The panels show heritability (h2) estimates for fractional anisotropy, radial diffusivity, and axial diffusivity in extended (A) and nuclear (B) families. Superior and anterior views are provided. In the extended families, tracts are shown that were significantly heritable at a Bonferroni-adjusted value of P = .0015. In the nuclear families, tracts are confirmed as heritable at P < .05. Two of these 12 heritable tracts properties were also significantly associated with inattentive symptoms, and 1 tract property was associated with hyperactivity/impulsivity symptoms.
In each panel, regions are shown (in red) that have heritable functional connectivity with the rest of that network. For each network, the connectivity regression coefficients are thresholded at the 95th percentile for visualization (in blue). Results are shown for the default mode (A), the ventral attention network (B), and the frontoparietal (cognitive control) network (C). Associations were found between both symptoms’ dimensions and the heritable functional connectivity of the default mode network. Additionally, there was an association between hyperactivity/impulsivity symptoms and the functional connectivity patterns within the ventral attention network.
Each line represents a significant correlation (applying a false discovery rate of q < .05). Heritable components of the ventral attention network showed both phenotypic (A) and genetic (B) correlations with the inferior fronto-occipital fasciculus. CC indicates corpus callosum; Cog, cognitive control network; DAN, dorsal attention network; DMN, default mode network; IFO, inferior fronto-occipital; ILF, inferior longitudinal fasciculus; l, left; r, right; SLF, superior longitudinal fasciculus; UNC, uncinate; and VAN, ventral attention network.
eMethods. Detailed Methodology
eResults. Supplemental Findings
eFigure 1. Diagnostic Details for the Extended Families
eFigure 2. Diagnostic Details for the Nuclear Families
eFigure 3. White Matter Tracts Properties That Are Either Associated With ADHD Diagnostic Categories, Heritable or Both
eFigure 4. Diffusion Values Are Given for the Right Superior Longitudinal Fasciculus and for the Left Corticospinal Tract
eFigure 5. The Functional Connectivity of the Posterior Cingulate Hub With the Remainder of the DMN
eFigure 6. Correlation Between Radial Diffusivity of the Right Inferior Fronto-Occipital Fasciculus and Axial Diffusivity of the Left Superior Longitudinal
eFigure 7. Correlation Between Radial Diffusivity of the Right Inferior Fronto- Occipital Fasciculus and the Connectivity of the Heritable Hub Within the Ventral Attention Network
eTable 1. Demographic Details of Nuclear Families With Clinical and Imaging Phenotypes
eTable 2. Heritability of White Matter Tracts
eTable 3. White Matter Tract Heritability for the Entire Cohort and Association With ADHD Symptoms
eTable 4. Heritability of the Intrinsic Functional Networks in Extended and Nuclear Families and Association With ADHD
eTable 5. The Number of Participants on Psychostimulant and Other Psychotropic Medications
eTable 6. Heritability of the White Matter Tracts Excluding Those on Psychostimulants and Those on Any Psychotropics
eTable 7. Heritability of Functional Connectivity Within Intrinsic Networks, Excluding Those on Psychostimulants and Those on Any Psychotropics
eTable 8. The Best Fitting Age Model for Each Tract Property Is Given
eTable 9. Heritability of White Matter Tract Metrics in Young (21 and Under) and Adult Age Groups
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Sudre G, Choudhuri S, Szekely E, et al. Estimating the Heritability of Structural and Functional Brain Connectivity in Families Affected by Attention-Deficit/Hyperactivity Disorder. JAMA Psychiatry. 2017;74(1):76–84. doi:10.1001/jamapsychiatry.2016.3072
Copyright 2017 American Medical Association. All Rights Reserved.
What facets of the brain’s structural and functional connections are both heritable and associated with attention-deficit/hyperactivity disorder?
This observational study evaluated 24 multigenerational extended families and 52 nuclear families. The most heritable features were part of the attention and default mode networks and the white matter tracts that lie within them.
Facets of structural and functional brain connectivity are strong candidate phenotypes for future genomic study.
Despite its high heritability, few risk genes have been identified for attention-deficit/hyperactivity disorder (ADHD). Brain-based phenotypes could aid gene discovery. There is a myriad of structural and functional connections that support cognition. Disruption of such connectivity is a key pathophysiologic mechanism for ADHD, and identifying heritable phenotypes within these connections could provide candidates for genomic studies.
To identify the structural and functional connections that are heritable and pertinent to ADHD.
