Behavior Genetics

Wellbeing is commonly defined as the combination of feeling good and functioning well and typically conceptualized as two related but distinct components. Hedonic wellbeing emphasizes pleasure, happiness, and life satisfaction, while eudaimonic wellbeing focuses on meaning, personal growth, flourishing, and the realization of ones potential. The Mental Health Continuum-Short Form was developed as a comprehensive measure of wellbeing and includes three subscales assessing emotional, social, and psychological wellbeing. Although the Mental Health Continuum total score is often interpreted as an indicator of overall wellbeing, the underlying genetic structure of its three subscales and its genetic overlap with other commonly used wellbeing measures remains unclear. Using data from 5,212 individuals from the Netherlands Twin Register (72% female, mean age 36.4), we fitted multivariate twin models to examine the genetic architecture of the Mental Health Continuum and its associations with other wellbeing measures (quality of life, life satisfaction, subjective happiness, and flourishing). Results indicate that, at the genetic level, the Mental Health Continuum is best explained by its three distinct subscales rather than by a latent factor. When considering the Mental Health Continuum together with the other wellbeing measures, we found moderate to high genetic correlations (r = 0.52 - 0.83), indicating substantial overlap in the genetics underlying the wellbeing constructs. However, we did not find evidence for a single common genetic factor underlying all constructs. These findings highlight the multidimensional structure of wellbeing, but the moderate to high genetic correlations across measures suggest that it is important to align the level of measurement (phenotypic vs genetic) with the research question.

The German Twin Family Panel TwinLife is a nationwide longitudinal study of twins and their family members. Primarily focusing on the development of social inequalities over the life course, TwinLife has been collecting data since October 2014 starting with 4,096 twin families (Ntotal = 16,951 individuals). As Germanys largest twin study to date, TwinLife has been surveying four birth cohorts of monozygotic and dizygotic same-sex twin pairs (initially [~]5, 11, 17, and 23 years old) and their families for 11 years. Survey data have been collected through five biennial face-to-face interviews with four computer-assisted telephone interviews in the years between. In addition, saliva samples were collected before the COVID-19 pandemic (2018-2020), during the pandemic (2021), and after (2022-2024). In this Cohort Profile, we describe the curation and initial analyses of molecular genetic and epigenetic data from the two TwinLife satellite projects TwinSNPs and TECS. Together, these projects currently comprise 12,108 processed DNA samples from 6,450 participants, extracted from the first two saliva collections before and during the COVID-19 pandemic. We compared the subsamples with the overall TwinLife sample and provide an overview of derived polygenic scores (PGS), epigenetic clocks and other methylation profile scores (MPS). We found that PGS predicted sample attrition in TwinLife, with small but significant associations between higher PGS for educational attainment and continued participation. Epigenetic clocks derived from saliva were highly correlated with chronological age (r = .71 to r = .94) and were generally more stable over time than other MPS. PGS for epigenetic clocks were associated with the respective clock only during but not before the start of the pandemic. We discuss opportunities of combining prospectively assessed molecular (epi)genetic data in within-family designs such as TwinLife and its implications and avenues for future research.

BackgroundThe prevalences of suicidal ideation (SI) and suicide attempt (SA) are influenced by genetic, behavioral, and environmental factors. Alcohol use disorder (AUD) and adverse childhood experiences (ACEs) may mediate or moderate genetic liability for suicidality. MethodsUsing data from 10,275 participants (43.8% female; 47.2% African-like genetic ancestry [AFR], 52.8% European-like genetic ancestry [EUR]), we tested whether polygenic scores (PGS) for SI and SA predicted lifetime SI or SA. We also evaluated whether alcohol use disorder (AUD) mediated these associations and whether adverse childhood experiences (ACEs) moderated the direct and indirect pathways. ResultsAlthough there were significant direct associations of the SA PGS with SA (AFR: b = 0.36, SE = 0.01; EUR: b = 0.17, SE = 0.01; both ps < 2e-16), the SI PGS did not predict SI (p > 0.55). AUD mediated SA genetic risk (average causal mediation effect (ACME): AFR = 0.01, 95% CI [0.01-0.01]; EUR = 0.02, 95% CI [0.01-0.02]; both ps < 2e-16). Moderation analyses indicated that indirect effects were attenuated by ACEs score ({Delta}ACME: AFR = 0.02, p < 2e-16; EUR = 0.01, p = 0.03). There was neither mediation nor moderated mediation for SI. ConclusionsGenetic liability to SA operates partly through AUD, particularly among individuals with lower childhood adversity. Under higher adversity, alternative pathways to SA likely predominate. These findings highlight the need to consider distinct etiological pathways to the development of suicidality and the relevance of AUD as a modifiable target for suicide prevention among individuals at high genetic liability.

