Behavior Genetics

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 ([≤]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 [≤]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.

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.

Intrinsic capacity (IC) summarizes functional health across multiple domains in healthy aging research, yet evidence on whether IC can be measured and tracked before older age remains limited. Using data from the 1958 British birth cohort at ages 50 and 62 (N = 7,804), we examined whether IC could be measured as a coherent, valid and longitudinally comparable construct from midlife to early old age. A second-order model applied to 30 indicators across sensory, cognitive, physical, psychological and vitality domains supported a five-domain IC construct, with scalar invariance across sweeps enabling comparison of scores over time. IC scores showed graded associations with self-rated health and chronic disease burden in the expected directions. Mean IC declined by 6.3 points on a 0-100 scale from age 50 to 62. These findings establish a basis for studying IC trajectories from midlife, before functional decline is usually clinically apparent.

Polygenic risk scores (PRS) improve progressively as genome-wide association studies (GWAS) increase in sample size and ancestral diversity, yet the effect of successive GWAS releases on individual PRS rankings remains poorly characterised. Here, we quantify how individual PRS rankings change across GWAS releases, whether those changes favour cases over controls, how consistently individuals maintain their relative position, and whether those in high-risk strata retain that classification over time. Using PRS derived from four GWAS releases for bipolar disorder, major depressive disorder, and schizophrenia in three Australian cohorts, we observed widespread bidirectional reclassification that exceeded the theoretical minimum of expected reclassification, and was directionally consistent with case-control status when discriminative performance improved. Rank variability was substantial and uniformly distributed across all levels of risk, rank persistence was limited across releases, and retention of high-risk classifications was variable across disorders and largely accounted for by the inter-release correlation. These findings demonstrate that individual PRS rankings are dynamic and shaped by progressive improvements in effect-size estimates, carrying important implications for PRS-based risk stratification strategies that rely on stable classifications in psychiatric research and clinical practice.

I ntroduction: Prospective memory (PM) deficits in children with attention-deficit/hyperactivity disorder (ADHD) significantly impact academic and daily functioning. Through two experiments, this study investigated how cognitive load and encoding strategies modulate PM performance. Methods: Experiment 1 included 43 children (21 ADHD, 22 typically developing) who completed an n-back task under high and low cognitive load. Experiment 2 included 44 children with ADHD who were randomly assigned to either a standard encoding group or an implementation intention encoding group, also completing the n-back task under both load conditions. Results: Experiment 1 showed that children with ADHD had significantly lower PM accuracy than typically developing peers. Signal detection analysis revealed that this deficit stemmed from a more conservative response bias rather than impaired perceptual sensitivity. Unexpectedly, PM accuracy and perceptual sensitivity were higher under high cognitive load than low load for both groups. Experiment 2 demonstrated that implementation intention encoding significantly enhanced PM accuracy and perceptual sensitivity in children with ADHD, with stable effects across load conditions and no interference with ongoing task performance. Discussion: These findings indicate that PM deficits in children with ADHD reflect a conservative response strategy rather than an inability to detect target cues. Implementation intention encoding provides an effective, load-independent cognitive strategy for enhancing PM performance. These results offer novel insights into the cognitive mechanisms underlying PM deficits in ADHD and provide evidence-based guidance for targeted interventions.

The persistence of a left-handed minority of slightly over 10% of the population is enigmatic because it is associated with stigma, increased psychopathology, and cognitive deficits. In a community sample of 9,352 individuals (age range 8-21 years) with neurobehavioral assessments, left-handers (N=1,281, 673 male) indeed showed greater psychopathology and performed more poorly than right-handers (N=8,076, 3,839 male) on tests of executive function, memory, complex cognition, and social cognition, while excelling in motor speed. Furthermore, the variance was higher and within-individual variability (WIV) - the extent to which scores in the different domains varied within individuals - was higher in left-handers. Since low WIV indicates even distribution of abilities while high WIV reflects specialization in circumscribed areas, the finding indicates that left-handers are "neurocognitive specialists". This combination of behavioral traits could confer resilience against natural selection pressures and help explain preponderance of left-handers in highly specialized professions requiring specific talents. Our findings encourage more research on left-handers, who are currently excluded from multiple brain behavior studies.

