The genetic architecture of the human cerebral cortex

Associations of hearing loss and structural changes in specific cortical regions: a Mendelian randomization study

INTRODUCTION

Previous studies have suggested a correlation between hearing loss (HL) and cortical alterations, but the specific brain regions that may be affected are unknown.

METHODS

Genome-wide association study (GWAS) data for 3 subtypes of HL phenotypes, sensorineural hearing loss (SNHL), conductive hearing loss, and mixed hearing loss, were selected as exposures, and GWAS data for brain structure-related traits were selected as outcomes. The inverse variance weighted method was used as the main estimation method.

RESULTS

Negative associations were identified between genetically predicted SNHL and brain morphometric indicators (cortical surface area, cortical thickness, or volume of subcortical structures) in specific brain regions, including the bankssts (β = -0.006 mm, P = 0.016), entorhinal cortex (β = -4.856 mm2, P = 0.029), and hippocampus (β = -24.819 cm3, P = 0.045), as well as in brain regions functionally associated with visual perception, including the pericalcarine (β = -10.009 cm3, P = 0.013).

CONCLUSION

Adaptive changes and functional remodeling of brain structures occur in patients with genetically predicted HL. Brain regions functionally associated with auditory perception, visual perception, and memory function are the main brain regions vulnerable in HL.

The causal effect of sarcopenia-associated traits on brain cortical structure: A Mendelian randomization study

BACKGROUND

Previous observational studies have reported sarcopenia can affect the structure and function of brain cortical structure. However, the causality inferred from those studies was subjected to residual confounding and reverse causation. Herein, we use a two-sample Mendelian randomization (MR) analysis to illustrate the causal effect of sarcopenia-associated traits on brain cortical structure.

METHODS

We selected appendicular lean mass (ALM), hand grip strength (left and right) (HGSL and HGSR), and usual walking pace (UWP) to symbolize sarcopenia. The definition of brain cortical structure is human brain cortical surface area (SA) and cortical thickness (TH) globally and in 34 functional regions measured by magnetic resonance imaging. Instrumental variables at the genome-wide significance level were obtained from publicly available datasets, and inverse variance weighted as the primary method was used for MR analysis.

RESULT

At the global level, we found ALM (β=2604.68, 95 % confidence interval (CI): 1886.17 to 3323.19, P = 1.20 × 10-12) and HGSR (β=4733.05, 95 % CI: 2245.08 to 7221.01, P = 1.93 × 10-4) were associated with increased SA. At the region level, the SA of 25 functional gyrus without global weighted was influenced by ALM. The HGSR significantly increased SA of medial orbitofrontal and precentral gyrus without global weighted and ALM was associated with decrease of TH of lateral occipital gyrus with global weighted. No pleiotropy was detected.

CONCLUSION

This was the first MR study investigated the causal effect of sarcopenia-associated traits on brain cortical structure. In our study, we revealed genetically predicted sarcopenia-associated traits including ALM and HGSR could affect brain cortical structure.

Neuroimaging genomics as a window into the evolution of human sulcal organization

Primate brain evolution has involved prominent expansions of the cerebral cortex, with largest effects observed in the human lineage. Such expansions were accompanied by fine-grained anatomical alterations, including increased cortical folding. However, the molecular bases of evolutionary alterations in human sulcal organization are not yet well understood. Here, we integrated data from recently completed large-scale neuroimaging genetic analyses with annotations of the human genome relevant to various periods and events in our evolutionary history. These analyses identified single-nucleotide polymorphism (SNP) heritability enrichments in fetal brain human-gained enhancer (HGE) elements for a number of sulcal structures, including the central sulcus, which is implicated in human hand dexterity. We zeroed in on a genomic region that harbors DNA variants associated with left central sulcus shape, an HGE element, and genetic loci involved in neurogenesis including ZIC4, to illustrate the value of this approach for probing the complex factors contributing to human sulcal evolution.

Transcriptomic Similarity Informs Neuromorphic Deviations in Depression Biotypes

BACKGROUND

Major depressive disorder (MDD) is complicated by population heterogeneity, motivating the investigation of biotypes through imaging-derived phenotypes. However, neuromorphic heterogeneity in MDD remains unclear, and how the correlated gene expression (CGE) connectome constrains these neuromorphic anomalies in MDD biotypes has not yet been studied.

METHODS

Here, we related cortical thickness deviations in MDD biotypes to a pattern of CGE connectome. Cortical thickness was estimated from 3-dimensional T1-weighted magnetic resonance images in 2 independent cohorts (discovery cohort: N = 425; replication cohort: N = 217). The transcriptional activity was measured according to Allen Human Brain Atlas. A density peak-based clustering algorithm was used to identify MDD biotypes.

RESULTS

We found that patients with MDD were clustered into 2 replicated biotypes based on single-patient regional deviations from healthy control participants across 2 datasets. Biotype 1 mainly exhibited cortical thinning across the brain, whereas biotype 2 mainly showed cortical thickening in the brain. Using brainwide gene expression data, we found that deviations of transcriptionally connected neighbors predicted regional deviation for both biotypes. Furthermore, putative CGE-informed epicenters of biotype 1 were concentrated on the cognitive control circuit, whereas biotype 2 epicenters were located in the social perception circuit. The patterns of epicenter likelihood were separately associated with depression- and anxiety-response maps, suggesting that epicenters of MDD biotypes may be associated with clinical efficacies.

CONCLUSIONS

Our findings linked the CGE connectome and neuromorphic deviations to identify distinct epicenters in MDD biotypes, providing insight into how microscale gene expressions informed MDD biotypes.

Bridging the gap: improving correspondence between low-field and high-field magnetic resonance images in young people

Background

Portable low-field-strength magnetic resonance imaging (MRI) systems represent a promising alternative to traditional high-field-strength systems with the potential to make MR technology available at scale in low-resource settings. However, lower image quality and resolution may limit the research and clinical potential of these devices. We tested two super-resolution methods to enhance image quality in a low-field MR system and compared their correspondence with images acquired from a high-field system in a sample of young people.

Methods

T1- and T2-weighted structural MR images were obtained from a low-field (64mT) Hyperfine and high-field (3T) Siemens system in N = 70 individuals (mean age = 20.39 years, range 9-26 years). We tested two super-resolution approaches to improve image correspondence between images acquired at high- and low-field: (1) processing via a convolutional neural network ('SynthSR'), and (2) multi-orientation image averaging. We extracted brain region volumes, cortical thickness, and cortical surface area estimates. We used Pearson correlations to test the correspondence between these measures, and Steiger Z tests to compare the difference in correspondence between standard imaging and super-resolution approaches.