Background and AimsSubstance use disorders (SUDs) are heritable and share genetic variance with externalizing and internalizing psychopathology. Although recent gene identification efforts have demonstrated the value of modeling the shared genetic architecture among SUDs and externalizing, most research has thus far failed to account for overlap with internalizing. In this study, we aim to characterize the genetic relationships of both externalizing and internalizing with SUDs. Design and settingWe used genome-wide association study (GWAS) summary statistics derived from previously published studies of externalizing, internalizing, and SUD outcomes to quantify the genetic overlap between these phenotypes. We characterize this overlap using omnibus, partial, and local genetic correlations, estimates of their shared polygenic effects, genetic causality models, polygenic score (PGS) analyses, and estimates of each SUDs residual variance derived from models in Genomic SEM. ParticipantsWe used GWAS summary statistics from individuals whose genomes were most similar to those from reference panels sampled from Europe (Ns ranged from 45,395 to 1,565,618) and Africa (Ns ranged from 30,000 to 122,571). For polygenic scores analyses, we used data from individuals of European and African ancestry groups available in the Collaborative Study on the Genetics of Alcoholism (COGA) sample (NMaximum = 7,394 for European-like genomes and 3,238 for African-like genomes) MeasurementsMeasurements in this study include GWAS summary statistics for externalizing, internalizing, and four substance use disorders: problematic alcohol use (PAU), cannabis use disorder (CUD), opioid use disorder (OUD), and tobacco use disorder (TUD). SUD outcomes in COGA were DSM-IV symptom counts of AUD, CUD, and OUD and scores on the Fagerstrom Test for Nicotine Dependence. FindingsWe found strong genetic relationships of externalizing and, to a lesser extent, internalizing with all SUDs across methods. Despite their more modest associations, internalizing emerged as an important genetic correlate of SUDs. After accounting for variance shared with externalizing, partial genetic correlations between internalizing and SUDs were attenuated but, with the exception of TUD, still significant. Similarly, the PGSINT accounted for a statistically significant increase in variance over and above PGSEXT. Two SUD specific patterns emerged such that TUD was least associated with both psychopathology spectra and OUD was most strongly related to internalizing relative to other SUDs. ConclusionsFrom these findings we conclude that shared genetic influences may explain comorbidity observed between SUDs and internalizing disorders and suggest that genetic risk for internalizing should be incorporated into SUD identification and prevention efforts. Future gene identification efforts should study SUDs in the context of both externalizing and internalizing psychopathology.

