No evidence for a link between childhood (6-10y) cellular aging and brain morphology (12y) in a preregistered longitudinal study

Animal studies show that early life environmental factors, such as stress and trauma, can have a significant impact on a variety of bodily processes, including cellular aging and brain development. However, whether cellular wear-and-tear effects are also associated with individual differences in brain structures in humans, remains unknown. In this pre-registered study in a community sample of children (N=94, Mean age=12.71 years), we prospectively investigated the predictive value of two markers of cellular aging in childhood (at age 6 and 10) for brain morphology in early adolescence (age 12). More specifically, we associated buccal cell telomere length and epigenetic age in childhood to individual differences in adolescent whole-brain grey matter volume (GMV) including volumes of three regions of interest that have been found to be sensitive to effects of early life stress (i.e. amygdala, hippocampus, (pre)frontal cortex -PFC). Multiple regression analyses revealed no significant associations between childhood cellular aging (at 6 and 10 years) and early adolescent brain morphology. Exploratory Bayesian analyses indicated moderate to strong evidence for the null-findings. These results suggest that although our sample is modest, the associations between middle childhood cellular aging and early adolescent brain morphology are, if they do exist, likely not particularly large in community children. Future work should investigate whether these effects are similarly absent in large samples, in samples with a higher risk profile and in samples characterized by different age ranges. Highlights (3-5) - Investigation of cellular aging in relation to brain morphology in a community sample (N=95) - Epigenetic aging and telomere shortening were not associated with brain structure - Exploratory Bayesian Analyses reveal moderate to strong evidence for null findings - No association was found between cellular aging and white matter volume

In sum, while there is accumulating evidence linking adverse early life events to both 95 cellular aging and brain morphology (Colich et al., 2020; Rebello et al., 2019), it remains 96 unclear whether signs of cellular aging can also be linked to brain morphology. Therefore, the 97 aim of the current preregistered study is to investigate potential associations between two 98 biomarkers of cellular aging (i.e. telomere length and epigenetic age), and brain structure at 99 age 12. Specifically, we will look at telomere length and epigenetic aging at ages 6 and 10, which reflect the cellular aging differences between individual, as well as at how they change al the 23% of the children that did not participate and the 77% that did (see Table 1).   The pace of epigenetic age acceleration between age 6 and age 10 was operationalised

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We used the Markov Chain Monte Carlo procedure in SPSS to impute data of 9 children who 225 were missing data from either the 6-year or 10-year measurement waves. The remaining 226 participant was missing data of more than one predictor and was excluded from further 227 analysis.

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The six biological variables (telomere length at age 6 and 10, telomere erosion 229 between age 6 and 10, epigenetic age at age 6 and 10, and epigenetic pace between age 6 and correlation was found between buccal cell count at age 10 and epigenetic pace between age 6 and 10 (0.577, p=<.001, df= 92). Therefore, a residual of epigenetic pace was calculated using 241 a regression of buccal cell count at age 10 on epigenetic pace. 242 243 2.3.2 MRI data pre-processing.

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Raw structural T1-weighted images were checked for anatomical abnormalities, movement 245 artefacts, and alignment to the anterior commissure. We performed the following pre-  To investigate the associations between accelerated cellular aging at age 6 and whole-brain 264 GMV, a whole-brain multiple regression analysis was performed in SPM12 including the predictors at age 6, that is telomere length and epigenetic age. Additionally, a second 266 multiple-regression analysis was performed including telomere erosion between 6 and 10 267 years, and epigenetic pace between 6 and 10 years, and whole-brain GMV at age 12 as 268 outcome variable, to investigate the association between the longitudinal changes of the 269 accelerated cellular aging markers and GMV. In both whole-brain multiple regressions, age, To exploratorily investigate the associations between accelerated cellular aging at age 10 and 285 whole-brain GMV, a whole-brain multiple regression analysis was performed in SPM12 286 including the biomarkers of cellular aging at age 10, that is telomere length and epigenetic 287 age.

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Additionally, to exclude the possibility that the biomarkers of accelerated cellular 289 aging are associated with brain regions that were not part of our a priori selection, all main analyses described above were repeated in an exploratory fashion with the following brain

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To explore whether accelerated cellular aging is linked to brain volume through a link 300 with WMV, two multiple regression analyses were performed. The first included the 301 predictors at age 6, that is telomere length and epigenetic age. The second analysis was 302 performed including telomere erosion between 6 and 10 years, and epigenetic pace between 6 303 and 10 years, and WMV at age 12 years as the outcome variable, to investigate the association 304 between the longitudinal changes of the accelerated cellular aging markers and WMV.

