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Background: Widely used psychotropic medications for obsessive-compulsive disorder (OCD) may change the volumes of subcortical brain structures, and differently in children vs. adults. We measured subcortical volumes cross-sectionally in patients finely stratified for age taking various common classes of OCD drugs. Methods: The ENIGMA-OCD consortium sample (1081 medicated/1159 unmedicated OCD patients and 2057 healthy controls aged 6–65) was divided into six successive 6–10-year age-groups. Individual structural MRIs were parcellated automatically using FreeSurfer into 8 regions-of-interest (ROIs). ROI volumes were compared between unmedicated and medicated patients and controls, and between patients taking serotonin reuptake inhibitors (SRIs), tricyclics (TCs), antipsychotics (APs), or benzodiazepines (BZs) and unmedicated patients. Results: Compared to unmedicated patients, volumes of accumbens, caudate, and/or putamen were lower in children aged 6–13 and adults aged 50–65 with OCD taking SRIs (Cohen's d = −0.24 to −0.74). Volumes of putamen, pallidum (d = 0.18–0.40), and ventricles (d = 0.31–0.66) were greater in patients aged 20–29 receiving APs. Hippocampal volumes were smaller in patients aged 20 and older taking TCs and/or BZs (d = −0.27 to −1.31). Conclusions: Results suggest that TCs and BZs could potentially aggravate hippocampal atrophy of normal aging in older adults with OCD, whereas SRIs may reduce striatal volumes in young children and older adults. Similar to patients with psychotic disorders, OCD patients aged 20–29 may experience subcortical nuclear and ventricular hypertrophy in relation to APs. Although cross-sectional, present results suggest that commonly prescribed agents exert macroscopic effects on subcortical nuclei of unknown relation to therapeutic response.

Vascular endothelial growth factor (VEGF) is a complex signaling protein that supports vascular and neuronal function. Alzheimer's disease (AD) -neuropathological hallmarks interfere with VEGF signaling and modify previously detected positive associations between cerebral spinal fluid (CSF) VEGF and cognition and hippocampal volume. However, it remains unknown 1) whether regional relationships between VEGF and glucose metabolism and cortical thinning exist, and 2) whether AD-neuropathological hallmarks (CSF Aβ, t-tau, p-tau) also modify these relationships. We addressed this in 310 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants (92 cognitively normal, 149 mild cognitive impairment, 69 AD; 215 CSF Aβ+, 95 CSF Aβ-) with regional cortical thickness and cognition measurements and 158 participants with FDG-PET. In Aβ + participants (CSF Aβ42 ≤ 192 pg/mL), higher CSF VEGF levels were associated with greater FDG-PET signal in the inferior parietal, and middle and inferior temporal cortices. Abnormal CSF amyloid and tau levels strengthened the positive association between VEGF and regional FDG-PET indices. VEGF also had both direct associations with semantic memory, as well as indirect associations mediated by regional FDG-PET signal to cognition.

We aimed to investigate the relationship between striatal morphology in Huntington disease (HD) and measures of motor and cognitive dysfunction. MRI scans, from the IMAGE-HD study, were obtained from 36 individuals with pre-symptomatic HD (pre-HD), 37 with early symptomatic HD (symp-HD), and 36 healthy matched controls. The neostriatum was manually segmented and a surface-based parametric mapping protocol derived two pointwise shape measures: thickness and surface dilation ratio. Significant shape differences were detected between all groups. Negative associations were detected between lower thickness and surface area shape measure and CAG repeats, disease burden score, and UHDRS total motor score. In symp-HD, UPSIT scores were correlated with higher thickness in left caudate tail and surface dilation ratio in left posterior putamen; Stroop scores were positively correlated with the thickness of left putamen head and body. Self-paced tapping (slow) was correlated with higher thickness and surface dilation ratio in the right caudate in symp-HD and with bilateral putamen in pre-HD. Self-paced tapping (fast) was correlated with higher surface dilation ratio in the right anterior putamen in symp-HD. Shape changes correlated with functional measures subserved by corticostriatal circuits, suggesting that the neostriatum is a potentially useful structural basis for characterisation of endophenotypes of HD.

