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ImportancePsychiatric disorders can have an immense impact on socioeconomic, physical, and social-psychological facets of life. Psychiatric disorders are also highly heritable. Under a liability threshold model, an important question arises as to what extent genetic liability for psychiatric disorders relates to, and possibly impacts on, different aspects of quality of life in the general population.ObjectiveTo characterize the link between psychiatric genetic liability and diverse aspects of quality of life in childhood and adulthood.Design, setting, and participantsWe used data from two multi-site, population-based cohorts, i.e. preadolescent children in the USA enrolled at age 9-10 years from the Adolescent Brain Cognitive Development (ABCD) study (N=4,645) and white British adults between age 40-69 years from the UK Biobank (UKB) study (N=377,664). Due to the current limitations of our genetic methods, only data from unrelated individuals of European descent could be included.Main outcomes and measuresTo derive robust measures capturing multiple domains of quality of life in each of the cohorts, we integrated an array of measurements of academic, economic, and physical status, as well as social well-being, in a second-level three-factor confirmatory factor analysis. The genetic liabilities to seven major psychiatric disorders were quantified by a set of polygenic scores (PGSs) derived from the largest genome-wide association studies to date, independent of the target cohorts, of major depressive disorder (MDD, N=142k-173k), anxiety disorders (ANX, N=22k-144k), attention-deficit/hyperactivity disorder (ADHD, N=226k), autism spectrum disorder (ASD, N=55k), schizophrenia (SCZ, N=130k), bipolar disorder (BIP, N=353k-414k), and cannabis use disorder (CUD, N=384k). Using general linear models we assessed associations between PGSs and the estimated latent factors, controlling for age, sex, site, genotyping batch, plate, and genetic ancestry.ResultsIn each cohort, three latent factors indexing distinct but correlated quality of life domains, (1) educational performance and cognition (Edu, in ABCD) / social economic status (SES, in UKB), (2) physical health (Hea), (3) adverse social experience (Adv, in ABCD) / social well-being (Soc, in UKB), were estimated with excellent model fit indices. In addition, a general factor was derived that captured the covariances between the three latent factors (QoL). In the ABCD cohort, ADHD-PGS was significantly associated with Edu (β = -0.13, t = -8.29, p = 1.53e-16), Adv (β = -0.09, t = -5.79, p = 7.81e-09), and general QoL (β = -0.14, t = -8.74, p = 3.37e-18) factors. In the UKB cohort, all examined disorder PGSs were significantly associated with the general QoL latent factor and at least one first-order subdomain, with ADHD-PGS (β = -0.06 ∼ -0.10, t = -29.1 ∼ -52.5, p < 5.91e-186) and MDD-PGS (β = -0.04 ∼ -0.07, t = -23.8 ∼ -36.3, p < 3.63e-125) showing the largest effects.Conclusions and relevanceThe present study reveals an inverse relationship between psychiatric genetic liabilities and multiple quality of life metrics, with ADHD-associated genetic risk being the main contributor in both children and adults, and MDD additionally showing effects in adults. All effect sizes observed were small, as expected. Understanding potential real-world outcomes of quantitative measures of disorder-related genetic risks in the general population can provide a scientific foundation for societal intervention and policy-making processes, with profound implications for promoting a flourishing society.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by age-inappropriate levels of inattention and/or hyperactivity-impulsivity. ADHD has been related to differences in white matter (WM) microstructure. However, much remains unclear regarding the nature of these WM differences and which clinical aspects of ADHD they reflect. We systematically investigated whether fractional anisotropy (FA) is associated with current and/or lifetime categorical diagnosis, impairment in daily life, and continuous ADHD symptom measures.METHODS: Diffusion-weighted imaging data were obtained from 654 participants (322 unaffected, 258 affected, 74 subthreshold; 7-29 years of age). We applied automated global probabilistic tractography on 18 major WM pathways. Linear mixed-effects regression models were used to examine associations of clinical measures with overall brain and tract-specific FA.RESULTS: There were significant interactions of tract with all ADHD variables on FA. There were no significant associations of FA with current or lifetime diagnosis, nor with impairment. Lower FA in the right cingulum angular bundle was associated with higher hyperactivity-impulsivity symptom severity (pfamilywise error = .045). There were no significant effects for other tracts.CONCLUSIONS: This is the first time global probabilistic tractography has been applied to an ADHD dataset of this size. We found no evidence for altered FA in association with ADHD diagnosis. Our findings indicate that associations of FA with ADHD are not uniformly distributed across WM tracts. Continuous symptom measures of ADHD may be more sensitive to FA than diagnostic categories. The right cingulum angular bundle in particular may play a role in symptoms of hyperactivity and impulsivity.

IntroductionHuman brain structure and function, as measured using magnetic resonance imaging (MRI), is heritable. The genetic associations are highly polygenic and pleiotropic, complicating translation of genetic association studies to concrete biological processes. We recently proposed genomic independent component analysis (ICA) to reduce a large array of genome-wide association study (GWAS) statistics into a number of more interpretable multivariate components. Here, we extend this work with genomic principal component analysis (PCA). We also estimate the inter-trait stability and test-retest reliability of genomic PCA and ICA. As a benchmark, we provide a head-to-head comparison with the reproducibility of original (i.e., raw univariate) GWAS variant effect sizes from which the components were derived.MethodsWe considered summary statistics of two rounds of brain MRI GWAS in UK biobank encompassing 22,138 and 11,086 subjects and thousands of imaging-derived phenotypes (IDPs) retrieved from Oxford BIG-40 server. We decomposed the clumped brain-wide genome-wide matrix (n=157,893 variants and m=2,240 brain IDPs) by PCA and ICA to obtain up to 50 principal and independent genome-wide components. We tested the reproducibility of these genomic components using tail overlap coefficient and Pearson’s correlation. Decompositions were repeated 20 times on randomly permuted split-half matrices to arrive at an empirical distribution of the above reproducibility metrics. As a benchmark, we also provide comparisons with the reproducibility of the original univariate GWAS effect sizes from which the components were derived.ResultsThe first ten principal genomic components were highly stable across trait-subsets within samples (r=0.82±0.15; mean ± standard deviation). PCA cross-sample reproducibility dropped to r=0.16±0.07 (r-max=0.30) was still a substantial improvement over univariate GWAS reproducibility r=0.09±0.05. ICA components showed higher within-sample reproducibility at lower dimensions (ICA dimension-5: r=0.81±0.16 vs. ICA dimension-50: r=0.41±0.13). The same trend was observed for their cross-sample reproducibility, achieving an r-max of 0.27 at the lowest ICA dimension of five (average r=0.20±0.3) vs. r-max of 0.11 at dimension 50 (average r=0.05±0.02).ConclusionOverall, the cross-sample reproducibility of PCA and ICA components are moderate, but considerably better than the reproducibility of the raw univariate GWAS effect sizes. Genomic PCA identified highly reproducible and pleiotropic genomic effects across many brain traits in just 1-3 factors. Genomic ICA captured mutually independent genome-wide effects that may be more sensitive to distinct biological pathways. As GWAS samples continue to increase and more (endo)phenotypes become available in biobanks, multi-trait genome-wide associations of the brain decomposed by ICA and PCA will likely become more reproducible and interpretable.