BackgroundSubstance use initiation in adolescence is influenced by both genetic and environmental factors; however, large-scale genetic studies often treat initiation as a binary outcome and underuse longitudinal timing information. MethodsWe conducted time-to-event (survival) genome-wide association analyses (GWAS) of initiation for four outcomes--alcohol, nicotine, cannabis, and any substance use--using longitudinal follow-up data from the Adolescent Brain Cognitive Development (ABCD) Study. We performed ancestry-stratified GWAS within European (EUR), African (AFR), and Hispanic (HISP) groups, applying consistent quality control and covariate adjustment. Summary statistics were harmonized across ancestries and meta-analyzed using inverse-variance weighted fixed-effects and DerSimonian-Laird random-effects models. We evaluated genomic inflation and heterogeneity (Cochrans Q and I2), identified independent lead variants at genome-wide and suggestive significance thresholds, and assessed cross-trait overlap of associated loci. ResultsIn the multi-ancestry meta-analysis, we observed suggestive association signals across traits (minimum p-values: alcohol [~] 1 x 10-7, any [~] 1 x 10-7, cannabis [~] 5 x 10-8, nicotine [~] 1 x 10-8). Nicotine initiation showed one genome-wide significant variant in both fixed- and random-effects meta-analyses (p < 5 x 10-8). Across traits, suggestive loci demonstrated limited overlap, with the strongest concordance between alcohol and any substance use, consistent with shared liability. Heterogeneity statistics indicated that some loci exhibited cross-ancestry variation in effect estimates. ConclusionsSurvival GWAS leveraging initiation timing can identify genetic signals that may be missed by binary designs and enables principled multi-ancestry synthesis. Our results highlight both shared and trait-specific genetic contributions to early substance initiation and provide a foundation for downstream functional annotation and integrative modeling with environmental risk factors. These findings demonstrate the value of incorporating developmental timing into genetic discovery and provide a framework for integrating longitudinal risk modeling with genomic analyses.

Early life adversity (ELA) has a well-established link to mental health disorders later in life, yet the molecular mechanisms behind this relationship are incompletely understood. The Future of Families Child Wellbeing Study (FFCWS) provides an opportunity to examine experience encoding in the genome through functional changes in DNA methylation (DNAm) in a cohort enriched in subjects exposed to ELA. We investigated epigenome-wide differences in DNAm across thirteen early-life exposures in salivary samples from FFCWS participants. We calculated differential methylation associations with disease-linked genetic variants, evaluated tissue-specific gene expression, and assessed the persistence of DNAm changes from ages 9 to 15 years. Using data from the mSTARR-seq assay, we characterized methylation-dependent regulatory activity. Differential methylation in the FFCWS validated prior results and identified new genomic regions associated with child adversity. Differential methylation occurs in genomic regions likely to impact gene expression, and affected genes are expressed in disease-relevant tissues. We also identified association of genetic variants associated with downstream disorders near differential methylation, including depression, alcohol and substance use, and anxiety disorders. Overall, cumulative ELA is associated with specific DNAm changes, functional regulation, and persistence over time. Our findings indicate that ELA-associated differential methylation in the FFCWS does not simply occur at random, but in genomic regions that are functional. Our results support the conclusion that altered DNAm represents a biological link between early life experience and later health outcomes.

BackgroundThe present study examines the link between DNA methylation at the nerve growth factor-induced protein A (NGFI-A) binding domain of the NR3C1 1F promoter and later cognitive functions in children from families living in disadvantaged psychosocial conditions. MethodsParticipants were 132 children who took part in a Swiss Parents as Teachers (PAT) randomized controlled trial (72 in the intervention group, 60 in the control group). DNA methylation was quantified from saliva samples collected at age three using sodium bisulfite next-generation sequencing (NGS). Cognitive functions were assessed at age five using the SON-R 2.5-7 Intelligence Test. Results(a) DNA methylation at age three predicted lower IQ at age five through increased concentration problems; (b) participation in the three-year PAT program predicted lower methylation levels at the end of the intervention; and (c) early life stressors predicted lower IQ through increased methylation and concentration problems with descriptively stronger effects in the control group. ConclusionsThese findings demonstrate a link between early DNA methylation at the NGFI-A binding site of the NR3C1 1F promoter and later cognitive functions in children and highlight the role of early life stressors and the PAT intervention in shaping these associations.