Results

Single pairs of T1- and T2-weighted images acquired at low field showed high correspondence to high-field-strength images for estimates of total intracranial volume, surface area cortical volume, subcortical volume, and total brain volume (r range = 0.60-0.88). Correspondence was lower for cerebral white matter volume (r = 0.32, p = 0.007, q = 0.009) and non-significant for mean cortical thickness (r = -0.05, p = 0.664, q = 0.664). Processing images with SynthSR yielded significant improvements in correspondence for total brain volume, white matter volume, total surface area, subcortical volume, cortical volume, and total intracranial volume (r range = 0.85-0.97), with the exception of global mean cortical thickness (r = 0.14). An alternative multi-orientation image averaging approach improved correspondence for cerebral white matter and total brain volume. Processing with SynthSR also significantly improved correspondence across widespread regions for estimates of cortical volume, surface area and subcortical volume, as well as within isolated prefrontal and temporal regions for estimates of cortical thickness.

Conclusion

Applying super-resolution approaches to low-field imaging improves regional brain volume and surface area accuracy in young people. Finer-scale brain measurements, such as cortical thickness, remain challenging with the limited resolution of low-field systems.

Intrauterine growth and the tangential expansion of the human cerebral cortex in times of food scarcity and abundance

Tangential growth of the human cerebral cortex is driven by cell proliferation during the first and second trimester of pregnancy. Fetal growth peaks in mid-gestation. Here, we explore how genes associated with fetal growth relate to cortical growth. We find that both maternal and fetal genetic variants associated with higher birthweight predict larger cortical surface area. The relative dominance of the maternal vs. fetal variants in these associations show striking variations across birth years (1943 to 1966). The birth-year patterns vary as a function of the epigenetic status near genes differentially methylated in individuals exposed (or not) to famine during the Dutch Winter of 1944/1945. Thus, it appears that the two sets of molecular processes contribute to early cortical development to a different degree in times of food scarcity or its abundance.

Cortical structure and the risk of amyotrophic lateral sclerosis: A bidirectional Mendelian randomization study

BACKGROUND

Current observational studies indicate progressive brain atrophy is closely associated with the clinical feature of amyotrophic lateral sclerosis. However, it is unclear whether the changes in cortical structure are the cause or result of ALS. Our study aimed to investigate the causal relationship between cortical structure and ALS risk using a bidirectional two-sample MR study.

METHODS

We collected publicly available genome-wide association studies' summary statistics for cortical structure from UK Biobank and ENIGMA consortium (n = 33,992) and ALS from the Project MinE (n = 138,086). We used the inverse variance weighted method (IVW) as primary analysis in order to evaluate the causal effects. In addition, the weighted median and MR Egger methods were performed to ensure the robustness and reliability of the IVW results.

RESULTS

We found the decreased surface of the paracentral lobule and thickness of the frontal pole and middle temporal lobe were suggestively associated with an increased risk of ALS as well as the increased surface of medial orbitofrontal and middle temporal lobe. In another aspect, the causalities between the susceptibility to ALS and the volume of the transverse temporal gyrus and superior temporal gyrus were negative. Besides, the susceptibility to ALS might also contribute to an increased thickness of the postcentral gyrus and superior parietal gyrus.

CONCLUSION

In this two-sample MR analysis, we observed that multiple cortical brain regions are associated with a higher ALS risk. Further research into the underlying mechanisms is required to back up our findings.

Dissociation of Reliability, Heritability, and Predictivity in Coarse- and Fine-Scale Functional Connectomes during Development

The functional connectome supports information transmission through the brain at various spatial scales, from exchange between broad cortical regions to finer-scale, vertex-wise connections that underlie specific information processing mechanisms. In adults, while both the coarse- and fine-scale functional connectomes predict cognition, the fine scale can predict up to twice the variance as the coarse-scale functional connectome. Yet, past brain-wide association studies, particularly using large developmental samples, focus on the coarse connectome to understand the neural underpinnings of individual differences in cognition. Using a large cohort of children (age 9-10 years; n = 1,115 individuals; both sexes; 50% female, including 170 monozygotic and 219 dizygotic twin pairs and 337 unrelated individuals), we examine the reliability, heritability, and behavioral relevance of resting-state functional connectivity computed at different spatial scales. We use connectivity hyperalignment to improve access to reliable fine-scale (vertex-wise) connectivity information and compare the fine-scale connectome with the traditional parcel-wise (coarse scale) functional connectomes. Though individual differences in the fine-scale connectome are more reliable than those in the coarse-scale, they are less heritable. Further, the alignment and scale of connectomes influence their ability to predict behavior, whereby some cognitive traits are equally well predicted by both connectome scales, but other, less heritable cognitive traits are better predicted by the fine-scale connectome. Together, our findings suggest there are dissociable individual differences in information processing represented at different scales of the functional connectome which, in turn, have distinct implications for heritability and cognition.

Systolic blood pressure is associated with abnormal alterations in brain cortical structure: Evidence from a Mendelian randomization study

BACKGROUND

Hypertension has been recognized as a significant risk factor for cerebrovascular diseases and cognitive decline. However, the specific impact of hypertension, systolic/diastolic blood pressure, pulse pressure (PP) and mean arterial pressure (MAP) on brain cortical structure remains unclear. Mendelian randomization (MR) provides a robust approach to investigate the causal relationship between blood pressure components and brain cortical changes.

METHODS

In this MR study, data from large-scale genome-wide association studies for blood pressure components and neuroimaging were utilized to conduct our analyses. We leveraged genetic variants associated specifically with hypertension (122,620 cases and 332,683 controls), systolic (469,767 individuals), diastolic (490,469 individuals) blood pressure, PP (810,865 individuals) and MAP (over 1 million individuals) to evaluate their effects on brain cortex surficial area (51,665 individuals) and cortex thickness (51,665 individuals).