Genome-wide association studies (GWAS) indicate neuropsychiatric disorders to be highly polygenic. Polygenicity refers to the additive influence of multiple genes on variation in a disorder. GWAS have identified many single-nucleotide polymorphisms (SNPs) across the genome associated with neuropsychiatric disorders, each explaining a very small part of individual variance within a trait. This complicates the understanding of the genetic architecture and biological mechanisms underlying these disorders. Previous studies have successfully used common genetic variants associated psychiatric disorders to generate Polygenic Risk scores (PRS). PRSs estimate the aggregate genetic liability of an individual for a particular disorder or trait based on a genome-wide association study (GWAS) of said trait. Here, we present a novel bottom-up approach to polygenic scoring that starts at the brain, rather than at behavior or clinical diagnosis. We used GWAS of structural brain imaging derived phenotypes (IDPs) from the UK Biobank as a basis to generate polygenic imaging derived scores (PIDS). As a proof-of-concept of its application, we applied PIDS to quantify differences in the genetic influence on brain structure between persons with ADHD and unaffected controls. 94 IDPs were selected using the subcortical segmentation atlas and the Desikan-Killiany cortical atlas from FreeSurfer. In the polygenic model training stage, 72 out 94 PIDS were associated with their respective IDP in an independent sample. Global measures such as cerebellum white matter, cerebellum cortex and cerebral white matter ranked amongst the highest in variance explained ranging between 3% and 5.7%. Our results indicate that a majority of GWAS of structural neuroimaging traits are becoming sufficiently powered to enable reliable and meaningful use of polygenic scoring applications that accurately reflect the underlying polygenic architecture well. Larger discovery GWAS will further improve upon this. Conversely, our associations with ADHD were relatively weak. Larger target samples are required to establish robust links of PIDS with behavioral or clinical traits like ADHD. With this novel approach to polygenic risk scoring we provide a new tool for other researchers to build on in the field of psychiatric genetics.

The dense co-occurrence of psychiatric disorders questions the categorical classification tradition and motivates efforts to establish dimensional constructs with neurobiological foundations that transcend diagnostic boundaries. In this study, we examined the genetic liability for eight major psychiatric disorder phenotypes under both a disorder-specific and a transdiagnostic framework. In a deeply-phenotyped sample (n=513) consisting of 452 patients from tertiary care with mood disorders, anxiety disorders, attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders (ASD), and/or substance use disorders (SUD) and 61 unaffected comparison individuals, we derived subject-specific multi-base polygenic risk score (PRS) profiles and assessed their associations with psychiatric diagnoses, comorbidity status, as well as cross-disorder behavioral dimensions. High PRS for depression was unselectively associated with the diagnosis of SUD, ADHD, anxiety disorders, mood disorders, and the comorbidities among them. In the dimensional approach, four distinct functional domains were uncovered, namely the negative valence, social, cognitive, and regulatory systems, closely matching the major functional domains proposed by the Research Domain Criteria (RDoC) framework. Critically, the genetic predisposition for depression was selectively reflected in the functional aspect of negative valence systems but not others. This study highlights a misalignment between current psychiatric nosology and the underlying psychiatric genetic etiology, and underscores the effectiveness of the dimensional approach in both the functional characterization of psychiatric patients and the delineation of the genetic liability for psychiatric disorders.

Contains fulltext : 251409.pdf (Publisher’s version ) (Open Access) BACKGROUND: Attention-deficit hyperactivity disorder (ADHD) is associated with white matter (WM) microstructure. Our objective was to investigate how WM microstructure is longitudinally related to symptom remission in adolescents and young adults with ADHD. METHODS: We obtained diffusion-weighted imaging (DWI) data from 99 participants at two timepoints (mean age baseline: 16.91 years, mean age follow-up: 20.57 years). We used voxel-wise Tract-Based Spatial Statistics (TBSS) with permutation-based inference to investigate associations of inattention (IA) and hyperactivity-impulsivity (HI) symptom change with fractional anisotropy (FA) at baseline, follow-up, and change between time-points. RESULTS: Remission of combined HI and IA symptoms was significantly associated with reduced FA at follow-up in the left superior longitudinal fasciculus and the left corticospinal tract (CST; P (FWE) = 0.038 and P (FWE) = 0.044, respectively), mainly driven by an association between HI remission and follow-up CST FA (P (FWE) = 0.049). There was no significant association of combined symptom decrease with FA at baseline or with changes in FA between the two assessments. CONCLUSIONS: In this longitudinal DWI study of ADHD using dimensional symptom scores, we show that greater symptom decrease is associated with lower follow-up FA in specific WM tracts. Altered FA thus may appear to follow, rather than precede, changes in symptom remission. Our findings indicate divergent WM developmental trajectories between individuals with persistent and remittent ADHD, and support the role of prefrontal and sensorimotor tracts in the remission of ADHD.