Patients with schizophrenia show severe impairment in social function and have difficulty in their daily social life. Although a recent large-scale multicenter study revealed alterations in white matter microstructures, the association between these anatomical changes and social dysfunction in schizophrenia remains unknown. Therefore, we investigated the association between the white matter integrity of regions of interest and social function in schizophrenia. A total of 149 patients with schizophrenia and 602 healthy comparison subjects (HCS) underwent DTI and completed the Picture Arrangement subtest of the Wechsler Adult Intelligence Scale-Third Edition and the Finance subscale of the University of California, San Diego, Performance-Based Skills Assessment Brief, as social indices of interest. The fractional anisotropy (FA) in the anterior corona radiata and corpus callosum was significantly lower in patients than in HCS, and the radial diffusivity (RD) in the anterior corona radiata and corpus callosum was significantly higher in patients. The Picture Arrangement and Finance scores were both significantly impaired in patients. The effect of the FA of the right anterior corona radiata on the Finance score and the Picture Arrangement score, of the RD of the right anterior corona radiata on the Picture Arrangement score, and of the RD of the corpus callosum on the Picture Arrangement score were significant. In conclusion, our results confirmed the association between structural connectivity in the right frontal white matter and corpus callosum and social function in schizophrenia. These findings may provide a foundation for developing an intervention for functional recovery in schizophrenia.

Inflammatory processes may contribute to risk for Alzheimer's disease (AD) and age-related brain degeneration. Metabolic and genetic risk factors, and physical activity may, in turn, influence these inflammatory processes. Some of these risk factors are modifiable, and interact with each other. Understanding how these processes together relate to brain aging will help to inform future interventions to treat or prevent cognitive decline. We used brain magnetic resonance imaging (MRI) to scan 335 older adult humans (mean age 77.3 ± 3.4 years) who remained non-demented for the duration of the 9-year longitudinal study. We used structural equation modeling (SEM) in a subset of 226 adults to evaluate whether measures of baseline peripheral inflammation (serum C-reactive protein levels; CRP), mediated the baseline contributions of genetic and metabolic risk, and physical activity, to regional cortical thickness in AD-relevant brain regions at study year 9. We found that both baseline metabolic risk and AD risk variant apolipoprotein E e4 (APOE4), modulated baseline serum CRP. Higher baseline CRP levels, in turn, predicted thinner regional cortex at year 9, and mediated an effect between higher metabolic risk and thinner cortex in those regions. A higher polygenic risk score composed of variants in immune-associated AD risk genes (other than APOE) was associated with thinner regional cortex. However, CRP levels did not mediate this effect, suggesting that other mechanisms may be responsible for the elevated AD risk. We found interactions between genetic and environmental factors and structural brain health. Our findings support the role of metabolic risk and peripheral inflammation in age-related brain decline.

Scientific reports of sex differences in brain asymmetry - the difference between the two hemispheres - are rather inconsistent. Some studies report no sex differences whatsoever, others reveal striking sex effects, with large discrepancies across studies in the magnitude, direction, and location of the observed effects. One reason for the lack of consistency in findings may be the confounding effects of brain size as male brains are usually larger than female brains. Thus, the goal of this study was to investigate the differential contributions of sex and brain size to asymmetry with a particular focus on gray matter. For this purpose, we applied a well-validated workflow for voxel-wise gray matter asymmetry analyses in a sample of 96 participants (48 males/48 females), in which a subsample of brains (24 males/24 females) were matched for size. By comparing outcomes based on three different contrasts - all males versus all females; all large brains versus all small brains; matched males versus matched females - we were able to disentangle the contributing effects of sex and brain size, to reveal true (size-independent) sex differences in gray matter asymmetry: Males show a significantly stronger rightward asymmetry than females within the cerebellum, specifically in lobules VII, VIII, and IX. This finding agrees closely with prior research suggesting sex differences in sensorimotor, cognitive and emotional function, which are all moderated by the respective cerebellar sections. No other significant sex effects on gray matter were detected across the remainder of the brain.

