The genetic architecture of the human cerebral cortex

Morphological alterations and gene expression levels in the cerebral cortex causally influence susceptibility to type 2 diabetes: A Mendelian randomization study

BACKGROUND

The associations between type 2 diabetes (T2D) and neurological as well as psychiatric disorders have garnered growing interest. Previous evidence has indicated a correlation between the cerebral cortex and these conditions. However, the causal direction between the cerebral cortex and T2D remains ambiguous.

METHODS

We conducted a cerebral cortex-focused systematic Mendelian randomization (MR) study based on multiple data sourced from genome-wide association studies and expression quantitative trait locus.

RESULTS

The surficial area (SA) of Pars Opercularis and the thickness (TH) of the Supramarginal gyrus were found as significant contributors to the risk of T2D. Conversely, thickening in the Precentral area, Caudal Anterior Cingulate cortex, and banks of the Superior Temporal Sulcus, as well as SA amplification of the Precentral area, were associated with a reduced risk of T2D. There was no evidence of reverse causation. These alterations also have an impact on susceptibility to T2D complications. Combining the summary-data-based MR (SMR) analysis and colocalization analysis, we prioritized the expression of three causal genes in the cerebral cortex with genetic evidence for influencing T2D susceptibility. Elevated expression levels of NUDC and PACC1 increased susceptibility to T2D, whereas RAB29 expression exhibits an inverse association with T2D susceptibility. Mediation MR analysis revealed that TH of the Banks of the Superior Temporal Sulcus, SA of Precentral area, SA of Pars Opercularis, and SA of Supramarginal gyrus mediated the effect of RAB29 on T2D. Cross-tissue colocalization analysis demonstrated that the expression pattern of NUDC displayed brain tissue specificity. PACC1 and RAB29 also exhibited colocalization signals in several specific tissues beyond brain tissue. The phenome-wide association study suggested that these genes underscore the shared genetic burden of T2D with a range of disease phenotypes including mental disorders, cardiovascular disease, and malignancies.

CONCLUSIONS

These findings underscore the novel role of the central nervous system in genetic liability to T2D and provide valuable clues for future mechanism studies.

The developing visual system: A building block on the path to autism

Longitudinal neuroimaging studies conducted over the past decade provide evidence of atypical visual system development in the first years of life in autism spectrum disorder (ASD). Findings from genomic analyses, family studies, and postmortem investigations suggest that changes in the visual system in ASD are linked to genetic factors, making the visual system an important neural phenotype along the path from genes to behavior that deserves further study. This article reviews what is known about the developing visual system in ASD in the first years of life; it also explores the potential canalizing role that atypical visual system maturation may have in the emergence of ASD by placing findings in the context of developmental cascades involving brain development, attention, and social and cognitive development. Critical gaps in our understanding of human visual system development are discussed, and future research directions are proposed to improve our understanding of ASD as a complex neurodevelopmental disorder with origins in early brain development.

Role of air pollution exposure in the alteration of brain cortical structure: A Mendelian randomization study

BACKGROUND

Accumulating research has linked ambient air pollution exposure to alterations in cortical surface area (SA) and thickness; however, the causal inferences remain controversial. Our investigation aims to determine the causality between air pollution and brain cortical morphology using the Mendelian randomization (MR) approach.

METHODS

Public accessible genome-wide association studies data on particulate matter 2.5 (PM2.5), PM2.5 absorbance, PM10, PM2.5-10, nitrogen dioxide (NO2), and nitrogen oxides (NOX) concentration were screened to select instrumental variables. Univariable MR (UVMR) was performed to assess the causality of air pollution on brain cortical structure using five MR methods. Multivariable MR (MVMR) was further conducted to strengthen the robustness of the identified relationships by adjusting for related pollutant phenotypes, household income, and unhealthy eating habits.

RESULTS

The UVMR analysis identified fourteen causal associations between air pollution susceptibility and alterations in brain cortical morphology, with nine showing negative effects and five showing positive effects concurrently. The MVMR models indicated negative causal relationships between PM2.5 level and the SA of the inferior temporal cortex (beta [95 %CI] = -215.739 [-404.284 to -27.194], p = 0.025), NO2 level and the SA of the lateral occipital cortex (beta [95 %CI] = -548.577 [-1086.450 to -10.699], p = 0.046), and a positive correlation between PM2.5 absorbance and SA of the bankssts cortex (beta [95 %CI] = 76.491 [14.267-138.716], p = 0.016). No evidence of heterogeneity or pleiotropy was noticed.

CONCLUSIONS

Our exploration established causal relationships between air pollution exposure and brain cortical structure, underscoring the significance of mitigating air pollution to preserve brain cortical morphology.

Socioeconomic factors, brain-derived neurotrophic factor Val66Met polymorphism, and cortical structure in children and adolescents

Variability in associations between socioeconomic status and cortical gray matter may be due in part to the common, functional brain-derived neurotrophic factor (BDNF) Val66Met polymorphism, which alters BDNF signaling. In this study, we examined whether BDNF Val66Met genotype moderated the associations between socioeconomic factors (family income, parental education) and cortical surface area (SA) and thickness (CT) in two large independent samples of typically-developing children and adolescents. Participants were 3- to 21-year-olds (N = 383; 47% female) from the Pediatric Imaging, Neurocognition, and Genetics (PING) study and 11- to 14-year-olds (N = 2566; 46% female) in the Adolescent Brain Cognitive Development (ABCD) study. High-resolution, T1-weighted magnetic resonance imaging data were acquired in both studies. Analyses were conducted on global and regional SA and CT. In the PING sample, BDNF Val66Met genotype significantly moderated the association between family income and total SA and SA in the left fusiform gyrus. In the ABCD sample, there were no significant interactions for global or regional SA or CT. Collectively, these results suggest that BDNF Val66Met genotype may not explain variability in associations between socioeconomic factors and SA or CT in children and adolescents.

Causal relationships between white matter connectome and mental disorders: a large-scale genetic correlation study

BACKGROUND

Abnormalities in white matter integrity in mental disorders have attracted widespread attention, yet the genetic correlations and causal effects between white matter structural connectome and various psychiatric conditions remain largely unexplored.

METHODS

In this study, we employed linkage disequilibrium score (LDSC) and high-definition likelihood (HDL) methods to analyze genetic correlations between white matter connectome and mental disorders, followed by bidirectional two-sample Mendelian randomization (MR) analysis to investigate causal relationships. We utilized 206 white matter connectome magnetic resonance imaging (MRI) phenotypes derived from the processed UK Biobank dataset (n = 26,333 individuals) and 12 mental disorders from the latest FinnGen database (n = 402,965 to 449,029 individuals).

RESULTS

Using both methods, we observed 26 pairs of brain white matter connectivity phenotypes and mental disorders showing significant correlations. Forward MR analysis identified two white matter structural connectome phenotypes causally associated with psychiatric disorder risk. Increased connectivity in left-hemisphere visual network(VIS) to right-hemisphere limbic network(LIM)white-matter structural connectivity was associated with increased risk of anxiety disorders. Additionally, decreased connectivity in left-hemisphere visual network to hippocampus white-matter structural connectivity was associated with reduced risk of post-traumatic stress disorder (PTSD). However, reverse MR analysis results did not survive multiple testing correction.

CONCLUSION

These findings provide crucial insights into the complex interplay between white matter structural connectivity and mental disorders, potentially offering new avenues for understanding the neurobiological underpinnings of psychiatric conditions and informing future diagnostic and therapeutic strategies.

Penetrance of neurodevelopmental copy number variants is associated with variations in cortical morphology

BACKGROUND

Copy number variants (CNVs) increase risk for neurodevelopmental conditions. The neurobiological mechanisms linking these high-risk genetic variants to clinical phenotypes are largely unknown. An important question is whether brain abnormalities in individuals carrying CNVs are associated with their degree of penetrance.

METHODS

We investigated if increased CNV-penetrance for schizophrenia and other developmental disorders was associated with variations in cortical and subcortical morphology. We pooled T1-weighted brain magnetic resonance imaging and genetic data from 22 cohorts from the ENIGMA-CNV consortium. In the main analyses, we included 9,268 individuals (aged 7 to 90 years, 54% females), from which we identified 398 carriers of 36 neurodevelopmental CNVs at 20 distinct loci. A secondary analysis was performed including additional neuroimaging data from the ENIGMA-22q consortium, including 274 carriers of the 22q11.2 deletion and 291 non-carriers. CNV-penetrance was estimated through penetrance scores that were previously generated from large cohorts of patients and controls. These scores represent the probability risk to develop either schizophrenia or other developmental disorders (including developmental delay, autism spectrum disorder and congenital malformations).

RESULTS

For both schizophrenia and developmental disorders, increased penetrance scores were associated with lower surface area in the cerebral cortex and lower intracranial volume. For both conditions, associations between CNV-penetrance scores and cortical surface area were strongest in regions of the occipital lobes, specifically in the cuneus and lingual gyrus.

