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.

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.

Although dietary intake is a leading risk factor for many common diseases, adherence to dietary recommendations remains low. This may partly reflect limited consideration of individual differences in eating behavior that arise from both environmental and genetic factors. While genome-wide association studies (GWAS) of dietary intake have identified hundreds of associated loci, the X chromosome has largely been ignored. To address this gap, we applied multiple X-chromosome-wide association study (X-WAS) models on dietary intake phenotypes to identify novel associations. We performed X-WAS of 46 dietary intake traits from food frequency questionnaires in up to 424,758 European participants from the UK Biobank. Phenotypes included quantitative measures (e.g., fruit intake), binary traits (e.g., decaffeinated vs caffeinated coffee), and principal component-derived food groups. We tested for genetic associations using several models: a traditional sex-combined additive GWAS, additive models stratified by sex, and two joint models accounting for sex-interaction effects and non-additivity. We also conducted X-WAS in five additional genetic ancestry groups and performed a sex-combined multi-ancestry additive GWAS meta-analysis with up to 445,773 individuals. We identified 18 loci associated with 20 dietary intake traits (P < 5x10-8), including 17 variants without prior associations in the GWAS Catalog. Among these loci, 10 were significant across multiple X-WAS models, and 5 were strongest in a model other than the traditional sex-combined additive GWAS, highlighting the value of approaches that address known complexities of the X chromosome. These results demonstrate that incorporating the X chromosome in GWAS can reveal novel loci, even for complex behavioral traits such as dietary intake. Applying multiple association models further improves discovery by accounting for unique features of the X chromosome. Author SummaryAlthough diet is a major risk factor for many common diseases, adherence to healthy eating guidelines remains low. One reason is that current recommendations do not account for individual differences in food choice that arise from environmental or genetic factors. Previous genetic studies have identified hundreds of genetic variants associated with dietary behaviors, but most have excluded the X chromosome due to its analytical complexity and differences between males and females. However, accumulating evidence suggests that the X chromosome contains important genetic variation that impacts complex traits. We analyzed data from hundreds of thousands of individuals to identify genetic variants on the X chromosome associated with dietary intake. To address the unique features of the X chromosome, we applied multiple different models that account for sex-differences and non-additive genetic effects. We identified 18 regions in the genome associated with at least one dietary intake trait. These results reveal new insights into the genetics underlying eating behavior and highlight the importance of incorporating the X chromosome in genetic studies of complex traits.

BackgroundEarly adolescence is a common period of onset for depressive symptoms. In part, this may reflect a developmental manifestation of individuals genetic propensities as they undergo physiological and hormonal changes and interact with new environments. Many commonly proposed mechanisms assume direct effects of an individuals own genes on emerging variation in their depressive symptomatology. However, estimates of genetic influence based on analyses in unrelated individuals capture not only direct genetic effects but also genetic effects from parents and other biologically related family members. AimIn data from the Norwegian Mother, Father and Child Cohort (MoBa), we used linear mixed models to distinguish developmentally-stable and adolescence-specific direct and parental indirect genetic effects. We examined effects of polygenic scores for major depressive disorder (MDD), ADHD, anxiety disorders, and educational attainment (EA) on depressive symptoms, which were assessed by maternal reports at ages 8 and 14. ResultsChildrens own MDD polygenic scores showed adolescence-specific effects on depressive symptoms ({beta}PGS*wave=0.041, [95% CI: 0.017, 0.065]). Developmentally-stable direct effects from childrens polygenic scores for MDD ({beta}=0.016, [0.006, 0.039]), ADHD ({beta}=0.024, [0.008, 0.041]) and EA ({beta}=-0.02, [-0.038, -0.002]) were also evident. The only evidence of indirect genetic effects was a stable effect of maternal EA polygenic scores ({beta}=0.04, [0.024, 0.054]). ConclusionDirect genetic effects linked to genetic liability to MDD accounted for emerging variation in depressive symptoms in adolescence. These results imply that specific etiological mechanisms related to MDD may become particularly relevant for depressive symptoms during early adolescence compared to at earlier ages.

