Development and aging of cortical thickness correspond to genetic organization patterns

Cortical Surface Area Profile Mediates Effects of Childhood Disadvantage on Later-Life General Cognitive Ability

OBJECTIVES

Childhood disadvantage is associated with lower general cognitive ability (GCA) and brain structural differences in midlife and older adulthood. However, the neuroanatomical mechanisms underlying childhood disadvantage effects on later-life GCA remain poorly understood. Although total surface area (SA) has been linked to lifespan GCA differences, total SA does not capture the nonuniform nature of childhood disadvantage effects on neuroanatomy, which varies across unimodal and transmodal cortices. Here, we examined whether cortical SA profile-the extent to which the spatial patterning of SA deviates from the normative unimodal-transmodal cortical organization-is a mediator of childhood disadvantage effects on later-life GCA.

METHODS

In 477 community-dwelling men aged 56-72 years old, childhood disadvantage index was derived from four indicators of disadvantages and GCA was assessed using a standardized test. Cortical SA was obtained from structural magnetic resonance imaging. For cortical SA profile, we calculated the spatial similarity between maps of individual cortical SA and MRI-derived principal gradient (i.e., unimodal-transmodal organization). Mediation analyses were conducted to examine the indirect effects of childhood disadvantage index through cortical SA profile on GCA.

RESULTS

Around 1.31% of childhood disadvantage index effects on later-life GCA were mediated by cortical SA profile, whereas total SA did not. Higher childhood disadvantage index was associated with more deviation of the cortical SA spatial patterning from the principal gradient, which in turn related to lower later-life GCA.

DISCUSSION

Childhood disadvantage may contribute to later-life GCA differences partly by influencing the spatial patterning of cortical SA in a way that deviates from the normative cortical organizational principle.

Age-related decline in thickness and surface area in the cortical surface and hippocampus: lifespan trajectories and decade-by-decade analyses

Previous studies on age-related changes in cortical and hippocampal morphology were not designed or able to reveal the complex spatial patterns of changes across the lifespan. To this end, the current study examined these changes in a decade-by-decade manner by comparing consecutive age decades at the vertex-wise level. Additionally, the lifespan trajectories of cortical/hippocampal mean thickness and total surface area were modeled and plotted out to provide an overview of their age-related changes. Using two lifespan datasets (Ntotal = 1378; 18 ≤ age ≤ 100), vertex-wise thickness and surface area measurements were extracted from the cortical and unfolded hippocampal surfaces and analyzed using whole-brain/hippocampus vertex-wise analyses. Lifespan trajectories of cortical/hippocampal mean thickness and total surface area were modeled with generalized additive models for location, scale, and shape. These models revealed fairly linear declines in both cortical measures and inverted U-shaped trajectories for both hippocampal measures. Across the different age decades, the sizes and locations of cortical thinning clusters were highly variable across the age decades. No significant clusters of cortical surface area changes were observed across the age decades. Significant clusters of hippocampal surface area and thickness reduction were not observed until the 70s. Generally, the agreement between datasets on the hippocampal findings was much higher than those of the cortical surface. These findings revealed important nuances in the age-related changes of cortical and hippocampal morphology and cautioned against using lifespan trajectories to infer decade-by-decade changes in the cortical surface and the hippocampus.

Synesthesia is linked to large and extensive differences in brain structure and function as determined by whole-brain biomarkers derived from the HCP (Human Connectome Project) cortical parcellation approach

There is considerable interest in understanding the developmental origins and health implications of individual differences in brain structure and function. In this pre-registered study we demonstrate that a hidden subgroup within the general population-people with synesthesia (e.g. who "hear" colors)-show a distinctive behavioral phenotype and wide-ranging differences in brain structure and function. We assess the performance of 13 different brain-based biomarkers (structural and functional MRI) for classifying synesthetes against general population samples, using machine learning models. The features in these models were derived from subject-specific parcellations of the cortex using the Human Connectome Project approach. All biomarkers performed above chance with intracortical myelin being a particularly strong predictor that has not been implicated in synesthesia before. Resting state data show widespread changes in the functional connectome (including less hub-based connectivity). These brain-based individual differences within the neurotypical population can be as large as those that differentiate neurotypical from clinical brain states.

Population clustering of structural brain aging and its association with brain development

Structural brain aging has demonstrated strong inter-individual heterogeneity and mirroring patterns with brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, most of the existing research focused on the cross-sectional changes of brain aging. In this investigation, we present a data-driven approach that incorporate both cross-sectional changes and longitudinal trajectories of structural brain aging and identified two brain aging patterns among 37,013 healthy participants from UK Biobank. Participants with accelerated brain aging also demonstrated accelerated biological aging, cognitive decline and increased genetic susceptibilities to major neuropsychiatric disorders. Further, by integrating longitudinal neuroimaging studies from a multi-center adolescent cohort, we validated the 'last in, first out' mirroring hypothesis and identified brain regions with manifested mirroring patterns between brain aging and brain development. Genomic analyses revealed risk loci and genes contributing to accelerated brain aging and delayed brain development, providing molecular basis for elucidating the biological mechanisms underlying brain aging and related disorders.

The genetics of spatiotemporal variation in cortical thickness in youth

Prior studies have shown strong genetic effects on cortical thickness (CT), structural covariance, and neurodevelopmental trajectories in childhood and adolescence. However, the importance of genetic factors on the induction of spatiotemporal variation during neurodevelopment remains poorly understood. Here, we explore the genetics of maturational coupling by examining 308 MRI-derived regional CT measures in a longitudinal sample of 677 twins and family members. We find dynamic inter-regional genetic covariation in youth, with the emergence of regional subnetworks in late childhood and early adolescence. Three critical neurodevelopmental epochs in genetically-mediated maturational coupling were identified, with dramatic network strengthening near eleven years of age. These changes are associated with statistically-significant (empirical p-value <0.0001) increases in network strength as measured by average clustering coefficient and assortativity. We then identify genes from the Allen Human Brain Atlas with similar co-expression patterns to genetically-mediated structural covariation in children. This set was enriched for genes involved in potassium transport and dendrite formation. Genetically-mediated CT-CT covariance was also strongly correlated with expression patterns for genes located in cells of neuronal origin.

COVID-19 lockdown effects on adolescent brain structure suggest accelerated maturation that is more pronounced in females than in males

Adolescence is a period of substantial social-emotional development, accompanied by dramatic changes to brain structure and function. Social isolation due to lockdowns that were imposed because of the COVID-19 pandemic had a detrimental impact on adolescent mental health, with the mental health of females more affected than males. We assessed the impact of the COVID-19 pandemic lockdowns on adolescent brain structure with a focus on sex differences. We collected MRI structural data longitudinally from adolescents prior to and after the pandemic lockdowns. The pre-COVID data were used to create a normative model of cortical thickness change with age during typical adolescent development. Cortical thickness values in the post-COVID data were compared to this normative model. The analysis revealed accelerated cortical thinning in the post-COVID brain, which was more widespread throughout the brain and greater in magnitude in females than in males. When measured in terms of equivalent years of development, the mean acceleration was found to be 4.2 y in females and 1.4 y in males. Accelerated brain maturation as a result of chronic stress or adversity during development has been well documented. These findings suggest that the lifestyle disruptions associated with the COVID-19 pandemic lockdowns caused changes in brain biology and had a more severe impact on the female than the male brain.

Sleep-dependent memory consolidation in young and aged brains

Young children and aged individuals are more prone to memory loss than young adults. One probable reason is insufficient sleep-dependent memory consolidation. Sleep timing and sleep-stage duration differ between children and aged individuals compared to adults. Frequent daytime napping and fragmented sleep architecture are common in children and older individuals. Moreover, sleep-dependent oscillations that play crucial roles in long-term memory storage differ among age groups. Notably, the frontal cortex, which is important for long-term memory storage undergoes major structural changes in children and aged subjects. The similarities in sleep dynamics between children and aged subjects suggest that a deficit in sleep-dependent consolidation contributes to memory loss in both age groups.

Functional network modules overlap and are linked to interindividual connectome differences during human brain development

The modular structure of functional connectomes in the human brain undergoes substantial reorganization during development. However, previous studies have implicitly assumed that each region participates in one single module, ignoring the potential spatial overlap between modules. How the overlapping functional modules develop and whether this development is related to gray and white matter features remain unknown. Using longitudinal multimodal structural, functional, and diffusion MRI data from 305 children (aged 6 to 14 years), we investigated the maturation of overlapping modules of functional networks and further revealed their structural associations. An edge-centric network model was used to identify the overlapping modules, and the nodal overlap in module affiliations was quantified using the entropy measure. We showed a regionally heterogeneous spatial topography of the overlapping extent of brain nodes in module affiliations in children, with higher entropy (i.e., more module involvement) in the ventral attention, somatomotor, and subcortical regions and lower entropy (i.e., less module involvement) in the visual and default-mode regions. The overlapping modules developed in a linear, spatially dissociable manner, with decreased entropy (i.e., decreased module involvement) in the dorsomedial prefrontal cortex, ventral prefrontal cortex, and putamen and increased entropy (i.e., increased module involvement) in the parietal lobules and lateral prefrontal cortex. The overlapping modular patterns captured individual brain maturity as characterized by chronological age and were predicted by integrating gray matter morphology and white matter microstructural properties. Our findings highlight the maturation of overlapping functional modules and their structural substrates, thereby advancing our understanding of the principles of connectome development.