CONCLUSIONS

Our findings link global and regional cortical morphometric features with CNV-penetrance, providing new insights into neurobiological mechanisms of genetic risk for schizophrenia and other developmental disorders.

Application of improved graph convolutional network for cortical surface parcellation

Accurate cortical surface parcellation is essential for elucidating brain organizational principles, functional mechanisms, and the neural substrates underlying higher cognitive and emotional processes. However, the cortical surface is a highly folded complex geometry, and large regional variations make the analysis of surface data challenging. Current methods rely on geometric simplification, such as spherical expansion, which takes hours for spherical mapping and registration, a popular but costly process that does not take full advantage of inherent structural information. In this study, we propose an Attention-guided Deep Graph Convolutional network (ADGCN) for end-to-end parcellation on primitive cortical surface manifolds. ADGCN consists of a deep graph convolutional layer with a symmetrical U-shaped structure, which enables it to effectively transmit detailed information of the original brain map and learn the complex graph structure, help the network enhance feature extraction capability. What's more, we introduce the Squeeze and Excitation (SE) module, which enables the network to better capture key features, suppress unimportant features, and significantly improve parcellation performance with a small amount of computation. We evaluated the model on a public dataset of 100 artificially labeled brain surfaces. Compared with other methods, the proposed network achieves Dice coefficient of 88.53% and an accuracy of 90.27%. The network can segment the cortex directly in the original domain, and has the advantages of high efficiency, simple operation and strong interpretability. This approach facilitates the investigation of cortical changes during development, aging, and disease progression, with the potential to enhance the accuracy of neurological disease diagnosis and the objectivity of treatment efficacy evaluation.

Asthma causally affects the brain cortical structure: a Mendelian randomization study

OBJECTIVE

The potential causal relationship between asthma and brain structures remains uncertain. We performed a two-sample Mendelian randomization to investigate the causal effects of various asthma phenotypes - unspecified asthma, moderate-to-severe asthma, childhood-onset asthma, and adult-onset asthma (AOA) - on cerebral cortex structure.

METHODS

We utilized phenotype data derived from genome-wide association studies (GWASs). The ENIGMA Consortium GWAS provided outcome variables for surface area (SA) and thickness across the whole brain and 34 region-specific areas of the cerebral cortex. Using the inverse variance-weighted method as our primary estimation approach, we employed several techniques, including Cochran's Q statistic, the MR-PRESSO global test, MR-Egger, and weighted median, to assess heterogeneity and pleiotropy, thereby ensuring the robustness of our findings. Additionally, we conducted enrichment analyses of gene sets with causal effects on cortical structure and applied bioinformatics techniques to construct interaction networks and identify hub nodes.

RESULTS

At the global level, AOA was associated with a significant reduction in full cortical SA (β = -58.49 mm2, p = 0.017). In regional analyses, moderate-to-severe asthma exhibited a more pronounced impact on the cerebral cortex compared to other phenotypes. Enrichment analysis revealed that pathways implicated in brain morphology among asthma patients were primarily linked to immune and inflammation-driven pathways.

CONCLUSIONS

Our findings provide new evidence supporting a causal relationship between asthma and alterations in cortical structure, offering potential explanations for cognitive and psychiatric impairments observed in individual post-asthma.

Cortical differences across psychiatric disorders and associated common and rare genetic variants

Genetic studies have identified common and rare variants increasing the risk for neurodevelopmental and psychiatric disorders (NPDs). These risk variants have also been shown to influence the structure of the cerebral cortex. However, it is unknown whether cortical differences associated with genetic variants are linked to the risk they confer for NPDs. To answer this question, we analyzed cortical thickness (CT) and surface area (SA) for common and rare variants associated with NPDs, in ~33000 individuals from the general population and clinical cohorts, as well as ENIGMA summary statistics for 8 NPDs. Rare and common genetic variants increasing risk for NPDs were preferentially associated with total SA, while NPDs were preferentially associated with mean CT. Larger effects on mean CT, but not total SA, were observed in NPD medicated subgroups. At the regional level, genetic variants were preferentially associated with effects in sensorimotor areas, while NPDs showed higher effects in association areas. We show that schizophrenia- and bipolar-disorder-associated SNPs show positive and negative effect sizes on SA suggesting that their aggregated effects cancel out in additive polygenic models. Overall, CT and SA differences associated with NPDs do not relate to those observed across individual genetic variants and may be linked with critical non-genetic factors, such as medication and the lived experience of the disorder.

Epigenetic and genetic profiling of comorbidity patterns among substance dependence diagnoses

This study investigated the genetic and epigenetic mechanisms underlying the comorbidity of five substance dependence diagnoses (SDs; alcohol, AD; cannabis, CaD; cocaine, CoD; opioid, OD; tobacco, TD). A latent class analysis (LCA) was performed on 22,668 individuals from six cohorts to identify comorbid DSM-IV SD patterns. In subsets of this sample, we tested SD-latent classes with respect to polygenic overlap of psychiatric and psychosocial traits in 7659 individuals of European descent and epigenome-wide changes in 886 individuals of African, European, and Admixed-American descents. The LCA identified four latent classes related to SD comorbidities: AD + TD, CoD + TD, AD + CoD + OD + TD (i.e., polysubstance addiction, PSU), and TD. In the epigenome-wide association analysis, SPATA4 cg02833127 was associated with CoD + TD, AD + TD, and PSU latent classes. AD + TD latent class was also associated with CpG sites located on ARID1B, NOTCH1, SERTAD4, and SIN3B, while additional epigenome-wide significant associations with CoD + TD latent class were observed in ANO6 and MOV10 genes. PSU-latent class was also associated with a differentially methylated region in LDB1. We also observed shared polygenic score (PGS) associations for PSU, AD + TD, and CoD + TD latent classes (i.e., attention-deficit hyperactivity disorder, anxiety, educational attainment, and schizophrenia PGS). In contrast, TD-latent class was exclusively associated with posttraumatic stress disorder-PGS. Other specific associations were observed for PSU-latent class (subjective wellbeing-PGS and neuroticism-PGS) and AD + TD-latent class (bipolar disorder-PGS). In conclusion, we identified shared and unique genetic and epigenetic mechanisms underlying SD comorbidity patterns. These findings highlight the importance of modeling the co-occurrence of SD diagnoses when investigating the molecular basis of addiction-related traits.

Cortical scaling of the neonatal brain in typical and altered development

Theoretically derived scaling laws capture the nonlinear relationships between rapidly expanding brain volume and cortical gyrification across mammalian species and in adult humans. However, the preservation of these laws has not been comprehensively assessed in typical or pathological brain development. Here, we assessed the scaling laws governing cortical thickness (CT), surface area (SA), and cortical folding in the neonatal brain. We also assessed multivariate morphological terms that capture brain size, shape, and folding processes. The sample consisted of 345 typically developing infants, 73 preterm infants, and 107 infants with congenital heart disease (CHD) who underwent brain MRI. Our results show that typically developing neonates and those with CHD follow the cortical folding scaling law obtained from mammalian brains, children, and adults which captures the relationship between exposed SA, total SA, and CT. Cortical folding scaling was not affected by gestational age at birth, postmenstrual age at scan, sex, or multiple birth in these populations. CHD was characterized by a unique reduction in the multivariate morphological term capturing size, suggesting that CHD affects cortical growth overall but not cortical folding processes. In contrast, preterm birth was characterized by altered cortical folding scaling and altered shape, suggesting that the developmentally programmed processes of cortical folding are disrupted in this population. The degree of altered shape was associated with cognitive abilities in early childhood in preterm infants.

Overexpression of OTX2 in human neural cells links depression risk genes

Genome wide association studies (GWAS) have implicated the OTX2 (Orthodenticle homeobox 2) gene locus in major depressive disorders (MDD) as well as genetically correlated traits. Of the genes identified by MDD GWAS, the gene for the transcription factor OTX2 stands out as it is responsible for both opening and closing of critical and sensitive brain periods. These are developmental periods where the brain is more sensitive to environmental input and are critical for normal brain development. Evidence suggests that the brain may also be more sensitive to negative environmental impact during sensitive periods. Critically, human and animal models both specifically implicate OTX2 gene expression in the response to stress and risk for depression. Based on the genetic findings, and the potential role of OTX2 as a mediator of environmental risk for depression, we identified genes regulated by OTX2 in human neural precursor cells (NPCs) using CRISPR activation (CRISPRa) to increase expression. We identified 17 significantly differentially expressed genes, including OTX2 which was increased 4-fold. In addition to OTX2, 4 genes of the 17 have been directly implicated in depression/depressive behaviours from human and animal studies (GPER1, VGF, TAFA5, P3H2). Additional differentially expressed genes are involved in processes implicated in depression (e.g. neurogenesis, neuroplasticity, response to stress). These novel findings link OTX2 expression with genes previously implicated in depression from human and animal studies, suggesting OTX2 as a master regulator of depression risk.