Contains fulltext : 251347.pdf (Publisher’s version ) (Open Access) While pharmacological treatment with methylphenidate (MPH) is a first line intervention for ADHD, its mechanisms of action have yet to be elucidated. We here seek to identify the white matter tracts that mediate MPH's effect on beta oscillations. We implemented a double-blind placebo-controlled crossover design, where boys diagnosed with ADHD underwent behavioral and MEG measurements during a spatial attention task while on and off MPH. The results were compared with an age/IQ-matched control group. Estimates of white matter tracts were obtained using diffusion tensor imaging (DTI). Via a stepwise model selection strategy, we identified the fiber tracts (regressors) significantly predicting values of the dependent variables of interest (i.e., oscillatory power, behavioral performance, and clinical symptoms): the anterior thalamic radiation (ATR), the superior longitudinal fasciculus ("parietal endings") (SLFp), and superior longitudinal fasciculus ("temporal endings") (SLFt). ADHD symptoms severity was associated with lower fractional anisotropy (FA) within the ATR. In addition, individuals with relatively higher FA in SLFp compared to SLFt, led to stronger behavioral effects of MPH in the form of faster and more accurate responses. Furthermore, the same parietotemporal FA gradient explained the effects of MPH on beta modulation: subjects with ADHD exhibiting higher FA in SLFp compared to SLFt also displayed greater effects of MPH on beta power during response preparation. Our data suggest that the behavioral deficits and aberrant oscillatory modulations observed in ADHD depend on a possibly detrimental structural connectivity imbalance within the SLF, caused by a diffusivity gradient in favor of parietal rather than temporal, fiber tracts.

General factors capturing the shared genetics in psychiatric (genomic p-factor) and cognitive traits (genomic g-factor), and more recently in resting-state functional magnetic resonance imaging-derived brain networks, have contributed to our increased understanding of the etiologies in their respective domains. Yet it remains unclear whether general factors can capture the three-way genetic overlap of psychopathology, cognition and brain function. Here we tested for the presence of this genetic overlap via genetic correlation analyses using summary statistics of genome-wide association studies of the p-factor (N = 162,151 cases and 276,846 controls), the g-factor (N = 269,867), and the two genomic factors estimated from the amplitude in resting-state functional magnetic resonance imaging-derived brain networks (N = 31,688). Unlike hypothesized, only the genetic correlation between the p-factor and the g-factor was significant. We conclude that specific functional brain network constructs may have more potential than their derived general dimensions to capture relevant genetic variation for cognition and psychopathology.

BackgroundVariation in the longitudinal course of childhood attention deficit/hyperactivity disorder (ADHD) coincides with neurodevelopmental maturation of brain structure and function. Prior work has attempted to determine how alterations in white matter (WM) relate to changes in symptom severity, but much of that work has been done in smaller cross-sectional samples using voxel-based analyses. Using standard diffusion-weighted imaging (DWI) methods, we previously showed WM alterations were associated with ADHD symptom remission over time in a longitudinal sample of probands, siblings, and unaffected individuals. Here, we extend this work by further assessing the nature of these changes in WM microstructure by including an additional follow-up measurement (aged 18 – 34 years), and using the more physiologically informative fixel-based analysis (FBA).MethodsData were obtained from 139 participants over 3 clinical and 2 follow-up DWI waves, and analyzed using FBA in regions-of-interest based on prior findings. We replicated previously reported significant models and extended them by adding another time-point, testing whether changes in combined ADHD and hyperactivity-impulsivity (HI) continuous symptom scores are associated with fixel metrics at follow-up.ResultsClinical improvement in HI symptoms over time was associated with more fiber density at follow-up in the left corticospinal tract (lCST) (tmax=1.092, standardized effect[SE]=0.044, pFWE=0.016). Improvement in combined ADHD symptoms over time was associated with more fiber cross-section at follow-up in the lCST (tmax=3.775, SE=0.051, pFWE=0.019). Conclusions: Aberrant white matter development involves both lCST micro- and macrostructural alterations, and its path may be moderated by preceding symptom trajectory.

Contains fulltext : 208627.pdf (Publisher’s version ) (Closed access) White matter microstructure is affected by immune system activity via the actions of circulating pro-inflammatory cytokines. Although white matter microstructure and inflammatory measures are significantly heritable, it is unclear if overlapping genetic factors influence these traits in humans. We conducted genetic correlation analyses of these traits using randomly ascertained extended pedigrees from the Genetics of Brain Structure and Function Study (N = 1862, 59% females, ages 18-97 years; 42 +/- 15.7). White matter microstructure was assessed using fractional anisotropy (FA) calculated from diffusion tensor imaging (DTI). Circulating levels (pg/mL) of pro-inflammatory cytokines (IL-6, IL-8, and TNFalpha) phenotypically associated with white matter microstructure were quantified from blood serum. All traits were significantly heritable (h(2) ranging from 0.41 to 0.66 for DTI measures and from 0.18 to 0.30 for inflammatory markers). Phenotypically, higher levels of circulating inflammatory markers were associated with lower FA values across the brain (r = -.03 to r = -.17). There were significant negative genetic correlations between most DTI measures and IL-8 and TNFalpha, although effects for TNFalpha were no longer significant when covarying for body mass index. Genetic correlations between DTI measures and IL-6 were not significant. Understanding the genetic correlation between specific inflammatory markers and DTI measures may help researchers focus questions related to inflammatory processes and brain structure.

The amplitude of activation in brain resting state networks (RSNs), measured with resting-state functional MRI, is heritable and genetically correlated across RSNs, indicating pleiotropy. Recent univariate genome-wide association studies (GWAS) explored the genetic underpinnings of individual variation in RSN activity. Yet univariate genomic analyses do not describe the pleiotropic nature of RSNs. In this study we used a novel multivariate method called genomic SEM to model latent factors that capture the shared genomic influence on RSNs and to identify SNPs and genes driving this pleiotropy. Using summary statistics from GWAS of 21 RSNs reported in UK Biobank (N = 31,688), the genomic latent factor analysis was first conducted in a discovery sample (N = 21,081), and then tested in an independent sample from the same cohort (N = 10,607). In the discovery sample, we show that the genetic organization of RSNs can be best explained by two distinct but correlated genetic factors that divide multimodal association networks and sensory networks. Eleven of the 17 factor loadings were replicated in the independent sample. With the multivariate GWAS, we found and replicated nine independent SNPs associated with the joint architecture of RSNs. Further, by combining the discovery and replication samples, we discovered additional SNP and gene associations with the two factors of RSN amplitude. We conclude that modelling the genetic effects on brain function in a multivariate way is a powerful approach to learn more about the biological mechanisms involved in brain function.

