Cortical gyrification in women and men and the (missing) link to prenatal androgens.

Previous studies have reported sex differences in cortical gyrification. Since most cortical folding is principally defined in utero, sex chromosomes as well as gonadal hormones are likely to influence sex-specific aspects of local gyrification. Classic congenital adrenal hyperplasia (CAH) causes high levels of androgens during gestation in females, whereas levels in males are largely within the typical male range. Therefore, CAH provides an opportunity to study the possible effects of prenatal androgens on cortical gyrification. Here, we examined the vertex-wise absolute mean curvature-a common estimate for cortical gyrification-in individuals with CAH (33 women and 20 men) and pair-wise matched controls (33 women and 20 men). There was no significant main effect of CAH and no significant CAH-by-sex interaction. However, there was a significant main effect of sex in five cortical regions, where gyrification was increased in women compared to men. These regions were located on the lateral surface of the brain, specifically left middle frontal (rostral and caudal), right inferior frontal, left inferior parietal, and right occipital. There was no cortical region where gyrification was increased in men compared to women. Our findings do not only confirm prior reports of increased cortical gyrification in female brains but also suggest that cortical gyrification is not significantly affected by prenatal androgen exposure. Instead, cortical gyrification might be determined by sex chromosomes either directly or indirectly-the latter potentially by affecting the underlying architecture of the cortex or the size of the intracranial cavity, which is smaller in women.

BrainAGE: Revisited and reframed machine learning workflow.

Since the introduction of the BrainAGE method, novel machine learning methods for brain age prediction have continued to emerge. The idea of estimating the chronological age from magnetic resonance images proved to be an interesting field of research due to the relative simplicity of its interpretation and its potential use as a biomarker of brain health. We revised our previous BrainAGE approach, originally utilising relevance vector regression (RVR), and substituted it with Gaussian process regression (GPR), which enables more stable processing of larger datasets, such as the UK Biobank (UKB). In addition, we extended the global BrainAGE approach to regional BrainAGE, providing spatially specific scores for five brain lobes per hemisphere. We tested the performance of the new algorithms under several different conditions and investigated their validity on the ADNI and schizophrenia samples, as well as on a synthetic dataset of neocortical thinning. The results show an improved performance of the reframed global model on the UKB sample with a mean absolute error (MAE) of less than 2 years and a significant difference in BrainAGE between healthy participants and patients with Alzheimer's disease and schizophrenia. Moreover, the workings of the algorithm show meaningful effects for a simulated neocortical atrophy dataset. The regional BrainAGE model performed well on two clinical samples, showing disease-specific patterns for different levels of impairment. The results demonstrate that the new improved algorithms provide reliable and valid brain age estimations.

Cortical thickness alterations and systemic inflammation define long-COVID patients with cognitive impairment.

As the heterogeneity of symptoms is increasingly recognized among long-COVID patients, it appears highly relevant to study potential pathophysiological differences along the different subtypes. Preliminary evidence suggests distinct alterations in brain structure and systemic inflammatory patterns in specific groups of long-COVID patients. To this end, we analyzed differences in cortical thickness and peripheral immune signature between clinical subgroups based on 3 T-MRI scans and signature inflammatory markers in n = 120 participants comprising healthy never-infected controls (n = 30), healthy COVID-19 survivors (n = 29), and subgroups of long-COVID patients with (n = 26) and without (n = 35) cognitive impairment according to screening with Montreal Cognitive Assessment. Whole-brain comparison of cortical thickness between the 4 groups was conducted by surface-based morphometry. We identified distinct cortical areas showing a progressive increase in cortical thickness across different groups, starting from healthy individuals who had never been infected with COVID-19, followed by healthy COVID-19 survivors, long-COVID patients without cognitive deficits (MoCA ≥ 26), and finally, long-COVID patients exhibiting significant cognitive deficits (MoCA < 26). These findings highlight the continuum of cortical thickness alterations associated with COVID-19, with more pronounced changes observed in individuals experiencing cognitive impairment (p < 0.05, FWE-corrected). Affected cortical regions covered prefrontal and temporal gyri, insula, posterior cingulate, parahippocampal gyrus, and parietal areas. Additionally, we discovered a distinct immunophenotype, with elevated levels of IL-10, IFNγ, and sTREM2 in long-COVID patients, especially in the group suffering from cognitive impairment. We demonstrate lingering cortical and immunological alterations in healthy and impaired subgroups of COVID-19 survivors. This implies a complex underlying pathomechanism in long-COVID and emphasizes the necessity to investigate the whole spectrum of post-COVID biology to determine targeted treatment strategies targeting specific sub-groups.