BackgroundAttention-deficit/hyperactivity disorder (ADHD) is a common heritable neurodevelopmental disorder, affecting [~]7 million children (11.4%) in the U.S. However, ADHDs underlying genetic architecture remains largely unknown. Transcriptome-wide association studies (TWAS), which integrate expression quantitative trait loci (eQTL) and GWAS summary data, can identify differentially expressed risk genes underlying complex phenotypes. Here we conduct a TWAS of ADHD using expression data from multiple brain tissues to improve understanding of the complex genetic architecture underlying this psychopathology. MethodsWe applied the TWAS framework OTTERS to train multiple gene expression imputation models using cis-eQTL summary statistics from MetaBrain for three brain regions: cortex (n=2,683), basal ganglia (n=208), and cerebellum (n=492), and GWAS summary statistics from the most recent meta-analysis of ADHD (n=225,534; case fraction =0.17). We further conducted fine-mapping, colocalization analysis, and functional enrichment analysis. ResultsWe identified 29 significant TWAS risk genes for ADHD (11 in cortex, 4 in basal ganglia, and 14 in cerebellum). Six genes appear novel for ADHD (MPL, C1orf210, MDFIC, NKX2-2, FAM183A, HIGD1A) while four genes were previously implicated in autism spectrum disorder (XRN2, KIZ, NKX2-4, NKX2-2). Pathway analysis indicated cortex and basal ganglia were enriched for neurodevelopmental pathways and regulation of cell development, and the protein-protein interaction network was statistically significant (p=1.12E-04). ConclusionThis multi-tissue TWAS refines the genetic architecture of ADHD by identifying genes whose genetically regulated expression is associated with risk, including six candidates not previously linked to ADHD. Together, these findings provide novel insights for potential targets in translational research and drug discovery.

Background: Attention problems are common transdiagnostic symptoms of psychiatric illness. Although environmental exposures and experiences influence attention during adolescent development, the underlying neural pathways by which they do so is unclear. Methods: We measured attention problems, attention-related brain networks, and multidimensional environmental experiences (the exposome) using data from the ABCD Study (N = 11,878). We tested whether the exposome is associated with 9-10-year-olds attention-related brain network strength and current and future attention problems. We further examined cross-sectional indirect pathways linking the exposome, brain network strength, and attention problems. Results: The exposome predicted youths current and future self-, caregiver-, and teacher-reported attention problems as well as their current attention-related brain network strength. This brain network signature of sustained attention also predicted attention problems from all three reporters. Indirect effects models revealed that the exposome was associated with current reported attention problems both directly and indirectly though this brain signature. Conversely, predictive brain network strength was related to attention problems both directly and indirectly through the exposome. Conclusion: Interactions between environmental exposures, experiences, and brain network organization are associated with attention problems in early adolescence. These findings support a bidirectional framework linking the environment and functional brain networks in the development of attention problems.

Background: The Adolescent Brain Cognitive Development (ABCD) Study provides rich longitudinal data on environmental, genetic, and behavioral factors related to substance use initiation. Classical marginal structural models (MSMs) require selecting covariates for propensity models, which is challenging when there are many correlated predictors. Methods: We analyzed longitudinal panel data from 11,868 ABCD participants with repeated observations over time. Interval-level binary outcomes were defined for initiation of alcohol, nicotine, cannabis, and any substance, including only participants at risk before initiation. All predictors were constructed as lagged variables to preserve temporal ordering. We used a two-stage machine learning-based causal framework. First, we performed graph discovery using a Granger-inspired lagged predictive modeling approach with elastic-net logistic regression to identify relationships between past predictors and future outcomes. Stable candidate edges were selected using subject-level bootstrap stability selection. Second, we estimated adjusted effects for stable predictors using double machine learning (DML) with partialling-out and cross-fitting. For each predictor, the lagged variable was treated as the exposure and adjusted for high-dimensional lagged covariates. Cross-fitting with group-based splitting accounted for within-subject dependence. Nuisance functions were estimated using random forests, and cluster-robust standard errors were used for inference. Results: We identified stable predictors across multiple domains, including sleep patterns, family environment, peer relationships, behavioral traits, and genetic risk. Many predictors were shared across substance outcomes, while some were outcome-specific. Effect sizes were modest, typically ranging from -0.01 to 0.02 per standard deviation increase in the predictor. Both risk-increasing and protective associations were observed. Risk factors included sleep disturbance and behavioral risk indicators, while protective factors included parental monitoring and structured environments. Conclusions: This study presents a practical framework for analyzing high-dimensional longitudinal data and identifying time-varying predictors of substance use initiation. The approach combines machine learning for variable selection with causal inference for effect estimation. The results highlight both shared and outcome-specific risk factors and identify modifiable targets, such as family environment and sleep, that may inform prevention strategies.