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.

ImportanceAdverse neighborhood conditions can lead to poorer health outcomes, potentially through accelerated biological aging. However, whether these relationships are explained by individual- or neighborhood-level factors remains unclear. ObjectiveTo examine the association between neighborhood deprivation, measured by the Area Deprivation Index (ADI), and epigenetic age acceleration and assess whether individual- and neighborhood-level characteristics mediate or modify these associations. DesignCross-sectional study using data from a Yale Stress Center study between 2008 and 2012. Data analysis was conducted from July 2025 to January 2026. SettingCommunity-based sample from the greater New Haven, CT area. ParticipantsA total of 370 healthy adults aged 18 to 50 years without major psychiatric, medical, or cognitive disorders who provided blood samples for DNA methylation analysis. Main Outcomes and MeasuresEpigenetic age acceleration measured from DNA methylation using four second-generation epigenetic clocks, with associations assessed among aging, neighborhood deprivation, and individual- and neighborhood-level factors. ResultsData were analyzed from 370 participants (212 women [57.3%], 158 men [42.7%]; mean [SEM] age, 29.3 [0.46] years). Greater neighborhood deprivation was associated with greater lifetime adversity ({beta}=0.112, p<.001) and lower educational attainment ({beta}=-0.019, p=.012), and accelerated epigenetic aging as measured by GrimAge ({beta}=0.037, p<.001), PCGrimAge ({beta}=0.019, p<.001), and PCPhenoAge ({beta}=0.041, p<.001), but not PhenoAge (p=.23). In multivariable models accounting for individual factors, neighborhood deprivation remained associated with these three clocks. Lifetime adversity partially mediated the association between ADI and accelerated GrimAge (20.3% of total effect) and PCGrimAge (23.3%). Race moderated the direct association between ADI and epigenetic aging, with stronger associations between neighborhood deprivation and accelerated GrimAge ({beta}=0.061, p=.004) and PCPhenoAge ({beta}=0.057, p=.02) observed among Black participants compared to White. ConclusionsGreater neighborhood deprivation was associated with accelerated epigenetic aging across multiple second-generation clocks, with lifetime adversity partially mediating these associations. Stronger effects were observed among Black participants. These findings suggest that neighborhood environments and cumulative stress may contribute to biological aging and racial disparities in aging trajectories. Key PointsO_ST_ABSQuestionC_ST_ABSIs neighborhood deprivation associated with epigenetic age acceleration, and if so, how do neighborhood- and individual-level factors impact this relationship? FindingsIn this cross-sectional study of 370 adults, greater neighborhood deprivation was associated with accelerated epigenetic aging across multiple second-generation clocks. Lifetime adversity partially mediated these associations, and the relationship between neighborhood deprivation and accelerated aging was stronger among Black participants than White participants. MeaningThese findings suggest that neighborhood conditions and lifetime stress contribute to accelerated biological aging and suggest that epigenetic aging may represent one biological pathway through which neighborhood-level racial inequalities contribute to health disparities.

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.

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.