Cortical atrophy patterns in myelin oligodendrocyte glycoprotein antibody-associated disease

OBJECTIVES

Global brain volume changes in patients with myelin oligodendrocyte glycoprotein antibody-associated disease compared with healthy controls (HC) could be revealed by magnetic resonance imaging, but specific atrophy patterns of cortical structures and relation to cognitive impairment are not yet comprehensively known. Thus, we aimed to investigate cortical thickness differences in patients with myelin oligodendrocyte glycoprotein antibody-associated disease compared with HC.

METHODS

3-Tesla brain magnetic resonance imaging was performed in 23 patients with myelin oligodendrocyte glycoprotein antibody-associated disease and 49 HC for voxel-wise group comparisons and neuropsychological testing in patients. Surface-based morphometry with region of interest-based surface analysis and region of interest-based extraction of cortical thickness was performed in patients compared with HC and in patient subgroups with and without cognitive impairment.

RESULTS

Comparing patients with myelin oligodendrocyte glycoprotein antibody-associated disease with HC, exploratory surface-based morphometry demonstrated cortical volume reduction in pericalcarine and lingual cortical regions. Region of interest-based surface analysis specified reduced cortical thickness in the adjacent pericalcarine and orbitofrontal regions in myelin oligodendrocyte glycoprotein antibody-associated disease, as well as reduced temporal cortical thickness in patients with cognitive impairment (n = 10). Patients without cognitive impairment (n = 13) showed only circumscribed cortical brain volume loss compared with HC in the pericalcarine region.

INTERPRETATION

In conclusion, cortical atrophy in myelin oligodendrocyte glycoprotein antibody-associated disease was characterized by cortical thickness reduction in the adjacent pericalcarine and orbitofrontal regions, with a tendency of temporal thickness reduction in cognitively impaired patients.

Causal associations between chronic heart failure and the cerebral cortex: results from Mendelian randomization study and integrated bioinformatics analysis

Background

Chronic heart failure (CHF) patients exhibit alterations in cerebral cortical structure and cognitive function. However, the mechanisms by which CHF affects cortical structure and functional regions remain unknown. This study aims to investigate potential causal relationship between CHF and cerebral cortical structure through Mendelian randomization (MR).

Methods

The research utilized genome-wide association studies (GWAS) to explore the causal association between CHF and cerebral cortical structure. The results were primarily analyzed using the inverse-variance weighted (IVW). The reliability of the data was verified through horizontal pleiotropy and heterogeneity analysis by MR-Egger intercept test and Cochran's Q-test, respectively. Replication analysis was conducted in the Integrative Epidemiology Unit (IEU) OpenGWAS project for further validation. In addition, we collected mediator genes that mediate causality to reveal potential mechanisms. Integrated bioinformatics analysis was conducted using the Open Target Genetics platform, the STRING database, and Cytoscape software.

Results

The IVW results did not reveal any significant causal association between genetically predicted CHF and the overall structure of the cerebral cortex or the surface area (SA) of the 34 functional regions of the cerebral cortex (P > 0.05). However, the results revealed that CHF increased the thickness (TH) of pars opercularis (IVW: β = 0.015, 95% CI: 0.005-0.025, P = 3.16E-03). Replication analysis supported the causal association between CHF and pars opercularis TH (IVW: β = 0.02, 95% CI: 0.010-0.033, P = 1.84E-04). We examined the degree centrality values of the top 10 mediator genes, namely CDKN1A, CELSR2, NME5, SURF4, PSMA5, TSC1, RPL7A, SURF6, PRDX3, and FTO.

Conclusion

Genetic evidence indicates a positive correlation between CHF and pars opercularis TH.

Genes associated with cortical thickness alterations in behavioral addiction

Behavioral addiction (BA) is a conceptually new addictive phenotype characterized by compulsive reward-seeking behaviors despite adverse consequences. Currently, its underlying neurogenetic mechanism remains unclear. Here, this study aimed to investigate the association between cortical thickness (CTh) and genetic phenotypes in BA. We conducted a systematic search in five databases and extracted gene expression data from the Allen Human Brain Atlas. Meta-analysis of 10 studies (343 addicted individuals and 355 controls) revealed that the BA group showed thinner CTh in the precuneus, postcentral gyrus, orbital-frontal cortex, and dorsolateral prefrontal cortex (P < 0.005). Meta-regression showed that the CTh in the precuneus and postcentral gyrus were negatively associated with the addiction severity (P < 0.0005). More importantly, the CTh phenotype of BA was spatially correlated with the expression of 12 genes (false discovery rate [FDR] < 0.05), and the dopamine D2 receptor had the highest correlation (rho = 0.55). Gene enrichment analysis further revealed that the 12 genes were involved in the biological processes of behavior regulation and response to stimulus (FDR < 0.05). In conclusion, our findings demonstrated the thinner CTh in cognitive control-related brain areas in BA, which could be associated with the expression of genes involving dopamine metabolism and behavior regulation.

Spatiotemporal patterns in cortical development: Age, puberty, and individual variability from 9 to 13 years of age

Humans and nonhuman primate studies suggest that timing and tempo of cortical development varies neuroanatomically along a sensorimotor-to-association (S-A) axis. Prior human studies have reported a principal S-A axis across various modalities, but largely rely on cross-sectional samples with wide age-ranges. Here, we investigate developmental changes and individual variability in cortical organization along the S-A axis between the ages of 9-13 years using a large, longitudinal sample (N = 2487-3747, 46-50% female) from the Adolescent Brain Cognitive Development Study (ABCD Study®). This work assesses multiple aspects of neurodevelopment indexed by changes in cortical thickness, cortical microarchitecture, and resting-state functional fluctuations. First, we evaluated S-A organization in age-related changes and, then, computed individual-level S-A alignment in brain changes and assessing differences therein due to age, sex, and puberty. Varying degrees of linear and quadratic age-related brain changes were identified along the S-A axis. Yet, these patterns of cortical development were overshadowed by considerable individual variability in S-A alignment. Even within individuals, there was little correspondence between S-A patterning across the different aspects of neurodevelopment investigated (i.e., cortical morphology, microarchitecture, function). Some of the individual variation in developmental patterning of cortical morphology and microarchitecture was explained by age, sex, and pubertal development. Altogether, this work contextualizes prior findings that regional age differences do progress along an S-A axis at a group level, while highlighting broad variation in developmental change between individuals and between aspects of cortical development, in part due to sex and puberty.

Significance Statement

Understanding normative patterns of adolescent brain change, and individual variability therein, is crucial for disentangling healthy and abnormal development. We used longitudinal human neuroimaging data to study several aspects of neurodevelopment during early adolescence and assessed their organization along a sensorimotor-to-association (S-A) axis across the cerebral cortex. Age differences in brain changes were linear and curvilinear along this S-A axis. However, individual-level sensorimotor-association alignment varied considerably, driven in part by differences in age, sex, and pubertal development.

Associations between accelerometer-measured circadian rest-activity rhythm, brain structural and genetic mechanisms, and dementia

AIM

Knowledge of how circadian rhythm influences brain health remains limited. We aimed to investigate the associations of accelerometer-measured circadian rest-activity rhythm (CRAR) with incident dementia, cognitive dysfunction, and structural brain abnormalities in the general population and underlying biological mechanisms.

METHODS

Fifty-seven thousand five hundred and two participants aged over 60 years with accelerometer data were included to investigate the association of CRAR with incidental dementia. Non-parametric CRAR parameters were utilized, including activity level during active periods of the day (M10), activity level during rest periods of the day (L5), and the relative difference between the M10 and L5 (relative amplitude, RA). Associations of CRAR with cognitive dysfunction and brain structure were studied in a subset of participants. Neuroimaging-transcriptomics analysis was utilized to identify the underlying molecular mechanisms.

