Physical sequelae of anorexia nervosa (AN) include a marked reduction in whole brain volume and subcortical structures such as the hippocampus. Previous research has indicated aberrant levels of inflammatory markers and growth factors in AN, which in other populations have been shown to influence hippocampal integrity.

Here we investigated the influence of concentrations of two pro-inflammatory cytokines (tumor necrosis factor-alpha [TNF-α] and interleukin-6 [IL-6]) and brain-derived neurotrophic factor (BDNF) on the whole hippocampal volume, as well as the volumes of three regions (the hippocampal body, head, and tail) and 18 subfields bilaterally. Investigations occurred both cross-sectionally between acutely underweight adolescent/young adult females with AN (acAN; n = 82) and people recovered from AN (recAN; n = 20), each independently pairwise age-matched with healthy controls (HC), and longitudinally in acAN after partial renourishment (n = 58). Hippocampal subfield volumes were quantified using FreeSurfer. Concentrations of molecular factors were analyzed in linear models with hippocampal (subfield) volumes as the dependent variable.

Cross-sectionally, there was no evidence for an association between IL-6, TNF-α, or BDNF and between-group differences in hippocampal subfield volumes. Longitudinally, increasing concentrations of BDNF were positively associated with longitudinal increases in bilateral global hippocampal volumes after controlling for age, age2, estimated total intracranial volume, and increases in body mass index (BMI).

These findings suggest that increases in BDNF may contribute to global hippocampal recovery over and above increases in BMI during renourishment. Investigations into treatments targeted toward increasing BDNF in AN may be warranted.

Individuals with bipolar disorder are commonly correctly diagnosed a decade after symptom onset. Machine learning techniques may aid in early recognition and reduce the disease burden. As both individuals at risk and those with a manifest disease display structural brain markers, structural magnetic resonance imaging may provide relevant classification features.

Following a pre-registered protocol, we trained linear support vector machine (SVM) to classify individuals according to their estimated risk for bipolar disorder using regional cortical thickness of help-seeking individuals from seven study sites (N = 276). We estimated the risk using three state-of-the-art assessment instruments (BPSS-P, BARS, EPIbipolar).

For BPSS-P, SVM achieved a fair performance of Cohen's κ of 0.235 (95% CI 0.11–0.361) and a balanced accuracy of 63.1% (95% CI 55.9–70.3) in the 10-fold cross-validation. In the leave-one-site-out cross-validation, the model performed with a Cohen's κ of 0.128 (95% CI −0.069 to 0.325) and a balanced accuracy of 56.2% (95% CI 44.6–67.8). BARS and EPIbipolar could not be predicted. In post hoc analyses, regional surface area, subcortical volumes as well as hyperparameter optimization did not improve the performance.

Individuals at risk for bipolar disorder, as assessed by BPSS-P, display brain structural alterations that can be detected using machine learning. The achieved performance is comparable to previous studies which attempted to classify patients with manifest disease and healthy controls. Unlike previous studies of bipolar risk, our multicenter design permitted a leave-one-site-out cross-validation. Whole-brain cortical thickness seems to be superior to other structural brain features.

The amygdala is a subcortical limbic structure consisting of histologically and functionally distinct subregions. New automated structural magnetic resonance imaging (MRI) segmentation tools facilitate the in vivo study of individual amygdala nuclei in clinical populations such as patients with anorexia nervosa (AN) who show symptoms indicative of limbic dysregulation. This study is the first to investigate amygdala nuclei volumes in AN, their relationships with leptin, a key indicator of AN-related neuroendocrine alterations, and further clinical measures.

T1-weighted MRI scans were subsegmented and multi-stage quality controlled using FreeSurfer. Left/right hemispheric amygdala nuclei volumes were cross-sectionally compared between females with AN (n = 168, 12–29 years) and age-matched healthy females (n = 168) applying general linear models. Associations with plasma leptin, body mass index (BMI), illness duration, and psychiatric symptoms were analyzed via robust linear regression.

Globally, most amygdala nuclei volumes in both hemispheres were reduced in AN v. healthy control participants. Importantly, four specific nuclei (accessory basal, cortical, medial nuclei, corticoamygdaloid transition in the rostral-medial amygdala) showed greater volumetric reduction even relative to reductions of whole amygdala and total subcortical gray matter volumes, whereas basal, lateral, and paralaminar nuclei were less reduced. All rostral-medially clustered nuclei were positively associated with leptin in AN independent of BMI. Amygdala nuclei volumes were not associated with illness duration or psychiatric symptom severity in AN.