Gene discovery and pleiotropic architecture of chronic pain in a genome-wide association study of >1.2 million individuals

Chronic pain is highly prevalent worldwide, and genome-wide association studies (GWAS) have identified a growing number of chronic pain loci. To further elucidate its genetic architecture, we leveraged data from 1,235,695 European ancestry individuals across three biobanks. In a meta-analytic GWAS, we identified 343 independent loci for chronic pain, 92 of which were new. Sex-specific meta-analyses revealed 115 independent loci (12 of which were new) for males (N = 583,066) and 12 loci (two of which were new) for females (N = 241,266). Multi-omics gene prioritization analyses highlighted 490 genes associated with chronic pain through their effects on brain- and blood-specific regulation. Loci associated with increased risk for chronic pain were also associated with increased risk for multiple other traits, with Mendelian randomization analyses showing that chronic pain was causally associated with psychiatric disorders, substance use disorders, and C-reactive protein levels. Chronic pain variants also exhibited pleiotropic associations with cortical area brain structures. This study expands our knowledge of the genetics of chronic pain and its pathogenesis, highlighting the importance of its pleiotropy with multiple disorders and elucidating its multi-omic pathophysiology.

Cortical structure in relation to empathy and psychopathy in 800 incarcerated men

Background

Reduced affective empathy is a hallmark of psychopathy, which incurs major interpersonal and societal costs. Advancing our neuroscientific understanding of this reduction and other psychopathic traits is crucial for improving their treatment.

Methods

In 804 incarcerated adult men, we administered the Perspective Taking (IRI-PT) and Empathic Concern (IRI-EC) subscales of the Interpersonal Reactivity Index, Hare Psychopathy Checklist-Revised (PCL-R; two factors), and T1-weighted MRI to quantify cortical thickness (CT) and surface area (SA). We also included the male sample of the Human Connectome Project (HCP; N = 501) to replicate patterns of macroscale structural organization.

Results

Factor 1 (Interpersonal/Affective) uniquely negatively related to IRI-EC, while Factor 2 (Lifestyle/Antisocial) uniquely negatively related to IRI-PT. Cortical structure did not relate to either IRI subscale, although there was effect-size differentiation by microstructural class and/or functional network. CT related to Factor 1 (mostly positively), SA related to both factors (only positively), and both cortical indices demonstrated out-of-sample predictive utility for Factor 1. The high-psychopathy group (N = 178) scored uniquely lower on IRI-EC while having increased SA (but not CT). Regionally, these SA increases localized primarily in the paralimbic class and somatomotor network, with meta-analytic task-based activations corroborating affective-sensory importance. High psychopathy also showed "compressed" global and/or network-level organization of both cortical indices, and this organization in the total sample replicated in HCP. All findings accounted for age, IQ, and/or total intracranial volume.

Conclusions

Psychopathy had negative relationships with affective empathy and positive relationships with paralimbic/somatomotor SA, highlighting the role of affect and sensation.

Measuring the associations between brain morphometry and polygenic risk scores for substance use disorders in drug-naive adolescents

Substance use has been associated with differences in adult brain morphology; however, it is unclear whether these differences precede or are a result of substance use substance use. We investigated the impact of polygenic risk scores (PRSs) for cannabis use disorder (CUD) and general substance use and substance use disorder liability (SU/SUD) on brain morphology in drug-naïve adolescents. Baseline data were used from 1,874 European-descent participants (ages 9-11) comprising 222, 328 and 387 pairs of MZ twins, DZ twins, and Non-Twin Siblings, respectively, in the Adolescent Brain Cognitive Development Study. We fitted multivariate twin models to estimate the putative effects of CUD, SU/SUD, and brain region-specific PRSs. These models assessed their influence on six subcortical and two cortical phenotypes. PRS for CUD and SU/SUD were created based on GWAS conducted by Johnson et al. (2020) and Hatoum et al. (2023), respectively. When decomposing variance in each brain region of interest (ROI), we used the corresponding ROI-specific PRS. Brain morphometry in drug-naive subjects was unrelated to CUD PRS. The variance explained in each ROI by its corresponding PRS ranged from 0.8-4.4%. The SU/SUD PRS showed marginally significant effects (0.2-0.4%) on cortical surface area and nucleus accumbens volume, but overall effect sizes were small. Our findings indicate that differences in brain morphometry among baseline drug-naive individuals are not associated with the genetic risk for CUD but show a weak association with general addiction and substance use risk (SU/SUD), particularly in nucleus accumbens volume and total cortical surface area.

Neurodevelopmental effects of omega-3 fatty acids and its combination with Methylphenidate in iPSC models of ADHD

Attention-Deficit/Hyperactivity Disorder (ADHD) has been linked to altered neurodevelopmental processes, including proliferation and differentiation of neural stem cells (NSC). We aimed to investigate the role of Wnt signaling, a pathway critical for brain development, in ADHD and to determine if modulation of this pathway using ω-3/6 polyunsaturated fatty acids (PUFAs) may provide a beneficial treatment approach. Given the symptom heterogeneity in ADHD and the limited response to conventional therapies for some patients, we examined the effects of ω-3/6 PUFA treatment combined with Methylphenidate (MPH) on neurodevelopmental mechanisms using induced pluripotent stem cell (iPSC)-derived NSCs, comparing controls to ADHD patients. Our results show that ω-3/6 PUFAs differentially regulate Wnt activity in NSCs depending on the patient's condition and the composition of the treatments. These findings highlight the potential of ω-3 PUFA treatment as personalized support for neurodevelopmental processes in ADHD. They also emphasize the importance of investigating ADHD subgroups, including those unresponsive to stimulant treatments, as they may exhibit distinct phenotypes.

Beyond case-control study in neuroimaging for psychiatric disorders: Harmonizing and utilizing the brain images from multiple sites

Recent magnetic resonance imaging (MRI) research has advanced our understanding of brain pathophysiology in psychiatric disorders. This progress necessitates re-evaluation of the diagnostic system for psychiatric disorders based on MRI-based biomarkers, with implications for precise clinical diagnosis and optimal therapeutics. To achieve this goal, large-scale multi-site studies are essential to develop a standardized MRI database, with the analysis of several thousands of images and the incorporation of new data. A critical challenge in these studies is to minimize sampling and measurement biases in MRI studies to accurately capture the diversity of disease-derived biomarkers. Various techniques have been employed to consolidate datasets from multiple sites in case-control studies. Traveling subject harmonization stands out as a powerful tool that can differentiate measurement bias from sample variety and sampling bias. A non-linear statistical model for a normative trajectory across the lifespan also strengthens the database to mitigate sampling bias from known factors such as age and sex. These approaches can enhance the alterations between psychiatric disorders and integrate new data and follow-up scans into existing life-course trajectory, enhancing the reliability of machine learning classification and subtyping. Although this approach has been developed using T1-weighted structural image features, future research may extend this framework to other modalities and measures. The required sample size and methodological establishment are needed for future investigations, leading to novel insights into the brain pathophysiology of psychiatric disorders and the development of optimal therapeutics for bedside clinical applications. Sharing big data and their findings also need to be considered.

Shared Overall Topological Impairments of Functional Brain Networks Across Diverse State of Bipolar Disorder With Relevance to Cognitive Deficits and Genetic and Transcriptomic Variations

OBJECTIVES

Investigating brain network properties in BD patients across mood states can offer insights into the underlying mechanisms of the disorder. This study aimed to explore the topological architecture of functional brain networks in BD and its relationship with clinical variables and genetic/transcriptomic variations.

METHODS

The study involved 100 BD patients and 95 healthy controls. Researchers used graph theory-based methods to analyze whole-brain functional networks and explore their relationship with clinical variables. We also conducted a neuroimaging-transcription association analysis using the Allen Human Brain Atlas.

RESULTS

Depressive and manic BD patients exhibited increased local efficiency and decreased global efficiency at the global network level compared to healthy controls. Nodal-level analysis revealed disrupted nodal parameters within specific brain networks, including the fronto-parietal, default mode, and somatomotor networks. Significant correlations were found between nodal properties and cognitive function. All BD groups showed enhanced connectivity strength in rich-club and feeder connections compared to controls. Neuroimaging-transcription analysis identified potential genetic factors related to BD.

CONCLUSION

Our investigation unveiled shared impairments in the overall topological architecture of functional brain networks across depressive, manic, and euthymic BD. These observed abnormalities were associated with cognitive deficits in BD patients across three mood states. These common deficits, possibly stemming from the segregated changes in structural and functional rich-club connections, might represent trait-like pathophysiological mechanisms inherent to BD. Furthermore, our neuroimaging-transcription association analysis indicates the potential use of brain functional anomalies as endophenotypes in BD.