RESULTS

Over 6.86 (4.94-8.78) years of follow-up, 494 participants developed dementia. The risk of incident dementia was associated with decreasing M10 (hazard ratio [HR] 1.45; 95% conference interval [CI], 1.28-1.64) and RA (HR 1.37; 95% CI, 1.28-1.64), increasing L5 (HR 1.14, 95% CI 1.07-1.21) and advanced L5 onset time (HR 1.12; 95% CI, 1.02-1.23). The detrimental associations were exacerbated by APOE ε4 status and age (>65 years). Decreased RA was associated with lower processing speed (Beta -0.04; SE 0.011), predominantly mediated by abnormalities in subcortical regions and white matter microstructure. The genes underlying CRAR-related brain regional structure variation were enriched for synaptic function.

CONCLUSIONS

Our study underscores the potential of intervention targeting at maintaining a healthy CRAR pattern to prevent dementia risk.

Age-atypical brain functional networks in autism spectrum disorder: a normative modeling approach

BACKGROUND

Despite extensive research into the neural basis of autism spectrum disorder (ASD), the presence of substantial biological and clinical heterogeneity among diagnosed individuals remains a major barrier. Commonly used case‒control designs assume homogeneity among subjects, which limits their ability to identify biological heterogeneity, while normative modeling pinpoints deviations from typical functional network development at individual level.

METHODS

Using a world-wide multi-site database known as Autism Brain Imaging Data Exchange, we analyzed individuals with ASD and typically developed (TD) controls (total n = 1218) aged 5-40 years, generating individualized whole-brain network functional connectivity (FC) maps of age-related atypicality in ASD. We then used local polynomial regression to estimate a networkwise normative model of development and explored correlations between ASD symptoms and brain networks.

RESULTS

We identified a subset exhibiting highly atypical individual-level FC, exceeding 2 standard deviation from the normative value. We also identified clinically relevant networks (mainly default mode network) at cohort level, since the outlier rates decreased with age in TD participants, but increased in those with autism. Moreover, deviations were linked to severity of repetitive behaviors and social communication symptoms.

CONCLUSIONS

Individuals with ASD exhibit distinct, highly individualized trajectories of brain functional network development. In addition, distinct developmental trajectories were observed among ASD and TD individuals, suggesting that it may be challenging to identify true differences in network characteristics by comparing young children with ASD to their TD peers. This study enhances understanding of the biological heterogeneity of the disorder and can inform precision medicine.

Population clustering of structural brain aging and its association with brain development

Structural brain aging has demonstrated strong inter-individual heterogeneity and mirroring patterns with brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, most of the existing research focused on the cross-sectional changes of brain aging. In this investigation, we present a data-driven approach that incorporate both cross-sectional changes and longitudinal trajectories of structural brain aging and identified two brain aging patterns among 37,013 healthy participants from UK Biobank. Participants with accelerated brain aging also demonstrated accelerated biological aging, cognitive decline and increased genetic susceptibilities to major neuropsychiatric disorders. Further, by integrating longitudinal neuroimaging studies from a multi-center adolescent cohort, we validated the "last in, first out" mirroring hypothesis and identified brain regions with manifested mirroring patterns between brain aging and brain development. Genomic analyses revealed risk loci and genes contributing to accelerated brain aging and delayed brain development, providing molecular basis for elucidating the biological mechanisms underlying brain aging and related disorders.

Adjustment of Regional Cortical Thickness Measures for Global Cortical Thickness Obscures Deficits Across the Schizophrenia Spectrum: A Cautionary Note About Normative Modeling of Brain Imaging Data

Recent neuroimaging studies and publicly disseminated analytic tools suggest that regional morphometric analyses covary for global thickness. We empirically demonstrated that this statistical approach severely underestimates regional thickness dysmorphology in psychiatric disorders. Study 1 included 90 healthy control participants, 51 participants at clinical high risk for psychosis, and 78 participants with early-illness schizophrenia. Study 2 included 56 healthy control participants, 83 participants with nonaffective psychosis, and 30 participants with affective psychosis. We examined global and regional thickness correlations, global thickness group differences, and regional thickness group differences with and without global thickness covariation. Global and regional thickness were strongly correlated across groups. Global thickness was lower in the schizophrenia spectrum groups than the other groups. Regional thickness deficits in schizophrenia spectrum groups were attenuated or eliminated with global thickness covariation. Eliminating the variation that regional thickness shares with global thickness eliminated disease-related effects. This statistical approach results in erroneous conclusions that regional thickness is normal in disorders like schizophrenia or clinical high risk syndrome.

Differences in scalp-to-cortex tissues across age groups, sexes and brain regions: Implications for neuroimaging and brain stimulation techniques

Aging affects the scalp-to-cortex distance (SCD) and the comprising tissues. This is crucial for noninvasive neuroimaging and brain stimulation modalities as they rely on traversing from the scalp to the cortex or vice versa. The specific relationship between aging and these tissues has not been comprehensively investigated. We conducted a study on 250 younger and older adults to examine age-related differences in SCD and its constituent tissues. We identified region-specific differences in tissue thicknesses related to age and sex. Older adults exhibit larger SCD in the frontocentral regions compared to younger adults. Men exhibit greater SCD in the inferior scalp regions, while women show similar-to-greater SCD values in regions closer to the vertex compared to men. Younger adults and men have thicker soft tissue layers, whereas women and older adults exhibit thicker compact bone layers. CSF is considerably thicker in older adults, particularly in men. These findings emphasize the need to consider age, sex, and regional differences when interpreting SCD and its implications for noninvasive neuroimaging and brain stimulation.

Aging Brain from a Lifespan Perspective

Research during the last two decades has shown that the brain undergoes continuous changes throughout life, with substantial heterogeneity in age trajectories between regions. Especially, temporal and prefrontal cortices show large changes, and these correlate modestly with changes in the corresponding cognitive abilities such as episodic memory and executive function. Changes seen in normal aging overlap with changes seen in neurodegenerative conditions such as Alzheimer's disease; differences between what reflects normal aging vs. a disease-related change are often blurry. This calls for a dimensional view on cognitive decline in aging, where clear-cut distinctions between normality and pathology cannot be always drawn. Although much progress has been made in describing typical patterns of age-related changes in the brain, identifying risk and protective factors, and mapping cognitive correlates, there are still limits to our knowledge that should be addressed by future research. We need more longitudinal studies following the same participants over longer time intervals with cognitive testing and brain imaging, and an increased focus on the representativeness vs. selection bias in neuroimaging research of aging.

Stimulant medication use and apparent cortical thickness development in attention-deficit/hyperactivity disorder: a prospective longitudinal study

Background

Stimulant medication is commonly prescribed as treatment for attention-deficit/hyperactivity disorder (ADHD). While we previously found that short-term stimulant-treatment influences apparent cortical thickness development in an age-dependent manner, it remains unknown whether these effects persist throughout development into adulthood.

Purpose

Investigate the long-term age-dependent effects of stimulant medication use on apparent cortical thickness development in adolescents and adults previously diagnosed with ADHD.

Methods

This prospective study included the baseline and 4-year follow-up assessment of the "effects of Psychotropic drugs On the Developing brain-MPH" ("ePOD-MPH") project, conducted between June-1-2011 and December-28-2019. The analyses were pre-registered (https://doi.org/10.17605/OSF.IO/32BHF). T1-weighted MR scans were obtained from male adolescents and adults, and cortical thickness was estimated for predefined regions of interest (ROIs) using Freesurfer. We determined medication use and assessed symptoms of ADHD, anxiety, and depression at both time points. Linear mixed models were constructed to assess main effects and interactions of stimulant medication use, time, and age group on regional apparent cortical thickness.

Results

A total of 32 male adolescents (aged mean ± SD, 11.2 ± 0.9 years at baseline) and 24 men (aged mean ± SD, 29.9 ± 5.0 years at baseline) were included that previously participated in the ePOD-MPH project. We found no evidence for long-term effects of stimulant medication use on ROI apparent cortical thickness. As expected, we did find age-by-time interaction effects in all ROIs (left prefrontal ROI: P=.002, right medial and posterior ROIs: P<.001), reflecting reductions in apparent cortical thickness in adolescents. Additionally, ADHD symptom severity (adolescents: P<.001, adults: P=.001) and anxiety symptoms (adolescents: P=0.03) were reduced, and more improvement of ADHD symptoms was associated with higher medication use in adults (P=0.001).

Conclusion

We found no evidence for long-term effects of stimulant-treatment for ADHD on apparent cortical thickness development in adolescents and adults. The identified age-dependent differences in apparent cortical thickness development are consistent with existing literature on typical cortical development.

