Phenotype‐environment mismatch due to epigenetic inheritance? Programming the offspring's epigenome and the consequences of migration

Willführ, Kai P.; Myrskylä, Mikko

doi:10.1002/ajhb.22362

Cited by 5 publications

(6 citation statements)

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“…Thus, why, and as well as whether, a case of developmental plasticity turns out to be adaptive will depend on the details of the biology of the organism. It is not a surprise, for example, that the 'mismatch' fitness crossover predicted by informational ADP models is not empirically ubiquitous [38,42]. Moreover, it is our impression that somatic state-based hypotheses have been neglected.…”

Section: Discussionmentioning

confidence: 99%

“…(Online version in colour. ) rspb [26,[38][39][40][41][42]. However, the fitness crossover sought was not the one shown in figure 2.…”

Section: Empirical Tests Of Adaptive Developmental Plasticitymentioning

confidence: 99%

“…Thus, the required variation should be identifiable. A number of recent empirical studies have attempted to establish whether there is a fitness crossover [26,[38][39][40][41][42]. However, the fitness crossover sought was not the one shown in figure 2.…”

Section: Empirical Tests Of Adaptive Developmental Plasticitymentioning

confidence: 99%

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Adaptive developmental plasticity: what is it, how can we recognize it and when can it evolve?

2015

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Developmental plasticity describes situations where a specific input during an individual's development produces a lasting alteration in phenotype. Some instances of developmental plasticity may be adaptive, meaning that the tendency to produce the phenotype conditional on having experienced the developmental input has been under positive selection. We discuss the necessary assumptions and predictions of hypotheses concerning adaptive developmental plasticity (ADP) and develop guidelines for how to test empirically whether a particular example is adaptive. Central to our analysis is the distinction between two kinds of ADP: informational, where the developmental input provides information about the future environment, and somatic state-based, where the developmental input enduringly alters some aspect of the individual's somatic state. Both types are likely to exist in nature, but evolve under different conditions. In all cases of ADP, the expected fitness of individuals who experience the input and develop the phenotype should be higher than that of those who experience the input and do not develop the phenotype, while the expected fitness of those who do not experience the input and do not develop the phenotype should be higher than those who do not experience the input and do develop the phenotype. We describe ancillary predictions that are specific to just one of the two types of ADP and thus distinguish between them.

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Section: Discussionmentioning

confidence: 99%

“…(Online version in colour. ) rspb [26,[38][39][40][41][42]. However, the fitness crossover sought was not the one shown in figure 2.…”

Section: Empirical Tests Of Adaptive Developmental Plasticitymentioning

confidence: 99%

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Adaptive developmental plasticity: what is it, how can we recognize it and when can it evolve?

2015

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“…There are trans-generational effects in humans [9]–[11], but the functional interpretation of these effects is unclear. A study examining the historical population of the St. Lawrence Valley in Quebec, Canada compared the mortality of children that were conceived under different pathogenic environments based on region of residence and found no evidence of functional effects or epigenetic inheritance [12]. However, most biological response mechanisms are cue- and context -specific.…”

Section: Introductionmentioning

confidence: 99%

Disease Load at Conception Predicts Survival in Later Epidemics in a Historical French-Canadian Cohort, Suggesting Functional Trans-Generational Effects in Humans

Willführ

Myrskylä

2014

PLoS ONE

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ObjectiveFunctional trans-generational and parental effects are potentially important determinants of health in several mammals. For humans, the existing evidence is weak. We investigate whether disease exposure triggers functional trans-generational response effects among humans by analyzing siblings who were conceived under different disease loads, and comparing their mortality in later epidemics. Under functional trans-generational response mechanisms, we expect that those who were conceived under high pathogenic stress load will have relatively low mortality during a later epidemic.MethodsWe use data from the Registre de la Population du Québec Ancien, which covers the historical population living in St. Lawrence Valley, Québec, Canada. Children born in 1705–1724 were grouped according to their exposure during conception to the measles 1714–15 epidemic. The 1714–15 epidemic was followed by two mortality crises in 1729–1734. The cause of the first crises in 1729 is not exactly known. The second crisis in 1732 was caused by a smallpox epidemic. Using proportional hazard Cox regression models with multivariate adjustment and with fixed-effects approach that compare siblings, we analyze whether mortality in 1729–1734 is affected by exposure to the 1714–15 epidemic.ResultsChildren who were conceived during the peak of the measles epidemic of 1714–15 exhibited significantly lower mortality during the 1729–1734 crisis than those who were born before the 1714–15 epidemic (mortality hazard ratio 0.106, p<.05 in multivariate adjusted models; 0.142 p<.1 in sibling comparison models).ConclusionsThe results are consistent with a trans-generational mechanism that functionally responds to pathogen stress and suggest that early disease exposure may be protective later in life. Alternative explanations for the mortality patterns are discussed and shown to be problematic.

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“…The literature also sometimes uses the term mismatch to refer to a mismatch between actual adult environment and the phenotype chosen based on expected adult environment[68]. We are referring to the mismatch between developmental environment and adult environment, consistent with our definition in the Mathematical Definitions and Predictions section 9.…”

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confidence: 99%

Conceptual and analytical approaches for modeling the developmental origins of inequality

Malani

Rosenbaum

Alberts

et al. 2022

Preprint

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Early life conditions can have profound effects on individual health, longevity, and biological fitness. Two classes of hypotheses are used to explain the evolutionary origins of these effects: developmental constraints (DC) hypotheses, which focus on the deleterious effects of low-quality early-life environments, and predictive adaptive response (PAR) models, which focus on organisms predictions about their adult environment, phenotypic adaptations based on that prediction, and the deleterious consequences of incorrect predictions. Despite their popularity, these ideas remain poorly defined. To remedy this, we provide mathematical definitions for DC, PARs, and related concepts, and develop statistical tests derived from these definitions. We use simulations to demonstrate that PARs are more readily detected by tests based on quadratic regressions than by tests based on more commonly used interaction regression models. Specifically, quadratic regression-based tests on simulated data yield 90.7% sensitivity and 71.5% specificity in detecting PARs, while interaction-based tests yield sensitivity and specificity roughly equal to chance. We demonstrate that the poor performance of interaction models stems from two problems: first, they are mathematically incapable of detecting a central prediction of PAR, and second, they conceptually conflate PARs with DC. Our results emphasize the value of formal statistical modeling to reveal the theoretical underpinnings of verbal and visual models, and their importance for helping resolve conflicting and ambiguous results in this field of research. We conclude by providing recommendations for how researchers can make use of explicit definitions and properly-aligned visualizations and statistical tests to make progress in this important research area.

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Phenotype‐environment mismatch due to epigenetic inheritance? Programming the offspring's epigenome and the consequences of migration

Cited by 5 publications

References 62 publications

Adaptive developmental plasticity: what is it, how can we recognize it and when can it evolve?

Adaptive developmental plasticity: what is it, how can we recognize it and when can it evolve?

Disease Load at Conception Predicts Survival in Later Epidemics in a Historical French-Canadian Cohort, Suggesting Functional Trans-Generational Effects in Humans

Conceptual and analytical approaches for modeling the developmental origins of inequality

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