In AN, amygdala nuclei are altered to different degrees. Severe volume loss in rostral-medially clustered nuclei, collectively involved in olfactory/food-related reward processing, may represent a structural correlate of AN-related symptoms. Hypoleptinemia might be linked to rostral-medial amygdala alterations.

Despite decades of brain MRI research demonstrating atypical neuroanatomical substrate in patients with autism spectrum disorder (ASD), it remains unclear whether and to what extent disorder-selective neuroanatomical abnormalities occur in this spectrum. This, and the fact that multiple brain disorders report a common neuroanatomical substrate, makes transference and the application of neuroimaging findings into the clinical setting an open challenge.

To investigate the selective neuroanatomical alteration profile of the ASD brain, we employed a meta-analytic, data-driven, and reverse inference-based approach (i.e.; Bayes fACtor mOdeliNg).

Eligible voxel-based morphometry data were extracted by a standardized search on BrainMap and MEDLINE databases (849 published experiments, 131 brain disorders, 22747 clinical subjects, 16572 x-y-z coordinates). Two distinct datasets were generated: the ASD dataset, composed of ASD-related data; and the non-ASD dataset, composed of all other clinical conditions data. Starting from the two unthresholded activation likelihood estimation (ALE) maps, the calculus of the Bayes fACtor mOdeliNg was performed. This allowed us to obtain posterior probability distributions on the evidence of brain alteration specificity in ASD.

We revealed both cortical and cerebellar areas of neuroanatomical alteration selectivity in ASD. Eight clusters showed a selectivity value ≥ 90%, namely the bilateral precuneus, the right inferior occipital gyrus, left lobule IX, left Crus II, right Crus I, and the right lobule VIIIA (Fig. 1).

The identification of this neuroanatomical pattern provides new insights into the complex pathophysiology of ASD, opening attractive prospects for future neuroimaging-based interventions.

No significant relationships.

Despite a well-established link between childhood traumatic brain injury (TBI) and elevated secondary attention-deficit/hyperactivity disorder (s-ADHD) symptomology, the neurostructural correlates of these symptoms are largely unknown. Based on the influential ‘triple-network model’ of ADHD, this prospective longitudinal investigation aimed to (i) assess the effect of childhood TBI on brain morphometry of higher-order cognitive networks proposed to play a key role in ADHD pathophysiology, including the default-mode network (DMN), salience network (SN) and central executive network (CEN); and (ii) assess the independent prognostic value of DMN, SN and CEN morphometry in predicting s-ADHD symptom severity after childhood TBI.

The study sample comprised 155 participants, including 112 children with medically confirmed mild-severe TBI ascertained from consecutive hospital admissions, and 43 typically developing (TD) children matched for age, sex and socio-economic status. High-resolution structural brain magnetic resonance imaging (MRI) sequences were acquired sub-acutely in a subset of 103 children with TBI and 34 TD children. Parents completed well-validated measures of ADHD symptom severity at 12-months post injury.

Relative to TD children and those with milder levels of TBI severity (mild, complicated mild, moderate), children with severe TBI showed altered brain morphometry within large-scale, higher-order cognitive networks, including significantly diminished grey matter volumes within the DMN, SN and CEN. When compared with the TD group, the TBI group showed significantly higher ADHD symptomatology and higher rates of clinically elevated symptoms. In multivariable models adjusted for other well-established risk factors, altered DMN morphometry independently predicted higher s-ADHD symptomatology at 12-months post-injury, whilst SN and CEN morphometry were not significant independent predictors.

Our prospective study findings suggest that neurostructural alterations within higher-order cognitive circuitry may represent a prospective risk factor for s-ADHD symptomatology at 12-months post-injury in children with TBI. High-resolution structural brain MRI has potential to provide early prognostic biomarkers that may help early identification of high-risk children with TBI who are likely to benefit from early surveillance and preventive measures to optimise long-term neuropsychiatric outcomes.

To examine the direct and indirect effects of age, APOE ϵ4 genotype, amyloid positivity, and volumetric reductions in AD-prone brain regions as it relates to semantic intrusion errors reflecting proactive semantic interference (PSI) and the failure to recover from proactive semantic interference (frPSI) on the Loewenstein-Acevedo Scales of Semantic Interference and Learning (LASSI-L), a cognitive stress test that has been consistently more predictive of preclinical and prodromal Alzheimer’s disease (AD) than traditional list-learning tests.

Cross-sectional study.

1Florida Alzheimer’s Disease Research Center baseline study.