ObjectiveObsessive-compulsive disorder (OCD) frequently co-occurs with bipolar disorder (BD) or schizophrenia (SCZ), and, importantly, can often precede their onset. However, the genetic architecture and directionality underlying these relationships remain unclear. We leveraged large-scale genome-wide association study (GWAS) data to examine shared genetic architecture and directional relationships among OCD, BD and SCZ, and used major depressive disorder (MDD) as a comparator. MethodsUsing linkage disequilibrium score regression (LDSC), MiXeR, and Generalized Summary-data-based Mendelian Randomization (GSMR) as well as complementary Mendelian randomization approaches, we characterized genetic correlations, polygenic overlap (Dice coefficient), and effect direction concordance ({rho}{beta}) across disorders. ResultsWe observed substantial genetic correlations between OCD and BD (rg=0.37), BD type 2 (BD2) (rg=0.54), and SCZ (rg=0.39), with a large proportion of shared causal variants between OCD and both BD (Dice=0.85) and SCZ (Dice=0.84). MiXeR analyses indicated that OCD and BD2 share a smaller proportion of causal variants (Dice=0.57) but there is a high concordance of effect directions amongst these causal variants ({rho}{beta}=0.96), whereas OCD and MDD showed minimal overlap but strong concordance among shared variants (Dice=0.09, {rho}{beta}=1). Directional GSMR and complementary TwoSampleMR analyses supported a causal effect of genetic risk to OCD on liability to BD (b=0.20, p=1.5x10{square}{square}), SCZ (b=0.52, p=9.5x10{square}{superscript 2}{superscript 1}), and MDD (b=0.24, p=1.06x10{square}{square}), with little evidence for reverse causal effects. ConclusionsTogether, these findings indicate that genetic liability to OCD can represent an early component of transdiagnostic psychiatric risk, with implications for understanding and potentially predicting the emergence of broader psychopathology across the life course.

Standard genome-wide association studies (GWASs) are vulnerable to confounding factors, including stratification, assortative mating, and dynastic effects. Family studies such as sibling-based GWAS (sib-GWAS) mitigate such confounding and are becoming the tool of choice for teasing apart direct genetic effects--causal effects of ones genotype on ones own phenotype-- from other factors. However, due in part to their smaller sample sizes, sib-GWAS allelic effect estimates are substantially more variable than standard (i.e., population-based) GWAS estimates. The quantification of this uncertainty is essential for many uses of sib-GWAS, including polygenic scoring, causal inference (e.g., Mendelian randomization), disentangling direct from indirect familial effects, and measuring assortative mating. Here, we investigate sources of uncertainty in sib-GWAS allelic effect estimators. We study their impacts on the biases of three uncertainty measurement methods, including two that are commonly used and a new resampling-based approach we propose. We find that heterogeneity in allelic effects or heteroskedasticity across families (e.g., due to variation in genetic backgrounds or environments) can bias existing methods, and that this bias is more severe for small samples and rare variants. In contrast, the resampling-based approach we propose is approximately unbiased under all scenarios we considered. We validate our theoretical predictions, as well as the importance of effect heterogeneity and heteroskedasticity, using simulations and empirical analysis in the UK Biobank. In sum, this study helps understand the sources of uncertainty in family-based genotype-phenotype association studies and provides a robust method to estimate uncertainty.

BackgroundFathers adolescent smoking and overweight affect respiratory health in offspring, suggesting that paternal puberty exposures may influence offspring biological ageing through preconception epigenetic mechanisms. MethodsWe analyzed epigenetic age acceleration using four validated epigenetic clocks derived from blood DNA methylation in 892 RHINESSA offspring (mean age 27 years), linked to parental data on smoking and body shapes from RHINE/ECRHS. Linear regression examined parental smoking initiation ([&le;]15 or >15 years) and overweight body shape (childhood/puberty or age 30) in relation to offspring epigenetic age acceleration, adjusting for offspring sex, age and parental socioeconomic status. Sensitivity analyses accounted for offspring smoking and BMI. ResultsPCHorvath ({beta} 1.53; 95% CI 0.02, 2.9), PCGrimAge (1.21; 0.03, 2.1), DunedinPACE (0.04; -0.001, 0.1) and PCPhenoAge (1.92; -0.3, 4.2) were accelerated in daughters of fathers who started smoking [&le;]15 years. Likewise, PCHorvath (2.25; 1.2, 3.3), PCGrimAge (1.36; -0.2, 2.9), DunedinPACE (0.07; 0.01, 0.1) and PCPhenoAge (3.11; 1.8, 4.4) were accelerated in daughters and sons of fathers who had been overweight in childhood and puberty. These results remained largely unchanged after additional adjustments or stratification in sensitivity analyses. No associations were found for maternal smoking or overweight in puberty. ConclusionsEpigenetic ageing is accelerated in offspring of fathers who smoked or were overweight in puberty, independent of offspring lifestyle. These findings suggest that adolescent boys environment and lifestyle may be critical for next-generation health. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/26352444v1_fig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1eea189org.highwire.dtl.DTLVardef@1af41f4org.highwire.dtl.DTLVardef@1132932org.highwire.dtl.DTLVardef@f5ba2c_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO Graphical abstract Legend to graphical abstract Figure Fathers smoking or overweight during puberty was associated with accelerated epigenetic aging in offspring (n=892), independent of the offsprings own lifestyle. No such pattern was observed for maternal puberty exposures, or when paternal exposures occurred after puberty. Male puberty may be a critical window for next-generation health. C_FIG