Contains fulltext : 231766.pdf (Publisher’s version ) (Open Access) Aging, the greatest risk factor for Alzheimer's disease (AD), may lead to the accumulation of somatic mutations in neurons. We investigated whether somatic mutations, specifically in longer genes, are implicated in AD etiology. First, we modeled the theoretical likelihood of genes being affected by aging-induced somatic mutations, dependent on their length. We then tested this model and found that long genes are indeed more affected by somatic mutations and that their expression is more frequently reduced in AD brains. Furthermore, using gene-set enrichment analysis, we investigated the potential consequences of such long gene disruption. We found that long genes are involved in synaptic adhesion and other synaptic pathways that are predicted to be inhibited in the brains of AD patients. Taken together, our findings indicate that long gene-dependent synaptic impairment may contribute to AD pathogenesis.

Contains fulltext : 231781.pdf (Publisher’s version ) (Open Access) Reversal learning deficits following reward and punishment processing are observed across disruptive behaviors (DB) and attention-deficit/hyperactivity disorder (ADHD), and have been associated with callous-unemotional (CU) traits. However, it remains unknown to what extent these altered reinforcement sensitivities are linked to the co-occurrence of oppositional traits, ADHD symptoms, and CU traits. Reward and punishment sensitivity and perseverative behavior were therefore derived from a probabilistic reversal learning task to investigate reinforcement sensitivity in participants with DB (n=183, ODD=62, CD=10, combined=57, age-range 8-18), ADHD (n=144, age-range 11-28), and controls (n=191, age-range 8-26). The SNAP-IV and Conners rating scales were used to assess oppositional and ADHD traits. The Inventory of CU traits was used to assess CU traits. Decreased reward sensitivity was associated with ADHD symptom severity (p=0.018) if corrected for oppositional symptoms. ADHD symptomatology interacted with oppositional behavior on perseveration (p=0.019), with the former aggravating the effect of oppositional behavior on perseveration and vice versa. Within a pooled sample, reversal learning alterations were associated with the severity of ADHD symptoms, underpinned by hyposensitivity to reward and increased perseveration. These results show ADHD traits, as opposed to oppositional behavior and CU traits, is associated with decreased reward-based learning in adolescents and adults. 01 april 2021

BackgroundAttention-deficit hyperactivity disorder (ADHD) is associated with white matter (WM) microstructure. Our objective was to investigate how WM microstructure is longitudinally related to symptom remission in adolescents and young adults with ADHD.MethodsWe obtained diffusion-weighted imaging (DWI) data from 99 participants at two time points (mean age baseline: 16.91 years, mean age follow-up: 20.57 years). We used voxel-wise Tract-Based Spatial Statistics (TBSS) with permutation-based inference to investigate associations of inattention (IA) and hyperactivity-impulsivity (HI) symptom change with fractional anisotropy (FA) at baseline, follow-up, and change between time points.ResultsRemission of combined HI and IA symptoms was significantly associated with reduced FA at follow-up in the left superior longitudinal fasciculus and the left corticospinal tract (CST) (PFWE=0.038 and PFWE=0.044, respectively), mainly driven by an association between HI remission and follow-up CST FA (PFWE=0.049). There was no significant association of combined symptom decrease with FA at baseline or with changes in FA between the two assessments.ConclusionsIn this longitudinal DWI study of ADHD using dimensional symptom scores, we show that greater symptom decrease is associated with lower follow-up FA in specific WM tracts. Altered FA thus may appear to follow, rather than precede, changes in symptom remission. Our findings indicate divergent WM developmental trajectories between individuals with persistent and remittent ADHD, and support the role of prefrontal and sensorimotor tracts in the remission of ADHD.

BackgroundWhile pharmacological treatment with Methylphenidate (MPH) is a first line intervention for ADHD, its mechanisms of action have yet to be elucidated. In a previous MEG study, we demonstrated that MPH in ADHD normalizes beta depression in preparation to motor responses (1). We here seek to identify the white matter tracts that mediate MPH’s effect on beta oscillations.MethodsWe implemented a double-blind placebo-controlled crossover design, where boys diagnosed with ADHD underwent behavioral and MEG measurements during a spatial attention task while on and off MPH. Results were compared with an age/IQ-matched typically developing (TD) group performing the same task. Estimates of white matter tracts were obtained through diffusion tensor imaging (DTI). Based on aprioristic selection model criteria, we sought to determine the fiber tracts associated with electrophysiological, behavioral and clinical features of attentional functions.ResultsWe identified three main tracts: the anterior thalamic radiation (ATR), the Superior Longitudinal Fasciculus (‘parietal endings’) (SLFp) and Superior Longitudinal Fasciculus (‘temporal endings’) (SLFt). ADHD symptoms severity was associated with lower fractional anisotropy (FA) within the ATR. In addition, individuals with relatively higher FA in SLFp compared to SLFt showed faster and more accurate behavioral responses to MPH. Furthermore, the same parieto-temporal FA gradient explained the effects of MPH on beta modulation: subjects with ADHD exhibiting higher FA in SLFp compared to SLFt also displayed greater effects of MPH on beta power during response preparation.ConclusionsBased on MPH’s modulatory effects on striatal dopamine levels, our data suggest that the behavioral deficits and aberrant oscillatory modulations observed in ADHD depend on a structural connectivity imbalance within the SLF, caused by a diffusivity gradient in favor of temporal rather than parietal, fiber tracts.

Most psychiatric disorders are highly heritable and associated with altered brain structural and functional patterns. Data fusion analyses on brain imaging and genetics, one of which is parallel independent component analysis (pICA), enable the link of genomic factors to brain patterns. Due to the small to modest effect sizes of common genetic variants in psychiatric disorders, it is usually challenging to reliably separate disorder-related genetic factors from the rest of the genome with the typical size of clinical samples. To alleviate this problem, we propose sparse parallel independent component analysis (spICA) to leverage the sparsity of individual genomic sources. The sparsity is enforced by performing Hoyer projection on the estimated independent sources. Simulation results demonstrate that the proposed spICA yields improved detection of independent sources and imaging-genomic associations compared to pICA. We applied spICA to gray matter volume (GMV) and single nucleotide polymorphism (SNP) data of 341 unrelated adults, including 127 controls, 167 attention-deficit/hyperactivity disorder (ADHD) cases, and 47 unaffected siblings. We identified one SNP source significantly and positively associated with a GMV source in superior/middle frontal regions. This association was replicated with a smaller effect size in 317 adolescents from ADHD families, including 188 individuals with ADHD and 129 unaffected siblings. The association was found to be more significant in ADHD families than controls, and stronger in adults and older adolescents than younger ones. The identified GMV source in superior/middle frontal regions was not correlated with head motion parameters and its loadings (expression levels) were reduced in adolescent (but not adult) individuals with ADHD. This GMV source was associated with working memory deficits in both adult and adolescent individuals with ADHD. The identified SNP component highlights SNPs in genes encoding long non-coding RNAs and SNPs in genes MEF2C, CADM2, and CADPS2, which have known functions relevant for modulating neuronal substrates underlying high-level cognition in ADHD.