Fetal influence on the human brain through the lifespan

Human fetal development has been associated with brain health at later stages. It is unknown whether growth in utero, as indexed by birth weight (BW), relates consistently to lifespan brain characteristics and changes, and to what extent these influences are of a genetic or environmental nature. Here we show remarkably stable and lifelong positive associations between BW and cortical surface area and volume across and within developmental, aging and lifespan longitudinal samples (N = 5794, 4-82 y of age, w/386 monozygotic twins, followed for up to 8.3 y w/12,088 brain MRIs). In contrast, no consistent effect of BW on brain changes was observed. Partly environmental effects were indicated by analysis of twin BW discordance. In conclusion, the influence of prenatal growth on cortical topography is stable and reliable through the lifespan. This early-life factor appears to influence the brain by association of brain reserve, rather than brain maintenance. Thus, fetal influences appear omnipresent in the spacetime of the human brain throughout the human lifespan. Optimizing fetal growth may increase brain reserve for life, also in aging.

Morphometrics of the preserved post-surgical hemisphere in pediatric drug-resistant epilepsy

Importance

Structural integrity of cortex following cortical resection for epilepsy management has been previously characterized, but only in adult patients.

Objective

This study sought to determine whether morphometrics of the preserved hemisphere in pediatric cortical resection patients differ from non-neurological controls.

Design

This was a case-control study, from 2013-2022.

Setting

This was a single-site study.

Participants

32 patients with childhood epilepsy surgery and 51 age- and gender-matched controls participated.

Main Measures

We quantified morphometrics of the preserved hemisphere at the level of gross anatomy (lateral ventricle size, volume of gray and white matter). Additionally, cortical thickness, volume, and surface area were measured for 34 cortical regions segmented with the Desikan-Killiany atlas, and, last, volumes of nine subcortical regions were also quantified.

Results

13 patients with left hemisphere (LH) surgery and a preserved right hemisphere (RH) (median age/median absolute deviation of age: 15.7/1.7 yr; 6 females, 7 males) and 19 patients with RH surgery and a preserved LH (15.4/3.7 yr; 11 females, 8 males) were compared to 51 controls (14.8/4.9 yr; 24 females, 27 males). Patient groups had larger ventricles and reduced total white matter volume relative to controls, and only patients with a preserved RH, but not patients with a preserved LH, had reduced total gray matter volume relative to controls. Furthermore, patients with a preserved RH had lower cortical thickness and volume and greater surface area of several cortical regions, relative to controls. Patients with a preserved LH had no differences in thickness, volume, or area, of any of the 34 cortical regions, relative to controls. Moreover, both LH and RH patients showed reduced volumes in select subcortical structures, relative to controls.

Conclusions and Relevance

That left-sided, but not right-sided, resection is associated with more pronounced reduction in cortical thickness and volume and increased cortical surface area relative to typically developing, age-matched controls suggests that the preserved RH undergoes structural plasticity to an extent not observed in cases of right-sided pediatric resection. Future work probing the association of the current findings with neuropsychological outcomes will be necessary to understand the implications of these structural findings for clinical practice.

CBLL1 is hypomethylated and correlates with cortical thickness in transgender men before gender affirming hormone treatment

Gender identity refers to the consciousness of being a man, a woman or other condition. Although it is generally congruent with the sex assigned at birth, for some people it is not. If the incongruity is distressing, it is defined as gender dysphoria (GD). Here, we measured whole-genome DNA methylation by the Illumina © Infinium Human Methylation 850k array and reported its correlation with cortical thickness (CTh) in 22 transgender men (TM) experiencing GD versus 25 cisgender men (CM) and 28 cisgender women (CW). With respect to the methylation analysis, TM vs. CW showed significant differences in 35 CpGs, while 2155 CpGs were found when TM vs. CM were compared. With respect to correlation analysis, TM showed differences in methylation of CBLL1 and DLG1 genes that correlated with global and left hemisphere CTh. Both genes were hypomethylated in TM compared to the cisgender groups. Early onset TM showed a positive correlation between CBLL1 and several cortical regions in the frontal (left caudal middle frontal), temporal (right inferior temporal, left fusiform) and parietal cortices (left supramarginal and right paracentral). This is the first study relating CBLL1 methylation with CTh in transgender persons and supports a neurodevelopmental hypothesis of gender identity.

Impaired mitophagosome-lysosome fusion mediates olanzapine-induced aging

The lifespan of schizophrenia patients is significantly shorter than the general population. Olanzapine is one of the most commonly used antipsychotic drugs (APDs) for treating patients with psychosis, including schizophrenia and bipolar disorder. Despite their effectiveness in treating positive and negative symptoms, prolonged exposure to APDs may lead to accelerated aging and cognitive decline, among other side effects. Here we report that dysfunctional mitophagy is a fundamental mechanism underlying accelerated aging induced by olanzapine, using in vitro and in vivo (Caenorhabditis elegans) models. We showed that the aberrant mitophagy caused by olanzapine was via blocking mitophagosome-lysosome fusion. Furthermore, olanzapine can induce mitochondrial damage and hyperfragmentation of the mitochondrial network. The mitophagosome-lysosome fusion in olanzapine-induced aging models can be restored by a mitophagy inducer, urolithin A, which alleviates defective mitophagy, mitochondrial damage, and fragmentation of the mitochondrial network. Moreover, the mitophagy inducer ameliorated behavioral changes induced by olanzapine, including shortened lifespan, and impaired health span, learning, and memory. These data indicate that olanzapine impairs mitophagy, leading to the shortened lifespan, impaired health span, and cognitive deficits. Furthermore, this study suggests the potential application of mitophagy inducers as therapeutic strategies to reverse APD-induced adverse effects associated with accelerated aging.

Maintaining brain health across the lifespan

Across the lifespan, the human body and brain endure the impact of a plethora of exogenous and endogenous factors that determine the health outcome in old age. The overwhelming inter-individual variance spans between progressive frailty with loss of autonomy to largely preserved physical, cognitive, and social functions. Understanding the mechanisms underlying the diverse aging trajectories can inform future strategies to maintain a healthy body and brain. Here we provide a comprehensive overview of the current literature on lifetime factors governing brain health. We present the growing body of evidence that unhealthy alimentary regime, sedentary behaviour, sleep pathologies, cardio-vascular risk factors, and chronic inflammation exert their harmful effects in a cumulative and gradual manner, and that timely and efficient intervention could promote healthy and successful aging. We discuss the main effects and interactions between these risk factors and the resulting brain health outcomes to follow with a description of current strategies aiming to eliminate, treat, or counteract the risk factors. We conclude that the detailed insights about modifiable risk factors could inform personalized multi-domain strategies for brain health maintenance on the background of increased longevity.

White matter tract microstructure, macrostructure, and associated cortical gray matter morphology across the lifespan

Characterizing how, when and where the human brain changes across the lifespan is fundamental to our understanding of developmental processes of childhood and adolescence, degenerative processes of aging, and divergence from normal patterns in disease and disorders. We aimed to provide detailed descriptions of white matter pathways across the lifespan by thoroughly characterizing white matter microstructure, white matter macrostructure, and morphology of the cortex associated with white matter pathways. We analyzed 4 large, high-quality, publicly-available datasets comprising 2789 total imaging sessions, and participants ranging from 0 to 100 years old, using advanced tractography and diffusion modeling. We first find that all microstructural, macrostructural, and cortical features of white matter bundles show unique lifespan trajectories, with rates and timing of development and degradation that vary across pathways - describing differences between types of pathways and locations in the brain, and developmental milestones of maturation of each feature. Second, we show cross-sectional relationships between different features that may help elucidate biological changes occurring during different stages of the lifespan. Third, we show unique trajectories of age-associations across features. Finally, we find that age associations during development are strongly related to those during aging. Overall, this study reports normative data for several features of white matter pathways of the human brain that will be useful for studying normal and abnormal white matter development and degeneration.

Predicting 'Brainage' in late childhood to adolescence (6-17yrs) using structural MRI, morphometric similarity, and machine learning

Brain development is regularly studied using structural MRI. Recently, studies have used a combination of statistical learning and large-scale imaging databases of healthy children to predict an individual's age from structural MRI. This data-driven, predicted 'Brainage' typically differs from the subjects chronological age, with this difference a potential measure of individual difference. Few studies have leveraged higher-order or connectomic representations of structural MRI data for this Brainage approach. We leveraged morphometric similarity as a network-level approach to structural MRI to generate predictive models of age. We benchmarked these novel Brainage approaches using morphometric similarity against more typical, single feature (i.e., cortical thickness) approaches. We showed that these novel methods did not outperform cortical thickness or cortical volume measures. All models were significantly biased by age, but robust to motion confounds. The main results show that, whilst morphometric similarity mapping may be a novel way to leverage additional information from a T1-weighted structural MRI beyond individual features, in the context of a Brainage framework, morphometric similarity does not provide more accurate predictions of age. Morphometric similarity as a network-level approach to structural MRI may be poorly positioned to study individual differences in brain development in healthy participants in this way.