Polygenic Associations between Motor Behaviour, Neuromotor Traits, and Active Music Engagement in Four Cohorts

Phenotypic investigations have shown that actively engaging with music, i.e., playing a musical instrument or singing may be protective of motor decline in aging. For example, music training associated with enhanced sensorimotor skills accompanied by changes in brain structure and function. Although it is possible that the benefits of active music engagement "transfer" to benefits in the motor domain, it is also possible that the genetic architecture of motor behaviour and the motor system structure may influence active music engagement. This study investigated whether polygenic scores (PGS) for five behavioural motor traits, 12 neuromotor structural brain traits, and seven rates of change in brain structure traits trained from existing discovery genome-wide association studies (GWAS) predict active music engagement outcomes in four independent cohorts of unrelated individuals of European ancestry: the Canadian Longitudinal Study on Aging (CLSA; N=22,198), Wisconsin Longitudinal Study (WLS; N=4,605), Vanderbilt's BioVU Repository (BioVU; N=6,150), and Vanderbilt's Online Musicality study (OM; N=1,559). Results were meta-analyzed for each PGS main effect across outcomes and cohorts, revealing that PGS for a faster walking pace was associated with higher amounts of active music engagement. Within CLSA, a higher PGS for walking pace was associated with greater odds of engaging with music. Findings suggest a shared genetic architecture between motor function and active music engagement. Future intervention-based research should consider the genetic underpinnings of motor behavior when evaluating the effects of music engagement on motor function across the lifespan.

Auditory cortex anatomy reflects multilingual phonological experience

This study examines whether auditory cortex anatomy reflects multilingual experience, specifically individuals' phonological repertoire. Using data from over 200 participants exposed to 1-7 languages across 36 languages, we analyzed the role of language experience and typological distances between languages they spoke in shaping neural signatures of multilingualism. Our findings reveal a negative relationship between the thickness of the left and right second transverse temporal gyrus (TTG) and participants' degree of multilingualism. Models incorporating phoneme-level information in the language experience index explained the most variance in TTG thickness, suggesting that a more extensive and more phonologically diverse language experience is associated with thinner cortices in the second TTG. This pattern, consistent across two datasets, supports the idea of experience-driven pruning and neural efficiency. Our findings indicate that experience with typologically distant languages appear to impact the brain differently than those with similar languages. Moreover, they suggest that early auditory regions seem to represent phoneme-level cross-linguistic information, contrary to the most established models of language processing in the brain, which suggest that phonological processing happens in more lateral posterior superior temporal gyrus (STG) and superior temporal sulcus (STS).

Vision Transformer Autoencoders for Unsupervised Representation Learning: Capturing Local and Non-Local Features in Brain Imaging to Reveal Genetic Associations

The discovery of genetic loci associated with brain architecture can provide deeper insights into neuroscience and improved personalized medicine outcomes. Previously, we designed the Unsupervised Deep learning-derived Imaging Phenotypes (UDIPs) approach to extract endophenotypes from brain imaging using a convolutional (CNN) autoencoder, and conducted brain imaging GWAS on UK Biobank (UKBB). In this work, we leverage a vision transformer (ViT) model due to a different inductive bias and its ability to potentially capture unique patterns through its pairwise attention mechanism. Our approach based on 128 endophenotypes derived from average pooling discovered 10 loci previously unreported by CNN-based UDIP model, 3 of which were not found in the GWAS catalog to have had any associations with brain structure. Our interpretation results demonstrate the ViT's capability in capturing non-local patterns such as left-right hemisphere symmetry within brain MRI data, by leveraging its attention mechanism and positional embeddings. Our results highlight the advantages of transformer-based architectures in feature extraction and representation for genetic discovery.

Genetics impact risk of Alzheimer's disease through mechanisms modulating structural brain morphology in late life

BACKGROUND

Alzheimer's disease (AD)-related neuropathological changes can occur decades before clinical symptoms. We aimed to investigate whether neurodevelopment and/or neurodegeneration affects the risk of AD, through reducing structural brain reserve and/or increasing brain atrophy, respectively.

METHODS

We used bidirectional two-sample Mendelian randomisation to estimate the effects between genetic liability to AD and global and regional cortical thickness, estimated total intracranial volume, volume of subcortical structures and total white matter in 37 680 participants aged 8-81 years across 5 independent cohorts (Adolescent Brain Cognitive Development, Generation R, IMAGEN, Avon Longitudinal Study of Parents and Children and UK Biobank). We also examined the effects of global and regional cortical thickness and subcortical volumes from the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium on AD risk in up to 37 741 participants.

RESULTS

Our findings show that AD risk alleles have an age-dependent effect on a range of cortical and subcortical brain measures that starts in mid-life, in non-clinical populations. Evidence for such effects across childhood and young adulthood is weak. Some of the identified structures are not typically implicated in AD, such as those in the striatum (eg, thalamus), with consistent effects from childhood to late adulthood. There was little evidence to suggest brain morphology alters AD risk.

CONCLUSIONS

Genetic liability to AD is likely to affect risk of AD primarily through mechanisms affecting indicators of brain morphology in later life, rather than structural brain reserve. Future studies with repeated measures are required for a better understanding and certainty of the mechanisms at play.

Uncovering drug targets for cluster headache through proteome-wide Mendelian randomization analysis

BACKGROUND

Cluster headache (CH) is a highly disabling primary headache disorder with a complex underlying mechanism. However, there are currently no effective targeted therapeutic drugs available. Existing medications often have limited efficacy and numerous side effects, which frequently fail to meet clinical needs. This study aims to identify potential new therapeutic targets for CH through proteome-wide mendelian randomization (PWMR).

METHODS

We used PWMR to estimate the causal effects of plasma proteins on CH. This analysis integrated plasma protein quantitative trait loci (pQTL) data with genome-wide association study (GWAS) results of CH phenotypes. In addition, we conducted various sensitivity analyses, enrichment analyses, phenome-wide MR assessments, protein-protein interaction network construction, and mediation MR analyses to further validate the drug potential of the identified protein targets.

RESULTS

We identified 11 protein targets for CH (p < 2.41 × 10-5), with high-priority candidates exhibiting minimal side effects. Phenome-wide MR revealed novel targets-PXDNL, CCN4, PKD1, LGALS9, and MRC1-that show no significant disease-related adverse effects and interact with established preventive CH drug targets. Notably, PXDNL interacts with both acute and preventive CH drug targets. Furthermore, the causal effect of plasma proteins on CH is partially mediated by cortical surface area, with mediation proportions ranging from 3.2% to 10.0%.

CONCLUSIONS

We identified a set of potential protein targets for CH, characterized by rare side effects and a strong association with the biological mechanisms underlying the disorder. These findings offer valuable insights for the development of targeted drug therapies in the treatment of CH.

Enhanced insights into the genetic architecture of 3D cranial vault shape using pleiotropy-informed GWAS

Large-scale GWAS studies have uncovered hundreds of genomic loci linked to facial and brain shape variation, but only tens associated with cranial vault shape, a largely overlooked aspect of the craniofacial complex. Surrounding the neocortex, the cranial vault plays a central role during craniofacial development and understanding its genetics are pivotal for understanding craniofacial conditions. Experimental biology and prior genetic studies have generated a wealth of knowledge that presents opportunities to aid further genetic discovery efforts. Here, we use the conditional FDR method to leverage GWAS data of facial shape, brain shape, and bone mineral density to enhance SNP discovery for cranial vault shape. This approach identified 120 independent genomic loci at 1% FDR, nearly tripling the number discovered through unconditioned analysis and implicating crucial craniofacial transcription factors and signaling pathways. These results significantly advance our genetic understanding of cranial vault shape and craniofacial development more broadly.

Multi-omics analysis of druggable genes to facilitate Alzheimer's disease therapy: A multi-cohort machine learning study

BACKGROUND

The swift rise in the prevalence of Alzheimer's disease (AD) alongside its significant societal and economic impact has created a pressing demand for effective interventions and treatments. However, there are no available treatments that can modify the progression of the disease.

METHODS

Eight AD brain tissues datasets and three blood datasets were obtained. Consensus clustering was utilized as a method to discern the various subtypes of AD. Then, module genes were screened using weighted correlation network analysis (WGCNA). Furthermore, screening hub genes was conducted through machine-learning analyses. Finally, A comprehensive analysis using a systematic approach to druggable genome-wide Mendelian randomization (MR) was conducted.

RESULTS

Two AD subclasses were identified, namely cluster.A and cluster.B. The levels of gamma secretase activity, beta secretase activity, and amyloid-beta 42 were found to be significantly elevated in patients classified within cluster A when compared to those in cluster B. Furthermore, by utilizing the differentially expressed genes shared among these clusters, along with identifying druggable genes and applying WGCNA to these subtypes, we were able to develop a scoring system referred to as DG.score. This scoring system has demonstrated remarkable predictive capability for AD when evaluated against multiple datasets. Besides, A total of 30 distinct genes that may serve as potential drug targets for AD were identified across at least one of the datasets investigated, whether derived from brain samples or blood analyses. Among the identified genes, three specific candidates that are considered druggable (LIMK2, MAPK8, and NDUFV2) demonstrated significant expression levels in both blood and brain tissues. Furthermore, our research also revealed a potential association between the levels of LIMK2 and concentrations of CSF Aβ (OR 1.526 (1.155-2.018)), CSF p-tau (OR 1.106 (1.024-01.196)), and hippocampal size (OR 0.831 (0.702-0.948)).

