Developmental Psychobiology

Animal vocalisations can convey information about external events, but whether this goes beyond reflecting the emotional state elicited by these events is debated. To explore this, we studied the acoustic structure of common marmoset (Callithrix jacchus) phee (long-distance contact) and ek (alert/mobbing) calls produced in five treatments varying in the emotional valence and arousal they elicit (internal state), as well as food and social context (external events). We measured changes in arousal via nasal temperature and analysed both basic acoustic parameters and Mel-frequency cepstral coefficients (MFCCs) of the calls. Support Vector Machines combined with Linear Mixed effect models revealed that phee calls encode both external events and internal states, while eks reflected predominantly arousal. Notably, an acoustic signature related to food context was present in phees both when provided (positive valence) and teased with highly preferred food items (negative valence), and even when food was not physically present (food call playback treatment). This suggests marmoset long-distant phee calls encode external information beyond emotional arousal and valence, and independently of the presence of an immediately triggering stimulus.

In a wide variety of animals, developmental crowding results in adults with smaller bodies. The crowding effect on body size in Drosophila melanogaster is canonically attributed to heightened competition for nutrition. However, whether other consequences of crowding also contribute to its effect on size remains an open question. We tested the relative contributions of nutritional competition, oxygen availability, and larval-generated metabolites to the crowding effect on size. We found that while nutrition explains most of the variation in body size due to crowding, oxygen also contributes in a sex- and nutrition-dependent manner. We found no evidence that larval-generated chemicals affect body size. These data confirm a widely suspected but untested role of nutrition in producing the crowding effect on size in D. melanogaster, while revealing an unexpected role of oxygen, and raise the possibility that behavior may be a mediator of density-dependent plasticity. Research HighlightsWe found that both nutrition and oxygen mediate the crowding effect on size in Drosophila melanogaster.

Reported perceptual differences in autism may arise from reduced use of prior context to shape incoming sensory input. Speech perception provides a critical test of this account because stable perception requires listeners to integrate variable acoustic signals with contextual expectations. This study examined context-dependent modulation of speech encoding in autistic and non-autistic adults using the frequency-following response (FFR), a neurophysiological measure of phase-locked auditory encoding. Participants heard English intonational pitch contours presented in repetitive and variable contexts while EEG was recorded. Principal component analysis of FFR metrics yielded components indexing neural encoding fidelity and timing. Non-autistic participants showed enhanced encoding fidelity in more predictable contexts, whereas autistic participants showed reduced context-dependent modulation. Neural encoding timing also showed divergent context effects across groups, suggesting altered balance between feedback-based predictive mechanisms and locally driven adaptation processes. Within the autistic group, greater context-related modulation of encoding fidelity was associated with lower ADOS-2 Social Affect severity but poorer speech-in-noise perception, suggesting that the functional impact of contextual modulation depends on input reliability and task demands. These findings indicate that context-dependent modulation of speech encoding is altered in autism and may contribute to individual differences in auditory and social-communicative function.

Vocalizations are increasingly proposed as indicators of affective state in animal welfare research. Yet many studies assign context-derived affective valence to vocalizations and then classify these using machine learning according to those context-derived labels. This circular dependence makes it unclear whether successful classification reflects affective state itself, broader contextual or acoustic differences, or the interpretive categories imposed by the task. Therefore, we examined human organization of pig vocalizations using free-classification and forced-choice tasks, and compared these patterns with acoustic structure recovered by convolutional neural network models. In a free-classification task, 224 participants sorted 2,192 pig vocalizations into self-defined categories. Next, in two forced-choice tasks, 159 participants recruited in a second wave classified vocalizations using predefined context and valence categories. Free classification revealed reproducible but broad perceptual structure rather than recovery of discrete recording contexts. Participant-generated labels for pig vocalizations were predominantly descriptive and spontaneous valence-related labeling was limited (19.6%) yet primarily negative. Forced-choice classification of recording context was weak (8.0% exact accuracy) and showed only slight agreement with source contexts. Valence judgments were more structured (60.1% exact accuracy), but agreement with the valence categories used to characterize the recording contexts was modest and largely driven by highly aversive situations such as castration, restraint, fighting, and crushing. After excluding pig vocalizations from these contexts, agreement with context-associated valence categories disappeared. Human-derived perceptual structure closely corresponded to convolutional neural network embedding spaces, indicating that human listeners and machine-learning models recovered similar acoustic organization. These findings suggest that pig vocalizations contain robust and recoverable acoustic organization, but that this organization only partially aligns with the contextual and valence frameworks commonly used to interpret it. More broadly, the results highlight a distinction between recovering acoustic structure and establishing its biological meaning, with implications for affective research and animal welfare assessment.