RESULTS

Our findings revealed a significant correlation between systolic blood pressure and abnormal reduction in brain cortex surficial area (β=-1330.69, 95% confident interval [CI]: -2655.35 to -6.02, p = 0.0489); however, no significant relationship was found between systolic blood pressure and brain cortex thickness (β=-0.0078, 95% CI: -0.0178 to 0.0022, p = 0.1287). Additionally, no significant associations were observed between hypertension (β=-200.05, p = 0.6884; β=-0.0051, p = 0.1179, respectively), diastolic blood pressure (β=-460.63, p = 0.5160; β=0.0047, p = 0.2448, respectively), PP (β=1041.84, p = 0.3725; β=-0.0112, p = 0.2212, respectively), MAP (β=-18.84, p = 0.8841; β=0.0002, p = 0.7654, respectively) and both brain cortex surficial area and brain cortex thickness.

CONCLUSION

Our MR study provides evidence supporting the hypothesis that systolic blood pressure, rather than diastolic blood pressure, PP or MAP, is associated with abnormal changes in brain cortical structure.

Neurogenetic and multi-omic sources of overlap among sensation seeking, alcohol consumption, and alcohol use disorder

Sensation seeking is bidirectionally associated with levels of alcohol consumption in both adult and adolescent samples, and shared neurobiological and genetic influences may in part explain these associations. Links between sensation seeking and alcohol use disorder (AUD) may primarily manifest via increased alcohol consumption rather than through direct effects on increasing problems and consequences. Here the overlap among sensation seeking, alcohol consumption, and AUD was examined using multivariate modelling approaches for genome-wide association study (GWAS) summary statistics in conjunction with neurobiologically informed analyses at multiple levels of investigation. Meta-analytic and genomic structural equation modelling (GenomicSEM) approaches were used to conduct GWAS of sensation seeking, alcohol consumption, and AUD. Resulting summary statistics were used in downstream analyses to examine shared brain tissue enrichment of heritability and genome-wide evidence of overlap (e.g., stratified GenomicSEM, RRHO, genetic correlations with neuroimaging phenotypes), and to identify genomic regions likely contributing to observed genetic overlap across traits (e.g., H-MAGMA and LAVA). Across approaches, results supported shared neurogenetic architecture between sensation seeking and alcohol consumption characterised by overlapping enrichment of genes expressed in midbrain and striatal tissues and variants associated with increased cortical surface area. Alcohol consumption and AUD evidenced overlap in relation to variants associated with decreased frontocortical thickness. Finally, genetic mediation models provided evidence of alcohol consumption mediating associations between sensation seeking and AUD. This study extends previous research by examining critical sources of neurogenetic and multi-omic overlap among sensation seeking, alcohol consumption, and AUD which may underlie observed phenotypic associations.

Mangiferin alleviates 6-OHDA-induced Parkinson's disease by inhibiting AKR1C3 to activate Wnt signaling pathway

Parkinson's disease (PD) is a neurodegenerative disorder with a lack of effective treatment options. mangiferin, a bioactive compound derived from mango, has been shown to possess strong neuroprotective properties. In this study, we investigated the neuroprotective effects of mangiferin on PD and its underlying mechanisms using both in vitro and in vivo models of 6-OHDA-induced PD. Additionally, we conducted molecular docking experiments to evaluate the interaction between mangiferin and AKR1C3 and β-catenin. Our results demonstrated that treatment with mangiferin significantly attenuated 6-OHDA-induced cell damage in PC12 cells, reducing intracellular oxidative stress, improving mitochondrial membrane potential, and restoring the expression of tyrosine hydroxylase (TH), a characteristic protein of dopaminergic neurons. Furthermore, mangiferin reduced the accumulation of α-synuclein and inhibited the expression of AKR1C3, thereby activating the Wnt/β-catenin signaling pathway. In vivo studies revealed that mangiferin improved motor dysfunction in 6-OHDA-induced PD mice. Molecular docking analysis confirmed the interaction between mangiferin and AKR1C3 and β-catenin. These findings indicate that mangiferin exerts significant neuroprotective effects in 6-OHDA-induced PD by inhibiting AKR1C3 and activating the Wnt/β-catenin signaling pathway. Therefore, mangiferin may emerge as an innovative therapeutic strategy in the comprehensive treatment regimen of PD patients, providing them with better clinical outcomes and quality of life.

Investigation of causal relationships between cortical structure and osteoporosis using two-sample Mendelian randomization

The mutual interaction between bone characteristics and brain had been reported previously, yet whether the cortical structure has any relevance to osteoporosis is questionable. Therefore, we applied a two-sample bidirectional Mendelian randomization analysis to investigate this relationship. We utilized the bone mineral density measurements of femoral neck (n = 32,735) and lumbar spine (n = 28,498) and data on osteoporosis (7300 cases and 358,014 controls). The global surficial area and thickness and 34 specific functional regions of 51,665 patients were screened by magnetic resonance imaging. For the primary estimate, we utilized the inverse-variance weighted method. The Mendelian randomization-Egger intercept test, MR-PRESSO, Cochran's Q test, and "leave-one-out" sensitivity analysis were conducted to assess heterogeneity and pleiotropy. We observed suggestive associations between decreased thickness in the precentral region (OR = 0.034, P = 0.003) and increased chance of having osteoporosis. The results also revealed suggestive causality of decreased bone mineral density in femoral neck to declined total cortical surface area (β = 1400.230 mm2, P = 0.003), as well as the vulnerability to osteoporosis and reduced thickness in the Parstriangularis region (β = -0.006 mm, P = 0.002). Our study supports that the brain and skeleton exhibit bidirectional crosstalk, indicating the presence of a mutual brain-bone interaction.

Causal effects of osteoporosis on structural changes in specific brain regions: a Mendelian randomization study

Observational studies have reported that osteoporosis is associated with cortical changes in the brain. However, the inherent limitations of observational studies pose challenges in eliminating confounding factors and establishing causal relationships. And previous observational studies have not reported changes in specific brain regions. By employing Mendelian randomization, we have been able to infer a causal relationship between osteoporosis and a reduction in the surficial area (SA) of the brain cortical. This effect is partially mediated by vascular calcification. We found that osteoporosis significantly decreased the SA of global brain cortical (β = -1587.62 mm2, 95%CI: -2645.94 mm2 to -529.32 mm2, P = 0.003) as well as the paracentral gyrus without global weighted (β = - 19.42 mm2, 95%CI: -28.90 mm2 to -9.95 mm2, P = 5.85 × 10-5). Furthermore, we estimated that 42.25% and 47.21% of the aforementioned effects are mediated through vascular calcification, respectively. Osteoporosis leads to a reduction in the SA of the brain cortical, suggesting the presence of the bone-brain axis. Vascular calcification plays a role in mediating this process to a certain extent. These findings establish a theoretical foundation for further investigations into the intricate interplay between bone, blood vessels, and the brain.