Imaging genetics analyses use neuroimaging traits as intermediate phenotypes to infer the degree of genetic contribution to brain structure and function in health and/or illness. Coefficients of relatedness (CR) summarize the degree of genetic similarity among subjects and are used to estimate the heritability – the proportion of phenotypic variance explained by genetic factors. The CR can be inferred directly from genome-wide genotype data to explain the degree of shared variation in common genetic polymorphisms (SNP-heritability) among related or unrelated subjects. We developed a central processing and graphics processing unit (CPU and GPU) accelerated Fast and Powerful Heritability Inference (FPHI) approach that linearizes likelihood calculations to overcome the ∼N2–3 computational effort dependency on sample size of classical likelihood approaches. We calculated for 60 regional and 1.3 × 105 voxel-wise traits in N = 1,206 twin and sibling participants from the Human Connectome Project (HCP) (550 M/656 F, age = 28.8 ± 3.7 years) and N = 37,432 (17,531 M/19,901 F; age = 63.7 ± 7.5 years) participants from the UK Biobank (UKBB). The FPHI estimates were in excellent agreement with heritability values calculated using Genome-wide Complex Trait Analysis software (r = 0.96 and 0.98 in HCP and UKBB sample) while significantly reducing computational (102–4 times). The regional and voxel-wise traits heritability estimates for the HCP and UKBB were likewise in excellent agreement (r = 0.63–0.76, p < 10−10). In summary, the hardware-accelerated FPHI made it practical to calculate heritability values for voxel-wise neuroimaging traits, even in very large samples such as the UKBB. The patterns of additive genetic variance in neuroimaging traits measured in a large sample of related and unrelated individuals showed excellent agreement regardless of the estimation method. The code and instruction to execute these analyses are available at www.solar-eclipse-genetics.org.

There is increasing interest in the potential contribution of the gut microbiome to autism spectrum disorder (ASD). However, previous studies have been underpowered and have not been designed to address potential confounding factors in a comprehensive way. We performed a large autism stool metagenomics study (n = 247) based on participants from the Australian Autism Biobank and the Queensland Twin Adolescent Brain project. We found negligible direct associations between ASD diagnosis and the gut microbiome. Instead, our data support a model whereby ASD-related restricted interests are associated with less-diverse diet, and in turn reduced microbial taxonomic diversity and looser stool consistency. In contrast to ASD diagnosis, our dataset was well powered to detect microbiome associations with traits such as age, dietary intake, and stool consistency. Overall, microbiome differences in ASD may reflect dietary preferences that relate to diagnostic features, and we caution against claims that the microbiome has a driving role in ASD.

Background: Neuroanatomical abnormalities have been reported along a continuum from at-risk stages, including high schizotypy, to early and chronic psychosis. However, a comprehensive neuroanatomical mapping of schizotypy remains to be established. The authors conducted the first large-scale meta-analyses of cortical and subcortical morphometric patterns of schizotypy in healthy individuals and compared these patterns with neuroanatomical abnormalities observed in major psychiatric disorders. Methods: The sample comprised 2,952 unmedicated healthy individuals (12-68 years, 46.5% male) from 26 cohorts of the worldwide ENIGMA Schizotypy working group. Cortical and subcortical effect size maps with schizotypy scores were generated using standardized methods. Pattern similarities were assessed between the schizotypy-related cortical and subcortical maps and effect size maps from comparisons of schizophrenia (SZ), bipolar disorder (BD) and major depression (MDD) patients with controls. Results: Cortical thickness in the right medial orbitofrontal/ventromedial prefrontal cortex (mOFC/vmPFC) showed a significant positive correlation with schizotypy scores (r=.07, pFDR=.02). The cortical thickness profile in schizotypy was positively correlated with cortical abnormalities in SZ (r=.33, pspin=.01), but not BD (r=.19, pspin=.16) or MDD (r=-.22, pspin=.10). The schizotypy-related subcortical volume pattern was negatively correlated with subcortical abnormalities in SZ (rho=-.65, pspin=.01), BD (rho=-.63, pspin=.01), and MDD (rho=-.69, pspin=.004). Conclusions: Comprehensive mapping of schizotypy-related brain morphometry in the general population revealed a significant relationship between higher schizotypy and thicker mOFC/vmPFC, in the absence of confounding effects due to antipsychotic medication or disease chronicity. The cortical pattern similarity between schizotypy and schizophrenia yields new insights into a dimensional neurobiological continuity across the extended psychosis phenotype. Matthias Kirschner acknowledges support from the Swiss National Foundation (P2SKP3_178175).