CONCLUSIONS

This study provides a notable advancement to the existing literature by offering genetic evidence that underscores the potential therapeutic advantages of focusing on the druggable gene LIMK2 in the treatment of AD. This insight not only contributes to our understanding of AD but also guides future drug discovery efforts.

Rapidly evolved genomic regions shape individual language abilities in present-day humans

1Minor genetic changes have produced profound differences in cognitive abilities between humans and our closest relatives, particularly in language. Despite decades of research, ranging from single-gene studies to broader evolutionary analyses[1, 2, 3, 4, 5], key questions about the genomic foundations of human language have persisted, including which sequences are involved, how they evolved, and whether similar changes occur in other vocal learning species. Here we provide the first evidence directly linking rapidly evolved genomic regions to language abilities in contemporary humans. Through extensive analysis of 65 million years of evolutionary events in over 30,000 individuals, we demonstrate that Human Ancestor Quickly Evolved Regions (HAQERs)[5] - sequences that rapidly accumulated mutations after the human-chimpanzee split - specifically influence language but not general cognition. These regions evolved to shape language development by altering binding of Forkhead domain transcription factors, including FOXP2. Strikingly, language-associated HAQER variants show higher prevalence in Neanderthals than modern humans, have been stable throughout recent human history, and show evidence of convergent evolution across other mammalian vocal learners. An unexpected pattern of balancing selection acting on these apparently beneficial alleles is explained by their pleiotropic effects on prenatal brain development contributing to birth complications, reflecting an evolutionary trade-off between language capability and reproductive fitness. By developing the Evolution Stratified-Polygenic Score analysis, we show that language capabilities likely emerged before the human-Neanderthal split - far earlier than previously thought[3, 6, 7]. Our findings establish the first direct link between ancient genomic divergence and present-day variation in language abilities, while revealing how evolutionary constraints continue to shape human cognitive development.

Mendelian randomization identifies proteins involved in neurodegenerative diseases

Proteins are involved in multiple biological functions. High-throughput technologies have allowed the measurement of thousands of proteins in population biobanks. In this study, we aimed to identify proteins related to Alzheimer's disease, Parkinson's disease, multiple sclerosis and amyotrophic lateral sclerosis by leveraging large-scale genetic and proteomic data. We performed a two-sample cis Mendelian randomization study by selecting instrumental variables for the abundance of >2700 proteins measured by either Olink or SomaScan platforms in plasma from the UK Biobank and the deCODE Health Study. We also used the latest publicly available genome-wide association studies for the neurodegenerative diseases of interest. The potentially causal effect of proteins on neurodegenerative diseases was estimated based on the Wald ratio. We tested 13 377 protein-disease associations, identifying 169 associations that were statistically significant (5% false discovery rate). Evidence of co-localization between plasma protein abundance and disease risk (posterior probability > 0.80) was identified for 61 protein-disease pairs, leading to 50 unique protein-disease associations. Notably, 23 of 50 protein-disease associations corresponded to genetic loci not previously reported by genome-wide association studies. The two-sample Mendelian randomization and co-localization analysis also showed that APOE abundance in plasma was associated with three subcortical volumes (hippocampus, amygdala and nucleus accumbens) and white matter hyper-intensities, whereas PILRA and PILRB abundance in plasma was associated with caudate nucleus volume. Our study provided a comprehensive assessment of the effect of the human proteome that is currently measurable through two different platforms on neurodegenerative diseases. The newly associated proteins indicated the involvement of complement (C1S and C1R), microglia (SIRPA, SIGLEC9 and PRSS8) and lysosomes (CLN5) in Alzheimer's disease; the interleukin-6 pathway (CTF1) in Parkinson's disease; lysosomes (TPP1), blood-brain barrier integrity (MFAP2) and astrocytes (TNFSF13) in amyotrophic lateral sclerosis; and blood-brain barrier integrity (VEGFB), oligodendrocytes (PARP1), node of Ranvier and dorsal root ganglion (NCS1, FLRT3 and CDH15) and the innate immune system (CR1, AHSG and WARS) in multiple sclerosis. Our study demonstrates how harnessing large-scale genomic and proteomic data can yield new insights into the role of the plasma proteome in the pathogenesis of neurodegenerative diseases.

Modifiable lifestyle factors influencing neurological and psychiatric disorders mediated by structural brain reserve: An observational and Mendelian randomization study

BACKGROUND

Modifiable lifestyle factors are implicated as risk factors for neurological and psychiatric disorders, but whether these associations are causal remains uncertain. We aimed to evaluate associations and ascertain causal relationships between modifiable lifestyle factors, neurological and psychiatric disorder risk, and brain structural magnetic resonance imaging (MRI) markers.

METHODS

We analyzed data from over 50,000 UK Biobank participants with self-reported lifestyle factors, including alcohol consumption, smoking, physical activity, diet, sleep, electronic device use, and sexual factors. Primary outcomes were stroke, all-cause dementia, Parkinson's disease (PD), Major depression disorder (MDD), Anxiety Disorders (ANX), and Bipolar Disorder (BIP), alongside MRI markers. Summary statistics were obtained from genome-wide association studies and Mendelian randomization (MR) analyses investigated bidirectional associations between lifestyle factors, neurological/psychiatric disorders, and MRI markers, with mediation assessed using multivariable Mendelian randomization (MVMR).

RESULTS

Cross-sectional analyses identified lifestyle factors were associated with neurological and psychiatric disorders and brain morphology. MR confirmed causal relationships, including lifetime smoking index on Stroke, PD, MDD, ANX and BIP; play computer games on BIP; leisure screen time on Stroke and MDD; automobile speeding propensity on MDD; sexual factors on MDD and BIP; sleep characteristics on BIP and MDD. Brain structure mediated several lifestyle-disorder associations, such as daytime dozing and dementia, lifetime smoking and PD and age first had sexual intercourse and PD.

CONCLUSION

Our results provide support for a causal effect of multiple lifestyle measures on the risk of neurological and psychiatric disorders, with brain structural morphology serving as a potential biological mediator in their associations.

Brain-Charting Autism and Attention-Deficit/Hyperactivity Disorder Reveals Distinct and Overlapping Neurobiology

BACKGROUND

Autism and attention-deficit/hyperactivity disorder (ADHD) are heterogeneous neurodevelopmental conditions with complex underlying neurobiology that is still poorly understood. Despite overlapping presentation and sex-biased prevalence, autism and ADHD are rarely studied together and sex differences are often overlooked. Population modeling, often referred to as normative modeling, provides a unified framework for studying age-specific and sex-specific divergences in brain development.

METHODS

Here, we used population modeling and a large, multisite neuroimaging dataset (N = 4255 after quality control) to characterize cortical anatomy associated with autism and ADHD, benchmarked against models of average brain development based on a sample of more than 75,000 individuals. We also examined sex and age differences and relationship with autistic traits and explored the co-occurrence of autism and ADHD.

RESULTS

We observed robust neuroanatomical signatures of both autism and ADHD. Overall, autistic individuals showed greater cortical thickness and volume that was localized to the superior temporal cortex, whereas individuals with ADHD showed more global increases in cortical thickness but lower cortical volume and surface area across much of the cortex. The co-occurring autism+ADHD group showed a unique pattern of widespread increases in cortical thickness and certain decreases in surface area. We also found that sex modulated the neuroanatomy of autism but not ADHD, and there was an age-by-diagnosis interaction for ADHD only.

CONCLUSIONS

These results indicate distinct cortical differences in autism and ADHD that are differentially affected by age and sex as well as potentially unique patterns related to their co-occurrence.

Causal Association Between Major Depressive Disorder and Cortical Structure: A Bidirectional Mendelian Randomization Study and Mediation Analysis

BACKGROUND

Previous observational studies have reported a possible association between major depressive disorder (MDD) and abnormal cortical structure. However, it is unclear whether MDD causes reductions in global cortical thickness (CT) and global area (SA).

OBJECTIVE

We aimed to test the bidirectional causal relationship between MDD and CT and SA using a Mendelian randomization (MR) design and performed exploratory analyses of MDD on CT and SA in different brain regions.

METHODS

Summary-level data were obtained from two GWAS meta-analysis studies: one screening for single nucleotide polymorphisms (SNPs) predicting the development of MDD (n = 135,458) and the other identifying SNPs predicting the magnitude of cortical thickness (CT) and surface area (SA) (n = 51,665).

RESULTS

The results showed that MDD caused a decrease in CT in the medial orbitofrontal region, a decrease in SA in the paracentral region, and an increase in SA in the lateral occipital region. C-reactive protein, tumor necrosis factor alpha (TNF-α), interleukin-1β, and interleukin-6 did not mediate the reduction. We also found that a reduction in CT in the precentral region and a reduction in SA in the orbitofrontal regions might be associated with a higher risk of MDD.

CONCLUSION

Our study did not suggest an association between MDD and cortical CT and SA.