Resting heart rate causally affects the brain cortical structure: Mendelian randomization study

Resting heart rate (RHR) has been linked to impaired cortical structure in observational studies. However, the extent to which this association is potentially causal has not been determined. Using genetic data, this study aimed to reveal the causal effect of RHR on brain cortical structure. A Two-Sample Mendelian randomization (MR) analysis was conducted. Sensitivity analyses, weighted median, MR Pleiotropy residual sum and outlier, and MR-Egger regression were conducted to evaluate heterogeneity and pleiotropy. A causal relationship between RHR and cortical structures was identified by MR analysis. On the global scale, elevated RHR was found to decrease global surface area (SA; P < 0.0125). On a regional scale, the elevated RHR significantly decreased the SA of pars triangularis without global weighted (P = 1.58 × 10-4) and the thickness (TH) of the paracentral with global weighted (P = 3.56 × 10-5), whereas it increased the TH of banks of the superior temporal sulcus in the presence of global weighted (P = 1.04 × 10-4). MR study provided evidence that RHR might be causally linked to brain cortical structure, which offers a different way to understand the heart-brain axis theory.

Structural connectome architecture shapes the maturation of cortical morphology from childhood to adolescence

Cortical thinning is an important hallmark of the maturation of brain morphology during childhood and adolescence. However, the connectome-based wiring mechanism that underlies cortical maturation remains unclear. Here, we show cortical thinning patterns primarily located in the lateral frontal and parietal heteromodal nodes during childhood and adolescence, which are structurally constrained by white matter network architecture and are particularly represented using a network-based diffusion model. Furthermore, connectome-based constraints are regionally heterogeneous, with the largest constraints residing in frontoparietal nodes, and are associated with gene expression signatures of microstructural neurodevelopmental events. These results are highly reproducible in another independent dataset. These findings advance our understanding of network-level mechanisms and the associated genetic basis that underlies the maturational process of cortical morphology during childhood and adolescence.

Relationship between autism and brain cortex surface area: genetic correlation and a two-sample Mendelian randomization study

BACKGROUND

Alterations in surface area (SA) in specific regions of the cortex have been reported in many individuals with autism spectrum disorder (ASD), however, the genetic background between ASD and SA is still unclear. This study estimated the genetic correlation and causal effect of ASD and cortical SA.

METHODS

Summarized data of genome-wide association studies (GWAS) were separately downloaded from the Psychiatric Genomics Consortium (18,381 cases of ASD, and 27,969 controls) and the Enhancing Neuroimaging Genetics through Meta-Analysis Consortium (33,992 participants of Europeans). We used Linkage disequilibrium score regression (LDSC) and Heritability Estimation from Summary Statistics (HESS) to calculate the heritability of each trait. As for the genetic correlation between ASD and SA, LDSC was used for global correlation and HESS was used to examine the local genetic covariance further. We used three Mendelian randomization (MR) methods, Inverse-variance weighted, MR-Egger, and weighted median to estimate the causal relationship.

RESULTS

LDSC observed a nominal significant genetic correlation (rg = 0.1229, P-value = 0.0346) between ASD and SA of the rostral anterior cingulate gyrus whereas analysis through HESS did not reveal any significant loci having genetic covariance. Based on MR results, statistically meaningful estimations were found in the following areas, postcentral cortex (β (SE) = 21.82 (7.84) mm, 95% CI: 6.46 to 37.19 mm, PIVW = 5.38 × 10- 3, PFDR = 3.09 × 10- 2), posterior cingulate gyrus (β (SE) = 6.23 (2.69) mm, 95% CI: 0.96 to 11.49 mm, PIVW = 2.05 × 10- 2, PFDR = 4.26 × 10- 2), supramarginal gyrus (β (SE) = 19.25 (8.43) mm, 95% CI: 29.29 to 35.77 mm, PIVW = 2.24 × 10- 2, PFDR = 4.31 × 10- 2).

CONCLUSION

Our results provided genetic evidence to support the opinion that individuals with ASD tend to develop differences in cortical SA of special areas. The findings contributed to understanding the genetic relationship between ASD and cortical SA.

From teeth to brain: dental caries causally affects the cortical thickness of the banks of the superior temporal sulcus

OBJECTIVES

Dental caries is one of the most prevalent oral diseases and causes of tooth loss. Cross-sectional studies observed epidemiological associations between dental caries and brain degeneration disorders, while it is unknown whether dental caries causally affect the cerebral structures. This study tested whether genetically proxied DMFS (the sum of Decayed, Missing, and Filled tooth Surfaces) causally impacts the brain cortical structure using Mendelian randomization (MR).

METHODS

The summary-level GWAS meta-analysis data from the GLIDE consortium were used for DMFS, including 26,792 participants. ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) consortium GWAS summary data of 51,665 patients were used for brain structure. This study estimated the causal effects of DMFS on the surface area (SA) and thickness (TH) of the global cortex and functional cortical regions accessed by magnetic resonance imaging (MRI). Inverse-variance weighted (IVW) was used as the primary estimate, the MR pleiotropy residual sum and outlier (MR-PRESSO), the MR-Egger intercept test, and leave-one-out analyses were used to examine the potential horizontal pleiotropy.

RESULTS

Genetically proxied DMFS decreases the TH of the banks of the superior temporal sulcus (BANSSTS) with or without global weighted (weighted, β = - 0.0277 mm, 95% CI: - 0.0470 mm to - 0.0085 mm, P = 0.0047; unweighted, β = - 0.0311 mm, 95% CI: - 0.0609 mm to - 0.0012 mm, P = 0.0412). The causal associations were robust in various sensitivity analyses.

CONCLUSIONS

Dental caries causally decrease the cerebral cortical thickness of the BANKSSTS, a cerebral cortical region crucial for language-related functions, and is the most affected brain region in Alzheimer's disease. This investigation provides the first evidence that dental caries causally affects brain structure, proving the existence of teeth-brain axes. This study also suggested that clinicians should highlight the causal effects of dental caries on brain disorders during the diagnosis and treatments, the cortical thickness of BANKSSTS is a promising diagnostic measurement for dental caries-related brain degeneration.

Causal relationship between multiple sclerosis and cortical structure: a Mendelian randomization study

BACKGROUND

Observational studies have suggested an association between multiple sclerosis (MS) and cortical structure, but the results have been inconsistent.