We present a continuous model for structural brain connectivity based on the Poisson point process. The model treats each streamline curve in a tractography as an observed event in connectome space, here the product space of the gray matter/white matter interfaces. We approximate the model parameter via kernel density estimation. To deal with the heavy computational burden, we develop a fast parameter estimation method by pre-computing associated Legendre products of the data, leveraging properties of the spherical heat kernel. We show how our approach can be used to assess the quality of cortical parcellations with respect to connectivity. We further present empirical results that suggest that “discrete” connectomes derived from our model have substantially higher test-retest reliability compared to standard methods. In this, the expanded form of this paper for journal publication, we also explore parcellation free analysis techniques that avoid the use of explicit partitions of the cortical surface altogether. We provide an analysis of sex effects on our proposed continuous representation, demonstrating the utility of this approach.

Background The C677T functional variant in the methylenetetrahydrofolate reductase ( MTHFR ) gene leads to reduced enzymatic activity and elevated blood homocysteine levels. Hyperhomocysteinemia has been linked with higher rates of cardiovascular diseases, cognitive decline, and late-life depression. Methods Three-dimensional magnetic resonance imaging data were analyzed from 738 individuals (aged 75.5 ± 6.8 years; 438 men, 300 women), including 173 patients with Alzheimer's disease, 359 subjects with mild cognitive impairment, and 206 healthy older adults, scanned as part of the Alzheimer's Disease Neuroimaging Initiative. Results We found that this variant associates with localized brain atrophy, after controlling for age, sex, and dementia status, in brain regions implicated in both intellectual and emotional functioning, notably the medial orbitofrontal cortices. The medial orbitofrontal cortex is involved in the cognitive modulation of emotional processes, and localized atrophy in this region was previously linked with both cognitive impairment and depressive symptoms. Here, we report that increased plasma homocysteine level mediates the association between MTHFR genotype and lower medial orbitofrontal volumes and that these volumes mediate the association between cognitive decline and depressed mood in this elderly cohort. We additionally show that vitamin B 12 deficiency interacts with the C677T variant in the etiology of hyperhomocysteinemia. Conclusions This study sheds light on important relationships between vascular risk factors, age-related cognitive decline, and late-life depression, and it represents a significant advance in our understanding of clinically relevant associations relating to MTHFR genotype.

High-dimensional shape descriptors (HDSD) are useful for modeling subcortical brain surface morphometry. Though HDSD is a useful basis for disease biomarkers, its high dimensionality requires careful treatment in its application to machine learning to mitigate the curse of dimensionality. We explored the use of HDSD feature sets by comparing the performance of two feature selection approaches, Regularized Random Forest (RRF) and LASSO, to no feature selection (NFS). Each feature set was applied to three classifiers: Random Forest (RF), Support Vector Machines (SVM) and Naive Bayes (NB). Paired feature-selection-classifier approaches were 10-fold cross-validated on two diagnostic contrasts: Alzheimer's disease and mild cognitive impairment, both relative to controls across varying sample sizes to evaluate their robustness. LASSO aided classification efficiency, however, RRF and NFS afforded more robust performances. Performance varied considerably by classifier with RF being most stable. We advise careful consideration of performance-efficiency tradeoffs in choosing feature selection strategies for HDSD.