Design, Setting, and Participants
Members of extended multigenerational families enriched for ADHD were evaluated. Structural connectivity was defined by diffusion tensor imaging (DTI) of white matter tract microstructure and functional connectivity through resting-state functional magnetic resonance imaging (rsfMRI). Heritability and association with ADHD symptoms were estimated in 24 extended multigenerational families enriched for ADHD (305 members with clinical phenotyping, 213 with DTI, and 193 with rsfMRI data). Findings were confirmed in 52 nuclear families (132 members with clinical phenotypes, 119 with DTI, and 84 with rsfMRI). The study and data analysis were conducted from April 1, 2010, to September 1, 2016.
In the 52 nuclear families, 86 individuals (65.2%) were male and the mean (SD) age at imaging was 20.9 (15.0) years; in the 24 multigenerational extended families, 145 individuals (47.5%) were male and mean age at imaging was 30.4 (19.7) years. Microstructural properties of white matter tracts connecting ipsilateral cortical regions and the corpus callosum were significantly heritable, ranging from total additive genetic heritability (h2) = 0.69 (SE, 0.13; P = .0000002) for radial diffusivity of the right superior longitudinal fasciculus to h2 = 0.46 (SE, 0.15; P = .0009) for fractional anisotropy of the right inferior fronto-occipital fasciculus. Association with ADHD symptoms was found in several tracts, most strongly for the right superior longitudinal fasciculus (t = −3.05; P = .003). Heritable patterns of functional connectivity were detected within the default mode (h2 = 0.36; SE, 0.16; cluster level significance, P < .002), cognitive control (h2 = 0.32; SE, 0.15; P < .002), and ventral attention networks (h2 = 0.36; SE, 0.16; P < .002). In all cases, subregions within each network showed heritable functional connectivity with the rest of that network. More symptoms of hyperactivity/impulsivity (t = −2.63; P = .008) and inattention (t = −2.34; P = .02) were associated with decreased functional connectivity within the default mode network. Some cross-modal correlations were purely phenotypic, such as that between axial diffusivity of the right superior longitudinal fasciculus and heritable aspects of the default mode network (phenotypic correlation, ρp = −0.12; P = .03). A genetic cross-modal correlation was seen between the ventral attention network and radial diffusivity of the right inferior fronto-occipital fasciculus (genetic correlation, ρg = −0.45, P = .02).
Analysis of data on multigenerational extended and nuclear families identified the features of structural and functional connectivity that are both significantly heritable and associated with ADHD. In addition, shared genetic factors account for some phenotypic correlations between functional and structural connections. Such work helps to prioritize the facets of the brain’s connectivity for future genomic studies.
There has been limited progress in identifying the specific genes contributing to the established high heritability of attention-deficit/hyperactivity disorder (ADHD).1,2 The use of heritable, brain-based phenotypes pertinent to the disorder might accelerate progress in part because they lie closer to genes than the more distal clinical phenotype.3,4 Herein we focus on the myriad structural and functional connections within the brain that support multiple cognitive, motor, and affective processes.5-8 We do so because ADHD is increasingly viewed as the product of anomalous connectivity or miswiring that results in disruption of large-scale brain systems, producing symptoms.8-10 In addition, such a focus addresses a gap in our knowledge. Although the heritability and association between ADHD and gray matter structure has been extensively investigated,11-13 less is known on which aspects of connectivity are both heritable and pertinent to ADHD. Such a study would complement estimates of the heritability of structural and functional connectivity among healthy twins and families14-23 as well as among families affected by bipolar affective disorder and schizophrenia.24-26
Structural and functional connectivity can be studied on many levels. We used resting-state functional magnetic resonance imaging (rsfMRI) to define in vivo the microstructural properties of major white matter tracts. We took this approach because ADHD and its core cognitive deficits have been associated6 with anomalies in the white matter tracts connecting different cerebral cortical regions. We also defined functional connectivity through the coordinated patterns of neural activity or intrinsic networks that emerge spontaneously when an individual is not engaged in task-oriented behavior.27,28 Attention-deficit/hyperactivity disorder has been conceptualized as an imbalance between these intrinsic networks, particularly the default mode network (DMN), which is prominent during internally directed thought, and the networks supporting cognitive control and attention.29,30
Imaging of the brain’s structural and functional connectivity provides a multitude of phenotypes, and it is important to prioritize these phenotypes for future genomic study. We took the strategy of first identifying the subset of phenotypes that is highly heritable. Such highly heritable phenotypes boost the chances of detecting underlying genes. Further prioritization can then be made on the strength of association with ADHD symptoms. We estimated connectivity within multigenerational extended families in which a high proportion of members are affected by ADHD. This approach affords an efficient strategy to define both heritability and association with ADHD symptoms. We confirmed initial heritability estimates in a separate cohort of nuclear families that were also affected by ADHD. In addition, this approach meets 3 further aims. First, the heritability of all of the major intrinsic networks can be defined, broadening the prior focus on the DMN.19,21 Second, heritable connectivity features that are also pertinent to the symptoms of ADHD can be determined. Finally, the family-based design allowed us to answer the question: Do components of the structural and functional connections share genetic determinants or are they genetically distinct?