Cortical thickness in the right medial frontal gyrus predicts planning performance in healthy children and adolescents

The ability to plan is an important part of the set of the cognitive skills called "executive functions." To be able to plan actions in advance is of great importance in everyday life and constitutes one of the major key features for academic as well as economic success. The present study aimed to investigate the neuroanatomical correlates of planning in normally developing children, as measured by the cortical thickness of the prefrontal cortex. Eighteen healthy children and adolescents underwent structural MRI examinations and the Tower of London (ToL) task. A multiple regression analysis revealed that the cortical thickness of the right caudal middle frontal gyrus (cMFG) was a significant predictor of planning performance. Neither the cortical thickness of any other prefrontal area nor gender were significantly associated with performance in the ToL task. The results of the present exploratory study suggest that the cortical thickness of the right, but not the left cMFG, is positively correlated with performance in the ToL task. We, therefore, conclude that increased cortical thickness may be more beneficial for higher-order processes, such as information integration, than for lower-order processes, such as the analysis of external information.

Correlation of NICU anthropometry in extremely preterm infants with brain development and language scores at early school age

Growth in preterm infants in the neonatal intensive care unit (NICU) is associated with increased global and regional brain volumes at term, and increased postnatal linear growth is associated with higher language scores at age 2. It is unknown whether these relationships persist to school age or if an association between growth and cortical metrics exists. Using regression analyses, we investigated relationships between the growth of 42 children born extremely preterm (< 28 weeks gestation) from their NICU hospitalization, standardized neurodevelopmental/language assessments at 2 and 4-6 years, and multiple neuroimaging biomarkers obtained from T1-weighted images at 4-6 years. We found length at birth and 36 weeks post-menstrual age had positive associations with language scores at 2 years in multivariable linear regression. No growth metric correlated with 4-6 year assessments. Weight and head circumference at 36 weeks post-menstrual age positively correlated with total brain volume and negatively with global cortical thickness at 4-6 years of age. Head circumference relationships remained significant after adjusting for age, sex, and socioeconomic status. Right temporal cortical thickness was related to receptive language at 4-6 years in the multivariable model. Results suggest growth in the NICU may have lasting effects on brain development in extremely preterm children.

Genetic risks of Alzheimer's by APOE and MAPT on cortical morphology in young healthy adults

Genetic risk factors such as APOE ε4 and MAPT (rs242557) A allele are associated with amyloid and tau pathways and grey matter changes at both early and established stages of Alzheimer's disease, but their effects on cortical morphology in young healthy adults remain unclear. A total of 144 participants aged from 18 to 24 underwent 3T MRI and genotyping for APOE and MAPT to investigate unique impacts of these genetic risk factors in a cohort without significant comorbid conditions such as metabolic and cardiovascular diseases. We segmented the cerebral cortex into 68 regions and calculated the cortical area, thickness, curvature and folding index for each region. Then, we trained machine learning models to classify APOE and MAPT genotypes using these morphological features. In addition, we applied a growing hierarchical self-organizing maps algorithm, which clustered the 68 regions into 4 subgroups representing different morphological patterns. Then, we performed general linear model analyses to estimate the interaction between APOE and MAPT on cortical patterns. We found that the classifiers using all cortical features could accurately classify individuals carrying genetic risks of dementia outperforming each individual feature alone. APOE ε4 carriers had a more convoluted and thinner cortex across the cerebral cortex. A similar pattern was found in MAPT A allele carriers only in the regions that are vulnerable for early tau pathology. With the clustering analysis, we found a synergetic effect between APOE ε4 and MAPT A allele, i.e. carriers of both risk factors showed the most deviation of cortical pattern from the typical pattern of that cluster. Genetic risk factors of dementia by APOE ε4 and MAPT (rs242557) A allele were associated with variations of cortical morphology, which can be observed in young healthy adults more than 30 years before Alzheimer's pathology is likely to occur and 50 years before dementia symptoms may begin.

Childhood socioeconomic status and the pace of structural neurodevelopment: accelerated, delayed, or simply different?

Socioeconomic status (SES) is associated with children's brain and behavioral development. Several theories propose that early experiences of adversity or low SES can alter the pace of neurodevelopment during childhood and adolescence. These theories make contrasting predictions about whether adverse experiences and low SES are associated with accelerated or delayed neurodevelopment. We contextualize these predictions within the context of normative development of cortical and subcortical structure and review existing evidence on SES and structural brain development to adjudicate between competing hypotheses. Although none of these theories are fully consistent with observed SES-related differences in brain development, existing evidence suggests that low SES is associated with brain structure trajectories more consistent with a delayed or simply different developmental pattern than an acceleration in neurodevelopment.

Systematic cortical thickness and curvature patterns in primates

Humans are known to have significant and consistent differences in thickness throughout the cortex, with thick outer gyral folds and thin inner sulcal folds. Our previous work has suggested a mechanical basis for this thickness pattern, with the forces generated during cortical folding leading to thick gyri and thin sulci, and shown that cortical thickness varies along a gyral-sulcal spectrum in humans. While other primate species are expected to exhibit similar patterns of cortical thickness, it is currently unknown how these patterns scale across different sizes, forms, and foldedness. Among primates, brains vary enormously from roughly the size of a grape to the size of a grapefruit, and from nearly smooth to dramatically folded; of these, human brains are the largest and most folded. These variations in size and form make comparative neuroanatomy a rich resource for investigating common trends that transcend differences between species. In this study, we examine 12 primate species in order to cover a wide range of sizes and forms, and investigate the scaling of their cortical thickness relative to the surface geometry. The 12 species were selected due to the public availability of either reconstructed surfaces and/or population templates. After obtaining or reconstructing 3D surfaces from publicly available neuroimaging data, we used our surface-based computational pipeline (https://github.com/mholla/curveball) to analyze patterns of cortical thickness and folding with respect to size (total surface area), geometry (i.e. curvature, shape, and sulcal depth), and foldedness (gyrification). In all 12 species, we found consistent cortical thickness variations along a gyral-sulcal spectrum, with convex shapes thicker than concave shapes and saddle shapes in between. Furthermore, we saw an increasing thickness difference between gyri and sulci as brain size increases. Our results suggest a systematic folding mechanism relating local cortical thickness to geometry. Finally, all of our reconstructed surfaces and morphometry data are available for future research in comparative neuroanatomy.

Integrative Bayesian tensor regression for imaging genetics applications

Identifying biomarkers for Alzheimer's disease with a goal of early detection is a fundamental problem in clinical research. Both medical imaging and genetics have contributed informative biomarkers in literature. To further improve the performance, recently, there is an increasing interest in developing analytic approaches that combine data across modalities such as imaging and genetics. However, there are limited methods in literature that are able to systematically combine high-dimensional voxel-level imaging and genetic data for accurate prediction of clinical outcomes of interest. Existing prediction models that integrate imaging and genetic features often use region level imaging summaries, and they typically do not consider the spatial configurations of the voxels in the image or incorporate the dependence between genes that may compromise prediction ability. We propose a novel integrative Bayesian scalar-on-image regression model for predicting cognitive outcomes based on high-dimensional spatially distributed voxel-level imaging data, along with correlated transcriptomic features. We account for the spatial dependencies in the imaging voxels via a tensor approach that also enables massive dimension reduction to address the curse of dimensionality, and models the dependencies between the transcriptomic features via a Graph-Laplacian prior. We implement this approach via an efficient Markov chain Monte Carlo (MCMC) computation strategy. We apply the proposed method to the analysis of longitudinal ADNI data for predicting cognitive scores at different visits by integrating voxel-level cortical thickness measurements derived from T1w-MRI scans and transcriptomics data. We illustrate that the proposed imaging transcriptomics approach has significant improvements in prediction compared to prediction using a subset of features from only one modality (imaging or genetics), as well as when using imaging and transcriptomics features but ignoring the inherent dependencies between the features. Our analysis is one of the first to conclusively demonstrate the advantages of prediction based on combining voxel-level cortical thickness measurements along with transcriptomics features, while accounting for inherent structural information.

Simple topological task-based functional connectivity features predict longitudinal behavioral change of fluid reasoning in the RANN cohort

Recent attention has been given to topological data analysis (TDA), and more specifically persistent homology (PH), to identify the underlying shape of brain network connectivity beyond simple edge pairings by computing connective components across different connectivity thresholds (see Sizemore et al., 2019). In the present study, we applied PH to task-based functional connectivity, computing 0-dimension Betti (B0) curves and calculating the area under these curves (AUC); AUC indicates how quickly a single connected component is formed across correlation filtration thresholds, with lower values interpreted as potentially analogous to lower whole-brain system segregation (e.g., Gracia-Tabuenca et al., 2020). One hundred sixty-three participants from the Reference Ability Neural Network (RANN) longitudinal lifespan cohort (age 20-80 years) were tested in-scanner at baseline and five-year follow-up on a battery of tests comprising four domains of cognition (i.e., Stern et al., 2014). We tested for 1.) age-related change in the AUC of the B0 curve over time, 2.) the predictive utility of AUC in accounting for longitudinal change in behavioral performance and 3.) compared system segregation to the PH approach. Results demonstrated longitudinal age-related decreases in AUC for Fluid Reasoning, with these decreases predicting longitudinal declines in cognition, even after controlling for demographic and brain integrity factors; moreover, change in AUC partially mediated the effect of age on change in cognitive performance. System segregation also significantly decreased with age in three of the four cognitive domains but did not predict change in cognition. These results argue for greater application of TDA to the study of aging.