Ocular measures are increasingly used as non-invasive proxies of cognitive processes such as attention and listening effort. However, their interpretation in aging populations is complicated by concurrent changes in ocular physiology and oculomotor control, raising a critical question: to what extent do age-related differences in these measures reflect cognitive rather than other physiological factors? Here, we dissociate these contributions by characterizing ocular dynamics (resting and event-evoked) during passive fixation in younger (N = 98, 18-35 years) and older adults (N = 71, 60+ years). Aging is associated with pronounced alterations in pupil dynamics, including reduced baseline variability and slower, attenuated responses to both auditory and visual events. In contrast, microsaccade dynamics did not correlate with aging. Across measures, ocular responses showed moderate-to-high within-subject stability across blocks, and factor analysis in the older cohort revealed separable components reflecting instantaneous pupil responsivity, sustained pupil responsivity, and microsaccade dynamics, with additional variance associated with sensory decline and age-related changes in pupil dynamics. Together, these findings demonstrate a clear dissociation: pupil-based metrics are strongly influenced by aging, whereas microsaccades remain comparatively stable across age groups. This dissociation provides a principled basis for interpreting ocular indices in aging research and highlights the need to account for baseline physiological differences when inferring cognitive processes from eye-based measures.

Background: It is well-established that males have a higher mortality risk than females. Immune cells and their function are known to undergo characteristic changes during aging, and immune cells are known to have sex differences. Immune cells and their function have been linked to mortality risk, but no studies have investigated to what degree, if at all, Immune Cell Biomarkers (ICBs) contribute to the known differences in mortality risk by sex. Methods: Using participant data from the Health and Retirement Study (n = 8,822), we applied multivariable linear regressions adjusting for age, cytomegalovirus (CMV) serostatus, sex, and race/ethnicity to identify differences by sex in 48 immune cell biomarker (ICB, e.g. T cells, B cells, Monocytes, etc.) percentages and counts (measured in 2016). We studied how the associations between ICBs and mortality risk differ by sex using stratified Cox Proportional Hazard (CPH) models. We estimated how inclusion of sex explained the relationship between ICBs and all-cause mortality, and conversely, how inclusion of individual and all ICBs combined explain the relationship between sex and all-cause mortality using multivariable modeling approaches. Results: Differences in ICBs by sex range between 2-38% (39/48 statistically significant). 9 ICBs were significantly associated with mortality risk in the entire sample. While different ICBs were significantly associated with mortality risk in the stratified analyses, particularly with respect to monocyte, B cell, and NK cell populations, adjusting for sex modestly influenced the hazard ratios of the ICBs (sex: 8 ICBs, percent change <5.4%). Furthermore, individual and cumulative contributions of ICBs in explaining the differences in mortality risk by sex were not significant.