Inclusion criteria for the extended families were (1) the presence of second-, third-, or higher-degree relatives and (2) a diagnosis of ADHD in at least 25% of family members (approximately 10 times the adult ADHD and 4 times the childhood ADHD prevalence rates31,32). For nuclear families, the main inclusion criterion was at least 2 first-degree relatives (sibling or parent-child) with at least 1 having ADHD. The institutional review board of the National Human Genome Research Institute approved the research protocol, and written informed consent was obtained from adult participants and parents; children gave written assent. Participants received financial compensation. The study and data analysis were conducted from April 1, 2010, to September 1, 2016.
The diagnosis of adult ADHD was determined with the Conners’ Adult ADHD Diagnostic Interview for DSM-IV.33 This clinician-administered structured interview establishes the number of symptoms, ranging from 0 symptoms through a maximum of 9 symptoms of inattention and 9 of hyperactivity-impulsivity. The interview ascertains both current adult symptoms of ADHD and the childhood history of these symptoms. We leveraged the family design to obtain collateral confirmation of childhood symptoms when possible. The presence of other psychiatric diagnoses was established through the Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Patient Edition.34 For children, the parental Diagnostic Interview for Children and Adolescents-IV (DICA)35 was used, which establishes the number of symptoms of inattention and hyperactivity-impulsivity (with a range from 0 to a maximum of 9 symptoms in each category). Interviews were conducted by 2 experienced clinicians (W.S. and P.S.) with interrater reliabilities of κ > 0.9, and neurologic assessment by a physician (P.S.). Exclusion criteria were an IQ less than 80 (determined with Wechsler intelligence scales36,37), neurologic disorders affecting brain structure, current substance dependence, or psychotic disorders. Twenty-one of the 24 extended families and 42 of the 52 nuclear families were white and non-Hispanic.
Diffusion tensor imaging (DTI) data were collected (3-T HDx MRI system; GE Healthcare) with a single-shot, dual-spin echo, echo-planar imaging sequence. Imaging parameters, preprocessing, and tensor fitting are described in the eMethods in the Supplement. The same acquisition parameters were used throughout the study except that 60 volumes were acquired for children to shorten the scan time compared with 80 volumes in adults. Quality control measures included the reacquisition of corrupted data in real time,38 visual inspection, and removal of corrupted data. Participants were excluded if they had more than 10% of corrupted volumes, a trait value exceeding the sample mean by 3 or more SDs, or a mean overall tract fractional anisotropy value of less than 0.25. Overall, 332 of the original 363 DTI data sets were retained. Although there were no significant correlations between head motion parameters and tract measures, we nonetheless considered motion as a covariate.
Software (DTI-TK, version 2.3.1 for Linux; http://dti-tk.sourceforge.net/) registered the diffusion tensors into a common template space.39,40 We considered all of the 11 tracts measured by this software, 5 of which are bilateral (uncinate, inferior-fronto-occipital, superior longitudinal, inferior longitudinal, corticospinal fasciculi), and the corpus callosum. For each tract, fractional anisotropy, a summary metric of overall tract diffusion properties, was defined along with axial diffusivity and radial diffusivity, which are proxies for the flow of water along the axis and the radius of the axon, respectively.