Causal associations between hypertension and abnormal brain cortical structures: Insights from a bidirectional Mendelian randomization study

Background

Observational studies suggest that hypertension affects brain cortical structure. However, the potential causal association has yet to be entirely determined. Thus, we aim to assess the causality between hypertension and abnormal cortical structure.

Methods

We conducted a bidirectional Mendelian randomization (MR) study to estimate their relationship. Genome-wide association study summary statistics of hypertension (n = 484,598) and brain cortical (surface area and thickness) (n = 51,665) were derived from publicly available databases. Sensitivity analyses were applied to ensure the robustness of the results.

Results

The study showed that hypertension was associated with a decline in total brain cortical thickness [β, -0.0308 mm; 95 % confidence interval (CI), -0.0610 to -0.0007; p = 0.045] and the insula thickness [β, -0.0415 mm; 95 % CI, -0.0772 to -0.0057; p = 0.023]. A null association was observed between hypertension and other brain regions. In the reverse MR analysis, the total cortical surface area (per 1 SD increase) significantly decreased the incidence of hypertension [odds ratio (OR), 0.976; 95 % CI, 0.963 to 0.990; p = 5.15E-04]. The caudal anterior cingulate cortex thickness (per 1 SD increase) was significantly associated with an increased risk of hypertension [OR, 1.057; 95 % CI, 1.034 to 1.082; p = 1.08E-06]. Moreover, we found several nominally associated gyri, including cuneus, isthmus cingulate, middle temporal, para hippocampal, posterior cingulate, superior temporal, and medial orbitofrontal, influence the incidence of hypertension.

Conclusion

Our study showed causal relationships between hypertension and changes in specific brain cortical, providing new evidence for the heart-brain axis theory.

Subtypes of brain change in aging and their associations with cognition and Alzheimer's disease biomarkers

Structural brain changes underlie cognitive changes and interindividual variability in cognition in older age. By using structural MRI data-driven clustering, we aimed to identify subgroups of cognitively unimpaired older adults based on brain change patterns and assess how changes in cortical thickness, surface area, and subcortical volume relate to cognitive change. We tested (1) which brain structural changes predict cognitive change (2) whether these are associated with core cerebrospinal fluid (CSF) Alzheimer's disease biomarkers, and (3) the degree of overlap between clusters derived from different structural modalities in 1899 cognitively healthy older adults followed up to 16 years. We identified four groups for each brain feature, based on the degree of a main longitudinal component of decline. The minimal overlap between features suggested that each contributed uniquely and independently to structural brain changes in aging. Cognitive change and baseline cognition were associated with cortical area change, whereas higher baseline levels of phosphorylated tau and amyloid-β related to changes in subcortical volume. These results may contribute to a better understanding of different aging trajectories.

Changes in degree centrality and its associated genes: A longitudinal study of patients with schizophrenia undergoing pharmacological treatment

BACKGROUND

The role of degree centrality (DC) in schizophrenia (SCZ), its trajectory following pharmacological treatment, and its potential as a prognostic biomarker and genetic mechanism remain unclear.

METHODS

We recruited 51 healthy controls (HC) and 56 patients with SCZ. Additionally, the SCZ patients underwent three months of antipsychotic medication treatment. We collected resting-state functional magnetic resonance imaging data, clinical variables, and conducted analyses using support vector machines, support vector regression, and gene expression correlation analysis.

RESULTS

Our study revealed that SCZ patients had generally reduced DC values in the cerebral cortex compared to HC at baseline, with increased DC values observed in the left occipital gyrus. After three months of treatment, SCZ patients exhibited a significant decrease in DC values in the left fusiform gyrus and an increase in the left inferior parietal gyrus. Variations in DC values in SCZ patients were associated with multiple genes, primarily enriched in molecular functions.

CONCLUSION

Changes in DC values in the right inferior occipital/fusiform gyrus and right calcarine/middle occipital gyrus may serve as neuroimaging markers to differentiate between HC and SCZ patients. Additionally, DC values in the left middle/postcentral gyrus could be used to predict treatment outcomes. Transcriptome-neuroimaging spatial correlation analysis provides valuable insights into the neurobiological mechanisms underlying SCZ pathology.

Causal association of sarcopenia-related traits with brain cortical structure: a bidirectional Mendelian randomization study

BACKGROUND

Patients with sarcopenia often experience cognitive decline, affecting cortical structures, but the causal link remains unclear. We used bidirectional Mendelian randomization (MR) to explore the relationship between sarcopenia-related traits and cortical structure.

METHODS

We selected genetic variables from genome-wide association study data. Three different MR methods were used: inverse-variance weighted analysis, MR-Egger regression, and the weighted median test. For significant estimates, we further conducted Cochran's Q test, MR-Egger intercept test, leave-one-out analyses, and MR-PRESSO to assess heterogeneity.

RESULTS

In forward MR analysis, appendicular lean mass (ALM) decreased the thickness (TH) of lateral occipital gyrus and increased the TH of pars opercularis gyrus (β = -0.0079 mm, 95% CI: -0.0117 mm to -0.0041 mm, P < 0.0001; β = 0.0080 mm, 95% CI: 0.0042 mm to 0.0117 mm, P < 0.0001). In reverse MR analysis, a significant negative correlation was found between the TH of bankssts and ALM, while positive correlations were observed between the TH of frontal pole, rostral anterior cingulate, temporal pole, and ALM. The TH of temporal pole was positively correlated with right hand grip strength (HGS-R) (β = 0.1596 mm, 95% CI: 0.1349 mm to 0.1843 mm, P < 0.0001), and the TH of pars triangularis was positively correlated with left-hand grip strength (HGS-L) (β = 0.3251 mm, 95% CI: 0.2339 mm to 0.4163 mm, P < 0.0001).

CONCLUSIONS

Sarcopenia-related traits and cortical structure have bidirectional effects, supporting the muscle-brain axis theory. This links sarcopenia to neurocognitive diseases and provides new strategies for the prevention and intervention of both sarcopenia and cognitive decline.

NeuroDISK: An AI Approach to Automate Continuous Inquiry-Driven Discoveries in Neuroimaging Genetics

Collaborative and multi-site neuroimaging studies have greatly accelerated the rate at which new and existing data can be aggregated to answer a neuroscientific question. New research initiatives are continuously collecting more data, allowing opportunities to refine previous published findings through continuous and dynamic updates. Yet, we lack a practical framework for researchers to systematically, automatically, and continuously update published findings. We developed NeuroDISK, an automated artificial intelligence based framework that: 1) performs automated and inquiry-driven analyses, and 2) continuously updates these analyses as new data becomes available. NeuroDISK was evaluated using published results from the ENIGMA consortium's work on the genetic architecture of the cerebral cortex. We incorporate both meta-analysis and meta-regression options to showcase our framework on the effect of specific genotypes and moderators on select brain regions. Initial NeuroDISK meta-analysis results replicate the original publication, and we show result updates after adding new data. The NeuroDISK framework can be generalized for users to define question(s), run corresponding workflow(s) and access results interactively and continuously.

Copy number variants and the tangential expansion of the cerebral cortex

The tangential expansion of the human cerebral cortex, indexed by its surface area (SA), occurs mainly during prenatal and early postnatal periods, and is influenced by genetic factors. Here we investigate the role of rare copy number variants (CNVs) in shaping SA, and the underlying mechanisms, by aggregating CNVs across the genome in community-based cohorts (N = 39,015). We reveal that genome-wide CNV deletions and duplications are associated with smaller SA. Subsequent analyses with gene expression in fetal cortex suggest that CNVs influence SA by interrupting the proliferation of neural progenitor cells during fetal development. Notably, the deletion of genes with strong (but not weak) coexpression with neural progenitor genes is associated with smaller SA. Follow up analyses reveal similar mechanisms at play in three clinical CNVs, 1q21.1, 16p11.2 and 22q11.2. Together, this study of rare CNVs expands our knowledge about genetic architecture of human cerebral cortex.

ATR-hippo drives force signaling to nuclear F-actin and links mechanotransduction to neurological disorders

The mechanical environment is sensed through cell-matrix contacts with the cytoskeleton, but how signals transit the nuclear envelope to affect cell fate decisions remains unknown. Nuclear actin coordinates chromatin motility during differentiation and genome maintenance, yet it remains unclear how nuclear actin responds to mechanical force. The DNA-damage kinase ataxia telangiectasia and Rad3-related protein (ATR) translocates to the nuclear envelope to protect the nucleus during cell motility or compression. Here, we show that ATR drives nuclear actin assembly via recruitment of Filamin-A to the inner nuclear membrane through binding of the hippo pathway scaffold and ATR substrate, RASSF1A. Moreover, we demonstrate how germline RASSF1 mutation disables nuclear mechanotransduction resulting in cerebral cortex thinning and associates with common psychological traits. Thus, defective mechanical-regulated pathways may contribute to complex neurological disorders.