The Influence of Obesity on Cognitive Functioning Among Healthcare Professionals: A Comprehensive Analysis

Background Excessive body fat, or obesity, is a worldwide epidemic and a major contributor to the development of dementia. Aim The research aimed to determine how obesity affected healthcare professionals' memory performance. Materials and Method A total of 474 participants (both male and female) were recruited in this study by random sampling method from three different health institutions. Participants were categorized into overweight, normal weight, and obese groups based on their body mass index (BMI) as per the WHO guidelines and for body fat participants. The memory function test was done using the Gilewski MJ scale. General frequency of forgetting, mnemonic usage, retrospective functioning, and seriousness of forgetting were measured and compared across the BMI and %body fat groups. Results The percentage of body fat of males and females was 38.19% and 42.26%. Statistically, a significant difference (p<0.05) was observed among the male and female BMI and percentage of body fat. The results showed that there was a significant difference between memory scale parameters and percentage BMI. Statistically, a significant difference was observed in the level of general frequency of forgetting among participants with different percentages of BMI (p<0.05). Similar, results were also observed in the level of seriousness of forgetting, retrospective functioning, and mnemonics usage with different % BMI (p<0.05). The findings showed a positive correlation between BMI and %body fat on the scale of general frequency of forgetting and seriousness of forgetting whereas, a negative correlation was observed on the scale of retrospective functioning and mnemonics usage. Conclusion Memory loss is one of the disorders that obesity is linked to more frequently. A focus on keeping a healthy weight may help prevent the development of future diseases.

Adolescent brain development in girls with Turner syndrome

Turner syndrome (TS) is a common sex chromosome aneuploidy in females associated with various physical, cognitive, and socio-emotional phenotypes. However, few studies have examined TS-associated alterations in the development of cortical gray matter volume and the two components that comprise this measure-surface area and thickness. Moreover, the longitudinal direct (i.e., genetic) and indirect (i.e., hormonal) effects of X-monosomy on the brain are unclear. Brain structure was assessed in 61 girls with TS (11.3 ± 2.8 years) and 55 typically developing girls (10.8 ± 2.3 years) for up to 4 timepoints. Surface-based analyses of cortical gray matter volume, thickness, and surface area were conducted to examine the direct effects of X-monosomy present before pubertal onset and indirect hormonal effects of estrogen deficiency/X-monosomy emerging after pubertal onset. Longitudinal analyses revealed that, whereas typically developing girls exhibited normative declines in gray matter structure during adolescence, this pattern was reduced or inverted in TS. Further, girls with TS demonstrated smaller total surface area and larger average cortical thickness overall. Regionally, the TS group exhibited decreased volume and surface area in the pericalcarine, postcentral, and parietal regions relative to typically developing girls, as well as larger volume in the caudate, amygdala, and temporal lobe regions and increased thickness in parietal and temporal regions. Surface area alterations were predominant by age 8, while maturational differences in thickness emerged by age 10 or later. Taken together, these results suggest the involvement of both direct and indirect effects of X-chromosome haploinsufficiency on brain development in TS.

Structural neuroimaging phenotypes and associated molecular and genomic underpinnings in autism: a review

Autism has been associated with differences in the developmental trajectories of multiple neuroanatomical features, including cortical thickness, surface area, cortical volume, measures of gyrification, and the gray-white matter tissue contrast. These neuroimaging features have been proposed as intermediate phenotypes on the gradient from genomic variation to behavioral symptoms. Hence, examining what these proxy markers represent, i.e., disentangling their associated molecular and genomic underpinnings, could provide crucial insights into the etiology and pathophysiology of autism. In line with this, an increasing number of studies are exploring the association between neuroanatomical, cellular/molecular, and (epi)genetic variation in autism, both indirectly and directly in vivo and across age. In this review, we aim to summarize the existing literature in autism (and neurotypicals) to chart a putative pathway from (i) imaging-derived neuroanatomical cortical phenotypes to (ii) underlying (neuropathological) biological processes, and (iii) associated genomic variation.

Neurocognitive basis of model-based decision making and its metacontrol in childhood

Human behavior is supported by both goal-directed (model-based) and habitual (model-free) decision-making, each differing in its flexibility, accuracy, and computational cost. The arbitration between habitual and goal-directed systems is thought to be regulated by a process known as metacontrol. However, how these systems emerge and develop remains poorly understood. Recently, we found that while children between 5 and 11 years displayed robust signatures of model-based decision-making, which increased during this developmental period, there were substantial individual differences in the display of metacontrol. Here, we inspect the neurocognitive basis of model-based decision-making and metacontrol in childhood and focus this investigation on executive functions, fluid reasoning, and brain structure. A total of 69 participants between the ages of 6-13 completed a two-step decision-making task and an extensive behavioral test battery. A subset of 44 participants also completed a structural magnetic resonance imaging scan. We find that individual differences in metacontrol are specifically associated with performance on an inhibition task and individual differences in thickness of dorsolateral prefrontal, temporal, and superior-parietal cortices. These brain regions likely reflect the involvement of cognitive processes crucial to metacontrol, such as cognitive control and contextual processing.

Longitudinal evolution of cortical thickness signature reflecting Lewy body dementia in isolated REM sleep behavior disorder: a prospective cohort study

BACKGROUND

The isolated rapid-eye-movement sleep behavior disorder (iRBD) is a prodromal condition of Lewy body disease including Parkinson's disease and dementia with Lewy bodies (DLB). We aim to investigate the longitudinal evolution of DLB-related cortical thickness signature in a prospective iRBD cohort and evaluate the possible predictive value of the cortical signature index in predicting dementia-first phenoconversion in individuals with iRBD.

METHODS

We enrolled 22 DLB patients, 44 healthy controls, and 50 video polysomnography-proven iRBD patients. Participants underwent 3-T magnetic resonance imaging (MRI) and clinical/neuropsychological evaluations. We characterized DLB-related whole-brain cortical thickness spatial covariance pattern (DLB-pattern) using scaled subprofile model of principal components analysis that best differentiated DLB patients from age-matched controls. We analyzed clinical and neuropsychological correlates of the DLB-pattern expression scores and the mean values of the whole-brain cortical thickness in DLB and iRBD patients. With repeated MRI data during the follow-up in our prospective iRBD cohort, we investigated the longitudinal evolution of the cortical thickness signature toward Lewy body dementia. Finally, we analyzed the potential predictive value of cortical thickness signature as a biomarker of phenoconversion in iRBD cohort.

RESULTS

The DLB-pattern was characterized by thinning of the temporal, orbitofrontal, and insular cortices and relative preservation of the precentral and inferior parietal cortices. The DLB-pattern expression scores correlated with attentional and frontal executive dysfunction (Trail Making Test-A and B: R = - 0.55, P = 0.024 and R = - 0.56, P = 0.036, respectively) as well as visuospatial impairment (Rey-figure copy test: R = - 0.54, P = 0.0047). The longitudinal trajectory of DLB-pattern revealed an increasing pattern above the cut-off in the dementia-first phenoconverters (Pearson's correlation, R = 0.74, P = 6.8 × 10^-4) but no significant change in parkinsonism-first phenoconverters (R = 0.0063, P = 0.98). The mean value of the whole-brain cortical thickness predicted phenoconversion in iRBD patients with hazard ratio of 9.33 [1.16-74.12]. The increase in DLB-pattern expression score discriminated dementia-first from parkinsonism-first phenoconversions with 88.2% accuracy.

CONCLUSION

Cortical thickness signature can effectively reflect the longitudinal evolution of Lewy body dementia in the iRBD population. Replication studies would further validate the utility of this imaging marker in iRBD.