Resting-state fMRI was acquired using a gradient-echo echo-planar series with whole-brain coverage. Participants were instructed to remain still for 5 minutes, 5 seconds, and gaze at a fixation point. Preprocessing used the AFNI software package.41 The first 3 gradient-echo echo-planar volumes were removed as well as any volumes that showed motion of more than 0.2 mm and volumes that contained more than 10% of voxels considered to be outliers. Following such scrubbing, the remaining participants had a mean (SD) of 278 (34) seconds of usable data and a lower limit of 180 seconds was set. In total, 277 (193 extended, 84 nuclear) of the 340 originally acquired rsfMRI scans were retained. The amount of usable data was associated with hyperactivity/impulsivity symptoms (t = 1.68; P = .09) and age (t = 3.59; P = .0004) but did not vary with inattention (t = 1.05; P = .29) or sex (t = 0.40; P = .69). The gradient-echo echo-planar volumes were registered to the individual’s T1-weighted anatomical image and to a Montreal Neurological Institute template.42 Activation in white matter and lateral ventricle masks was removed using anatomy-based correlation corrections, and the time derivative of the motion parameters was also regressed out.43
We used independent component analysis to decompose the blood oxygen level–dependent signal into spatially distinct maps and their time courses.44 Each independent component is a spatial map of functionally connected regions—an intrinsic network—that shows the strength of the contribution of every voxel to the intrinsic network. These intrinsic networks closely resemble and are named for large-scale brain networks that support cognition. We focused on the 7 major intrinsic networks described by Yeo and colleagues45: default mode, dorsal and ventral attention, cognitive control, affective, visual, and somatomotor networks. Finally, dual regression was used to create participant-specific spatial maps for each network.46 In each map, the value of each voxel shows the strength of the functional connection between that voxel and the rest of the network for that person.
Heritability was estimated using the sequential oligogenic linkage analysis routine (SOLAR).47 This routine uses a variance component method to estimate the proportion of phenotypic variance due to additive genetic factors (ie, narrow sense heritability) (eMethods in the Supplement). Inverse normalization was applied to phenotypes because heritability estimates in SOLAR are sensitive to skewed distributions. SOLAR also was used to estimate the phenotypic correlation between heritable traits and the underlying genetic and environmental correlations, applying a false discovery rate (FDR) of 0.05 to correct for multiple testing.48
Symptom counts of ADHD were regressed against each heritable trait with the use of a mixed-effects model, with family identity as the random term. For adults, we were primarily interested in current symptoms, as an earlier study on adult ADHD found that anomalies in white matter tracts were associated with current—not childhood—symptoms.10 Sex, age, age2, movement, and movement2 were considered as covariates and retained if P < .10.
We estimated the heritability of 33 white matter tract properties in the extended families (3 properties for 11 tracts). Bonferroni correction was applied and heritability was declared significant at P < .05/33 = .0015. Confirmation of heritability in the nuclear family cohort was taken at a nominal P < .05. In resting-state analyses in extended families, the probability of false-positive spatial clusters was estimated using a nonparametric approach (permutation) setting a voxelwise P < .05 with a cluster-corrected α level of P < .002 (eMethods in the Supplement provides details). Confirmation of the heritability in the nuclear families was taken at a nominal P < .05 at the voxel level. No cluster extent correction was applied in the nuclear families since we were testing heritability within a region of interest initially defined by the extended families. In testing for associations between heritable connectivity measures and ADHD symptoms, results within each modality were adjusted for multiple testing using Bonferroni correction.
Age-related change in the connectivity measures were modeled using linear mixed models (eMethods in the Supplement). We also examined whether heritability estimates were similar in youth (≤21 years) and adult (>21 years) groups. Finally, we determined whether associations between ADHD symptoms and the connectivity measures differed between these age groups.
Within the extended families, 115 of 305 relatives (37.7%) had ADHD; 145 individuals (47.5%) were male, and mean (SD) age at imaging was 30.4 (19.7) years (Table and eFigure 1 in the Supplement). In the nuclear families, 78 of 132 individuals (59.1%) were affected; 86 individuals (65.2%) were male and the mean age at imaging was 20.9 (15.0) years (eTable 1 and eFigure 2 in the Supplement).
Fourteen of 33 white matter tract properties (42.4%) emerged as significantly heritable (h2) in the 213 relatives from extended families (Figure 1 and eTable 2 in the Supplement). Estimates ranged from h2 = 0.69 (SE, 0.13; P = .0000002) for radial diffusivity of the right superior longitudinal fasciculus to h2 = 0.46 (SE, 0.15; P = .0009) for fractional anisotropy of the right inferior fronto-occipital fasciculus. Twelve of these tract properties were further confirmed as significantly heritable (at P < .05) in 119 individuals from nuclear families.