Objective: Pediatric epilepsy patients undergoing stereo-electroencephalography (sEEG) for ictal onset evaluation provide a rare window to study the developing brain. While methodological frameworks for task-based sEEG research are well-established in adults, pediatric-specific guidance remains underdeveloped. Furthermore, many pediatric epilepsy patients have comorbidities that might typically exclude them from participating in research. We examine factors that influence research participation and discuss considerations for conducting sEEG research in children. Methods: Here, we present a retrospective analysis of task-based research participation patterns from an NIH-funded study of speech and language representations (1R01DC018579) in 66 patients (ages 4-24) undergoing sEEG monitoring at Texas Children's Hospital to determine whether specific comorbidities influenced research participation. Results: Eighty-nine percent (n=66) of patients approached for consent agreed to participate in the study. Despite high rates of comorbidities including neurocognitive disorder (66.67%), language delay (31.75%), global developmental delay (23.81%), mood disorders (33.33%), ADHD (46.03%), autism spectrum disorder (14.29%) or other cognitive/intellectual disabilities (36.51%), all participants engaged in at least one task. While the majority of these diagnoses did not appear to influence subject participation, global developmental delay was associated with a significant reduction in time spent on active tasks. Discussion: Despite high prevalence of neuropsychological comorbidities among participants, our evidence suggests that these participants contribute meaningfully to studies investigating important developmental questions. We suggest strategies for tailoring task-based research to accommodate the unique needs of individuals in this population. Such practices are important for ensuring that research studies reflect the true diversity of the population.

Bayesian accounts of autism propose that perception is less influenced by prior expectations and more strongly driven by incoming sensory information in autistic than non-autistic individuals, with this altered balance cascading through the cognitive hierarchy to also influence higher cognitive functions. However, empirical support for these accounts remains mixed. Previous work has mostly tested these ideas in the context of objective environmental statistics, but recent work suggests that it may be subjective experience of structure, rather than structure itself, that shapes perceptual processing. Characterising these subjective experiences in autistic individuals is therefore crucial for understanding predictive processing in autism. In the present study, we thus examined subjective experience of statistical structure in autistic and non-autistic adults and tested how this experience relates to perceptual decisions. Participants were exposed to statistical regularities between action cues and visual stimuli (shapes), and we measured their speed and accuracy in reporting which shape they had seen. At the end of the study, participants were asked to estimate the probability and rate their surprise for each action-shape combination. Autistic and non-autistic participants showed similar subjective probability and surprise ratings and a comparable relationship between these ratings and perceptual decisions. Across participants, subjective ratings explained perceptual decisions better than objective structure. Together, these findings show that autistic and non-autistic adults experience statistical structure similarly, with these experiences exerting a similar influence on perceptual decisions - therefore suggesting that subjective experience plays a comparable role in predictive processing in autistic and non-autistic adults.