OBJECTIVE

We used two-sample Mendelian randomization (MR) to assess the causal relationship between MS and cortical structure.

METHODS

MS data as the exposure trait, including 14,498 cases and 24,091 controls, were obtained from the International Multiple Sclerosis Genetics Consortium. Genome-wide association study (GWAS) data for cortical surface area (SAw/nw) and thickness (THw/nw) in 51,665 individuals of European ancestry were obtained from the ENIGMA Consortium. The inverse-variance weighted (IVW) method was used as the primary analysis for MR. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy. Enrichment analysis was performed on MR analyses filtered by sensitivity analysis.

RESULTS

After IVW and sensitivity analysis filtering, only six surviving MR results provided suggestive evidence supporting a causal relationship between MS and cortical structure, including lingual SAw (p = .0342, beta (se) = 5.7127 (2.6969)), parahippocampal SAw (p = .0224, beta (se) = 1.5577 (0.6822)), rostral middle frontal SAw (p = .0154, beta (se) = - 9.0301 (3.7281)), cuneus THw (p = .0418, beta (se) =  - 0.0020 (0.0010)), lateral orbitofrontal THw (p = .0281, beta (se) = 0.0025 (0.0010)), and lateral orbitofrontal THnw (p = .0417, beta (se) = 0.0029 (0.0014)). Enrichment analysis suggested that leukocyte cell-related pathways, JAK-STAT signaling pathway, NF-kappa B signaling pathway, cytokine-cytokine receptor interaction, and prolactin signaling pathway may be involved in the effect of MS on cortical morphology.

CONCLUSION

Our results provide evidence supporting a causal relationship between MS and cortical structure. Enrichment analysis suggests that the pathways mediating brain morphology abnormalities in MS patients are mainly related to immune and inflammation-driven pathways.

Cortical alterations in relatives of patients with bipolar disorder: A review of magnetic resonance imaging studies

INTRODUCTION

Bipolar disorder (BD) is a severe mental disorder characterized by high heritability rates. Widespread brain cortical alterations have been reported in BD patients, mostly involving the frontal, temporal and parietal regions. Importantly, also unaffected relatives of BD patients (BD-RELs) present abnormalities in cortical measures, which are not influenced by disease-related factors, such as medication use and illness duration. Here, we collected all available evidence on cortical measures in BD-RELs to further our knowledge on the potential cortical alterations associated with the vulnerability and the resilience to BD.

METHODS

A search on PubMed, Web of Science and Scopus was performed to identify neuroimaging studies exploring cortical alterations in BD-RELs, including cortical thickness (CT), surface area (SA), gyrification (GI) and cortical complexity. Eleven studies were included. Of these, five assessed CT, five examined CT and SA and one explored CT, SA and GI.

RESULTS

Overall, a heterogeneous pattern of cortical alterations emerged. The areas more consistently linked with genetic liability for BD were the prefrontal and sensorimotor regions. Mixed evidence was reported in the temporal and cingulate areas.

LIMITATIONS

The small sample size and the heterogeneity in terms of methodologies and the characteristics of the participants limit the generalizability of our results.

CONCLUSIONS

Our findings suggest that the genetic liability for BD is related to reduced CT in the prefrontal cortex, which might be a marker of risk for BD, and increased CT within the sensorimotor cortex, which could represent a marker of resilience.

Principal and independent genomic components of brain structure and function

The highly polygenic and pleiotropic nature of behavioural traits, psychiatric disorders and structural and functional brain phenotypes complicate mechanistic interpretation of related genome-wide association study (GWAS) signals, thereby obscuring underlying causal biological processes. We propose genomic principal and independent component analysis (PCA, ICA) to decompose a large set of univariate GWAS statistics of multimodal brain traits into more interpretable latent genomic components. Here we introduce and evaluate this novel methods various analytic parameters and reproducibility across independent samples. Two UK Biobank GWAS summary statistic releases of 2240 imaging-derived phenotypes (IDPs) were retrieved. Genome-wide beta-values and their corresponding standard-error scaled z-values were decomposed using genomic PCA/ICA. We evaluated variance explained at multiple dimensions up to 200. We tested the inter-sample reproducibility of output of dimensions 5, 10, 25 and 50. Reproducibility statistics of the respective univariate GWAS served as benchmarks. Reproducibility of 10-dimensional PCs and ICs showed the best trade-off between model complexity and robustness and variance explained (PCs: |rz  - max| = 0.33, |rraw  - max| = 0.30; ICs: |rz  - max| = 0.23, |rraw  - max| = 0.19). Genomic PC and IC reproducibility improved substantially relative to mean univariate GWAS reproducibility up to dimension 10. Genomic components clustered along neuroimaging modalities. Our results indicate that genomic PCA and ICA decompose genetic effects on IDPs from GWAS statistics with high reproducibility by taking advantage of the inherent pleiotropic patterns. These findings encourage further applications of genomic PCA and ICA as fully data-driven methods to effectively reduce the dimensionality, enhance the signal to noise ratio and improve interpretability of high-dimensional multitrait genome-wide analyses.

Elucidating the relationship between breast cancer and brain cortical structure: a Mendelian randomization study

Cancer-associated cognitive impairment is a significant challenge for individuals who have survived breast cancer, affecting their quality of life. In this study, we conducted an inaugural comprehensive Mendelian randomization analysis discerning the causal relationship between breast cancer, including its two subtypes, and the cerebral cortical structure. Our analysis indicated that estrogen receptor-negative breast cancer significantly decreased surface area (β = -593.01 mm2, 95% CI: -1134.9 to -51.1 mm2, P = 0.032). At the regional level, estrogen receptor-negative breast cancer showed a significant association with surface area and thickness in 17 cortical regions. These regions included the insula, posterior cingulate, superior frontal, precuneus, fusiform, lateral occipital, and rostral middle frontal. Specifically, estrogen receptor-negative breast cancer had a significant impact on decreasing the surface area of the insula without considering global weight (β = -14.09 mm2, 95% CI: -22.91 to -5.27 mm2, P = 0.0017). The results from meta-analysis and LD Score Regression provide support for our findings. This investigation unveils the correlations between breast cancer, its various subcategories, and the cerebral cortical structure. Notably, breast cancer of the estrogen receptor-negative variety may elicit more widespread cerebral atrophy.