We next examined association between the heritable tract properties and ADHD symptom count (eTable 3 and eFigure 3 in the Supplement). Radial diffusivity of the right superior longitudinal fasciculus was associated with inattention at a corrected level of significance (t = −3.05; P < .003; Bonferroni adjusted, P = .004). Axial diffusivity of this tract showed a nominally significant association with inattention (t = −2.51; P = .01). Association was also found between fractional anisotropy of the right inferior fronto-occipital fasciculus and hyperactivity/impulsivity at a nominal level of significance (t = −2.35; P = .02). Results of DSM-5 diagnostic group contrasts are given in the eResults in the Supplement. Thus, radial diffusivity of the right superior longitudinal fasciculus emerged as the most robustly heritable and ADHD-associated white matter tract property.
The intrinsic functional networks found to have regions of heritable functional connectivity in the 193 relatives from extended families are shown in Figure 2 and eTable 4 in the Supplement. First, within the DMN, functional connectivity between a posterior cingulate region and the remainder of the network was heritable (h2 = 0.36; SE, 0.16; cluster level significance, P < .002). Within the cognitive control network, functional connectivity between its right inferior parietal component and the rest of the network emerged as heritable (h2 = 0.32; SE, 0.15; cluster level significance, P < .002). For the ventral attention networks, heritability localized to the right superior frontal gyrus (h2 = 0.36; SE, 0.15; P < .002). No patterns of heritable functional connectivity were found within the other networks.
These heritability findings were confirmed using rsfMRI data from 84 members of nuclear families (eTable 4 in the Supplement). Functional connectivity between the posterior cingulate region and the rest of the network was found to be heritable in nuclear families. Similarly, the patterns of heritable functional connectivity within the cognitive control, dorsal, and ventral attention networks first delineated in extended families were also present in nuclear families. Throughout the rsfMRI results, the heritable regions in the nuclear families were less extensive than those initially defined in the extended families.
Associations were found between the heritable functional connectivity of the DMN and both hyperactivity/impulsivity symptoms (t = −2.63; P = .008) and inattentive symptoms (t = −2.34; P = .02). Heritability estimates were robust to the exclusion of participants receiving psychostimulants and the exclusion of those receiving any psychotropic medication (eTables 5, 6, and 7 in the Supplement). A significant association between hyperactivity/impulsivity symptoms and the functional connectivity patterns within the ventral attention network was also found (t = −2.76; P = .006).
Considering developmental trends, the fractional anisotropy of most white matter tracts showed a childhood and adolescent increase, which stabilized and then decreased in adulthood (eResults, eTable 8, and eFigure 4 in the Supplement). We did not detect age-related changes in connectivity between the heritable regions and the rest of each network (eResults and eFigure 5 in the Supplement). Heritability estimates were mostly similar in younger (≤21 years) and adult (>21 years) groups (eTable 9 in the Supplement). In addition, associations between symptoms and connectivity measures did not vary significantly between these age groups.
Among white matter properties, 383 of 492 possible phenotypic trait pairs (77.8%) were significantly correlated (applying an FDR; q < 0.05). Correlated traits clustered more by diffusivity property than by tract location (Figure 3 and eFigures 6 and 7 in the Supplement). Functional connectivity was defined by an approach that provides independent components; thus, phenotypic correlations were neither expected nor found.
Genetic correlations were found within and across modalities. Within the 12 heritable white matter properties, shared heritability was found for 58 of the 66 possible pairs (87.9%) (FDR, q <0.05). Genetic correlations were present between the cognitive control and dorsal attention networks at trend level only (ρg = 0.41; P = .06).
Finally, we tested for cross-modal correlations. Heritable components of the ventral attention network showed both phenotypic and genetic correlations with the inferior fronto-occipital fasciculus. Specifically, the ventral attention network showed phenotypic (ρp = −0.11; P = .02) and genetic (ρg = −0.45; P = .02) correlations with radial diffusivity of the right interior fronto-occipital fasciculus. This finding implies that this phenotypic correlation is partly genetically determined. Some cross-modal correlations were purely phenotypic, including a correlation between the heritable aspects of the DMN and the right superior longitudinal fasciculus (ρp = −0.12; P = .03).