A comprehensive evaluation of multicentric reliability of single-subject cortical morphological networks on traveling subjects

Despite the prevalence of research on single-subject cerebral morphological networks in recent years, whether they can offer a reliable way for multicentric studies remains largely unknown. Using two multicentric datasets of traveling subjects, this work systematically examined the inter-site test-retest (TRT) reliabilities of single-subject cerebral morphological networks, and further evaluated the effects of several key factors. We found that most graph-based network measures exhibited fair to excellent reliabilities regardless of different analytical pipelines. Nevertheless, the reliabilities were affected by choices of morphological index (fractal dimension > sulcal depth > gyrification index > cortical thickness), brain parcellation (high-resolution > low-resolution), thresholding method (proportional > absolute), and network type (binarized > weighted). For the factor of similarity measure, its effects depended on the thresholding method used (absolute: Kullback-Leibler divergence > Jensen-Shannon divergence; proportional: Jensen-Shannon divergence > Kullback-Leibler divergence). Furthermore, longer data acquisition intervals and different scanner software versions significantly reduced the reliabilities. Finally, we showed that inter-site reliabilities were significantly lower than intra-site reliabilities for single-subject cerebral morphological networks. Altogether, our findings propose single-subject cerebral morphological networks as a promising approach for multicentric human connectome studies, and offer recommendations on how to determine analytical pipelines and scanning protocols for obtaining reliable results.

Emerging epigenetic dynamics in gut-microglia brain axis: experimental and clinical implications for accelerated brain aging in schizophrenia

Brain aging, which involves a progressive loss of neuronal functions, has been reported to be premature in probands affected by schizophrenia (SCZ). Evidence shows that SCZ and accelerated aging are linked to changes in epigenetic clocks. Recent cross-sectional magnetic resonance imaging analyses have uncovered reduced brain reserves and connectivity in patients with SCZ compared to typically aging individuals. These data may indicate early abnormalities of neuronal function following cyto-architectural alterations in SCZ. The current mechanistic knowledge on brain aging, epigenetic changes, and their neuropsychiatric disease association remains incomplete. With this review, we explore and summarize evidence that the dynamics of gut-resident bacteria can modulate molecular brain function and contribute to age-related neurodegenerative disorders. It is known that environmental factors such as mode of birth, dietary habits, stress, pollution, and infections can modulate the microbiota system to regulate intrinsic neuronal activity and brain reserves through the vagus nerve and enteric nervous system. Microbiota-derived molecules can trigger continuous activation of the microglial sensome, groups of receptors and proteins that permit microglia to remodel the brain neurochemistry based on complex environmental activities. This remodeling causes aberrant brain plasticity as early as fetal developmental stages, and after the onset of first-episode psychosis. In the central nervous system, microglia, the resident immune surveillance cells, are involved in neurogenesis, phagocytosis of synapses and neurological dysfunction. Here, we review recent emerging experimental and clinical evidence regarding the gut-brain microglia axis involvement in SCZ pathology and etiology, the hypothesis of brain reserve and accelerated aging induced by dietary habits, stress, pollution, infections, and other factors. We also include in our review the possibilities and consequences of gut dysbiosis activities on microglial function and dysfunction, together with the effects of antipsychotics on the gut microbiome: therapeutic and adverse effects, role of fecal microbiota transplant and psychobiotics on microglial sensomes, brain reserves and SCZ-derived accelerated aging. We end the review with suggestions that may be applicable to the clinical setting. For example, we propose that psychobiotics might contribute to antipsychotic-induced therapeutic benefits or adverse effects, as well as reduce the aging process through the gut-brain microglia axis. Overall, we hope that this review will help increase the understanding of SCZ pathogenesis as related to chronobiology and the gut microbiome, as well as reveal new concepts that will serve as novel treatment targets for SCZ.

Heritability of cognitive abilities and regional brain structures in middle-aged to elderly East Asians

This study examined the single-nucleotide polymorphism heritability and genetic correlations of cognitive abilities and brain structural measures (regional subcortical volume and cortical thickness) in middle-aged and elderly East Asians (Korean) from the Gwangju Alzheimer's and Related Dementias cohort study. Significant heritability was found in memory function, caudate volume, thickness of the entorhinal cortices, pars opercularis, superior frontal gyri, and transverse temporal gyri. There were 3 significant genetic correlations between (i) the caudate volume and the thickness of the entorhinal cortices, (ii) the thickness of the superior frontal gyri and pars opercularis, and (iii) the thickness of the superior frontal and transverse temporal gyri. This is the first study to describe the heritability and genetic correlations of cognitive and neuroanatomical traits in middle-aged to elderly East Asians. Our results support the previous findings showing that genetic factors play a substantial role in the cognitive and neuroanatomical traits in middle to advanced age. Moreover, by demonstrating shared genetic effects on different brain regions, it gives us a genetic insight into understanding cognitive and brain changes with age, such as aging-related cognitive decline, cortical atrophy, and neural compensation.

The heterogeneity of asymmetric tau distribution is associated with an early age at onset and poor prognosis in Alzheimer's disease

PURPOSE

Left-right asymmetry, an important feature of brain development, has been implicated in neurodegenerative diseases, although it's less discussed in typical Alzheimer's disease (AD). We sought to investigate whether asymmetric tau deposition plays a potential role in AD heterogeneity.

METHODS

Two independent cohorts consisting of patients with mild cognitive impairment due to AD and AD dementia with tau PET imaging were enrolled [the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort with 18F-Flortaucipir, the Shanghai Memory Study (SMS) cohort with 18F-Florzolotau]. Based on the absolute global tau interhemispheric differences, each cohort was divided into two groups (asymmetric versus symmetric tau distribution). The two groups were cross-sectionally compared in terms of demographic, cognitive characteristics, and pathological burden. The cognitive decline trajectories were analyzed longitudinally.

RESULTS

Fourteen (23.3%) and 42 (48.3%) patients in the ADNI and SMS cohorts showed an asymmetric tau distribution, respectively. An asymmetric tau distribution was associated with an earlier age at disease onset (proportion of early-onset AD: ADNI/SMS/combined cohorts, p = 0.093/0.026/0.001) and more severe pathological burden (i.e., global tau burden: ADNI/SMS cohorts, p < 0.001/= 0.007). And patients with an asymmetric tau distribution were characterized by a steeper cognitive decline longitudinally (i.e., the annual decline of Mini-Mental Status Examination score: ADNI/SMS/combined cohorts, p = 0.053 / 0.035 / < 0.001).

CONCLUSIONS

Asymmetry in tau deposition, which may be associated with an earlier age at onset, more severe pathological burden, and a steeper cognitive decline, is potentially an important characteristic of AD heterogeneity.

From scalp to cortex, the whole isn't greater than the sum of its parts: introducing GetTissueThickness (GTT) to assess age and sex differences in tissue thicknesses

Noninvasive techniques to record and stimulate the brain rely on passing through the tissues in between the scalp and cortex. Currently, there is no method to obtain detailed information about these scalp-to-cortex distance (SCD) tissues. We introduce GetTissueThickness (GTT), an open-source, automated approach to quantify SCD, and unveil how tissue thicknesses differ across age groups, sexes and brain regions (n = 250). We show that men have larger SCD in lower scalp regions and women have similar-to-larger SCD in regions closer to the vertex, with aging resulting in increased SCD in fronto-central regions. Soft tissue thickness varies by sex and age, with thicker layers and greater age-related decreases in men. Compact and spongy bone thickness also differ across sexes and age groups, with thicker compact bone in women in both age groups and an age-related thickening. Older men generally have the thickest cerebrospinal fluid layer and younger women and men having similar cerebrospinal fluid layers. Aging mostly results in grey matter thinning. Concerning SCD, the whole isn't greater than the sum of its parts. GTT enables rapid quantification of the SCD tissues. The distinctive sensitivity of noninvasive recording and stimulation modalities to different tissues underscores the relevance of GTT.

Development of Human Lateral Prefrontal Sulcal Morphology and Its Relation to Reasoning Performance

Previous findings show that the morphology of folds (sulci) of the human cerebral cortex flatten during postnatal development. However, previous studies did not consider the relationship between sulcal morphology and cognitive development in individual participants. Here, we fill this gap in knowledge by leveraging cross-sectional morphologic neuroimaging data in the lateral PFC (LPFC) from individual human participants (6-36 years old, males and females; N = 108; 3672 sulci), as well as longitudinal morphologic and behavioral data from a subset of child and adolescent participants scanned at two time points (6-18 years old; N = 44; 2992 sulci). Manually defining thousands of sulci revealed that LPFC sulcal morphology (depth, surface area, and gray matter thickness) differed between children (6-11 years old)/adolescents (11-18 years old) and young adults (22-36 years old) cross-sectionally, but only cortical thickness showed differences across childhood and adolescence and presented longitudinal changes during childhood and adolescence. Furthermore, a data-driven approach relating morphology and cognition identified that longitudinal changes in cortical thickness of four left-hemisphere LPFC sulci predicted longitudinal changes in reasoning performance, a higher-level cognitive ability that relies on LPFC. Contrary to previous findings, these results suggest that sulci may flatten either after this time frame or over a longer longitudinal period of time than previously presented. Crucially, these results also suggest that longitudinal changes in the cortex within specific LPFC sulci are behaviorally meaningful, providing targeted structures, and areas of the cortex, for future neuroimaging studies examining the development of cognitive abilities.SIGNIFICANCE STATEMENT Recent work has shown that individual differences in neuroanatomical structures (indentations, or sulci) within the lateral PFC are behaviorally meaningful during childhood and adolescence. Here, we describe how specific lateral PFC sulci develop at the level of individual participants for the first time: from both cross-sectional and longitudinal perspectives. Further, we show, also for the first time, that the longitudinal morphologic changes in these structures are behaviorally relevant. These findings lay the foundation for a future avenue to precisely study the development of the cortex and highlight the importance of studying the development of sulci in other cortical expanses and charting how these changes relate to the cognitive abilities those areas support at the level of individual participants.