Evidence from many countries shows that later life cognitive health is shaped by childhood poverty. However, whether it is associated with neurodegenerative biomarkers measured in population settings remains unclear. Methods We conducted a pooled analysis of 5,473 adults aged [&ge;]50 years from Denmark, Sweden and Germany participating in Wave 6 (2015) of the Survey of Health, Ageing and Retirement in Europe. Neurodegenerative biomarkers (neurofilament light chain, glial fibrillary acidic protein and phosphorylated tau) were assayed from dried blood spots. Childhood poverty was constructed as a latent variable from retrospective life histories. Weighted Poisson regression models estimated associations adjusting for age, sex, education, marital status and wealth in later life. Marginal predictions along age and across country were derived. Results Childhood poverty was strongly associated with higher NfL concentrations ({beta}=1.66, p<0.001), but not with GFAP or p-tau217. Predicted values indicated substantially elevated NfL among the childhood poor (10.3 pg/mL vs 2.0 pg/mL for the non-poor). Age profiles showed widening disparities: the childhood poor in midlife exhibited higher NfL levels than the oldest old who grew up not poor. No consistent differences were observed for GFAP or p-tau217. Findings were robust and similar across all three countries with different histories and health systems. Conclusions Childhood poverty is associated with markedly elevated levels of NfL in later life, suggesting long-term neuroaxonal injury consistent with life course shaping of brain health. Moreover, the evidence implies substantial acceleration of neurobiological ageing. These findings emphasise the importance of early-life interventions for brain health in ageing populations.

Adult ADHD is increasingly recognized across the lifespan, yet the psychometric equivalence of the Adult ADHD Self-Report Scale (ASRS) remains unverified for older populations. This study examined age-related Differential Item Functioning (DIF) in 600 adults (n = 100 per decade, ages 20-80) who completed the 18-item ASRS. Using a bi-factor Graded Response Model, we extracted latent ADHD trait scores ({omega}H = .895) and assessed DIF via ordinal logistic regression with adaptive age modeling. Five of 18 items exhibited significant uniform DIF. At equivalent latent severity, older adults were less likely to endorse hyperactivity symptoms in Part A (fidgeting, feeling "driven by a motor") but more likely to endorse specific symptoms in Part B (careless mistakes, misplacing items, interrupting). From ages 20 to 80, expected Part A scores decreased by 1.36 points (~0.27 per decade), while Part B scores increased by 1.15 points (~0.23 per decade). These findings indicate a phenotypic redistribution of ADHD symptoms as individuals age. Because the 6-item Part A screener serves as the primary clinical gatekeeper, its concentration of negative DIF suggests standard screening practice may systematically underestimate ADHD severity in older adults. We recommend using the full 18-item ASRS when screening older populations and suggest that developing age-adjusted norms would improve diagnostic accuracy.

Background: Epigenetic clocks based on DNA methylation (DNAm) have emerged as promising biomarkers of biological aging, yet their associations with cognitive performance remain inconsistent. This study investigates the relationship between epigenetic age acceleration and cognitive performance in older adults using 14 DNAm clocks from five generations of development. Methods: We analyzed data from the Berlin Aging Study II (BASE-II) using genome-wide DNAm profiles and cognitive assessments ascertained at baseline (T0) and two follow-up time points (T1, T2) in up to 1,014 individuals. DNAm-based age and age acceleration estimates were calculated using Biolearn and MethylCIPHER. Analyses focused on cross-sectional and longitudinal associations between DNAm clock estimates and cognitive performance, including sex-specific effects and comparisons with frailty as non-cognitive positive control. Results: Among all tested DNAm clocks, DunedinPACE (a third-generation clock) showed the strongest and most consistent associations with cognitive performance. In addition, the fifth-generation SystemsAge framework also demonstrated robust associations with cross-sectional and longitudinal cognitive outcomes. In contrast, second-generation clocks (GrimAge [v2], PhenoAge) showed occasional nominal associations, while first-generation clocks (Horvath [v1], Hannum) and the causally-informed, fourth-generation clocks (e.g. YingCausAge, YingDamAge) showed no noteworthy signals. Likewise, telomere length estimated from DNAm was not strongly associated with cognitive performance in this dataset. Conclusions: Our findings highlight DunedinPACE as a particularly informative biomarker for various aspects of cognitive aging, while other DNAm aging measures showed no consistent associations. Future work should further refine domain-specific epigenetic biomarkers to improve biological aging assessments and achieve a more reliable early detection of cognitive decline.