Several facets of structural and functional connectivity emerged as significantly heritable within extended families affected by ADHD. A separate cohort of nuclear families confirmed this heritability. For white matter tracts, heritability was found for microstructural features of the association (superior longitudinal fasciculi, inferior fronto-occipital, and uncinate fasciculi) and commissural (corpus callosum), but not for projection tracts (corticospinal tract). Heritable patterns of functional connectivity were also noted within the default mode, cognitive control, and attention networks. Association with ADHD symptom severity emerged primarily for the heritable facets of the right superior longitudinal fasciculus and the DMN. Finally, cross-modal phenotypic and genetic correlations were found. A white matter tract (inferior fronto-occipital fasciculus) was phenotypically correlated and shared common genetic determinants with the ventral attention network.
Microstructural properties of the right superior longitudinal fasciculus were both heritable and associated with ADHD following adjustment for multiple comparisons. Meta-analyses6 have found this tract to be compromised in ADHD, to be associated with working memory and sustained attention in children with and without ADHD,49-52 and to contain lesions that are tied to deficits in these cognitive domains.53,54 Thus, the tract is a promising candidate phenotype for future genetic studies.
Our estimates of heritability of white matter tracts are consistent with prior studies14-18,20,24-26 of extended families and twins who are either unaffected or heavily affected by psychiatric disorders. However, different tracts appear to be associated with different psychiatric disorders. For example, although heritable measures of the corpus callosum have been associated with bipolar affective disorder,24 we link ADHD symptoms with heritable properties of the right superior longitudinal fasciculus.
Using families enriched for ADHD, we confirmed the heritability of the DMN that was first reported19 among extended families not ascertained for mental illness. We also showed an association between these heritable DMN components and ADHD symptoms, implying a partly genetic determination of the atypical DMN activity that can disrupt goal-directed activity and drive ADHD symptoms. Furthermore, we found that other intrinsic networks closely associated with ADHD (the cognitive control and ventral attention networks) had heritable patterns of functional connectivity.
We detected genetic and phenotypic correlations spanning our measures of structural and functional connectivity. We found that genetic factors contribute to the phenotypic correlation between the functional connectivity within the ventral attention network and a major white matter tract: the inferior fronto-occipital fasciculus. The inferior fronto-occipital fasciculus connects dorsal parieto-occipital and basal temporo-occipital regions to the dorsolateral prefrontal and orbitofrontal cortex,55,56 making the inferior fronto-occipital fasciculus a plausible substrate for the physical connections within the ventral attention network. The ventral attention system is right lateralized and it is thus of note that the right inferior fronto-occipital fasciculus was found to be correlated.57 Altered microstructural properties of this tract have been reported in adult ADHD,5,58 which is consonant with its role in cognitive skills that are often impaired in ADHD, such as visuospatial integration and attention set shifting.59-62 Such cross-modal phenotypes that share genetic determinants may provide well-constrained phenotypes that are ideal for future genomic studies.
There are several limitations to the study. First, although the study’s cross-sectional design limits inferences about developmental trends, we found that heritability estimates and the associations between symptoms and connectivity measures did not differ by age group. However, a longitudinal study is needed to fully characterize possible interactions between age and heritability in ADHD. Second, many (but not all) findings in the extended families were confirmed in the nuclear families. The lack of confirmation could arise from differences in age composition between the extended and nuclear families and the smaller overall size of the nuclear family cohort. Finally, although we estimated movement during rsfMRI, we did not inquire whether the participant was able to sustain gaze throughout.
Demonstrating heritability and associations with a disorder is an initial but vital stage for the use of the structural and functional connectivity as phenotypes. The next step is to ask which genes drive this heritability and confer risk for ADHD.
Corresponding Author: Gustavo Sudre, PhD, Section on Neurobehavioral Clinical Research, Social and Behavioral Research Branch, National Human Genome Research Institute, Bldg 31, B1 B37, Bethesda, MD 20892 (firstname.lastname@example.org).
Accepted for Publication: September 27, 2016.
Published Online: November 16, 2016. doi:10.1001/jamapsychiatry.2016.3072
Author Contributions: Dr Sudre had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Shaw.
Acquisition, analysis, or interpretation of data: Sudre, Choudhury, Szekely, Bonner, Goduni, Sharp.
Drafting of the manuscript: Sudre, Szekely, Bonner.
Critical revision of the manuscript for important intellectual content: Sudre, Choudhury, Goduni, Sharp, Shaw.
Statistical analysis: Sudre, Goduni.
Administrative, technical, or material support: Sudre, Choudhury, Sharp.
Conflict of Interest Disclosures: None reported.
Funding/Support: Funded by the intramural research program of the National Human Genome Research Institute and the National Institute of Mental Health.
Role of the Funder/Sponsor: The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
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