Non-alcoholic fatty liver disease causally affects the brain cortical structure: a Mendelian randomization study

Background

Reduced brain volume, impaired cognition, and possibly a range of psychoneurological disorders have been reported in patients with non-alcoholic fatty liver disease (NAFLD); however, no underlying cause has been specified. Here, Mendelian randomization (MR) was employed to determine the causative NAFLD effects on cortical structure.

Methods

We used pooled-level data from FinnGen's published genome-wide association study (GWAS) of NAFLD (1908 cases and 340,591 healthy controls), as well as published GWAS with NAFLD activity score (NAS) and fibrosis stage-associated SNPs as genetic tools, in addition to the Enigma Consortium data from 51,665 patients, were used to assess genetic susceptibility in relation to changes with cortical thickness (TH) and surface area (SA). A main estimate was made by means of inverse variance weighted (IVW), while heterogeneity and pleiotropy were detected using MR-Egger, weighted median, and MR Pleiotropy RESidual Sum and Outlier to perform a two-sample MR analysis.

Results

At the global level, NAFLD reduced SA (beta = -586.72 mm2, se = 217.73, p = 0.007) and several changes in the cortical structure of the cerebral gyrus were found, with no detectable pleiotropy.

Conclusion

NAFLD causally affects cortical structures, which supports the presence of an intricate liver-brain axis.

Proxy-analysis of the genetics of cognitive decline in Parkinson's disease through polygenic scores

Cognitive decline is common in Parkinson's disease (PD) and its genetic risk factors are not well known to date, besides variants in the GBA and APOE genes. However, variation in complex traits is caused by numerous variants and is usually studied with genome-wide association studies (GWAS), requiring a large sample size, which is difficult to achieve for outcome measures in PD. Taking an alternative approach, we computed 100 polygenic scores (PGS) related to cognitive, dementia, stroke, and brain anatomical phenotypes and investigated their association with cognitive decline in six longitudinal cohorts. The analysis was adjusted for age, sex, genetic ancestry, follow-up duration, GBA and APOE status. Then, we meta-analyzed five of these cohorts, comprising a total of 1702 PD participants with 6156 visits, using the Montreal Cognitive Assessment as a cognitive outcome measure. After correction for multiple comparisons, we found four PGS significantly associated with cognitive decline: intelligence (p = 5.26e-13), cognitive performance (p = 1.46e-12), educational attainment (p = 8.52e-10), and reasoning (p = 3.58e-5). Survival analyses highlighted an offset of several years between the first and last quartiles of PGS, with significant differences for the PGS of cognitive performance (5 years) and educational attainment (7 years). In conclusion, we found four PGS associated with cognitive decline in PD, all associated with general cognitive phenotypes. This study highlights the common genetic factors between cognitive decline in PD and the general population, and the importance of the participant's cognitive reserve for cognitive outcome in PD.

A role for the serotonin 2A receptor in the expansion and functioning of human transmodal cortex

Integrating independent but converging lines of research on brain function and neurodevelopment across scales, this article proposes that serotonin 2A receptor (5-HT2AR) signalling is an evolutionary and developmental driver and potent modulator of the macroscale functional organization of the human cerebral cortex. A wealth of evidence indicates that the anatomical and functional organization of the cortex follows a unimodal-to-transmodal gradient. Situated at the apex of this processing hierarchy-where it plays a central role in the integrative processes underpinning complex, human-defining cognition-the transmodal cortex has disproportionately expanded across human development and evolution. Notably, the adult human transmodal cortex is especially rich in 5-HT2AR expression and recent evidence suggests that, during early brain development, 5-HT2AR signalling on neural progenitor cells stimulates their proliferation-a critical process for evolutionarily-relevant cortical expansion. Drawing on multimodal neuroimaging and cross-species investigations, we argue that, by contributing to the expansion of the human cortex and being prevalent at the apex of its hierarchy in the adult brain, 5-HT2AR signalling plays a major role in both human cortical expansion and functioning. Owing to its unique excitatory and downstream cellular effects, neuronal 5-HT2AR agonism promotes neuroplasticity, learning and cognitive and psychological flexibility in a context-(hyper)sensitive manner with therapeutic potential. Overall, we delineate a dual role of 5-HT2ARs in enabling both the expansion and modulation of the human transmodal cortex.

Genetics of human brain development

Brain development in humans is achieved through precise spatiotemporal genetic control, the mechanisms of which remain largely elusive. Recently, integration of technological advances in human stem cell-based modelling with genome editing has emerged as a powerful platform to establish causative links between genotypes and phenotypes directly in the human system. Here, we review our current knowledge of complex genetic regulation of each key step of human brain development through the lens of evolutionary specialization and neurodevelopmental disorders and highlight the use of human stem cell-derived 2D cultures and 3D brain organoids to investigate human-enriched features and disease mechanisms. We also discuss opportunities and challenges of integrating new technologies to reveal the genetic architecture of human brain development and disorders.

Population Neuroscience: Principles and Advances

In population neuroscience, three disciplines come together to advance our knowledge of factors that shape the human brain: neuroscience, genetics, and epidemiology (Paus, Human Brain Mapping 31:891-903, 2010). Here, I will come back to some of the background material reviewed in more detail in our previous book (Paus, Population Neuroscience, 2013), followed by a brief overview of current advances and challenges faced by this integrative approach.

Overview: Research on the Genetic Architecture of the Developing Cerebral Cortex in Norms and Diseases

The human brain is characterized by high cell numbers, diverse cell types with diverse functions, and intricate connectivity with an exceedingly broad surface of the cortex. Human-specific brain development was accomplished by a long timeline for maturation from the prenatal period to the third decade of life. The long timeline makes complicated architecture and circuits of human cerebral cortex possible, and it makes human brain vulnerable to intrinsic and extrinsic insults resulting in the development of variety of neuropsychiatric disorders. Unraveling the molecular and cellular processes underlying human brain development under the elaborate regulation of gene expression in a spatiotemporally specific manner, especially that of the cortex will provide a biological understanding of human cognition and behavior in health and diseases. Global research consortia and the advancing technologies in brain science including functional genomics equipped with emergent neuroinformatics such as single-cell multiomics, novel human models, and high-volume databases with high-throughput computation facilitate the biological understanding of the development of the human brain cortex. Knowing the process of interplay of the genome and the environment in cortex development will lead us to understand the human-specific cognitive function and its individual diversity. Thus, it is worthwhile to overview the recent progress in neurotechnology to foresee further understanding of the human brain and norms and diseases.