Causal association of long COVID with brain structure changes: Findings from a 2-sample Mendelian randomization study

Nearly 7.5% U.S. adults have long COVID. Recent epidemiological studies indicated that long COVID, is significantly associated with subsequent brain structure changes. However, it remains unknown if long COVID is causally associated with brain structure change. Here we applied two Mendelian Randomization (MR) methods - Inverse Variance Weighting MR method (IVW) for correlated instrument variables and Component analysis-based Generalized Method of Moments (PC-GMM) - to examine the potential causal relationships from long COVID to brain structure changes. The MR study was based on an instrumental variable analysis of data from a recent long COVID genome-wide association study (GWAS) (3,018 cases and 994,582 controls), the Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA) (Global and regional cortical measures, N = 33,709; combined hemispheric subcortical volumes, N = 38,851), and UK Biobank (left/right subcortical volumes, N = 19,629). We found no significant causal relationship between long COVID and brain structure changes. As we gain more insights into long COVID and its long-term health outcomes, future works are necessary to validate our findings and understand the mechanisms underlying the observed associations, though not causal, of long COVID with subsequent brain structure changes.

Reevaluating the Role of Education in Cognitive Decline and Brain Aging: Insights from Large-Scale Longitudinal Cohorts across 33 Countries

Why education is linked to higher cognitive function in aging is fiercely debated. Leading theories propose that education reduces brain decline in aging, enhances tolerance to brain pathology, or that it does not affect cognitive decline but rather reflects higher early-life cognitive function. To test these theories, we analyzed 407.356 episodic memory scores from 170.795 participants > 50 years, alongside 15.157 brain MRIs from 6.472 participants across 33 Western countries. More education was associated with better memory, larger intracranial volume and slightly larger volume of memory-sensitive brain regions. However, education did not protect against age-related decline or weakened effects of brain decline on cognition. The most parsimonious explanation for the results is that the associations reflect factors present early in life, including propensity of individuals with certain traits to pursue more education. While education has numerous benefits, the notion that it provides protection against cognitive or brain decline is not supported.

Genetic and neurochemical profiles underlying cortical morphometric vulnerability to Parkinson's disease

BACKGROUND

Increasing evidence has documented cortical involvement at all stages of PD. The local vulnerabilities within certain brain regions in PD have been previously demonstrated, whereas its underlying genetic and neurochemical factors remain unclear. This study aims to investigate the spatial spectrum of cortical atrophy in Parkinson's disease (PD) and link these variances in gray matter properties and curvature respectively to putative molecular pathways and neurotransmitter factors.

METHODS

We recruited 141 clinically diagnosed PD patients and 70 healthy controls. Cortical morphological abnormalities of PD were obtained by intergroup comparisons in gray matter properties metrics and curvature measurements. Then we performed gene-category enrichment and spatial correlation analyses to evaluate the specific correspondence between cortical alteration in PD and genetic expression from the Allen Human Brain Atlas and normative neurotransmitter atlases from Neuromaps.

RESULTS

We found decreased gray matter properties in temporal, somatomotor, cingulate and occipital cortices, decreased curvature measures in occipital, temporal and orbitofrontal cortices, and increased curvature measures in somatomotor, prefrontal and posterior parietal cortices for PD patients. The related genes were enriched for the glucose metabolism, mitochondrial function, and post-translational histone modifications processes. In addition, the serotonin and norepinephrine transporter devoted more to gray matter properties alterations while the dopamine, gamma-aminobutyric acid receptors, and norepinephrine transporter were strong contributors of curvature abnormalities in PD.

CONCLUSIONS

Collectively, the present study offered interpretation of cortical morphological alterations and the cortical pathogenic theory in PD from genetic and neurochemical perspectives, which inspire further research on new pharmacotherapeutic approaches.

Just a SNP away: The future of in vivo massively parallel reporter assay

The human genome is largely noncoding, yet the field is still grasping to understand how noncoding variants impact transcription and contribute to disease etiology. The massively parallel reporter assay (MPRA) has been employed to characterize the function of noncoding variants at unprecedented scales, but its application has been largely limited by the in vitro context. The field will benefit from establishing a systemic platform to study noncoding variant function across multiple tissue types under physiologically relevant conditions. However, to date, MPRA has been applied to only a handful of in vivo conditions. Given the complexity of the central nervous system and its widespread interactions with all other organ systems, our understanding of neuropsychiatric disorder-associated noncoding variants would be greatly advanced by studying their functional impact in the intact brain. In this review, we discuss the importance, technical considerations, and future applications of implementing MPRA in the in vivo space with the focus on neuropsychiatric disorders.

Reevaluating the Role of Education in Cognitive Decline and Brain Aging: Insights from Large-Scale Longitudinal Cohorts across 33 Countries

Why education is linked to higher cognitive function in aging is fiercely debated. Leading theories propose that education reduces brain decline in aging, enhances tolerance to brain pathology, or that it does not affect cognitive decline but rather reflects higher early-life cognitive function. To test these theories, we analyzed 407.356 episodic memory scores from 170.795 participants >50 years, alongside 15.157 brain MRIs from 6.472 participants across 33 Western countries. More education was associated with better memory, larger intracranial volume and slightly larger volume of memory-sensitive brain regions. However, education did not protect against age-related decline or weakened effects of brain decline on cognition. The most parsimonious explanation for the results is that the associations reflect factors present early in life, including propensity of individuals with certain traits to pursue more education. While education has numerous benefits, the notion that it provides protection against cognitive or brain decline is not supported.

The X chromosome's influences on the human brain

Genes on the X chromosome are extensively expressed in the human brain. However, little is known for the X chromosome's impact on the brain anatomy, microstructure, and functional networks. We examined 1045 complex brain imaging traits from 38,529 participants in the UK Biobank. We unveiled potential autosome-X chromosome interactions while proposing an atlas outlining dosage compensation for brain imaging traits. Through extensive association studies, we identified 72 genome-wide significant trait-locus pairs (including 29 new associations) that share genetic architectures with brain-related disorders, notably schizophrenia. Furthermore, we found unique sex-specific associations and assessed variations in genetic effects between sexes. Our research offers critical insights into the X chromosome's role in the human brain, underscoring its contribution to the differences observed in brain structure and functionality between sexes.

Causal relationships between hippocampal volumetric traits and the risk of Alzheimer's disease: a Mendelian randomization study

Alzheimer's disease, a common and progressive neurodegenerative disorder, is associated with alterations in hippocampal volume, as revealed by neuroimaging research. However, the causal links between the volumes of the hippocampus and its subfield structures with Alzheimer's disease remain unknown. A genetic correlation analysis using linkage disequilibrium score regression was conducted to identify hippocampal volumetric traits linked to Alzheimer's disease. Following this, to examine the causal links between Alzheimer's disease and hippocampal volumetric traits, we applied a two-sample Mendelian randomization approach, utilizing a bidirectional framework. Seven hippocampal volumetric traits were found as genetically correlated with Alzheimer's disease in the genetic correlation analysis and were then included in the Mendelian randomization analyses. Inverse variance weighted Mendelian randomization analyses revealed that increased volumes in the left whole hippocampus, left hippocampal body, right presubiculum head and right cornu ammonis 1 head were causally related to higher risks of Alzheimer's disease. Conversely, a higher risk of Alzheimer's disease was causally associated with decreased volumes of the left hippocampal body and left whole hippocampus. These results were validated through other Mendelian randomization approaches and sensitivity analysis. Our findings uncover bidirectional causal relationships between Alzheimer's disease and hippocampal volumetric traits, suggesting not only the potential significance of these traits in predicting Alzheimer's disease but also the reciprocal influence of Alzheimer's disease on hippocampal volumes.

Genetic Associations between Obesity and Brain Cortical Thickness: Combined Genetic Correlation, Multi-Trait Meta-Analysis, and Mendelian Randomization

INTRODUCTION

Obesity may lead to cognitive impairment and neuropsychiatric disorders, which are associated with changes in the brain cortical structure, particularly in cortical thickness. However, the exact genetic association between obesity and brain cortical thickness remains inconclusive. We aimed to identify the relationship between obesity-related traits (body mass index [BMI], waist-hip ratio [WHR], and waist-hip ratio adjusted for BMI [WHRadjBMI]) and brain cortical thickness.

METHODS

Leveraging summary statistics of large-scale GWAS(s) conducted in European-ancestry populations on BMI (N = 806,834), WHR (N = 697,734), WHRadjBMI (N = 694,649), and brain cortex thickness (N = 33,709), we performed GWAS combining genetic correlation, multi-trait meta-analysis, and Mendelian randomization analysis.

RESULTS

Our findings revealed a strong genetic correlation between BMI and brain cortical thickness (rg = -0.0542, p = 0.0435), and a significant result was also observed for WHR and brain thickness (rg = -0.0744, p = 0.009). In addition, we identified three loci between obesity-related traits. Mendelian randomization analysis supported the causal role of BMI (inverse-variance-weighted [IVW] beta = -0.006, 95% CI = -0.011 to -3.85E-04; weighted median beta = -0.006, 95% CI = -0.013 to -0.002), WHR (IVW beta = -0.011, 95% CI = -0.018 to -0.005; weighted median beta = -0.008, 95% CI = -0.018 to -0.003), and WHRadjBMI (IVW beta = 0.011, 95% CI = -0.018 to -0.005; weighted median beta = -0.008, 95% CI = -0.018 to -0.002) in brain cortical thickness.