Normal cohorts in automated brain atrophy estimation: how many healthy subjects to include?

OBJECTIVES: This study investigates the influence of normal cohort (NC) size and the impact of different NCs on automated MRI-based brain atrophy estimation. METHODS: A pooled NC of 3945 subjects (NCpool) was retrospectively created from five publicly available cohorts. Voxel-wise gray matter volume atrophy maps were calculated for 48 Alzheimer's disease (AD) patients (55-82 years) using veganbagel and dynamic normal templates with an increasing number of healthy subjects randomly drawn from NCpool (initially three, and finally 100 subjects). Over 100 repeats of the process, the mean over a voxel-wise standard deviation of gray matter z-scores was established and plotted against the number of subjects in the templates. The knee point of these curves was defined as the minimum number of subjects required for consistent brain atrophy estimation. Atrophy maps were calculated using each NC for AD patients and matched healthy controls (HC). Two readers rated the extent of mesiotemporal atrophy to discriminate AD/HC. RESULTS: The maximum knee point was at 15 subjects. For 21 AD/21 HC, a sufficient number of subjects were available in each NC for validation. Readers agreed on the AD diagnosis in all cases (Kappa for the extent of atrophy, 0.98). No differences in diagnoses between NCs were observed (intraclass correlation coefficient, 0.91; Cochran's Q, p = 0.19). CONCLUSION: At least 15 subjects should be included in age- and sex-specific normal templates for consistent brain atrophy estimation. In the study's context, qualitative interpretation of regional atrophy allows reliable AD diagnosis with a high inter-reader agreement, irrespective of the NC used. CLINICAL RELEVANCE STATEMENT: The influence of normal cohorts (NCs) on automated brain atrophy estimation, typically comparing individual scans to NCs, remains largely unexplored. Our study establishes the minimum number of NC-subjects needed and demonstrates minimal impact of different NCs on regional atrophy estimation. KEY POINTS: • Software-based brain atrophy estimation often relies on normal cohorts for comparisons. • At least 15 subjects must be included in an age- and sex-specific normal cohort. • Using different normal cohorts does not influence regional atrophy estimation.

Data-driven multivariate identification of gyrification patterns in a transdiagnostic patient cohort: A cluster analysis approach.

BACKGROUND: Multivariate data-driven statistical approaches offer the opportunity to study multi-dimensional interdependences between a large set of biological parameters, such as high-dimensional brain imaging data. For gyrification, a putative marker of early neurodevelopment, direct comparisons of patterns among multiple psychiatric disorders and investigations of potential heterogeneity of gyrification within one disorder and a transdiagnostic characterization of neuroanatomical features are lacking. METHODS: In this study we used a data-driven, multivariate statistical approach to analyze cortical gyrification in a large cohort of N = 1028 patients with major psychiatric disorders (Major depressive disorder: n = 783, bipolar disorder: n = 129, schizoaffective disorder: n = 44, schizophrenia: n = 72) to identify cluster patterns of gyrification beyond diagnostic categories. RESULTS: Cluster analysis applied on gyrification data of 68 brain regions (DK-40 atlas) identified three clusters showing difference in overall (global) gyrification and minor regional variation (regions). Newly, data-driven subgroups are further discriminative in cognition and transdiagnostic disease risk factors. CONCLUSIONS: Results indicate that gyrification is associated with transdiagnostic risk factors rather than diagnostic categories and further imply a more global role of gyrification related to mental health than a disorder specific one. Our findings support previous studies highlighting the importance of association cortices involved in psychopathology. Explorative, data-driven approaches like ours can help to elucidate if the brain imaging data on hand and its a priori applied grouping actually has the potential to find meaningful effects or if previous hypotheses about the phenotype as well as its grouping have to be revisited.