Within species, male testosterone is often linked to mating competition and paternal care, suggesting that sex differences in endogenous testosterone values across mammals may covary with broader reproductive strategies. Using a structured literature search, we compiled 63 studies, spanning 31 non-human species and 9 human populations, reporting endogenous, non-experimentally manipulated testosterone values for both adult males and females within the same population and context. From these studies, we calculated male-to-female testosterone ratios, and analysed these data using Bayesian phylogenetic multilevel models. We tested whether testosterone dimorphism was associated with paternal care and sexual size dimorphism while accounting for sampling matrix, assay method, breeding context, and wild versus captive setting. Across non-human mammals, neither paternal care nor sexual size dimorphism (indexing competition) showed a clear association with testosterone ratios, and the same pattern emerged in the primate-only subset. By contrast, sampling matrix was consistently associated with testosterone dimorphism across all analyses, with lower male-to-female ratios in non-blood than in blood-based measures. In primates, testosterone ratios were also lower in captive than in wild populations, although this pattern was not clearly supported in the broader non-human dataset. In the human-only analysis, testosterone ratios did not clearly differ between industrialized and small-scale societies, whereas the matrix effect remained evident. Overall, our results suggest that sampling matrix is a major source of variation even for ratio-based measures, highlighting the need for caution when inferring between-species endocrine differences from studies using different substrates. More broadly, directly comparable, non-experimentally manipulated testosterone data for both sexes remain rare across mammals, limiting comparative inference.

Population fertility patterns are closely linked to socioeconomic inequality, with educational attainment (EA) being a key predictor of completed fertility. While EA is partially heritable, the extent to which EA-associated genetic variation relates to fertility independently of education remains unclear, particularly outside Western European and North American populations. Using data from [~]40,000 women and [~]10,000 men in the Estonian Biobank, we examine sex-specific associations between EA polygenic scores (PGSEA) and completed fertility. We extend prior work by distinguishing cognitive and non-cognitive EA components, accounting for age at first pregnancy (AFP), and applying within-family analyses to assess the role of direct genetic effects. Among women, PGSEA is negatively associated with fertility, with a significantly stronger association for the non-cognitive than the cognitive EA polygenic score. The association between PGSEAand fertility is moderated by EA and changes sign across AFP strata, from negative among women with earlier AFP to positive among those with later AFP. Importantly, this association is not attenuated in within-family models, consistent with a predominant role of direct genetic effects. Among men, associations are weak or slightly positive and stable across education groups. Overall, EA-related genetic variation is associated with fertility through pathways that appear largely independent of educational attainment, suggesting that shared genetic influences operate through multiple mechanisms that differ by sex and reproductive timing. SignificanceEducational attainment is closely linked to completed fertility, yet the mechanisms behind this relationship remain not fully understood. Using a population-based cohort from Estonia, we show that genetic variants associated with education relate to fertility in markedly different ways for women and men and that these associations cannot be explained by education level alone. Differences between cognitive and non-cognitive education-related genetic components further point to multiple life-course pathways linking genetics and reproduction. Family-based analyses suggest that these associations are largely consistent with direct genetic effects and not driven by correlated family environments. Together, our findings suggest that education-related genetic variation shapes fertility through multiple sex-specific and life-course-dependent pathways, rather than acting solely through educational attainment.

Adolescence is a critical developmental window for the emergence of substance use and psychosis-spectrum symptoms, yet early risk for these outcomes remains poorly understood. Using longitudinal data from the Adolescent Brain Cognitive Development (ABCD) Study (n=10,134), we tested whether demographic, clinical, and structural and functional neuroimaging measures assessed in childhood (mean baseline age=9.96 years) predict later adolescent substance use, psychotic-like experiences, and/or their co-occurrence. Multivariate machine learning models reliably predicted later emergence of psychotic-like experiences (AUROC=0.780) and their co-occurrence with substance use (AUROC= 0.828), as well as substance use on its own (AUROC=0.626). Distinct patterns of functional brain connectivity, task-related brain activation, demographic, and clinical factors differentiated each outcome. Findings suggest that partially dissociable developmental risk profiles are detectable as early as childhood, and results underscore the importance of explicitly modeling comorbidity when interrogating risk factors for mental health outcomes.