Stress involves coordinated central and peripheral processes that unfold dynamically and can be assessed through brain, autonomic, endocrine, and subjective measures. Centrally, acute stress has been linked to altered functional connectivity, particularly in the salience (SN), frontoparietal networks (FPN), and default mode networks (DMN). Here, we used cortical gradients to characterize stress-related reconfiguration in macroscale functional space and assessed their relation to peripheral stress measures. We performed secondary analyses on data from 67 young males completing the Trier Social Stress Test or a control task with resting-state fMRI before and after, concurrent peripheral (autonomic, endocrine) and subjective measures. To assess region- and network-specific changes in functional organization, we derived eccentricity and within- and between-network dispersion for the first three cortical gradients. Acute stress was associated with selective gradient reconfigurations in the right ventral prefrontal cortex and left insula and with increased SN-DMN and SN-FPN dispersion, indicating DMN and FPN decoupling from the SN. Although no associations with peripheral or subjective stress measures survived multiple-comparison correction, nominal effects suggested partly distinct links of saliva cortisol with local gradient changes and HRV with network-level reconfiguration. Together, these findings show that acute stress selectively reconfigures macroscale cortical organization.

The cortisol awakening response (CAR) marks the transition from rest to wake phase by a sharp increase in cortisol levels upon awakening in the morning. This increase may assist in cognitive and behavioral awakening, but its function is not fully understood yet. In this pilot study we aimed to provide first data on the influence of immune system activity on the CAR. Thereby, a within-subject analysis approach was applied to avoid confounding by between-subject bias and improve inference of the results. Three healthy subjects collected their overnight urine for analysis of neopterin (Th1 immune activation marker) and sampled saliva at 0, 30, and 45 minutes after awakening in the morning for cortisol determination and CAR estimation. Additionally, subjects wore an EEG-headband overnight for objective determination of the awakening timepoint. Random-effects models were computed to estimate the effect of overnight neopterin on the CAR. There was a significant positive effect of overnight neopterin levels on the CAR, indicating that overnight Th1 immune activation may predict the dynamic increase of cortisol in the morning, with higher immune levels leading to a stronger CAR. These results provide first evidence for the immunological awakening hypothesis and a potential role of the CAR in the maintenance of circadian immune rhythms, but given the small number of participants, findings should be interpreted as exploratory.

Obesity arises from interactions between several factors including physiology, environment and genes. Studies in humans have revealed that up to 70% of overweight and obesity can be attributed to biological and genetic factors. Thus, rodent models that capture innate susceptibility or resistance to obesity have been invaluable for disentangling inherent drivers of obesity from neurobiological alterations that occur in response to consumption of obesogenic foods and/or increased adiposity. For example, studies of rats selectively bred for their propensity vs resistance to diet-induced weight gain (DIO and DR) have uncovered differences in hypothalamic circuits involved in leptin signaling and revealed relationships between susceptibility to obesity and motivational response to food cues, as well as inherent and diet-induced alterations in mesocorticolimbic systems that differ between these populations. Maintaining selectively bred lines in a closed breeding population requires the periodic introduction of new genes to avoid inbreeding. Here we describe a process for maintaining these lines, characterize key phenotypes across the selection process and verify weight gain and obesity phenotypes in the resulting colony. In addition, given the central role of the striatum in motivation for food, we examined basal striatal function and food motivation in these refreshed lines using whole-cell patch clamping and instrumental procedures. Key weight and metabolic phenotypes were maintained in the resulting colony, as was enhanced motivation for food in obesity prone rats. This provides a strong basis for examination of interactions between genes, environment and neurobehavioral plasticity that promote weight gain and obesity.