Cortical and subcortical neuroanatomical signatures of schizotypy in 3004 individuals assessed in a worldwide ENIGMA study.

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. The sample comprised 3004 unmedicated healthy individuals (12-68 years, 46.5% male) from 29 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. Thicker right medial orbitofrontal/ventromedial prefrontal cortex (mOFC/vmPFC) was associated with higher schizotypy scores (r = 0.067, pFDR = 0.02). The cortical thickness profile in schizotypy was positively correlated with cortical abnormalities in SZ (r = 0.285, pspin = 0.024), but not BD (r = 0.166, pspin = 0.205) or MDD (r = -0.274, pspin = 0.073). The schizotypy-related subcortical volume pattern was negatively correlated with subcortical abnormalities in SZ (rho = -0.690, pspin = 0.006), BD (rho = -0.672, pspin = 0.009), and MDD (rho = -0.692, pspin = 0.004). 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.

Gray matter atrophy in relapsing-remitting multiple sclerosis is associated with white matter lesions in connecting fibers.

BACKGROUND: Lesions of brain white matter (WM) and atrophy of brain gray matter (GM) are well-established surrogate parameters in multiple sclerosis (MS), but it is unclear how closely these parameters relate to each other. OBJECTIVE: To assess across the whole cerebrum whether GM atrophy can be explained by lesions in connecting WM tracts. METHODS: GM images of 600 patients with relapsing-remitting MS (women = 68%; median age = 33.0 years, median expanded disability status scale score = 1.5) were converted to atrophy maps by data from a healthy control cohort. An atlas of WM tracts from the Human Connectome Project and individual lesion maps were merged to identify potentially disconnected GM regions, leading to individual disconnectome maps. Across the whole cerebrum, GM atrophy and potentially disconnected GM were tested for association both cross-sectionally and longitudinally. RESULTS: We found highly significant correlations between disconnection and atrophy across most of the cerebrum. Longitudinal analysis demonstrated a close temporal relation of WM lesion formation and GM atrophy in connecting fibers. CONCLUSION: GM atrophy is associated with WM lesions in connecting fibers. Caution is warranted when interpreting group differences in GM atrophy exclusively as differences in early neurodegeneration independent of WM lesion formation.

Alzheimer resemblance atrophy index, BrainAGE, and normal pressure hydrocephalus score in the prediction of subtle cognitive decline: added value compared to existing MR imaging markers.