Neuroanatomical Correlates of Emotion-Related Impulsivity

BACKGROUND

Emotion-related impulsivity (ERI) refers to chronically poor self-control during periods of strong emotion. ERI robustly predicts psychiatric disorders and related problems, yet its neuroanatomical correlates are largely unknown. We tested whether local brain morphometry in targeted brain regions that integrate emotion and control could explain ERI severity.

METHODS

One hundred twenty-two adults (ages 18-55 years) with internalizing or externalizing psychopathology completed a structural magnetic resonance imaging (MRI) scan, the Three-Factor Impulsivity Index, and the Structured Clinical Interview for DSM-5. The Three-Factor Impulsivity Index measures two types of ERI and a third type of impulsivity not linked to emotion. Cortical reconstruction yielded cortical thickness and local gyrification measurements. We evaluated whether morphometry in the orbitofrontal cortex (OFC), insula, amygdala, and nucleus accumbens was associated with ERI severity. Hypotheses and analyses were preregistered.

RESULTS

Lower cortical gyrification in the right lateral OFC was associated with high ERI severity in a full, preregistered model. Separate examinations of local gyrification and cortical thickness also showed a positive association between gyrification in the left lateral OFC and ERI. An integrated measure of hemispheric imbalance in lateral OFC gyrification (right < left) correlated with ERI severity. These findings were specific to ERI and did not appear with non-emotion-related impulsivity.

CONCLUSIONS

Local gyrification in the lateral OFC is associated with ERI severity. The current findings fit with existing theories of OFC function, strengthen the connections between the transdiagnostic literature in psychiatry and neuroscience, and may guide future treatment development.

Age and sex differentially shape brain networks in Parkinson's disease

AIMS

Age and sex are important individual factors modifying the clinical symptoms of patients with Parkinson's disease (PD). Our goal is to evaluate the effects of age and sex on brain networks and clinical manifestations of PD patients.

METHODS

Parkinson's disease participants (n = 198) receiving functional magnetic resonance imaging from Parkinson's Progression Markers Initiative database were investigated. Participants were classified into lower quartile group (age rank: 0%~25%), interquartile group (age rank: 26%~75%), and upper quartile group (age rank: 76%~100%) according to their age quartiles to examine how age shapes brain network topology. The differences of brain network topological properties between male and female participants were also investigated.

RESULTS

Parkinson's disease patients in the upper quartile age group exhibited disrupted network topology of white matter networks and impaired integrity of white matter fibers compared to lower quartile age group. In contrast, sex preferentially shaped the small-world topology of gray matter covariance network. Differential network metrics mediated the effects of age and sex on cognitive function of PD patients.

CONCLUSION

Age and sex have diverse effects on brain structural networks and cognitive function of PD patients, highlighting their roles in the clinical management of PD.

Predicting 'Brainage' in the Developmental Period using Structural MRI, Morphometric Similarity, and Machine Learning

Brain development is regularly studied using structural MRI. Recently, studies have used a combination of statistical learning and large-scale imaging databases of healthy-children to predict an individual's age from structural MRI. This data-driven, 'brainage' typically differs from the subjects chronological age, with this difference a potential measure of individual difference. Few studies have leveraged higher-order or connectomic representations of structural MRI data for this brainage approach. We leveraged morphometric similarity as a network-level approach to structural MRI to generate predictive models of age. We benchmarked these novel brain-age approaches using morphometric similarity against more typical, single feature (i.e. cortical thickness) approaches. We showed that these novel methods did not outperform cortical thickness or cortical volume measures. All models were significantly biased by age, but robust to motion confounds. The main results show that, whilst morphometric similarity mapping may be a novel way to leverage additional information from a T1-weighted structural MRI beyond individual features, in the context of a brain-age framework, morphometric similarity does not explain more variance than individual structural features. Morphometric similarity as a network-level approach to structural MRI may be poorly positioned to study individual differences in brain development in healthy individuals.

Sight restoration in congenitally blind humans does not restore visual brain structure

It is unknown whether impaired brain structure after congenital blindness is reversible if sight is restored later in life. Using structural magnetic resonance imaging, visual cortical surface area and cortical thickness were assessed in a large group of 21 sight-recovery individuals who had been born blind and who months or years later gained sight through cataract removal surgery. As control groups, we included 27 normally sighted individuals, 10 individuals with permanent congenital blindness, and 11 sight-recovery individuals with a late onset of cataracts. Congenital cataract-reversal individuals had a lower visual cortical surface area and a higher visual cortical thickness than normally sighted controls. These results corresponded to those of congenitally permanently blind individuals suggesting that impaired brain structure did not recover. Crucially, structural brain alterations in congenital-cataract reversal individuals were associated with a lower post-surgery visual acuity. No significant changes in visual cortex structure were observed in sight-recovery individuals with late onset cataracts. The results demonstrate that impaired structural brain development due to visual deprivation from birth is not fully reversible and limits functional recovery. Additionally, they highlight the crucial importance of prevention measures in the context of other types of aberrant childhood environments including low socioeconomic status and adversity.

No signs of neurodegenerative effects in 15q11.2 BP1-BP2 copy number variant carriers in the UK Biobank

The 15q11.2 BP1-BP2 copy number variant (CNV) is associated with altered brain morphology and risk for atypical development, including increased risk for schizophrenia and learning difficulties for the deletion. However, it is still unclear whether differences in brain morphology are associated with neurodevelopmental or neurodegenerative processes. This study derived morphological brain MRI measures in 15q11.2 BP1-BP2 deletion (n = 124) and duplication carriers (n = 142), and matched deletion-controls (n = 496) and duplication-controls (n = 568) from the UK Biobank study to investigate the association with brain morphology and estimates of brain ageing. Further, we examined the ageing trajectory of age-affected measures (i.e., cortical thickness, surface area, subcortical volume, reaction time, hand grip strength, lung function, and blood pressure) in 15q11.2 BP1-BP2 CNV carriers compared to non-carriers. In this ageing population, the results from the machine learning models showed that the estimated brain age gaps did not differ between the 15q11.2 BP1-BP2 CNV carriers and non-carriers, despite deletion carriers displaying thicker cortex and lower subcortical volume compared to the deletion-controls and duplication carriers, and lower surface area compared to the deletion-controls. Likewise, the 15q11.2 BP1-BP2 CNV carriers did not deviate from the ageing trajectory on any of the age-affected measures examined compared to non-carriers. Despite altered brain morphology in 15q11.2 BP1-BP2 CNV carriers, the results did not show any clear signs of apparent altered ageing in brain structure, nor in motor, lung or heart function. The results do not indicate neurodegenerative effects in 15q11.2 BP1-BP2 CNV carriers.

Neural similarity across task load relates to cognitive reserve and brain maintenance measures on the Letter Sternberg task: a longitudinal study

The aging process is characterized by change across several measures that index cognitive status and brain integrity. In the present study, 54 cognitively-healthy younger and older adults, were analyzed, longitudinally, on a verbal working memory task to investigate the effect of brain maintenance (i.e., cortical thickness) and cognitive reserve (i.e., NART IQ as proxy) factors on a derived measure of neural efficiency. Participants were scanned using fMRI while presented with the Letter Sternberg task, a verbal working memory task consisting of encoding, maintenance and retrieval phases, where cognitive load is manipulated by varying the number of presented items (i.e., between one and six letters). Via correlation analysis, we looked at region-level and whole-brain relationships between load levels within each phase and then computed a global task measure, what we term phase specificity, to analyze how similar neural responses were across load levels within each phase compared to between each phase. We found that longitudinal change in phase specificity was positively related to longitudinal change in cortical thickness, at both the whole-brain and regional level. Additionally, baseline NART IQ was positively related to longitudinal change in phase specificity over time. Furthermore, we found a longitudinal effect of sex on change in phase specificity, such that females displayed higher phase specificity over time. Cross-sectional findings aligned with longitudinal findings, with the notable exception of behavioral performance being positively linked to phase specificity cross-sectionally at baseline. Taken together, our findings suggest that phase specificity positively relates to brain maintenance and reserve factors and should be better investigated as a measure of neural efficiency.