Genetic architectures of cerebral ventricles and their overlap with neuropsychiatric traits

The cerebral ventricles are recognized as windows into brain development and disease, yet their genetic architectures, underlying neural mechanisms and utility in maintaining brain health remain elusive. Here we aggregated genetic and neuroimaging data from 61,974 participants (age range, 9 to 98 years) in five cohorts to elucidate the genetic basis of ventricular morphology and examined their overlap with neuropsychiatric traits. Genome-wide association analysis in a discovery sample of 31,880 individuals identified 62 unique loci and 785 candidate genes associated with ventricular morphology. We replicated over 80% of loci in a well-matched cohort of lateral ventricular volume. Gene set analysis revealed enrichment of ventricular-trait-associated genes in biological processes and disease pathogenesis during both early brain development and degeneration. We explored the age-dependent genetic associations in cohorts of different age groups to investigate the possible roles of ventricular-trait-associated loci in neurodevelopmental and neurodegenerative processes. We describe the genetic overlap between ventricular and neuropsychiatric traits through comprehensive integrative approaches under correlative and causal assumptions. We propose the volume of the inferior lateral ventricles as a heritable endophenotype to predict the risk of Alzheimer's disease, which might be a consequence of prodromal Alzheimer's disease. Our study provides an advance in understanding the genetics of the cerebral ventricles and demonstrates the potential utility of ventricular measurements in tracking brain disorders and maintaining brain health across the lifespan.

Diabetic Retinopathy and Brain Structure, Cognition Function, and Dementia: A Bidirectional Mendelian Randomization Study

BACKGROUND

Accumulating evidence has demonstrated that hyperglycemia is a possible risk factor for mild cognitive impairment or Alzheimer's disease. Diabetic retinopathy (DR) has been identified as a risk factor for dementia in patients with diabetes.

OBJECTIVE

This study aimed to investigate the causal relationships between DR and brain structure, cognitive function, and dementia.

METHODS

We performed bidirectional two-sample Mendelian randomization for DR, brain structure, cognitive function, and dementia using the inverse-variance weighted method.

RESULTS

Inverse-variance weighted analysis showed the association of DR with vascular dementia (OR = 1.68, 95% CI: 1.01-2.82), and dementia was significantly associated with the increased risk of non-proliferative DR (NPDR) (OR = 1.76, 95% CI: 1.04-2.98). Furthermore, better cognitive performance was significantly associated with a reduced risk of NPDR (OR = 0.85, 95% CI: 0.74-0.98). No association was observed between DR and brain structure.

CONCLUSIONS

These findings suggest that the association of DR with vascular dementia. The reciprocal effect of cognitive performance and dementia on NPDR risk highlights the potential benefits of dementia prevention for reducing the burden of DR.

Causal associations between gut microbiota and regional cortical structure: a Mendelian randomization study

Introduction

Observational studies have reported associations between gut microbiota composition and central nervous system diseases. However, the potential causal relationships and underlying mechanisms remain unclear. Here, we applied Mendelian randomization (MR) to investigate the causal effects of gut microbiota on cortical surface area (SA) and thickness (TH) in the brain.

Methods

We used genome-wide association study summary statistics of gut microbiota abundance in 18,340 individuals from the MiBioGen Consortium to identify genetic instruments for 196 gut microbial taxa. We then analyzed data from 56,761 individuals from the ENIGMA Consortium to examine associations of genetically predicted gut microbiota with alterations in cortical SA and TH globally and across 34 functional brain regions. Inverse-variance weighted analysis was used as the primary MR method, with MR Egger regression, MR-PRESSO, Cochran's Q test, and leave-one-out analysis to assess heterogeneity and pleiotropy.

Results

At the functional region level, genetically predicted higher abundance of class Mollicutes was associated with greater SA of the medial orbitofrontal cortex (β = 8.39 mm2, 95% CI: 3.08-13.70 mm2, p = 0.002), as was higher abundance of phylum Tenericutes (β = 8.39 mm2, 95% CI: 3.08-13.70 mm2, p = 0.002). Additionally, higher abundance of phylum Tenericutes was associated with greater SA of the lateral orbitofrontal cortex (β = 10.51 mm2, 95% CI: 3.24-17.79 mm2, p = 0.0046). No evidence of heterogeneity or pleiotropy was detected.

Conclusion

Specific gut microbiota may causally influence cortical structure in brain regions involved in neuropsychiatric disorders. The findings provide evidence for a gut-brain axis influencing cortical development, particularly in the orbitofrontal cortex during adolescence.

The Interaction of LAMA2 and Duration of Illness Affects the Thickness of the Right Transverse Temporal Gyrus in Major Depressive Disorder

Background

Depression is a heritable brain disorder. Laminin genes were recently identified to affect the brain's overall thickness through neurogenesis, differentiation, and migration in depression. This study aims to explore the effects of the LAMA2's single nucleotide polymorphisms (SNP), a subunit gene of laminin, on the detected brain regions of patients with major depressive disorder (MDD).

Methods

The study included 89 patients with MDD and 60 healthy controls with T1-weighted structural magnetic resonance imaging and blood samples for genotyping. The interactions between LAMA2 gene SNPs and diagnosis as well as duration of illness (DOI) were explored on brain measures controlled for age, gender, and site.

Results

The right transverse temporal gyrus and right parahippocampal gyrus showed reduced thickness in MDD. Almost all seven LAMA2 SNPs showed significant interactions with diagnosis on both gyrus (corrected p < 0.05 or trending). In MDD, rs6569604, rs2229848, rs2229849, rs2229850, and rs2784895 interacted with DOI on the right transverse temporal gyrus (corrected p < 0.05), but not the right parahippocampal gyrus.

Conclusion

The thickness of the right transverse temporal gyrus in patients with MDD may be affected by LAMA2 gene and DOI.