Abstract Background Gene dosage disorders impact cognition and psychopathology, but outcomes vary widely amongst carriers of the same variant. Recent work has sought to better predict proband outcomes using measures of corresponding traits in family members. However, family-based models have not yet been prospectively quantified across several traits in different genetic disorders, nor evaluated for the precision they afford: both crucial issues for clinical implementation. Methods In a first test case for these questions, we apply regression analyses to quantify and compare family-based prediction of 12 traits (including IQ, autism- and ADHD-related traits) in 433 individuals from families including a proband with XXY or XYY syndrome (N=93 and 58, respectively). Results The 12 traits vary substantially in their proband-family associations (0.001<|r|<0.55) - with differences emerging between XXY and XYY syndrome. Only two traits also show significant and similar proband-family associations in both aneuploidies, with the greatest concordance found for IQ. A family-based model for IQ prediction in male sex chromosome trisomies significantly reduces error vs. a group mean IQ model (F = 7.4, p = 0.006), but only in 65% of probands, and with mean error reduction of ~2 IQ points. Conclusions Family-based prediction of neuropsychiatric traits in genetic syndromes likely requires trait- and syndrome- specific models. Family models can significantly improve outcome prediction for IQ, but to variable degrees across individuals and with a small mean improvement. By mapping and quantifying these limits, our work helps draft a roadmap for refinement of family-based prediction of proband outcomes in gene dosage disorders.

Aim: To determine whether the neural phenotype (whole-brain resting-state functional connectivity pattern) of attention deficit hyperactivity disorder associated with prenatal alcohol exposure (ADHD+PAE) differs from that in unexposed children with ADHD of probable familial origin (ADHD-PAE). Method: Resting-state functional MRI was acquired from 26 children with ADHD+PAE, 25 with ADHD-PAE, and 25 typically developing (TD) children, all aged 8-13 years. Mean connectivity matrices based on the Cole-Anticevic Brainwide Network Parcellation of the brain were compared between the groups. Results: Within the frontoparietal network (FPN), children with ADHD+PAE showed widespread lower group-mean connectivity than children with ADHD-PAE; effects were concentrated primarily in cerebellar-cerebral cortical and cerebral cortical-cerebral cortical connections. Children with ADHD-PAE showed widespread hyperconnectivity relative to TD children. Children with ADHD+PAE showed mixed hyper- and hypoconnectivity relative to TD. Interpretation: These results are consistent with other MRI findings indicating that ADHD+PAE is neurally distinct from ADHD-PAE; PAE may be associated with broadly reduced connectivity, especially across cerebellar-cerebral cortical systems.

Studies of protein quantitative trait loci (pQTLs) provide opportunities to interpret complex trait genetics and identify potential biomarkers and therapeutic targets. Circulating proteins are commonly used in pQTL studies due to the accessibility of blood-based measurements, but their levels may not always reflect regulation in disease-relevant tissues. We assessed colocalization and discordance between plasma and dorsal prefrontal cortex cis-pQTLs using data from four large-scale studies and investigated their implications for downstream analyses. Across the proteins examined, at most 80% of the cis-pQTLs showed evidence of colocalization. Among the colocalized loci, approximately 20% exhibited opposite directions of genetic effects. We characterized tissue-specific gene expression profiles based on data from the Genotype-Tissue Expression project. Proteins with colocalized cis-pQTLs were more likely to have high gene expression levels in systemic tissues and immune cells, whereas the remaining proteins were more likely to have high expression in brain tissues. We conducted Mendelian randomization (MR) analyses using neuroticism as an illustrative outcome to compare effect estimates derived using instruments from different pQTL studies. MR analyses identified 13 proteins significantly associated with neuroticism, including six with opposite effect directions between plasma and dorsal prefrontal cortex, highlighting the importance of tissue context. Overall, circulating pQTLs remain informative for proteins from systemic and immune pathways, while incorporating tissue-specific data may provide additional insight for proteins with more localized expression. Considering multiple tissue contexts may refine the interpretation of protein-trait associations and may improve the prioritization of candidate targets.