Different psychiatric disorders and symptoms are highly correlated in the general population. A general psychopathology factor (or “P-factor”) has been proposed to efficiently describe this covariance of psychopathology. Recently, genetic and neuroimaging studies also derived general dimensions that reflect densely correlated genomic and neural effects on behaviour and psychopathology. While these three types of general dimensions show striking parallels, it is unknown how they are conceptually related. Here, we provide an overview of these three general dimensions, and suggest a unified interpretation of their nature and underlying mechanisms. We propose that the general dimensions reflect, in part, a combination of heritable ‘environmental’ factors, driven by a dense web of gene-environment correlations. This perspective calls for an update of the traditional endophenotype framework, and encourages methodological innovations to improve models of gene-brain-environment relationships in all their complexity. We propose concrete approaches, which by taking advantage of the richness of current large databases will help to better disentangle the complex nature of causal factors underlying psychopathology.

SummaryHuman brain structure changes throughout our lives. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental, and neurodegenerative diseases. Here, we identified common genetic variants that affect rates of brain growth or atrophy, in the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal MRI data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genesGPR139, DACH1andAPOEare associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene-set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and ageing.

Investigating the contribution of biology to human cognition has assumed a bottom-up causal cascade where genes influence brain systems that activate, communicate, and ultimately drive behavior. Yet few studies have directly tested whether cognitive traits with overlapping genetic underpinnings also rely on overlapping brain systems. Here, we report a step-wise exploratory analysis of genetic and functional imaging overlaps among cognitive traits. We used twin-based genetic analyses in the human connectome project (HCP) dataset (N=486), in which we quantified the heritability of measures of cognitive functions, and tested whether they were driven by common genetic factors using pairwise genetic correlations. Subsequently, we derived activation maps associated with cognitive tasks via functional imaging meta-analysis in BrainMap (N=4484), and tested whether cognitive traits that shared genetic variation also exhibited overlapping brain activation. Our genetic analysis determined that six cognitive measures (card sorting, no-go continuous performance, fluid intelligence, processing speed, reading decoding and vocabulary comprehension) were heritable (0.32gg=0.24), also had a significant brain activation overlap (ρperm=0.29). These findings indicate that fluid intelligence and executive functioning rely on overlapping biological features, both at the neural systems level and at the molecular level. The cross-disciplinary approach we introduce provides a concrete framework for data-driven quantification of biological convergence between genetics, brain function, and behavior in health and disease.

Highlights • Reduced volume in frontal lobes, striatum, and their interconnecting white matter in ADHD. • Cross-cultural and age-independent validity of the study including two independent cohorts. • Data driven approach using ICA of whole-brain morphometry images., Attention-Deficit/Hyperactivity Disorder (ADHD) has been associated with altered brain anatomy in neuroimaging studies. However, small and heterogeneous study samples, and the use of region-of-interest and tissue-specific analyses have limited the consistency and replicability of these effects. We used a data-driven multivariate approach to investigate neuroanatomical features associated with ADHD in two independent cohorts: the Dutch NeuroIMAGE cohort (n = 890, 17.2 years) and the Brazilian IMpACT cohort (n = 180, 44.2 years). Using independent component analysis of whole-brain morphometry images, 375 neuroanatomical components were assessed for association with ADHD. In both discovery (corrected-p = 0.0085) and replication (p = 0.032) cohorts, ADHD was associated with reduced volume in frontal lobes, striatum, and their interconnecting white-matter. Current results provide further evidence for the role of the fronto-striatal circuit in ADHD in children, and for the first time show its relevance to ADHD in adults. The fact that the cohorts are from different continents and comprise different age ranges highlights the robustness of the findings.

Molecular mechanisms underlying Alzheimer's disease (AD) are difficult to investigate, partly because diagnosis lags behind the insidious pathological processes. Therefore, identifying AD neuroimaging markers and their genetic modifiers may help study early mechanisms of neurodegeneration. We aimed to identify brain regions of the highest vulnerability to AD using a data‐driven search in the AD Neuroimaging Initiative (ADNI, n = 1,100 subjects), and further explored genetic variants affecting this critical brain trait using both ADNI and the younger UK Biobank cohort (n = 8,428 subjects). Tensor‐Based Morphometry (TBM) and Independent Component Analysis (ICA) identified the limbic system and its interconnecting white‐matter as the most AD‐vulnerable brain feature. Whole‐genome analysis revealed a common variant in SHARPIN that was associated with this imaging feature (rs34173062, p = 2.1 × 10−10). This genetic association was validated in the UK Biobank, where it was correlated with entorhinal cortical thickness bilaterally (p = .002 left and p = 8.6 × 10−4 right), and with parental history of AD (p = 2.3 × 10−6). Our findings suggest that neuroanatomical variation in the limbic system and AD risk are associated with a novel variant in SHARPIN. The role of this postsynaptic density gene product in β1‐integrin adhesion is in line with the amyloid precursor protein (APP) intracellular signaling pathway and the recent genome‐wide evidence.