BackgroundScreen use is pervasive in childhood and adolescence, yet its role in antisocial behaviour (ASB) remains uncertain. While cross-sectional studies consistently link higher screen use to elevated ASB, longitudinal evidence is mixed, and few studies have controlled adequately for prior behaviour and genetic liability. Thus, it remains unclear whether these associations reflect prospective influences of screen exposure, or underlying vulnerabilities shared with ASB. We investigated whether screen use is a modifiable risk factor or a marker of underlying vulnerability. MethodsWe analysed data from up to 41,562 children in the Norwegian Mother, Father, and Child Cohort Study (MoBa). ASB traits and ICD-10-based conduct disorder (CD) diagnoses were assessed at ages 5, 8 and 14 years, together with screen use (total exposure and modality). Cross-sectional logistic regression models examined associations between screen use and ASB traits/CD at each age, adjusting for sex and parental education. Polygenic risk scores for ASB (PRSASB) were used to assess genetic susceptibility and gene-environment interplay. Lagged logistic models tested whether screen use predicted later ASB, adjusting for prior ASB. Linear mixed-effects models examined developmental patterns across age. ResultsHigher screen use was positively associated with ASB traits and CD across all ages, with dose-response patterns across screen-use modalities. Social media showed the strongest modality-specific association at adolescence. In lagged models, screen use did not predict later ASB after adjustment for prior ASB. Longitudinal models showed significant but attenuating associations across development. PRSASB was independently and additively associated with ASB outcomes but did not interact with screen use. ConclusionsWe found that higher screen use was consistently associated with antisocial outcomes across childhood and adolescence. However, the absence of prospective associations after accounting for prior behaviour, together with independent genetic contributions, suggests that screen use may be better understood as a marker of underlying vulnerability rather than an independent driver of antisocial development.

Population ageing increases the importance of cognitive capacity for making decisions about retirement and living independently beyond it. We tested whether post-war educational expansion and working-life social mobility eliminate the association between social class of origin and cognition in early old age using the 1958 National Child Development Study. Two outcomes were analysed at age 62: standard episodic memory (immediate + delayed word recall) and long-term episodic memory, capturing accurate half-century recall of childhood household facts (rooms and people at age 11 validated against mothers responses). Social mobility trajectories derived in prior work were classified into predominantly manual versus non-manual class trajectories. Models were estimated separately for women and men across three specifications: (i) social origin and controls, (ii) adding social mobility, and (iii) adding weighting to address healthy survivor bias. Education was consistently associated with both outcomes. For long-term episodic memory, social origin gradients were clearer than for short-term episodic memory, with men from service/professional origins showing a 13 percentage-point higher probability of accurate half-century recall than men from manual origins. These findings indicate that education expansion and working-life social mobility failed to release the grip of social origin on long-term episodic memory.

Large-scale genomic studies have identified biomarkers of adult cognitive functioning and educational attainment, yet the developmental pathways connecting these biomarkers to adult outcomes remain unclear. Drawing on four cohorts, we examined the developmental correlates of an epigenetic index of adult cognitive function ( Epigenetic-g) alongside polygenic indices of cognition and education. Epigenetic-g and polygenic indices were uncorrelated and captured distinct variation in childrens cognitive and academic performance. Longitudinal analyses revealed that Epigenetic-g is plastic in early childhood, reaching moderate stability by adolescence, and, unlike polygenic indices, is not related to longitudinal cognitive growth. Twin models indicated that Epigenetic-g captures genetic and unique environmental variation relevant to cognitive and academic achievement that is not identified by current polygenic indices. Epigenetic indices relevant to psychological development can be generated from DNA methylation studies of adults, with most variation in these indices emerging early in life.