Social interactions are ubiquitous in nature and have the potential to affect trait evolution, particularly in group-living animals such as cooperative breeders. Interactions among conspecific individuals can affect the amount of additive genetic variation for a trait when the phenotype of an individual is also affected by the genotype of its social partner(s) via indirect genetic effects. Thus, quantifying both direct and indirect genetic effects of social partners is critical for understanding and predicting evolutionary trajectories. While much is known about maternal indirect genetic effects, empirical estimates of indirect genetic effects from other social partners remain limited, particularly in wild populations. Here, we use animal models to assess the contribution of indirect genetic effects from all social partners in a family group (mothers, fathers, and helpers) on juvenile morphometric traits across ontogeny in the cooperatively-breeding Florida scrub-jay (Aphelocoma coerulescens). We found indirect genetic effects of helpers and fathers on nestling weight, but no indirect genetic effect of mothers. Across ontogeny, we found increasing additive genetic variation in both weight and tarsus length. Our study provides a comprehensive assessment of within-group indirect genetic effects in a cooperative breeder and highlights the importance of considering indirect genetic effects beyond maternal effects.

Background: Prior neuroimaging suggests brain differences between children with attention deficit hyperactivity disorder due to prenatal alcohol exposure (ADHD+PAE) and non-exposed children with ADHD due to other, e.g., familial, causes (ADHD-PAE). There has been interest in regional brain levels of ;gamma-aminobutyric acid (GABA) and glutamate (Glu) measured in vivo with magnetic resonance spectroscopy (MRS) as possible indicators of local inhibitory, respectively, excitatory activity in ADHD. For the first time, we report here a comparison of GABA and Glu in ADHD+PAE vs. ADHD-PAE. Methods: At 3 T, we used J-difference-edited single-voxel MRS to assay GABA and Glu in 28 children with ADHD+PAE, 20 with ADHD-PAE, and 28 typically developing (TD) controls, all aged 8-14 years. MRS was sampled from midline anterior middle cingulate cortex (aMCC), the cognitive cingulate considered functionally relevant to ADHD. Spectra were fit with custom software, including a unique technique for isolating the GABA signal from the confounding macromolecular baseline (MMBL). Results: aMCC GABA was higher in ADHD+PAE and ADHD-PAE than in TD. GABA increased with age in TD, but not in ADHD+PAE or ADHD-PAE. Similar effects were observed for the ratios GABA/Glu and GABA/Glx. For GABA+MMBL (GABA+) these effects were not seen, rather GABA+ and MMBL increased with age for the ADHD+PAE group only. No significant effects were found for Glu or Glx. Conclusions: GABA in the aMCC does not distinguish the two etiologies of ADHD, rather elevated GABA that follows an abnormal developmental appears to be common to both. High GABA may reflect increased inhibition of the aMCC impairing its cognitive functions. GABA+ results in ADHD may not tract reliably with underlying GABA values. Negative results for Glu and Glx should be reexamined at shorter echo-times.

Autism spectrum disorder (ASD) is estimated to be up to four times as common in males as in females, yet the causes of this prevalence difference are not well established. One possible driver is genetic variation on the X chromosome, as it contains genes capable of contributing to ASD (e.g., PTCHD1, MECP2) and is known to play a role in genetic disorders with differential sex prevalence (e.g., color blindness). However, a lack of power compared to the autosomes combined with the complexities of modeling its biology have led to the X being largely overlooked in sequencing studies. Here, we develop quantitative X-linked TADA, a new model designed specifically for application to this chromosome, and use it to analyze rare variation from 50,663 individuals with ASD (and 136,670 individuals total). We find 9 genes on the X associated with ASD at a false discovery rate (FDR) < 0.05 and an additional 9 genes at FDR < 0.2, with many of these previously identified as involved in specific neurodevelopmental disorders. Point estimates of the liability conferred by de novo variants on the X are similar in females and males, with both sexes estimates elevated >20% above the corresponding autosomal values. We also develop a general theory of how X-linked variation of any additive or non-additive effect influences liability and describe its implications for prevalence. Using this theory and our empirical results, we show how genetic variation on the X could contribute to the sex-differential prevalence of ASD.