Two-hundred and twelve participants with Mini-Mental State Examination (MMSE) score above 16 and a broad array of cognitive diagnoses ranging from cognitively normal (CN) to dementia, of whom 58% were female, mean age of 72.1 (SD 7.9).

Participants underwent extensive clinical and neuropsychological evaluations, MR and amyloid Positron Emission Tomography/Computer/Computer Tomography (PET/CT) imaging, and analyses of APOE ϵ4 genotype. Confirmatory path analyses were conducted in the structural equation modeling framework that estimated multiple equations simultaneously while controlling for important covariates such as sex, education, language of evaluation, and global cognitive impairment.

Both amyloid positivity and decreased brain volumes in AD-prone regions were directly related to LASSI-L Cued B1 and Cued B2 intrusions (sensitive to PSI and frPSI effects) even after controlling for covariates. APOE ϵ4 status did not evidence direct effects on these LASSI-L cognitive markers, but rather exerted their effects on amyloid positivity, which in turn related to PSI and frPSI. Similarly, age did not have a direct relationship with LASSI-L scores, but exerted its effects indirectly through amyloid positivity and volumes of AD-prone brain regions.

Our study provides insight into the relationships among age, APOE ϵ4, amyloid, and brain volumetric reductions as it relates to semantic intrusion errors. The investigation expands our understanding of the underpinnings of PSI and frPSI intrusions in a large cohort.

Bipolar disorder (BD) is a familial psychiatric disorder associated with frontotemporal and subcortical brain abnormalities. It is unclear whether such abnormalities are present in relatives without BD, and little is known about structural brain trajectories in those at risk.

Neuroimaging was conducted at baseline and at 2-year follow-up interval in 90 high-risk individuals with a first-degree BD relative (HR), and 56 participants with no family history of mental illness who could have non-BD diagnoses. All 146 subjects were aged 12–30 years at baseline. We examined longitudinal change in gray and white matter volume, cortical thickness, and surface area in the frontotemporal cortex and subcortical regions.

Compared to controls, HR participants showed accelerated cortical thinning and volume reduction in right lateralised frontal regions, including the inferior frontal gyrus, lateral orbitofrontal cortex, frontal pole and rostral middle frontal gyrus. Independent of time, the HR group had greater cortical thickness in the left caudal anterior cingulate cortex, larger volume in the right medial orbitofrontal cortex and greater area of right accumbens, compared to controls. This pattern was evident even in those without the new onset of psychopathology during the inter-scan interval.

This study suggests that differences previously observed in BD are developing prior to the onset of the disorder. The pattern of pathological acceleration of cortical thinning is likely consistent with a disturbance of molecular mechanisms responsible for normal cortical thinning. We also demonstrate that neuroanatomical differences in HR individuals may be progressive in some regions and stable in others.

Major depressive disorder (MDD) is accompanied by alterations in grey matter volume. However, the biological processes associated with regional structural perturbations remain elusive.

We applied integrative omics analysis to investigate specialized transcriptome signatures and translational determinants associated with regional grey matter variations in 2737 MDD patients relative to 3098 controls by summarizing the results from gene co-expression network analysis of Allen human brain transcriptome profiles in six donors, enrichment analysis of gene-sets and cellular structure from rodents and mediation analysis of BrainSpan proteome profile in six donors.

We found convergent alterations of grey matter volume in MDD were associated with transcriptome profiles enriched for synaptic transmission, metabolism, immune processes and transmembrane transport. Genes with abnormal expression in post-mortem tissue in MDD were also associated with transcriptome signatures. Further gene co-expression network and enrichment analysis of MDD-related genes in these signatures revealed the modules with higher neuronal expression were enriched in the medial temporal cortex and temporo-parietal junction with genes differentially associated with neuronal development and metabolism. Also, the modules with higher non-neuronal (e.g. astrocyte and oligodendrocyte) expression were concentrated in the rostral and dorsal anterior cingulate cortex and were separately associated with immune response and transmembrane transport. Moreover, proteins as the gene expression products mediated the association between transcriptome signatures and brain volume changes in the visual and dorsolateral prefrontal cortex.

Our multidimensional analyses offer a novel approach to detect specific biological pathways that capture regional structural variations in MDD, which suggests structural endophenotypes associated with MDD.

Right cerebellar-left frontal (RC-LF) white matter integrity (WMI) has been associated with working memory. However, prior studies have employed measures of working memory that include processing speed and attention. We examined the relationships between the RC-LF WMI and processing speed, attention, and working memory to clarify the relationship of RC-LF WMI with a specific cognitive function. Right superior longitudinal fasciculus II (SLF II) WMI and visual attention were included as a negative control tract and task to demonstrate a double dissociation.