Globally, 60% of the population has experienced at least one type of adversity (e.g., emotional abuse, bullying) across infancy, childhood, and adolescence. Such experiences have been linked to an increased risk for mental health disorders. Changes in brain structure following experiences of childhood adversity have been hypothesised to be a mechanistic pathway explaining later mental health issues. However, to understand how changes in brain structure might mediate the effects of adversity, it is essential to identify which underlying neuronal processes may be affected by different types of adverse experiences. A key open question is whether grey or white matter is more vulnerable to adversity, as these two structures reflect distinct neurobiological mechanisms. This study investigated whether differences in trajectories of grey and white matter development during adolescence can be explained by exposure to different types of adversity. We applied the Adverse Adolescent Experiences Framework (Pollmann et al., 2025) categorising adversity into four levels: Intrapersonal (e.g., accidents), Caregiver (e.g., emotional neglect), Peer (e.g., bullying), and Community (e.g., neighbourhood safety). Exposure to each of the four factors was estimated through principal components analyses. We analysed two large longitudinal datasets: the Adolescent Brain Cognitive Development study (~12,000 adolescents measured at ages 10, 12, and 14) and the IMAGEN study (~1,400 adolescents measured at ages 14, 19, and 22). Using latent growth curve models, we captured individual differences in brain development by estimating baseline levels (intercepts) and rates of change (slopes) for total grey matter volume and mean white matter fractional anisotropy. In both cohorts, we found significant interindividual variability in baseline levels and rates of change for both grey matter volume and fractional anisotropy. Caregiver, Peer, and Community adversities were negatively associated only with the intercepts of grey matter volume and white matter fractional anisotropy. Importantly, associations differed between grey and white matter. In ABCD, Peer and Community adversities were more strongly associated with grey matter volume intercepts. In contrast, in IMAGEN, Caregiver, Peer and Community adversities were more strongly linked to white matter fractional anisotropy intercepts. This suggests that adversity has unique associations with grey and white matter, rather than exerting a uniform influence on brain structure. By demonstrating that different environments generate distinct biological associations with brain maturation, this work underscores the need to consider both grey and white matter when assessing the neurodevelopmental pathways to outcomes across the lifespan.

Early-life adversity durably alters neural development through complex mother-offspring interactions whose underlying mechanisms remain poorly understood. We investigated how neonatal maternal separation (NMS) affects the large repertoire of maternal behaviors and subsequently influences spinal nociceptive circuit development and pain responses in rat offspring. Rat dams underwent NMS from postnatal day 2 (P2) to P12, 3h/day, and maternal behaviors were assessed before and after the separation period. These behaviors were compared to those of control (non-separated) dams. Offspring spinal cord and dorsal root ganglia were analyzed at P14 and P24 for several neurotrophic, glutamatergic, and GABAergic gene expression patterns. Offspring nociceptive sensitivity was also assessed at P24. NMS induced increased maternal behaviors (including longer arched-back nursing, higher nest occupancy, and better pup retrieval efficiency), alongside reduced self-care behaviors. These behavioral adaptations were correlated with spinal gene reprogramming in offspring, characterized by a biphasic developmental pattern. At P14, we observed elevated neurotrophic signaling alongside increased GABAergic and glutamatergic markers. By P24, neurotrophic factors decreased while compensatory changes emerged, yet persistent excitatory-inhibitory imbalances remained evident. Parallel to these results, NMS rats also showed mechanical and thermal hot hypersensitivity at P24. These findings reveal that despite apparent maternal behavioral compensation following NMS, offspring exhibit neurotrophic-driven developmental dysregulation resulting in persistent spinal circuit alterations. The disconnect between maternal behavioral normalization and sustained molecular changes suggests that early separation stress triggers enduring neurobiological cascades independent of ongoing maternal care quantity, with long-term consequences for sensory processing and pain sensitivity.

Alcohol drinking motives vary among individuals and shape experiences and beliefs about alcohol, influencing the processing of alcohol-related cues. In real-life settings, these cues are contextually rich, amplifying the role of such individualized drinking motives on cue processing. However, previous literature has primarily relied on images of alcohol, which lack contexts and differ significantly from real-life. Here, aiming to investigate real-life craving, we examined the role of alcohol drinking motives in craving in response to naturalistic alcohol-drinking videos. We asked fifty-three problematic alcohol users to speak about their reasons for drinking alcohol to capture unique alcohol drinking motives of each individual. Participants also underwent functional MRI while watching fifteen alcohol-drinking videos, and reported their subjective level of craving and self-relatedness for each video. Behavioral data analysis revealed that individuals with greater alcohol use severity tended to report greater cue-induced craving, but only when they reported that a video was related to themselves. Inter-subject representational similarity analysis showed that participants with similar alcohol drinking motives, reflected in shared drinking reasons and similar self-relatedness to the videos, exhibited synchronized craving-related neural responses during video-watching. Notably, these shared neural processes mediated the link between similar drinking motives and similar self-reported craving levels across participants. Together, our findings highlight the crucial role of alcohol drinking motives in shaping cue-induced alcohol craving, and provide deeper insights into craving in real-world contexts.