OBJECTIVES: Established visual brain MRI markers for dementia include hippocampal atrophy (mesio-temporal atrophy MTA), white matter lesions (Fazekas score), and number of cerebral microbleeds (CMBs). We assessed whether novel quantitative, artificial intelligence (AI)-based volumetric scores provide additional value in predicting subsequent cognitive decline in elderly controls. METHODS: A prospective study including 80 individuals (46 females, mean age 73.4 ± 3.5 years). 3T MR imaging was performed at baseline. Extensive neuropsychological assessment was performed at baseline and at 4.5-year follow-up. AI-based volumetric scores were derived from 3DT1: Alzheimer Disease Resemblance Atrophy Index (AD-RAI), Brain Age Gap Estimate (BrainAGE), and normal pressure hydrocephalus (NPH) index. Analyses included regression models between cognitive scores and imaging markers. RESULTS: AD-RAI score at baseline was associated with Corsi (visuospatial memory) decline (10.6% of cognitive variability in multiple regression models). After inclusion of MTA, CMB, and Fazekas scores simultaneously, the AD-RAI score remained as the sole valid predictor of the cognitive outcome explaining 16.7% of its variability. Its percentage reached 21.4% when amyloid positivity was considered an additional explanatory factor. BrainAGE score was associated with Trail Making B (executive functions) decrease (8.5% of cognitive variability). Among the conventional MRI markers, only the Fazekas score at baseline was positively related to the cognitive outcome (8.7% of cognitive variability). The addition of the BrainAGE score as an independent variable significantly increased the percentage of cognitive variability explained by the regression model (from 8.7 to 14%). The addition of amyloid positivity led to a further increase in this percentage reaching 21.8%. CONCLUSIONS: The AI-based AD-RAI index and BrainAGE scores have limited but significant added value in predicting the subsequent cognitive decline in elderly controls when compared to the established visual MRI markers of brain aging, notably MTA, Fazekas score, and number of CMBs. KEY POINTS: • AD-RAI score at baseline was associated with Corsi score (visuospatial memory) decline. • BrainAGE score was associated with Trail Making B (executive functions) decrease. • AD-RAI index and BrainAGE scores have limited but significant added value in predicting the subsequent cognitive decline in elderly controls when compared to the established visual MRI markers of brain aging, notably MTA, Fazekas score, and number of CMBs.

Neural distinctiveness of fatigue and low sleep quality in multiple sclerosis.

BACKGROUND AND PURPOSE: Fatigue and low sleep quality in multiple sclerosis (MS) are closely related symptoms. Here, the associations between the brain's functional connectivity (FC) and fatigue and low sleep quality were investigated to determine the degree of neural distinctiveness of these symptoms. METHOD: A hundred and four patients with relapsing-remitting MS (age 38.9 ± 10.2 years, 66 females) completed the Modified Fatigue Impact Scale and the Pittsburgh Sleep Quality Index and underwent resting-state functional magnetic resonance imaging. FC was analyzed using independent-component analysis in sensorimotor, default-mode, fronto-parietal and basal-ganglia networks. Multiple linear regression models allowed us to test the association between FC and fatigue and sleep quality whilst controlling for one another as well as for demographic, disease-related and imaging variables. RESULTS: Higher fatigue correlated with lower sleep quality (r = 0.54, p < 0.0001). Higher fatigue was associated with lower FC of the precentral gyrus in the sensorimotor network, the precuneus in the posterior default-mode network and the superior frontal gyrus in the left fronto-parietal network, independently of sleep quality. Lower sleep quality was associated with lower FC of the left intraparietal sulcus in the left fronto-parietal network, independently of fatigue. Specific associations were found between fatigue and the sensorimotor network's global FC and between low sleep quality and the left fronto-parietal network's global FC. CONCLUSION: Despite the high correlation between fatigue and low sleep quality in the clinical picture, our findings clearly indicate that, on the neural level, fatigue and low sleep quality in MS are associated with decreased FC in distinct functional brain networks.

Experience-dependent structural plasticity in the adult brain: How the learning brain grows.

Volumetric magnetic resonance imaging studies have shown that intense learning can be associated with grey matter volume increases in the adult brain. The underlying mechanisms are poorly understood. Here we used monocular deprivation in rats to analyze the mechanisms underlying use-dependent grey matter increases. Optometry for quantification of visual acuity was combined with volumetric magnetic resonance imaging and microscopic techniques in longitudinal and cross-sectional studies. We found an increased spatial vision of the open eye which was associated with a transient increase in the volumes of the contralateral visual and lateral entorhinal cortex. In these brain areas dendrites of neurons elongated, and there was a strong increase in the number of spines, the targets of synapses, which was followed by spine maturation and partial pruning. Astrocytes displayed a transient pronounced swelling and underwent a reorganization of their processes. The use-dependent increase in grey matter corresponded predominantly to the swelling of the astrocytes. Experience-dependent increase in brain grey matter volume indicates a gain of structure plasticity with both synaptic and astrocyte remodeling.