BackgroundBipolar disorder (BIP) frequently co-occurs with heightened substance use (SU) and substance use disorders (SUDs). Although the strong co-occurrence of these heritable traits points to shared genetic susceptibility, the extent to which there are differences in how SU and SUD overlap with BIP genetic architecture remains unclear. MethodsWe quantified the polygenic overlap between BIP and SUDs (alcohol, cannabis, opioid, and tobacco), and BIP and SU traits (drinks per week, lifetime cannabis use, prescription_opioid use, and smoking initiation) using GWAS summary statistics and trivariate MiXeR. We then isolated the general and unique genetic contributions of SUD and SU using GWAS-by-subtraction via GenomicSEM. Next, we tested associations between polygenic risk scores (PRSs) derived from these latent factors and diagnostic and behavioral outcomes in the Norwegian Mother, Father and Child Cohort Study. Finally, we applied GSA-MiXeR to explore pleiotropic pathway enrichment shared between the latent factors and BIP. ResultsWe found extensive polygenic overlap between traits, with SUDs being more genetically correlated with BIP than SU traits. The unique SUD factor correlated positively with psychiatric disorders, whereas unique SU correlated negatively. PRSs for BIP, shared SUD/SU, and unique SUD were significantly associated with BIP, SUD, and comorbid SUD-BIP; PRS for unique SU was only associated with self-reported lifetime SU. GSA-MiXeR revealed richer gene-set enrichment for SUD/BIP than SU/BIP implicating dopamine signaling and interneuron function. ConclusionBy dissecting the genetic liability to SUD and SU and investigating their relationship with BIP we find a genetic link driven by substance dependence but not substance use more broadly.

Childhood weight development, especially overweight and obesity, has been associated with mental health, but their dynamic, causal relationships, and whether these differ by sex, remain unclear. We applied causal discovery to data from the Danish National Birth Cohort (n=67,593) spanning six periods from pregnancy to late adolescence and considering 67 variables related to child and parental weight, mental health, lifestyle, and socio-economic factors. We found no statistically significant difference between the causal graphs for boys and girls (P=0.079). The data-driven models found causal influence of childhood weight on subsequent weight status. Mental health pathways were exclusively within or across adjacent periods and centered on early adolescent stress. We examined the interplay between a subset of mental health variables, containing information on externalizing and internalizing problems, and weight, and found no direct causal pathway between the two processes. These findings suggest that observed links between weight and these mental health measures may be attributable to confounding. Our findings demonstrate the value of data-driven causal discovery in large cohort studies and how to test for differences in causal mechanisms across subgroups. Results are available in an interactive application, enabling future research to further explore the interplay between weight and mental health.

The most highly predictive polygenic scores in the behavioural sciences are for cognitive traits, especially general cognitive ability (g) and educational attainment. We combined polygenic scores derived from genome-wide association studies of adult g and educational attainment to create adult 'polygenic g scores' which we used to chart the course of cognitive development of 10,000 white British children from toddlerhood through early adulthood. We integrated cross-sectional regression, latent growth curve, and confirmatory factor analysis to systematically characterise cognitive development. Polygenic g score showed minimal prediction in toddlerhood, modest prediction in childhood, and substantial prediction by early adulthood accounting for 12% of the variance. Higher polygenic g scores were associated with faster cognitive growth in latent growth models. Prediction was strongest for a cross-time latent cognitive factor (15%) capturing cognitive ability across development. By integrating polygenic prediction directly into a structural equation model framework, we provided a theoretical upper bound of genetic influences on g under minimal measurement error. We also examined the polygenic g score's prediction of educational achievement, behaviour problems, and anthropometric outcomes and found similar developmental increases in prediction for educational achievement. Together, our findings demonstrate that adult polygenic g scores can be a useful tool for charting the development of cognitive traits.