Contextual word learning is a fundamental mechanism for vocabulary acquisition during childhood. In adults, successful inference of word meaning from context is intrinsically rewarding, and is associated with greater enjoyment and greater activity in reward-related brain regions. Whether similar reward mechanisms support word learning in children, and whether they differ as a function of ability, remains unknown. We used functional magnetic resonance imaging (fMRI) to examine neural responses during contextual word learning in 25 children aged 11-13 years with typical reading skills and in 20 age-matched children with dyslexia. Neurotypical readers showed enhanced activation in core reward-processing regions, including the ventral striatum, when successfully learning the meanings of novel words. In contrast, children with dyslexia did not exhibit comparable reward-related responses despite performing the same task. Crucially, this group difference was specific to word learning, as no significant group differences were observed in ventral striatal responses during a non-linguistic monetary reward task. In addition, to confirm the behavioural relevance of these neural findings, we examined an age-matched, independent sample of children. We found that stronger reading skills were associated with greater enjoyment during successful word learning. Together, these results suggest that interactions between reward and language systems during contextual word learning is influenced by reading proficiency. Reduced intrinsic reward responses to successful language learning may contribute to differences in reading development and have implications for the design of more engaging and effective reading interventions for struggling readers.

Language production requires the coordination of multiple cognitive processes. The ability to anticipate and override a habitual response in favor of a contextually-appropriate response are key subprocesses of cognitive control which enable speakers to communicate effectively. Word retrieval involves the co-activation of semantically related alternatives from which the speaker must select the appropriate target representation. Although cognitive control mechanisms have been proposed to contribute to resolving semantic interference during language production, the nature of these control processes remain unclear. Studies investigating the temporal dynamics of cognitive control during decision making tasks have led to a distinction between two operating processes: proactive control, initiated prior to the occurrence of conflict, and reactive control recruited after conflict is detected. We investigated the roles of proactive and reactive control in resolving interference between competing linguistic representations during word retrieval. We analyzed congruency sequence effects combined with delta-plot distributional analyses to dissociate potential adjustments in proactive versus reactive cognitive control in a picture-naming task manipulating semantic context compared to a minimally-linguistic Stroop-like paradigm. Reaction time distributional properties following semantically related trials revealed the engagement of proactive control in semantic interference resolution during word retrieval in the PWI task. In contrast, reactive inhibitory control was engaged in resolving semantic interference following low conflict trials. This distinction was not present in the minimally-linguistic task, which did not appear to engage adaptive control to the same extent. These findings demonstrate that both proactive and reactive cognitive control mechanisms contribute to language production, and are engaged dynamically, adjusting trial-by-trial to resolve semantic interference during word retrieval. In addition, our study provides important insight into the comparison of language with other cognitive domains and positions linguistic paradigms as being instrumental in the study of cognitive control dynamics.

Spinal cord injury (SCI) leads to the formation of a chronic scar composed of glial and fibrotic components that severely restrict neural regeneration and functional recovery. While the scar composition has been widely studied, the spatiotemporal evolution of tissue mechanics and the role it plays in regulating the post-injury responses remain poorly understood. Here we present an integrated mechanobiological and multi-omics analysis of spinal cord remodeling following a severe thoracic contusion injury. Using nanoindentation and viscoelasticity measurements taken via atomic force microscopy (AFM), we demonstrate that SCI induces a dynamic mechanical response characterized by rapid tissue softening during the acute phase reaching a minimum at one-month post-injury, followed by progressive stiffening associated with chronic scar maturation at six months. Bulk RNA sequencing reveals that early mechanical softening coincides with strong activation of inflammatory and matrix-degrading pathways whereas chronic stiffening correlates with upregulation of collagen synthesis, extracellular matrix (ECM) organization and fibrotic remodeling pathways. Concurrently, mechanotransduction regulators exhibit temporally coordinated activation, indicating that cells dynamically sense and respond to evolving mechanical cues. Viscoelastic analysis further shows that chronic scar tissue exhibited increased stiffness and prolonged relaxation dynamics, reflecting dense collagen deposition and proteoglycan accumulation that reinforces a mechanically restrictive microenvironment. Together, these findings establish that the post-injury scar represents a dynamic mechanobiological system in which the evolving tissue mechanics, viscoelasticity and mechanotransduction collectively regulate ECM remodeling, resulting in regenerative failure. This study provides a comprehensive mechanobiological framework for SCI progression and highlights the opportunities for mechanically informed therapeutic strategies aimed at modulating scar mechanics to promote tissue repair.