Nonclinical psychotic-like experiences and schizotypy dimensions: Associations with hippocampal subfield and amygdala volumes.

Schizotypy and psychotic-like experiences (PLE) form part of the wider psychosis continuum and may have brain structural correlates in nonclinical cohorts. This study aimed to compare the effects of differential schizotypy dimensions, PLE, and their interaction on hippocampal subfields and amygdala volumes in the absence of clinical psychopathology. In a cohort of 367 psychiatrically healthy individuals, we assessed schizotypal traits using the Oxford-Liverpool Inventory of Life Experiences (O-LIFE) and PLE using the short form of the Prodromal Questionnaire (PQ-16). Based on high-resolution structural MRI scans, we used automated segmentation to estimate volumes of limbic structures. Sex and total intracranial volume (Step 1), PLE and schizotypy dimensions (Step 2), and their interaction terms (Step 3) were entered as regressors for bilateral amygdala and hippocampal subfield volumes in hierarchical multiple linear regression models. Positive schizotypy, but not PLE, was negatively associated with left amygdala and subiculum volumes. O-LIFE Impulsive Nonconformity, as well as the two-way interaction between positive schizotypy and PLE, were associated with larger left subiculum volumes. None of the estimators for right hemispheric hippocampal subfield volumes survived correction for multiple comparisons. Our findings support differential associations of hippocampus subfield volumes with trait dimensions rather than PLE, and support overlap and interactions between psychometric positive schizotypy and PLE. In a healthy cohort without current psychosis risk syndromes, the positive association between PLE and hippocampal subfield volume occurred at a high expression of positive schizotypy. Further studies combining stable, transient, and genetic parameters are required.

Significant increases of the amygdala between immediate and late postpartum: Pronounced effects within the superficial subregion.

Research exploring the underlying neuroanatomical correlates of early motherhood seems to suggest that the period after giving birth is marked by tissue increases in the mother's brain. While some studies point to the amygdala as one of the areas undergoing postpartum changes, existing analyses did not discriminate between the different subregions of this functionally heterogeneous structure. Thus, to further extend this understudied field of research and to better understand the potential role of the amygdala when transitioning to motherhood, we applied an advanced region-of-interest technique that enabled us to analyze the amygdala as a whole as well as its different subareas, specifically the left and right centromedian (CM), laterobasal (LB), and superficial (SF) regions. Comparing the brains of 14 healthy women between immediate postpartum (within 1-2 days of childbirth) and late postpartum (at 4-6 weeks after childbirth), we revealed increases of the amygdala. However, effects manifested differentially across subareas, with particularly strong effects for the SF region, moderate effects for the CM region, and no effects for the LB region. These findings might reflect region-specific adaptations of the mother's brain tuning into the distinct and ever-changing needs of a newborn, either as a cause for it or as a consequence thereof.

Influence of Processing Pipeline on Cortical Thickness Measurement.

In recent years, replicability of neuroscientific findings, specifically those concerning correlates of morphological properties of gray matter (GM), have been subject of major scrutiny. Use of different processing pipelines and differences in their estimates of the macroscale GM may play an important role in this context. To address this issue, here, we investigated the cortical thickness estimates of three widely used pipelines. Based on analyses in two independent large-scale cohorts, we report high levels of within-pipeline reliability of the absolute cortical thickness-estimates and comparable spatial patterns of cortical thickness-estimates across all pipelines. Within each individual, absolute regional thickness differed between pipelines, indicating that in-vivo thickness measurements are only a proxy of actual thickness of the cortex, which shall only be compared within the same software package and thickness estimation technique. However, at group level, cortical thickness-estimates correlated strongly between pipelines, in most brain regions. The smallest between-pipeline correlations were observed in para-limbic areas and insula. These regions also demonstrated the highest interindividual variability and the lowest reliability of cortical thickness-estimates within each pipeline, suggesting that structural variations within these regions should be interpreted with caution.