Prenatal alcohol exposure (PAE) can lead to a range of deficits falling under the umbrella of Fetal Alcohol Spectrum Disorder (FASD), which included higher risk for adverse neurodevelopmental and mental health outcomes. Although the biological mechanisms underlying the link between PAE and mental health remain unclear, DNA methylation (DNAm), an epigenetic modification responsive to environmental exposures, may explain these relationships. Here, we applied a two-sample Mendelian randomization (MR) framework to assess whether DNAm loci previously associated with PAE or FASD are linked to 11 psychiatric outcomes. Using summary statistics from the Genetics of DNA Methylation Consortium (GoDMC) mQTL database and large-scale GWAS, we analyzed DNAm loci from two epigenome-wide association studies: one examining FASD by Lussier et al. (2018) and one examining PAE patterns by Sharp et al. (2018). A total of 106 associations (Lussier) and 28 associations (Sharp) reached nominal significance (p<0.05) and passed sensitivity tests, with several surviving multiple testing correction. Notably, schizophrenia and bipolar disorder had the highest number of associated loci across both studies. Functional analysis showed that DNAm loci were enriched in signaling pathways, embryonic development, and neuron differentiation. Regional enrichment analysis revealed that FASD-related loci were more likely to occur in enhancer and south shore, implicating distal regulatory elements. PAE patterns conferred heterogeneous effects on DNAm and mental health risk, underscoring the complexity of timing-specific epigenetic vulnerability. These findings offer novel insights into the potential mechanism of DNAm linking PAE to mental health, and demonstrate the utility of MR in epigenetic epidemiology.

IntroductionEarly-life adversity (ELA) encompasses a range of environmental stressors, including physical, emotional, and social challenges that can affect health during the critical early developmental period. Extensive research has linked ELA to negative long-term health outcomes, yet the underlying biological mechanisms remain poorly understood. The current study investigates how early institutional care changes the epigenetic landscape in young adults. The study also provides insights into role of DNA methylation as a potential mediator for disease susceptibility and altered health trajectories. Materials and MethodsDNA was extracted from blood samples obtained from 111 individuals (71 Controls; 40 ELA) who were part of the EpiPath cohort. DNA methylation was measured using the Infinium Methylation EPIC v2.0 BeadChip. Results3,785 differentially methylated CpG loci were identified in the ELA group in comparison with the control group (FDR <0.05). Pathway enrichment analysis highlighted biological processes involved in metabolic regulation, stress response, and neurodevelopment, with novel pathways such as GTPase-mediated signalling, efferocytosis and glucuronosyltransferase emerging as potential drivers of the ELA phenotype. A subset of 28 CpG loci was used to develop an epigenetic signature, which showed a significant association with the development of chronic diseases in ELA-exposed individuals. ConclusionThis study reinforces Barkers concept of sensitive periods and it underscores the enduring impact of ELA in shaping long-term health outcomes. The persistence of DNA methylation patterns decades after exposure to ELA, and their clear association with the resultant phenotype confirms that stable epigenetic imprints play a potential role in long-term disease risk and resilience.