Recent advances in spatially resolved transcriptomics (SRT) enabled measurement of sets of pathway genes activity within tissues. However, existing gene set activity scoring methods overlook spatial dependencies among tissue locations, restricting their ability to capture region-specific pathway activities associated with disease pathology or cellular communication. Moreover, these methods lack significance-level inference for activity scores, provide limited interpretability of gene-level contribution to a pathway, and scale poorly to advanced large-size SRT datasets. To address these limitations, we present GESSO (Gene sEt activity Score analysis with Spatial lOcation), a spatially informed gene set scoring method adaptable to diverse SRT platforms. GESSO models gene set activity levels through a graph-regularized matrix decomposition algorithm, jointly inferring spatially coherent gene set activity scores (GASs) and interpretable metagene weights that capture gene-level contributions. It further implements a permutation-based local significance test and a stratified low-resolution approximation that scales to high-resolution SRT datasets such as Visium HD, Stereo-seq, and Xenium Prime. Across 13 datasets from five SRT platforms, GESSO outperformed all existing methods in accuracy, calibration, interpretability, and scalability. Applications revealed novel biological programs, including spatially confined EMT activation within tumor-stroma interfaces, developmental signaling gradients across embryonic tissues, and coordinated B-cell, T-cell, and signaling pathways within germinal centers of human lymph node tissue, revealing the spatial organization of immune function at subregional resolution.

Single-nucleus transcriptomic atlases offer an unprecedented opportunity to connect cellular molecular states with Alzheimer's disease (AD) neuropathology, but whether these profiles encode reproducible, predictive information about pathological burden remains unclear. We present the SEA-AD DREAM Challenge, an open, international, model-to-data competition built on the Seattle Alzheimer's Disease Brain Cell Atlas to predict Alzheimer's disease neuropathological severity from single-nucleus RNA-sequencing data. Participants developed containerized models to predict categorical neuropathological staging, including overall Alzheimer's disease neuropathologic change, Braak stage, Thal phase, and CERAD score, as well as quantitative amyloid-{beta} and phospho-tau burden measured by 6E10 and AT8 immunohistochemistry. Across 17 eligible teams from 15 countries, the crowdsourcing framework enabled systematic comparison of diverse computational approaches and surfaced a broad landscape of modeling strategies and candidate predictive features. Top-performing methods achieved near-perfect prediction of categorical staging, with the best submission reaching a quadratic weighted kappa of 1.0 for the Overall AD Neuropathological Change score (ADNC), and competitive prediction of quantitative pathological burden in held-out data, with a best concordance correlation coefficient of 0.48. Post hoc perturbation analyses revealed that top categorical-stage predictions relied heavily on donor-level metadata-driven signals rather than transcriptomic features, whereas quantitative pathology prediction was more robust and supported by transcriptomic and cell-type-associated features with potential biological relevance to AD progression. The challenge also introduced the first AI Agent Track in a DREAM Challenge, providing an early benchmark for autonomous and human-guided agentic model development in single-cell neuroscience. This work demonstrates that single-nucleus transcriptomes encode substantial information about Alzheimer's disease pathology, establishes a reproducible benchmark for molecular neuropathology prediction, and highlights critical principles for designing privacy-preserving, leakage-aware community challenges using deeply phenotyped human brain data.