An analysis of MRI derived cortical complexity in premature-born adults: Regional patterns, risk factors, and potential significance.

Premature birth bears an increased risk for aberrant brain development concerning its structure and function. Cortical complexity (CC) expresses the fractal dimension of the brain surface and changes during neurodevelopment. We hypothesized that CC is altered after premature birth and associated with long-term cognitive development. One-hundred-and-one very premature-born adults (gestational age <32 weeks and/or birth weight <1500 â€‹g) and 111 term-born adults were assessed by structural MRI and cognitive testing at 26 years of age. CC was measured based on MRI by vertex-wise estimation of fractal dimension. Cognitive performance was measured based on Griffiths-Mental-Development-Scale (at 20 months) and Wechsler-Adult-Intelligence-Scales (at 26 years). In premature-born adults, CC was decreased bilaterally in large lateral temporal and medial parietal clusters. Decreased CC was associated with lower gestational age and birth weight. Furthermore, decreased CC in the medial parietal cortices was linked with reduced full-scale IQ of premature-born adults and mediated the association between cognitive development at 20 months and IQ in adulthood. Results demonstrate that CC is reduced in very premature-born adults in temporoparietal cortices, mediating the impact of prematurity on impaired cognitive development. These data indicate functionally relevant long-term alterations in the brain's basic geometry of cortical organization in prematurity.

Accelerated brain ageing in sepsis survivors with cognitive long-term impairment.

In the last years, cognitive impairment was emphasized to be a prominent long-term sequelae of sepsis. The level of cognitive impairment is comparable with that in mild cognitive impairment (MCI) patients. Whether sepsis survivors also show a comparable brain atrophy is still unclear. For the analysis of brain atrophy, a novel method named brain age gap estimation (BrainAGE) was used. In this analysis approach, an algorithm identifies age-specific atrophy across the whole brain and calculates a BrainAGE score in years. In case of accelerated brain atrophy, the BrainAGE score is increased in comparison to the healthy age reference group, indicating a difference in estimated chronological age. 20 survivors of severe sepsis (longer than 2 years post sepsis) with persistent cognitive deficits were investigated with a battery of neuropsychological tests. Their MRI images were compared to an age- and sex-matched control group. Sepsis survivors showed a significant higher BrainAGE score of 4.5 years compared to healthy controls. We also found a close relationship between the BrainAGE score and severity of cognitive impairment (a higher BrainAGE score was associated with more severe cognitive impairment). Consequently, sepsis survivors with persistent cognitive impairment showed an accelerated brain ageing, which was closely associated with the severity of cognitive impairment (similar to MCI patients).

Decreased cortical thickness mediates the relationship between premature birth and cognitive performance in adulthood.

Cortical thickness (CTh) reflects cortical properties such as dendritic complexity and synaptic density, which are not only vulnerable to developmental disturbances caused by premature birth but also highly relevant for cognitive performance. We tested the hypotheses whether CTh in young adults is altered after premature birth and whether these aberrations are relevant for general cognitive abilities. We investigated CTh based on brain structural magnetic resonance imaging and surface-based morphometry in a large and prospectively collected cohort of 101 very premature-born adults (<32 weeks of gestation and/or birth weight [BW] below 1,500 g) and 111 full-term controls at 26 years of age. Cognitive performance was assessed by full-scale intelligence quotient (IQ) using the Wechsler Adult Intelligence Scale. CTh was reduced in frontal, parietal, and temporal associative cortices predominantly in the left hemisphere in premature-born adults compared to controls. We found a significant positive association of CTh with both gestational age and BW, particularly in the left hemisphere, and a significant negative association between CTh and intensity of neonatal treatment within limited regions bilaterally. Full-scale IQ and CTh in the left hemisphere were positively correlated. Furthermore, CTh in the left hemisphere acted as a mediator on the association between premature birth and full-scale IQ. Results provide evidence that premature born adults have widespread reduced CTh that is relevant for their general cognitive performance. Data suggest lasting reductions in cortical microstructure subserving CTh after premature birth.