Serotonin (5-HT) is an important factor for prenatal neurodevelopment whereby its neurotrophic actions can be regulated through maternal-fetal interactions. We explored if maternal 5-HTTLPR genotype is associated with clinical and cognitive measures of attention-deficit/hyperactivity disorder (ADHD) and comorbid autism spectrum disorder (ASD) in typically-developing and ADHD-diagnosed offspring, beyond classical inheritance and environmental- and comorbidity-mediators/confounders. Family-based variance decomposition analyses were performed incorporating 6–31 year-old offsprings' as well as parental genotypes of 462 ADHD and control families from the NeuroIMAGE cohort. Dependent measures were offsprings' ADHD symptom- and ASD trait-scores and cognitive measures including executive functioning (including response inhibition and cognitive flexibility), sustained attention, reward processing, motor control, and emotion recognition. Offsprings' stereotyped behavior was predicted by an interaction between maternal 5-HTTLPR genotype and offsprings' sex. Furthermore, offspring of mothers with low-expressing genotypes demonstrated larger reward-related reductions in reaction time. While specifically adult male offspring of these mothers reported a faster reversal learning with less errors, specifically young female offspring of these mothers were more accurate in identifying happy faces. Adult offspring from the mothers with low-expressing 5-HTTLPR genotypes were also slower in identifying happy faces. However, this association seemed to be mediated by offsprings' high anxiety levels. In sum, we found some support for a role of the maternal 5-HT system in modulating fetal brain development and behavior. Offsprings' cognitive measures might be more sensitive to small alterations within the maternal 5-HT system than their ADHD and ASD clinical phenotypes. Further studies are needed to specify the association between maternal genotype and risk for neurodevelopmental disorders.

Contains fulltext : 191289.pdf (Publisher’s version ) (Open Access) Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen's d=-0.293; P=1.71 x 10(-21)), left fusiform gyrus (d=-0.288; P=8.25 x 10(-21)) and left rostral middle frontal cortex (d=-0.276; P=2.99 x 10(-19)). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.

The accurate estimation of age using methylation data has proved a useful and heritable biomarker, with acceleration in epigenetic age predicting a number of age-related phenotypes. Measures of white matter integrity in the brain are also heritable and highly sensitive to both normal and pathological aging processes across adulthood. We consider the phenotypic and genetic interrelationships between epigenetic age acceleration and white matter integrity in humans. Our goal was to investigate processes that underlie interindividual variability in age-related changes in the brain. Using blood taken from a Mexican-American extended pedigree sample (n= 628; age = 23.28–93.11 years), epigenetic age was estimated using the method developed by Horvath (2013). Forn= 376 individuals, diffusion tensor imaging scans were also available. The interrelationship between epigenetic age acceleration and global white matter integrity was investigated with variance decomposition methods. To test for neuroanatomical specificity, 16 specific tracts were additionally considered. We observed negative phenotypic correlations between epigenetic age acceleration and global white matter tract integrity (ρpheno= −0.119,p= 0.028), with evidence of shared genetic (ρgene= −0.463,p= 0.013) but not environmental influences. Negative phenotypic and genetic correlations with age acceleration were also seen for a number of specific white matter tracts, along with additional negative phenotypic correlations between granulocyte abundance and white matter integrity. These findings (i.e., increased acceleration in epigenetic age in peripheral blood correlates with reduced white matter integrity in the brain and shares common genetic influences) provide a window into the neurobiology of aging processes within the brain and a potential biomarker of normal and pathological brain aging.SIGNIFICANCE STATEMENTEpigenetic measures can be used to predict age with a high degree of accuracy and so capture acceleration in biological age, relative to chronological age. The white matter tracts within the brain are also highly sensitive to aging processes. We show that increased biological aging (measured using epigenetic data from blood samples) is correlated with reduced integrity of white matter tracts within the human brain (measured using diffusion tensor imaging) with data from a large sample of Mexican-American families. Given the family design of the sample, we are also able to demonstrate that epigenetic aging and white matter tract integrity also share common genetic influences. Therefore, epigenetic age may be a potential, and accessible, biomarker of brain aging.

ObjectiveNeuroimaging studies have associated Attention-Deficit/Hyperactivity Disorder (ADHD) with altered brain anatomy. However, small and heterogeneous study samples, and the use of region-of-interest and tissue-specific analyses have limited the consistency and replicability of these effects. The present study uses a fully data-driven multivariate approach to investigate alterations in both gray and white matter simultaneously, and capture neuroanatomical features associated with ADHD in two large, independent, demographically different cohorts.MethodsThe study comprised two ADHD cohorts with structural magnetic resonance imaging data: the Dutch NeuroIMAGE cohort (n=890, average age 17.2 years, discovery sample) and the Brazilian IMpACT cohort (n=180, average age 44.2 years, cross validation sample). Using independent component analysis of whole-brain morphometry images in the NeuroIMAGE cohort, 375 independent components of neuroanatomical variations were extracted and assessed their association with ADHD. Afterwards, ADHD-associated components were cross validated in the Brazilian IMpACT cohort.ResultsIn both discovery (corrected-p=0.020) and validation (p=0.033) cohorts, ADHD diagnosis was significantly associated with reduced brain volume in a component mapping to frontal lobes, striatum, and their interconnecting white-matter tracts. The most pronounced case-control differences were localized in white matter adjacent to the orbitofrontal cortex.ConclusionIndependent component analysis is a sensitive approach to uncover neuroanatomical alterations in ADHD and avoid bias attributable toa prioriregion-of-interest based methods. Current results provide further evidence for the role of the fronto-striatal circuit in ADHD. The fact that the two cohorts are from different continents and comprising different age ranges highlights the robustness of the findings.

BACKGROUND: Abnormal myelination has been proposed as a pathogenetic mechanism for schizophrenia. Ultra-high-field magnetic resonance imaging (MRI) offers unprecedented spatial resolution and is ideally suited for the in vivo examination of schizophrenia-associated abnormalities in intracortical myelin. METHODS: Twenty-two healthy individuals and 17 patients with schizophrenia were imaged at 7 Tesla MRI using a T1-weighted sequence optimized for intracortical myelin. T1 values were extracted at 20 cortical depth-levels covering the entire cortical ribbon from each of 148 cortical regions. In each cortical region, T1 values were used to infer myelin concentration and to compute a non-linearity index as a measure of the spatial organization of myelin across the cortical ribbon. These metrics were used to ascertain the effect of diagnosis, illness duration and medication using mixed-effects linear models. RESULTS: We identified case-control differences in intracortical myelin concentration (P