BackgroundPsychosocial adversity (PSA) contributes to long-term health disparities and increased risk for non-communicable diseases. The effects of PSA arise through complex interactions between genes and the environment, which involve immune, endocrine, and epigenetic dysregulation. MethodsTo examine how adversity affects mental and physical health via epigenetic alterations in a more controlled way, we examined the relationship between PSA and epigenetic aging in 28 monozygotic (MZ) twin pairs discordant for negative life experiences. Whole-blood DNA methylation (DNAm) profiling was performed using the Illumina Infinium EPIC v2 BeadChip array. Epigenetic age acceleration (EAA) was calculated using a panel of first to third-generation clocks, namely, Horvath, Hannum, PhenoAge (Levine), GrimAge (v2.0), Elastic Net and DunedinPACE. ResultsThough we did not observe any significant group-level differences in epigenetic age acceleration between PSA and control at large, sex-stratified analyses revealed that PSA exposed males exhibited significant reductions in EAA compared to their co-twins when assessed using the Hannum, PhenoAge, and DunedinPACE clocks. In females, regression analyses showed significant positive associations between EAA and both negative life events and shame perception. Application of the dimensional model of adversity further revealed that psychosocial threat was strongly associated with increased EAA in females, whereas deprivation showed a weaker but significant association with EAA in males. These findings suggest a sex-specific and context-dependent biological response to PSA, potentially reflecting either adaptive or maladaptive epigenetic remodelling. ConclusionThe observed epigenetic age deceleration in PSA-exposed males, together with the associations between EAA and threat, shame perception, and life events in females, highlight the importance of context and perception in shaping sex-specific responses to adversity. Our results underscore the utility of MZ twin study designs in isolating psychosocial stress driven epigenetic effects and support DNAm clocks as biomarkers of stress-related biological aging. Overall, this study advances our understanding of the molecular underpinnings of social health inequalities and may inform future interventions aimed at promoting resilience and stress adaptation.

Neurodevelopmental disorders (NDDs) influence lifespan neurocognitive trajectories and can be conceptualized as falling on a continuum. However, transdiagnostic neurodevelopmental investigations in cognitive aging are rare. This preliminary, cross-sectional study aimed at exploring lifespan manifestations of neurodevelopmental vulnerabilities (DVs) in cognitive aging, while adopting a dimensional approach to NDDs. The objectives, covered from childhood to adulthood, were: 1) to describe NDDs-related domains of vulnerability; 2) to estimate DVs frequency; 3) to evaluate the persistence of DVs symptoms from childhood to adulthood; 4) to explore the link between DVs, demographics and neuropsychological performance. Cognitively healthy participants underwent a neuropsychological assessment and answered a retrospective questionnaire on NDDs symptoms in childhood and in adulthood. Using a k-means clustering based on questionnaire answers, participants were assigned to a DV+ (with DV) or a DV- (without) cluster. The final sample consisted in 84 participants [age: 69 (8); years of education: 14 (3); 57% females]. In childhood, self-management, reading and writing, school performance, and visuospatial difficulties were reported. In adulthood, difficulties were mainly in self-management. Clustering revealed a DV in 15% of individuals during childhood, and in 21% during adulthood. Throughout life, 86% of participants had a consistent cluster assignation, while 13% changed clusters between childhood and adulthood. Childhood self-management and scholar difficulties significantly predicted self-management difficulties in adulthood. Nevertheless, no link was found between DVs, demographics and neuropsychological performance. Results highlight the relevance of lifespan, dimensional investigations of NDDs; and are discussed in terms of cognitive reserve, compensation processes, heterotypic continuity and psychopathological progression. Public Significance StatementThis preliminary study suggests that developmental vulnerabilities can be detected in cognitively healthy aging individuals. Difficulties in their childhood may relate to self-management, reading and writing, school performance, and visuospatial skills; and may predict self-management difficulties in adulthood. HighlightsO_LILifespan neurodevelopmental vulnerabilities (DVs) were screened using a retrospective questionnaire in 84 cognitively healthy older adults. C_LIO_LIA data-driven dimensional analysis identified DVs in 15% of participants during childhood and 18% during adulthood. C_LIO_LIIn childhood, reported difficulties included self-management, reading and writing, school performance, and visuospatial skills. In adulthood, difficulties were mainly in self-management. C_LIO_LIChildhood self-management and scholar difficulties significantly predicted self-management difficulties in adulthood. C_LI