Brain Structure and Subclinical Symptoms: A Dimensional Perspective of Psychopathology in the Depression and Anxiety Spectrum.

Human psychopathology is the result of complex and subtle neurobiological alterations. Categorial DSM or ICD diagnoses do not allow a biologically founded and differentiated description of these diverse processes across a spectrum or continuum, emphasising the need for a scientific and clinical paradigm shift towards a dimensional psychiatric nosology. The subclinical part of the spectrum is, however, of special interest for early detection of mental disorders. We review the current evidence of brain structural correlates (grey matter volume, cortical thickness, and gyrification) in non-clinical (psychiatrically healthy) subjects with minor depressive and anxiety symptoms. We identified 16 studies in the depressive spectrum and 20 studies in the anxiety spectrum. These studies show effects associated with subclinical symptoms in the hippocampus, anterior cingulate cortex, and anterior insula similar to major depression and changes in amygdala similar to anxiety disorders. Precuneus and temporal areas as parts of the default mode network were affected specifically in the subclinical studies. We derive several methodical considerations crucial to investigations of brain structural correlates of minor psycho(patho)logical symptoms in healthy participants. And we discuss neurobiological overlaps with findings in patients as well as distinct findings, e.g. in areas involved in the default mode network. These results might lead to more insight into the early pathogenesis of clinical significant depression or anxiety and need to be enhanced by multi-centre and longitudinal studies.

Aberrant gyrification contributes to the link between gestational age and adult IQ after premature birth.

Gyrification is a hallmark of human brain development, starting in the second half of gestation in primary cortices, followed by unimodal and then transmodal associative cortices. Alterations in gyrification have been noted in premature-born newborns and children, suggesting abnormal cortical folding to be a permanent feature of prematurity. Furthermore, both gyrification and prematurity are tightly linked with cognitive performance, indicating a link between prematurity, gyrification, and cognitive performance. To investigate this triangular relation, we tested the following two hypotheses: (i) gyrification is aberrant in premature-born adults; and (ii) aberrant gyrification contributes to the impact of prematurity on adult cognitive performance. One hundred and one very premature-born adults (i.e. adults born before 32 weeks of gestation, and/or with birth weight <1500 g) and 111 mature-born adults were assessed by structural MRI and cognitive testing at 27 years of age. Gyrification was measured by local cortical absolute mean curvature (AMC), evaluated through structural MRI. Cognitive performance was assessed by the Wechsler Adult Intelligence Scale, full-scale IQ test. Two-sample t-tests, regression and mediation analyses were used to assess AMC group differences and the relation between AMC, birth-related variables, and full-scale IQ. Three key findings were identified. First, local AMC was widely increased in fronto-temporo-parietal primary and associative cortices of very premature-born adults. Increase of AMC was inversely associated with gestational age and birth weight and positively associated with medical complications at birth, respectively. Second, increased AMC of temporal associative cortices specifically contributed to the association between prematurity and reduced adult IQ (two-path mediation), indicating that aberrant gyrification of temporal associative cortices is critical for impaired cognitive performance after premature birth. Finally, further investigation of the relationship of gyrification between the early folding postcentral cortices and associative temporal cortices, folding later during neurodevelopment, revealed that the effect of gyrification abnormalities in associative temporal cortices on adult IQ is influenced itself by gyrification abnormalities occurring in the early folding postcentral cortices (three-path mediation). These results indicate that gyrification development across cortical areas in the brain conveys prematurity effects on adult IQ. Overall, these results provide evidence that premature birth leads to permanently aberrant gyrification patterns suggesting an altered neurodevelopmental trajectory. Statistical mediation modelling suggests that both aberrant gyrification itself as well as its propagation across the cortex express aspects of impaired neurodevelopment after premature birth and lead to reduced cognitive performance in adulthood. Thus, markers of gyrification appear as potential candidates for prognosis and treatment of prematurity effects.