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Lastly, for all multiple regressions Bayesian analyses were performed, to quantify the 306 evidence in favor, or against, the regression models as compared to a null model. Results are 307 expressed as a Bayes factor, which represents the relative likelihood of one model compared 308 to another given the data and a prior expectation. This prior expectation was set as a default, for H1, and a bayes factor of 0 indicates no evidence for either one (Jeffreys, 1961 Figure 3). The whole-brain VBM analysis with telomere lengths and epigenetic age at 6 years did not With respect to telomere lengths and epigenetic age at 10 years of age, the whole-brain VBM 366 analysis did not yield any significant associations with these biomarkers and whole-brain 367 GMV (all corrected p-values above 0.998), nor with subregions of the brain thought to be 368 associated with early life adversity, i.e., the amygdala, hippocampus, and PFC.

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3.2.3 Changes in biomarkers of cellular age between 6 and 10 years of age.

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Regarding the changes in telomere length and epigenetic age between the age of 6 and 10, the 372 whole-brain VBM analysis did not yield any significant associations with whole-brain GMV To be able to quantify whether the frequentist absence of effects was indeed evidence in favor 392 of the null hypothesis, rather than an absence of precision or evidence either way, the main 393 analyses were tested using Bayesian analyses. These analyses yielded Bayes Factors 394 indicating a moderate to strong evidence for the null hypothesis (see Table 4).

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The current study investigated whether markers of cellular aging assessed in middle 411 childhood, namely telomere length and epigenetic age acceleration, were associated with 412 brain morphology in early adolescence in a low-risk sample. We hypothesized that shorter 413 telomere length and higher epigenetic age acceleration at age 6 and 10 would be associated 414 with smaller whole-brain grey matter, particularly in the three regions of interest (i.e. 415 amygdala, hippocampus, and PFC) at age 12. Contrary to our expectations, we found no 416 evidence for associations between the cellular aging markers and brain structure. These results 417 were supported by exploratory Bayesian analyses, revealing Bayes Factors indicating moderate to strong evidence for the null findings. Finally, exploratory analyses inspecting 419 associations between the two markers of cellular aging and both white matter as well as other 420 subregions of the brain, not previously described in relation to the topic, delivered null 421 findings as well.

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One explanation for these findings points to the fact that the neural effects were tested 423 two years after measuring cellular aging. Potentially, the associations between cellular aging 424 and brain morphometry are only short-lived. The brain develops rapidly and is known to be 425 vulnerable to environmental factors, particularly during its development in adolescence. It is 426 possible that cellular aging processes at ages 6 and 10 did lead to short-term changes in the 427 brain but that because of the brain's plasticity at these ages, potential temporary impacts of  Alternatively, it is possible that the effects of cellular aging processes on brain development 435 may be more permanent, as they could possibly be considered programming effects.

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Accordingly, a possible alternative explanation for our null-results could be that the period 437 from 6-10 years may be a period in which stress has less impact on the brain. Potentially, 438 stress early in life may impact cellular aging which in turn affects brain developmental 439 trajectories.

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Another explanation for our null-results is related to sensitivity of group versus 441 individual analyses; group-level analyses of alterations in brain structure may be less sensitive 442 than analyses that account for individual brain development. Early developmental studies focused on deterministic models of brain development, assuming brain development proceeds 444 via a prescribed blueprint that is innately specified in all individuals. Genome-wide 445 association studies have shown that volumetric brain changes are heritable, and associated 446 with substantial variability in brain volumes across different children of the same age (Brown,  sample. However, some limitations should also be acknowledged. First, cellular aging was 478 measured at ages 6 and 10, while brain morphology was measured at age 12 years. The lack 479 of cellular aging measures at age 12 could be considered a limitation, as it was not possible to 480 account for potential contemporary associations. A second potential limitation is that out of 481 the potential pool of 128 children that were eligible to participate in the 12-year measurement, 482 around 23% declined participation. However, because the cellular aging markers did not 483 differ between participating and non-participating children, this does not appear to be a 484 limitation that could have influenced the results. A final limitation is that while the markers 485 for cellular aging were assessed at two childhood ages, the whole-brain GMV were only 486 measured at 12 years, meaning we could not relate accelerated cellular aging to changes in 487 brain structure over time.

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In conclusion, we found no significant associations between childhood cellular aging (at 6 and 491 10 years) and adolescent brain morphology. Exploratory Bayesian analyses indicated moderate to strong evidence for the null-findings. These results point at the lack of a strong 493 relation between markers of cellular aging and brain volume during childhood. Future studies 494 might benefit from a longitudinal study design with cellular aging measures in early 495 development (younger ages), biological and brain measures at the same age, as well as 496 individual as opposed to group-level brain development trajectories. The data of this study is part of an ongoing longitudinal study of which the data is still 526 acquired and analyzed. Therefore, it cannot be made openly available in a public repository. individual. Individuals with shorter telomeres at age 6 than age 10 are depicted in dark blue, 733 and individuals with longer telomeres at age 6 than age 10 are depicted in light blue.