Altres ajuts: VR has served on the speakers for Eli Lilly, Rubio, and Shire in the last 5 years. She has received travel awards from Eli Lilly and Co. and Shire for participating in psychiatric meetings. The ADHD Program has received unrestricted educational and research support from Eli Lilly and Co., Janssen-Cilag, Shire, Rovi, Psious, and Laboratorios Rubió in the past 2 years. MC received travel awards for taking part in psychiatric meetings from Shire. CF received travel awards for taking part in psychiatric meetings from Shire and Lundbeck. GEM received travel awards for taking part in psychiatric meetings from Shire. EJSS-B received speaker fees, consultancy, research funding, and conference support from Shire Pharma. Consultancy from Neurotech Solutions, Copenhagen University and Berhanderling, Skolerne & KU Leuven. Book royalties from OUP and Jessica Kingsley. Financial support-Arhus University and Ghent University for visiting Professorship. Editor-in-Chief JCPP-supported by a buy-out of time to University of Southampton and personal Honorarium. King's College London received payments for work conducted by PA: consultancy for Shire, Eli Lilly, Novartis, and Lundbeck; educational and/or research awards from Shire, Eli Lilly, Novartis, Vifor Pharma, GW Pharma, and QbTech; speaker at events sponsored by Shire, Eli Lilly, Janssen-Cilag, and Novartis. JKB has been in the past 3 years a consultant to/member of advisory board of and/or speaker for Shire, Roche, Medice, and Servier. He is not an employee of any of these companies, and not a stock shareholder of any of these companies. He has no other financial or material support, including expert testimony, patents, royalties. In the past year, SVF received income, potential income, travel expenses continuing education support and/or research support from Tris, Otsuka, Arbor, Ironshore, Shire, Akili Interactive Labs, Enzymotec, Sunovion, Supernus, and Genomind. With his institution, he has US patent US20130217707 A1 for the use of sodium-hydrogen exchange inhibitors in the treatment of ADHD. He also receives royalties from books published by Guilford Press: Straight Talk about Your Child's Mental Health, Oxford University Press: Schizophrenia: The Facts and Elsevier: ADHD: Non-Pharmacologic Interventions. He is principal investigator of www.adhdinadults.com. JK has given talks at educational events sponsored by Medice; all funds are received by King's College London and used for studies of ADHD. HL has served as a speaker for Evolan Pharma and Shire and has received research grants from Shire; all outside the submitted work. K-PL served as a speaker for Eli Lilly and received research support from Medice, and travel support from Shire, all outside the submitted work. LAR reported receiving honoraria, serving on the speakers' bureau/advisory board, and/or acting as a consultant for Eli Lilly, Janssen-Cilag, Novartis, and Shire in the last 3 years; receiving authorship royalties from Oxford Press and ArtMed; and receiving travel awards from Shire for his participation in the 2015 WFADHD meetings and from Novartis to take part of the 2016 AACAP meeting. The ADHD and juvenile bipolar disorder outpatient programs chaired by him received unrestricted educational and research support from the following pharmaceutical companies in the last 3 years: Janssen-Cilag, Novartis, and Shire. MC has received travel grants and research support from Eli Lilly and Co., Janssen-Cilag, Shire, and Lundbeck and served as consultant for Eli Lilly and Co., Janssen-Cilag, Shire, and Lundbeck. BF has received educational speaking fees from Medice and Shire. JAR-Q was on the speakers' bureau and/or acted as consultant for Eli Lilly, Janssen-Cilag, Novartis, Shire, Lundbeck, Almirall, Braingaze, Sincrolab, Medice, and Rubió in the last 5 years. He also received travel awards (air tickets + hotel) for taking part in psychiatric meetings from Janssen-Cilag, Rubió, Shire, Medice, and Eli- Lilly. The Department of Psychiatry chaired by him received unrestricted educational and research support from the following companies in the last 5 years: Eli Lilly, Lundbeck, Janssen- Cilag, Actelion, Shire, Ferrer, Oryzon, Roche, Psious, and Rubió. The other authors have nothing to disclose. All members of the 23andMe Research Team are current or former employees of 23andMe, Inc. and hold stock or stock options in 23andMe. Authors of the ADHD Working group of the PGC that participated in this study: Catharina A. Hartman, Ziarih Hawi, Jennifer Crosbie, Sandra Loo, Josephine Elia, Russell Schachar, Christie Burton, Ted Reichborn-Kjennerud, Aribert Rothenberger, Søren Dalsgaard, Irwin Waldman, Mark Bellgrove, Hakon Hakonarson, Johannes Hebebrand, Anke Hinney, and Robert Oades have nothing to disclose. Joseph Biederman 2019-2020: he received research support from Genentech, Headspace Inc., Lundbeck AS, Neurocentria Inc, Pfizer Pharmaceuticals, Roche TCRC Inc., Shire Pharmaceuticals Inc., Sunovion Pharmaceuticals Inc., and Tris. He was a consultant for Akili, Avekshan, Jazz Pharma, and Shire/Takeda. Through MGH CTNI, he participated in a scientific advisory board for Supernus. Dr Biederman's program has received departmental royalties from a copyrighted rating scale used for ADHD diagnoses, paid by Bracket Global, Ingenix, Prophase, Shire, Sunovion, and Theravance; these royalties were paid to the Department of Psychiatry at MGH. Tobias Banaschewski served in an advisory or consultancy role for Lundbeck, Medice, Neurim Pharmaceuticals, Oberberg GmbH, Shire, and Infectopharm. He received conference support or speaker's fee by Lilly, Medice, and Shire. He received royalties from Hogrefe, Kohlhammer, CIP Medien, and Oxford University Press. James McGough is an expert testimony for Eli Lilly; DSMB for Sunovion. Benjamin Neale is a member of the scientific advisory board at Deep Genomics and consultant for Camp4 Therapeutics, Takeda Pharmaceutical, and Biogen. Ole Andreas Andreassen received speaker's honorarium from Lundbeck, and is a consultant for HealthLytix. The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 602805 (Aggressotype) as well as from the European Union H2020 Programme (H2020/2014-2020). The work was also supported by the ECNP Network "ADHD across the Lifespan" (https://www.ecnp.eu/research-innovation/ECNP-networks/List-ECNP-Networks/ADHD.aspx). Over the course of this investigation, PR is a recipient of a pre-doctoral fellowship from the Agència de Gestió d'Ajuts Universitaris i de Recerca (AGAUR), Generalitat de Catalunya, Spain. The iPSYCH project is funded by the Lundbeck Foundation (grant nos. R102-A9118 and R155-2014-1724) and the universities, and university hospitals of Aarhus and Copenhagen. ADB and NRM's work is also supported by the EU's Horizon 2020 programme. Data handling and analysis was supported by NIMH (1U01MH109514-01 to Michael O'Donovan and ADB). CSM is a recipient of a Sara Borrell contract from the Instituto de Salud Carlos III, Ministerio de Economía, Industria y Competitividad, Spain. K-PL and his team are supported by the Deutsche Forschungsgemeinschaft (DFG: CRU 125, CRC TRR 58 A1/A5, no. 44541416), ERA-Net NEURON/RESPOND, no. 01EW1602B, ERA-Net NEURON/DECODE, no. 01EW1902, and 5-100 Russian Academic Excellence Project. JH thanks Stiftelsen K.G. Jebsen, University of Bergen, the Western Norwegian Health Authorities (Helse Vest). HL thanks the Swedish research council. BC received financial support from the Spanish "Ministerio de Economía y Competitividad" and AGAUR. MSA is a recipient of a contract from the Biomedical Network Research Center on Mental Health (CIBERSAM), Madrid, Spain. MR is a recipient of a Miguel de Servet contract from the Instituto de Salud Carlos III, Spain. The research leading to these results has received funding from the Instituto de Salud Carlos III , and cofinanced by the European Regional Development Fund (ERDF), from the Pla estratègic de recerca i innovació en salut (PERIS); Generalitat de Catalunya, from "la Marató de TV3" (092330/31) and from the Agència de Gestió d'Ajuts Universitaris i de Recerca-AGAUR, Generalitat de Catalunya. ES's work is supported by a personal Hypatia grant from the Radboud University Medical Center. MH received a Veni grant from of the Netherlands Organization for Scientific Research (NWO, grant number 91619115). The NeuroIMAGE study was supported by NIH Grant R01MH62873 (to SVF), NWO Large Investment Grant 1750102007010 (to JKB), ZonMW grant 60-60600-97-193, NWO grants 056-13-015 and 433-09-242, and matching grants from Radboud University Nijmegen Medical Center, University Medical Center Groningen and Accare, and Vrije Universiteit Amsterdam. Organization for Scientific Research (NWO; grant 016-130-669). BF and MK's work is supported by the Dutch National Science Agenda (NWA) for the NeurolabNL project (grant 400-17-602). This paper represents independent research part funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. BF received additional funding from a personal Vici grant of the Dutch. Attention deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder characterized by age-inappropriate symptoms of inattention, impulsivity, and hyperactivity that persist into adulthood in the majority of the diagnosed children. Despite several risk factors during childhood predicting the persistence of ADHD symptoms into adulthood, the genetic architecture underlying the trajectory of ADHD over time is still unclear. We set out to study the contribution of common genetic variants to the risk for ADHD across the lifespan by conducting meta-analyses of genome-wide association studies on persistent ADHD in adults and ADHD in childhood separately and jointly, and by comparing the genetic background between them in a total sample of 17,149 cases and 32,411 controls. Our results show nine new independent loci and support a shared contribution of common genetic variants to ADHD in children and adults. No subgroup heterogeneity was observed among children, while this group consists of future remitting and persistent individuals. We report similar patterns of genetic correlation of ADHD with other ADHD-related datasets and different traits and disorders among adults, children, and when combining both groups. These findings confirm that persistent ADHD in adults is a neurodevelopmental disorder and extend the existing hypothesis of a shared genetic architecture underlying ADHD and different traits to a lifespan perspective.