Premature brain aging in humans exposed to maternal nutrient restriction during early gestation.

BACKGROUND: Prenatal exposure to undernutrition is widespread in both developing and industrialized countries, causing irreversible damage to the developing brain, resulting in altered brain structure and decreased cognitive function during adulthood. The Dutch famine in 1944/45 was a humanitarian disaster, now enabling studies of the effects of prenatal undernutrition during gestation on brain aging in late adulthood. METHODS: We hypothesized that study participants prenatally exposed to maternal nutrient restriction (MNR) would demonstrate altered brain structure resembling premature brain aging in late adulthood, expecting the effect being stronger in men. Utilizing the Dutch famine birth cohort (n = 118; mean age: 67.5 ± 0.9 years), this study implements an innovative biomarker for individual brain aging, using structural neuroimaging. BrainAGE was calculated using state-of-the-art pattern recognition methods, trained on an independent healthy reference sample, then applied to the Dutch famine MRI sample, to evaluate the effects of prenatal undernutrition during early gestation on individual brain aging in late adulthood. RESULTS: Exposure to famine in early gestation was associated with BrainAGE scores indicative of an older-appearing brain in the male sample (mean difference to subjects born before famine: 4.3 years, p < 0.05). Furthermore, in explaining the observed variance in individual BrainAGE scores in the male sample, maternal age at birth, head circumference at birth, medical treatment of hypertension, history of cerebral incidences, actual heart rate, and current alcohol intake emerged to be the most influential variables (adjusted R2 = 0.63, p < 0.01). INTERPRETATION: The findings of our study on exposure to prenatal undernutrition being associated with a status of premature brain aging during late adulthood, as well as individual brain structure being shaped by birth- and late-life health characteristics, are strongly supporting the critical importance of sufficient nutrient supply during pregnancy. Interestingly, the status of premature brain aging in participants exposed to the Dutch famine during early gestation occurred in the absence of fetal growth restriction at birth as well as vascular pathology in late-life. Additionally, the neuroimaging brain aging biomarker presented in this study will further enable tracking effects of environmental influences or (preventive) treatments on individual brain maturation and aging in epidemiological and clinical studies.

Brain structural correlates of irritability: Findings in a large healthy cohort.

Irritability and nonviolent aggression are common behavioral features across the population, yet there is limited neurobiological research into subclinical phenotypes representing the lower edge of a symptom continuum ranging from slight irritability to criminal violence. We studied brain structural correlates of irritability in a large healthy cohort to test the hypothesis of associations with fronto-limbic brain structures implicated in mood regulation. In a large multicenter effort, we recruited 409 mentally healthy adults from the community, who received T1-weighted high-resolution 3 T MRI scans. These structural scans were automatically preprocessed for voxel- and surface-based morphometry measurements with the CAT 12 toolbox implemented in SPM 12. Subclinical aggressive symptoms were assessed using the SCL-90-R aggression/hostility subscale and then correlated with cortical volume (VBM), and cortical thickness and gyrification. VBM analysis showed significant (P < 0.05, FDR-corrected at peak-level) positive correlations of cortical volume with SCL-90-R aggression subscale values in large clusters spanning bilateral anterior cingulate and orbitofrontal cortices and left lingual and postcentral gyri. Surface-based morphometry yielded mostly uncorrected positive correlations with cortical thickness in bilateral precentral gyri and with gyrification in left insula and superior temporal gyrus. Our findings imply an association of subclinical aggressive symptoms with cortical volume in areas important for emotion awareness and regulation, which might also be related to cortical adaptation to mental stress. These results overlap with several findings on impulsive aggression in patients suffering from affective and disruptive behavior disorders. They also suggest a biological symptom continuum manifesting in these brain areas. Hum Brain Mapp 38:6230-6238, 2017. © 2017 Wiley Periodicals, Inc.