Adult survivors of childhood brain tumors [n = 29, age: M = 22 years (SD = 5), 45% female] and demographically matched controls were recruited (n = 29). Tests of auditory attention span, working memory, and visual attention served as cognitive measures. Participants completed a 3-T MRI diffusion-weighted imaging scan. Fractional anisotropy (FA) and radial diffusivity (RD) served as WMI measures. Partial correlations between WMI and cognitive scores included controlling for type of treatment.

A correlational double dissociation was found. RC-LF WMI was associated with auditory attention (FA: r = .42, p = .03; RD: r = −.50, p = .01) and was not associated with visual attention (FA: r = −.11, p = .59; RD: r = −.11, p = .57). SLF II FA WMI was associated with visual attention (FA: r = .44, p = .02; RD: r = −.17, p = .40) and was not associated with auditory attention (FA: r = .24, p = .22; RD: r = −.10, p = .62).

The results show that RC-LF WMI is associated with auditory attention span rather than working memory per se and provides evidence for a specificity based on the correlational double dissociation.

The aim of the current study was to examine whether and to what extent mood disorders, comprising major depression and bipolar disorder, are accompanied by structural changes in the brain as measured using voxel-based morphometry (VBM).

We performed a VBM study using a 3Т MRI system (GE Discovery 750w) in patients with mood disorders (n=50), namely, 39 with major depression and 11 with bipolar disorder compared to 42 age-, sex- and education-matched healthy controls.

Our results show that depression was associated with significant decreases in grey matter (GM) volume of the regions located within the medial frontal and anterior cingulate cortex on the left side and middle frontal gyrus, medial orbital gyrus, inferior frontal gyrus (triangular and orbital parts) and middle temporal gyrus (extending to the superior temporal gyrus) on the right side. When the patient group was separated into bipolar disorder and major depression, the reductions remained significant only for patients with major depressive disorder.

Using VBM the present study was able to replicate decreases in GM volume restricted to frontal and temporal regions in patients with mood disorders, mainly major depression, compared with healthy controls.

Although recent studies have suggested that the γ-aminobutyric acid type A (GABAA) receptor binding affinity can be a more sensitive marker of age-related neuronal loss than regional gray matter (GM) volume, knowledge about the relationship between decreased GABAA receptor binding affinity and cognitive decline during normal aging is still limited.

Thirty-seven healthy elderly individuals (aged 50–77 years (mean, 64.5 ± 7.3 years); 15 males and 22 females) were enrolled in this study. We investigated the association of the performance of the healthy elderly in the attentional function test with regional GM volume, regional cerebral bold flow (rCBF), and GABAA receptor binding affinity in the resting state by structural magnetic resonance imaging (MRI), arterial spin labeling (ASL), and 123I-iomazenil (IMZ) SPECT, with the analysis focusing on the bilateral inferior frontal gyri.

The score of the rapid visual information processing (RVP) test, which is used to assess visual sustained attention, showed a positive correlation with GABAA receptor binding affinity in the right inferior frontal gyrus. No significant correlation was found between RVP test score and regional GM volume or rCBF.

The findings of 123I-IMZ SPECT, but not those of structural MRI or ASL, suggest that a decreased GABAA receptor binding affinity can be a sensitive marker of cognitive impairment.

Schizophrenia is a highly heritable disorder, linked to several structural abnormalities of the brain. More specifically, previous findings have suggested that increased gyrification in frontal and temporal regions are implicated in the pathogenesis of schizophrenia.

The current study included participants at high familial risk of schizophrenia who remained well (n = 31), who developed sub-diagnostic symptoms (n = 28) and who developed schizophrenia (n = 9) as well as healthy controls (HC) (n = 16). We first tested whether individuals at high familial risk of schizophrenia carried an increased burden of trait-associated alleles using polygenic risk score analysis. We then assessed the extent to which polygenic risk was associated with gyral folding in the frontal and temporal lobes.

We found that individuals at high familial risk of schizophrenia who developed schizophrenia carried a significantly greater burden of risk-conferring variants for the disorder compared to those at high risk (HR) who developed sub-diagnostic symptoms or remained well and HC. Furthermore, within the HR cohort, there was a significant and positive association between schizophrenia polygenic risk score and bilateral frontal gyrification.

These results suggest that polygenic risk for schizophrenia impacts upon early neurodevelopment to confer greater gyral folding in adulthood and an increased risk of developing the disorder.