The spatial arrangement of immune cells in the tumor microenvironment (TME) varies widely, from dispersed to clustered and tumor excluded to infiltrating. Multiplexed spatial profiling is an effective means of characterizing tumor-infiltrating lymphocytes (TILs) and immune complexes such as tertiary lymphoid structures (TLS) in the TME. However, few approaches have been described for objectively parametrizing patterns of immune organization and assessing their association with biological or clinical variables. This makes it difficult to evaluate whether a set of tumors is relatively immunologically cold or hot. Here we describe an intuitive set of statistical tools (available in the R package, tlsR) for characterizing lymphocyte patterns in the TME of solid cancers. We apply tlsR to primary prostate cancer (PCa), which is often described as immunologically cold. Using a cohort of 29 radical prostatectomy specimens stratified into low Gleason-grade (LGG; n=15) and high Gleason-grades (HGG; n =14) we show that HGG PCa is significantly more infiltrated than LGG PCa with lymphocytes organized into B cell or T cell enriched immune clusters (BICs and TICs). A subset of these ICs have the B and T cell zonation and follicular dendritic cells characteristic of a bona fide TLS. HGGs are also enriched with ICs containing precursor exhausted T cells (Tpex) and proliferating B cells and their tumor compartments harbor granzyme-B+ cytotoxic T cells in contact with cancer cells. Thus, far from being cold, a subset of HGG PCa has features associated with active immune surveillance, a finding with implications for emerging PCa immunotherapies.

The incidence of early-onset colorectal cancer (CRC) has risen sharply in recent decades1, yet the biological basis underlying the distinct behavior of tumors arising in young versus aged tissues remains poorly understood. Here we show that aging reprograms the epigenetic landscape of the colon, restricting colon tumor growth through stable silencing of developmental and fetal gene programs. We find that colon tumors arising in aged mice are intrinsically less proliferative than those arising in young animals. Multi-omic profiling of normal colon and colon tumors reveals that aging drives DNA hypermethylation, loss of Polycomb-associated chromatin states, and reduced chromatin accessibility at a defined set of developmental genes that are bivalent (marked by both H3K27me3 and H3K4 methylation), transcriptionally active in colon tumors from young animals and repressed in both tumors and normal tissue from old animals. Among the genes most strongly repressed in old animals is Tacstd2 (Trop2), a regulator of fetal intestinal programs and epithelial stemness. Pharmacologic inhibition of DNA methylation reactivates the aging-silenced gene network in organoids from old animals, whereas genetic disruption of Tacstd2 suppresses growth and developmental transcriptional programs in young tumor organoids. TACSTD2, fetal gene signatures, and the aging-associated bivalent gene program are likewise repressed in late-onset vs. early-onset human colorectal cancers. Collectively, these findings identify age-associated epigenetic silencing of developmental gene programs as a causal mechanism that constrains colorectal tumor growth and provide a mechanistic framework for understanding the distinct biology of early-onset colorectal cancer.

Extrahepatic delivery of lipid nanoparticles (LNPs) to non-phagocytic cells is a major challenge, with the leading strategy involving surface functionalization with target-specific monoclonal antibody (mAb) ligands. We investigate the stability of mAb-conjugated LNPs using two anchoring systems: the commonly used DSPE-PEG2kDa-maleimide and a block copolymer, PCL5kDa-b-PEG2kDa -maleimide, with the hypothesis that conjugation to a 150,000 Da antibody could overwhelm the relatively small ~600 Da aliphatic anchor on the PEG-lipid in vivo. Shedding of the mAB would compromise targeting. Conjugation integrity following IV injection was assessed by tagging LNPs and mAbs with metal ion tracers that could be quantified by ICP-MS. Results show that DSPE-PEG-mAb rapidly (within 1h) dissociates from LNPs in blood, leading to accelerated LNP clearance. In contrast, mAbs conjugated using PCL-b-PEG remained stably associated with the LNP over the 24h circulation and clearance of the construct. Results are connected to a thermodynamic model that reproduces experimental findings for PEG-anchor(-mAb) shedding in vitro and in vivo. This study identifies anchoring strength as a critical, unconsidered parameter for in vivo performance when conjugating mAbs to LNPs for extrahepatic delivery.