CONCLUSION

This study has shown that genetically predicted obesity-related traits have a causal relationship with reduced cortical thickness. These findings provide genetic evidence for a link between obesity and structural changes in the brain and suggest that obesity may be associated with neuropsychiatric disorders by affecting brain structure, particularly cortical thickness.

Case Report: Clinical awareness about the effect of laser interstitial thermal therapy on pediatric high-grade brain tumors after radiotherapy

The use of magnetic resonance-guided laser interstitial thermal therapy (LITT) for the treatment of brain tumors and epileptic lesions has increased in the field of pediatric neurosurgery. However, very little is known about the effect of LITT on pediatric high-grade tumors that have been previously treated with radiotherapy. We report on two cases of children with an unexpected rapid brain tumor progression after LITT. The first case was an 11-year-old boy with a periventricular metastasis of a recurrent anaplastic ependymoma treated with proton-therapy and radiosurgery. The second case was a 6-year-old girl with a Lynch-syndrome and a recurrence of a mesio-temporo-occipital high-grade glioma admitted to gross total resection, proton-therapy, chemotherapy, bevacizumab and immune checkpoint inhibitor. Due to evidence of tumor progression in both cases, a decision was made to perform LITT. Shortly after the laser ablation, we observed a significant tumor growth along the trajectory of the LITT catheters, accompanied by clinical deterioration. The effect of LITT on pediatric ependymoma and high-grade glioma recurrence after radiotherapy is still unclear. The tumor expansion following LITT in these two patients should drive a deeper awareness of the effect of radiation and LITT on the tumor-environment. The breakage of the morphogenetic boundaries of the neuromeres, to which each tumor was initially confined, through the placement of the LITT catheters should be considered while trying to understand the disease spread mechanisms. Based on the experience of our center, we advise a careful implementation of this technique on pediatric high-grade central nervous system tumors, particularly in recurrent tumors that were previously treated with radiotherapy, until the underlying pathophysiologic mechanism has been better understood.

Cerebral cortex changes in FD, IBS, and GERD: A Mendelian randomization study

BACKGROUND

Prospective and cross-sectional studies have reported an association between functional gastrointestinal disorders and anxiety and depression. However, the causal relationship remains uncertain. To clarify this, we utilized Mendelian randomization (MR) to assess the causal effects of common gastrointestinal disorders on cortical structures.

METHODS

Genome-wide association study (GWAS) data was gathered for functional dyspepsia (FD), irritable bowel syndrome (IBS), and gastroesophageal reflux disease (GERD) from European populations numbering 329,262, 16,792, and 602,604, respectively. GWAS cerebral cortical architecture data for cortical thickness (TH) and surface area (SA) were obtained from 51,665 MRI scans. MR was used to analyze the casual relationship between FD, IBS, GERD, and cortical structures. Inverse-variance weighted, weighted median, and MR-Egger tests were performed as assessment indicators. We also evaluated heterogeneity and pleiotropy.

RESULTS

FD significantly decreases the TH in the rostral anterior cingulate cortex (βTH = -0.022 mm; 95%CI: -0.035 mm to -0.009 mm2; PTH = 6.89 × 10-4), and IBS significantly decreases the SA of the pars triangularis (βSA = -21.91 mm2; 95%CI: -32.99 mm to -10.83 mm2; PSA = 1.06 × 10-4), precuneus (βSA = -47.53 mm2; 95%CI: -73.57 mm to-21.48 mm2; PSA = 3.48 × 10-4) and superior frontal regions (βSA = -78.70 mm2; 95%CI: -122.61 mm to -34.78 mm2; PSA = 4.4 × 10-4). At the local functional level, GERD significantly increases the SA of the inferior temporal region (βSA = -113.58 mm2, 95%CI: -113.58 mm to -39.01 mm2, PSA = 6.05 × 10-5).

CONCLUSIONS

FD, IBS and GERD can affect the cerebral cortex architecture through the brain-gut axis, potentially increasing the risks of mental illness and cognitive impairment.

Genetically predicted brain cortical structure mediates the causality between insulin resistance and cognitive impairment

Background

Insulin resistance is tightly related to cognition; however, the causal association between them remains a matter of debate. Our investigation aims to establish the causal relationship and direction between insulin resistance and cognition, while also quantifying the mediating role of brain cortical structure in this association.

Methods

The publicly available data sources for insulin resistance (fasting insulin, homeostasis model assessment beta-cell function and homeostasis model assessment insulin resistance, proinsulin), brain cortical structure, and cognitive phenotypes (visual memory, reaction time) were obtained from the MAGIC, ENIGMA, and UK Biobank datasets, respectively. We first conducted a bidirectional two-sample Mendelian randomization (MR) analysis to examine the susceptibility of insulin resistance on cognitive phenotypes. Additionally, we applied a two-step MR to assess the mediating role of cortical surficial area and thickness in the pathway from insulin resistance to cognitive impairment. The primary Inverse-variance weighted, accompanied by robust sensitivity analysis, was implemented to explore and verify our findings. The reverse MR analysis was also performed to evaluate the causal effect of cognition on insulin resistance and brain cortical structure.

Results

This study identified genetically determined elevated level of proinsulin increased reaction time (beta=0.03, 95% confidence interval [95%CI]=0.01 to 0.05, p=0.005), while decreasing the surface area of rostral middle frontal (beta=-49.28, 95%CI=-86.30 to -12.27, p=0.009). The surface area of the rostral middle frontal mediated 20.97% (95%CI=1.44% to 40.49%) of the total effect of proinsulin on reaction time. No evidence of heterogeneity, pleiotropy, or reverse causality was observed.

Conclusions

Briefly, our study noticed that elevated level of insulin resistance adversely affected cognition, with a partial mediation effect through alterations in brain cortical structure.

Putative epicenters identified by transcriptome-neuromorphic interactions in attention-deficit/hyperactivity disorder biotypes

Attention-deficit hyperactivity disorder (ADHD) is a heterogenous behavioral disorder with inattention, hyperactivity and impulsivity symptoms, indicating the important implication of identifying biotypes and its epicenters in understanding disease's pathogenesis. The study investigated the neuromorphic heterogeneity relating to transcriptional similarity architecture in ADHD, and further analyzed the epicenters of network-spreading in each ADHD biotype and their correlations with clinical characteristics. Individuals with ADHD could be identified into two discriminative biotypes that exhibited distinct neuromorphic aberrances. As increased regional cortical thickness deviation in ADHD, the first component of partial least squares (PLS1) positively weighted genes were over-expressed, whereas PLS1 negatively weighted genes were under-expressed as its reduction. Both ADHD biotypes exhibited distinct disease epicenters that distributed in cognitive control and attention networks with significantly heterogeneous characteristics, holding promise for advancing our understanding, and ultimately the treatment, of ADHD. Overall, our findings identified two discriminative biotypes and its epicenters in ADHD, promoting the understanding of underlying transcriptome-neuroimaging relationships.

Revealing potential drug targets in schizophrenia through proteome-wide Mendelian randomization genetic insights

BACKGROUND

Schizophrenia (SCZ) is a severe, chronic mental disorder with no current cure. Identifying novel pharmacological targets is crucial for developing more effective treatments.

METHODS

We performed two-sample Mendelian randomization (MR) analyses to estimate the associations between cerebrospinal fluid (CSF) containing 154 proteins and plasma containing 734 proteins and risk of SCZ. Bidirectional MR analysis, steiger filtering, bayesian colocalization, phenotypic scanning, and validation analysis were examined to validate the assumptions of MR. For proteins significantly associated with SCZ identified by MR, we explored their potential impact on brain structures, including cortical surface area (SA), thickness (TH), and the volume of subcortical structures.

RESULTS

MR analysis identified 13 protein-SCZ pairs at Bonferroni significance (P < 5.63 × 10-5). Notably, the genetically proxied protein level of neuromedin B (NMB) was associated with an increased risk for SCZ (odds ratio [OR] = 1.41; 95 % CI, 1.27 to 1.58; P = 6.68 × 10-10). Bayesian colocalization suggested that NMB shares genetic variations with SCZ. Further, NMB interacts with target proteins of current SCZ drugs and was validated in the UK Biobank. The genetically proxied NMB was positively associated with an increase in the surface area (SA) of the parahippocampal gyrus (β = 8.93 mm2, 95 % CI, 1.58 to 16.3, P = .02). Additionally, an increase in the genetically proxied SA of the parahippocampal gyrus was inversely associated with the risk of SCZ (OR = 0.996, 95 % CI, 0.993 to 0.999, P = .04).

CONCLUSIONS

The findings suggest that NMB may represent a promising target for pharmacological intervention in SCZ. This warrants further investigation into the specific constituents involved, which could have potential for follow-up studies.