Heat Shock Protein 90 (HSP90) functions as an evolutionary capacitor, allowing populations to store cryptic genetic variation that can be released under stress. While former studies have described the release of morphological variation, its behavioural consequences remain unexplored. In the red flour beetle, Tribolium castaneum, HSP90 inhibition released a phenotype with much smaller, less defined eyes that confers fitness benefits in continuous light and was subsequently assimilated. We hypothesized that altered eye morphology affects light perception and thereby changes light-dependent behaviours. To test whether phenotypes released via evolutionary capacitance can beneficially alter behaviour, we examined locomotor activity rhythm entrainment to light-dark cycles as well as individual and group light choice behaviour. Males of the reduced-eye phenotype exhibited a diminished startle response to sudden light exposure in locomotor activity assays. We also found reduced negative phototaxis in groups of beetles with reduced eyes. This modified behaviour, indicating reduced light sensitivity, may stem from impaired light perception caused by altered eye morphology. Lower light sensitivity could be beneficial under stressful environmental conditions by promoting the exploration of alternative niches. Therefore, this study provides the first evidence for potentially beneficial behavioural changes in a HSP90-released phenotype, reinforcing HSP90s role as an evolutionary capacitor.

Background and objectivesComparing childrens growth across the world and at different moments in history can yield insight into both health challenges and healthy morphological variation in our species. A difficulty of such comparative analyses is that, in marginalized populations, there are often logistical complications to obtaining repeat measures of individual childrens height and weight. The problem is even more acute for historical populations: bioarchaeological datasets comprise single measures of individuals at death. Additionally, for both contemporary and historical populations, there is often non-trivial uncertainty about childrens ages. Both of these factors complicate estimation of growth trajectories. Here we evaluate the degree to which we can accurately estimate a population-mean growth trajectory using only a small number of (randomly) uncertain measurements, like those that compose many contemporary and bioarchaeological datasets. MethodologyWe recently derived a causal model of human growth from fundamental principles of metabolism and allometry, permitting exploration of genetic and environmental contributions to childrens growth. Here, we fit this model in a Bayesian framework to simulated cross-sectional and longitudinal datasets of varying size, where age is uncertain. ResultsWe show that, for large-scale comparative purposes, reasonably accurate population-mean growth trajectories may be obtained from single height measures of 100 children. However, detailed analyses of pubertal growth spurts and the metabolic and allometric parameters underlying growth require more extensive longitudinal datasets. Conclusions and implicationsWe conclude that this new model and estimation strategy constitute a potentially useful toolkit for comparing mean growth trajectories across contemporary and historical populations.

IntroductionResearch has shown that social and physical stressors of early-life adversity (ELA) can negatively affect long-term health trajectories. Despite differences in types of ELA exposure, previous studies have identified common health-related outcomes in adults who had experienced less favourable conditions during developmentally sensitive periods. This meta-analysis investigates the potential role of DNA methylation in mediating these adverse health trajectories by identifying common biological signatures across cohorts with distinct adversity exposures and environmental backgrounds. Materials and MethodsDNA methylation data from previously published studies was used to perform a meta-analysis on 227 individuals across three cohorts. These include the EpiPath cohort consisting of adults who were exposed early institutional care, ImmunoTwin cohort consisting of adversity discordant monozygotic twin pairs and lastly a cohort of young children exposed to early institutional care. ResultsDNA methylation analysis across the three cohorts revealed differential methylation at CpG loci associated with 15 genes common to all cohorts. These genes are involved in neuronal development, chromatin remodeling and metabolism. Pathway enrichment analysis of the combined dataset showed potential associations with oxytocin signalling, regulation of nervous system development, and calcium signalling in relation to the later-life phenotype of the adversity exposed individuals. In addition, a poly-epigenetic score was developed by identifying a subset of 200 differentially methylated CpG sites through PLS-DA analysis with the combined beta matrix of these cohorts. ConclusionThis study highlights the long-term impact of adversity by identifying common DNA methylation signatures of negative life experiences across three cohorts. The development of a poly-epigenetic score represents the first steps towards identifying group differences by combining weighted methylation values for CpG sites of interest. This method illustrates the potential to track changes in individuals across long-term studies that may benefit research in lifelong healthoutcomes.