Background Diffusion tensor imaging studies show reductions in fractional anisotropy (FA) in individuals with bipolar disorder and their unaffected siblings. However, the use of various analysis methods is an important source of between-study heterogeneity. Using tract-based spatial statistics, we previously demonstrated widespread FA reductions in patients and unaffected relatives. To better interpret the neuroanatomical pattern of this previous finding and to assess the influence of methodological heterogeneity, we here applied tractography to the same sample. Methods Diffusion-weighted images were acquired for 96 patients, 69 unaffected siblings and 56 controls. We applied TRACULA, an extension of a global probabilistic tractography algorithm, to automatically segment 18 major fiber tracts. Average FA within each tract and at each cross-section along each tract was compared between groups. Results Patients had reduced FA compared to healthy controls and their unaffected siblings in general, and in particular in the parietal part of the superior longitudinal fasciculus. In unaffected siblings, FA was nominally reduced compared to controls in the corpus callosum. Point-wise analyses indicated that similar effects were present along extended sections, but with variable effect sizes. Current symptom severity negatively correlated with FA in several fronto-limbic association tracts. Conclusions The differential sensitivity of analysis techniques likely explains between-study heterogeneity in anatomical localization of FA reductions. The present tractography analysis confirms the presence of overall FA reductions in patients with bipolar disorder, which are most pronounced in the superior longitudinal fasciculus. Unaffected siblings may display similar, albeit more subtle and anatomically restricted FA reductions. Hum Brain Mapp, 2016. © 2016 Wiley Periodicals, Inc.

Item does not contain fulltext BACKGROUND: Mood disorders are familial psychiatric diseases, in which patients show reduced white matter (WM) integrity. We sought to determine whether WM integrity was affected in young offspring at high-familial risk of mood disorder before they go on to develop major depressive disorder (MDD). METHODS: The Bipolar Family study is a prospective longitudinal study examining young individuals (age 16-25 years) at familial risk of mood disorder on three occasions 2 years apart. This study used baseline imaging data, categorizing groups according to clinical outcome at follow-up. Diffusion tensor MRI data were acquired for 61 controls and 106 high-risk individuals, the latter divided into 78 high-risk subjects who remained well throughout the study ('high-risk well') and 28 individuals who subsequently developed MDD ('high-risk MDD'). Voxel-wise between-group comparison of fractional anisotropy (FA) based on diagnostic status was performed using tract-based spatial statistics (TBSS). RESULTS: Compared to controls, both high-risk groups showed widespread decreases in FA (pcorr < .05) at baseline. Although FA in the high-risk MDD group negatively correlated with subthreshold depressive symptoms at the time of scanning (pcorr < .05), there were no statistically significant differences at p-corrected levels between the two high-risk groups. CONCLUSIONS: These results suggest that decreased FA is related to the presence of familial risk for mood disorder along with subdiagnostic symptoms at the time of scanning rather than predictive of subsequent diagnosis. Due to the difficulties performing such longitudinal prospective studies, we note, however, that this latter analysis may be underpowered due to sample size within the high-risk MDD group. Further clinical follow-up may clarify these findings.