that was cited for this KER description. More help

Bestman JE, Stackley KD, Rahn JJ, Williamson TJ, Chan SS. 2015. The cellular and molecular progression of mitochondrial dysfunction induced by 2,4-dinitrophenol in developing zebrafish embryos. Differentiation 89:51-69. DOI: 10.1016/j.diff.2015.01.001.

Binder BJ, Landman KA, Simpson MJ, Mariani M, Newgreen DF. 2008. Modeling proliferative tissue growth: a general approach and an avian case study. Phys Rev E Stat Nonlin Soft Matter Phys 78:031912. DOI: 10.1103/PhysRevE.78.031912.

Conlon I, Raff M. 1999. Size control in animal development. Cell 96:235-244. DOI: 10.1016/s0092-8674(00)80563-2.

Jarrett AM, Lima EABF, Hormuth DA, McKenna MT, Feng X, Ekrut DA, Resende ACM, Brock A, Yankeelov TE. 2018. Mathematical models of tumor cell proliferation: A review of the literature. Expert Review of Anticancer Therapy 18:1271-1286. DOI: 10.1080/14737140.2018.1527689.

Mosca G, Adibi, M., Strauss, S., Runions, A., Sapala, A., Smith, R.S. 2018. Modeling Plant Tissue Growth and Cell Division. In Morris R., ed, Mathematical Modelling in Plant Biology. Springer, Cham.