Association Between Wnt Target Genes and Cortical Volumes in Alzheimer's Disease

The disproportionate cortical atrophy is an established biomarker for the pathophysiological process of Alzheimer's disease (AD). However, the genetic basis underlying the cortical atrophy remains poorly defined. Herein, we aim to illustrate the effect of the Wnt target genes on the cortical volumes of AD patients. 82 sporadic AD patients were recruited. All the subjects had history survey, blood biochemical examination, cognitive assessment, MRI morphometry and whole exome sequencing. This report focused on 84 common variants (minor allele frequency > 0.01) of 32 Wnt target genes, including the APC, DAAM1, DACT1, DISC1, LATS2, TLR2, WDR61, and the AXIN, DVL, FZD, LRP, TCF/LEF, WNT family genes. The Wnt target genes showed asymmetric effects on the cortical volumes of AD patients. The right temporal/parietal/occipital cortices were more affected than left temporal/parietal/occipital cortices. Nevertheless, the reverse applied to the frontal cortex. The DACT1 affected the cortical thickness most, followed by the TCF3 and APC. The DACT1 rs698025-GG genotype displayed greater right temporal pole and left medial orbito-frontal gyrus than rs698025-GA genotype (2.4 ± 0.4 vs. 2.0 ± 0.6, P = 0.005; 5.2 ± 0.6 vs. 5.0 ± 0.6, P = 0.001). The brain region most influenced by the Wnt target genes was the right calcarine cortex. In conclusion, the common variants of the Wnt target genes exert asymmetric effects on the cortical volumes of AD patients. The Wnt signaling pathway may play a role in the cortical atrophy of AD patients.

Isoform-level transcriptome-wide association uncovers genetic risk mechanisms for neuropsychiatric disorders in the human brain

Methods integrating genetics with transcriptomic reference panels prioritize risk genes and mechanisms at only a fraction of trait-associated genetic loci, due in part to an overreliance on total gene expression as a molecular outcome measure. This challenge is particularly relevant for the brain, in which extensive splicing generates multiple distinct transcript-isoforms per gene. Due to complex correlation structures, isoform-level modeling from cis-window variants requires methodological innovation. Here we introduce isoTWAS, a multivariate, stepwise framework integrating genetics, isoform-level expression and phenotypic associations. Compared to gene-level methods, isoTWAS improves both isoform and gene expression prediction, yielding more testable genes, and increased power for discovery of trait associations within genome-wide association study loci across 15 neuropsychiatric traits. We illustrate multiple isoTWAS associations undetectable at the gene-level, prioritizing isoforms of AKT3, CUL3 and HSPD1 in schizophrenia and PCLO with multiple disorders. Results highlight the importance of incorporating isoform-level resolution within integrative approaches to increase discovery of trait associations, especially for brain-relevant traits.

Causal relationship between sleep traits and cognitive impairment: A Mendelian randomization study

OBJECTIVE

Observational studies had demonstrated a link between sleep disturbances and cognitive decline. Here, we aimed to investigate the causal association between genetically predicted sleep traits and cognitive impairment using Mendelian randomization (MR).

METHODS

Using strict criteria, we selected genetic variants from European ancestry Genome-wide association studies (GWAS) from the Sleep Disorders Knowledge Portal and UK Biobank as instrumental variables for several sleep traits, including insomnia, sleep duration, daytime sleepiness, daytime napping, and chronotype. Summary statistics related to cognitive impairment were derived from five different GWAS, including the Social Science Genetic Association Consortium. The role of self-reported sleep trait phenotypes in the etiology of cognitive impairment was explored using inverse-variance weighted (IVW) tests, MR-Egger tests, and weighted medians, and sensitivity analyses were conducted to ensure robustness.

RESULTS

In the main IVW analysis, sleep duration (reaction time: β = -0.05, 95% CI -0.07 to -0.04, p = 1.93×10-12 ), daytime sleepiness (average cortical thickness: β = -0.12, 95% CI -0.22 to -0.02, p = 0.023), and daytime napping (fluid intelligence: β = -0.47, 95% CI -0.87 to -0.07, p = 0.021; hippocampal volume in Alzheimer's disease: β = -0.99, 95% CI -1.64 to -0.35, p = 0.002) were significantly negatively correlated with cognitive performance. However, any effects of insomnia and chronotype on cognitive impairment were not determined.

CONCLUSIONS

Our findings highlighted that focusing on sleep behaviors or distinct sleep patterns-particularly sleep duration, daytime sleepiness, and daytime napping, was a promising approach for preventing cognitive impairment. This study also shed light on risk factors for and potential early markers of cognitive impairment risk factors.

Shared Genetic Architecture between Parkinson's Disease and Brain Structural Phenotypes

BACKGROUND

Patients with Parkinson's disease (PD) have consistently demonstrated brain structure abnormalities, indicating the presence of shared etiological and pathological processes between PD and brain structures; however, the genetic relationship remains poorly understood.

OBJECTIVE

The aim of this study was to investigate the extent of shared genetic architecture between PD and brain structural phenotypes (BSPs) and to identify shared genomic loci.

METHODS

We used the summary statistics from genome-wide association studies to conduct MiXeR and conditional/conjunctional false discovery rate analyses to investigate the shared genetic signatures between PD and BSPs. Subsequent expression quantitative trait loci mapping in the human brain and enrichment analyses were also performed.

RESULTS

MiXeR analysis identified genetic overlap between PD and various BSPs, including total cortical surface area, average cortical thickness, and specific brain volumetric structures. Further analysis using conditional false discovery rate (FDR) identified 21 novel PD risk loci on associations with BSPs at conditional FDR < 0.01, and the conjunctional FDR analysis demonstrated that PD shared several genomic loci with certain BSPs at conjunctional FDR < 0.05. Among the shared loci, 16 credible mapped genes showed high expression in the brain tissues and were primarily associated with immune function-related biological processes.

CONCLUSIONS

We confirmed the polygenic overlap with mixed directions of allelic effects between PD and BSPs and identified multiple shared genomic loci and risk genes, which are likely related to immune-related biological processes. These findings provide insight into the complex genetic architecture associated with PD. © 2023 International Parkinson and Movement Disorder Society.

Cerebellar Volume and Disease Staging in Parkinson's Disease: An ENIGMA-PD Study

BACKGROUND

Increasing evidence points to a pathophysiological role for the cerebellum in Parkinson's disease (PD). However, regional cerebellar changes associated with motor and non-motor functioning remain to be elucidated.

OBJECTIVE

To quantify cross-sectional regional cerebellar lobule volumes using three dimensional T1-weighted anatomical brain magnetic resonance imaging from the global ENIGMA-PD working group.

METHODS

Cerebellar parcellation was performed using a deep learning-based approach from 2487 people with PD and 1212 age and sex-matched controls across 22 sites. Linear mixed effects models compared total and regional cerebellar volume in people with PD at each Hoehn and Yahr (HY) disease stage, to an age- and sex- matched control group. Associations with motor symptom severity and Montreal Cognitive Assessment scores were investigated.

RESULTS

Overall, people with PD had a regionally smaller posterior lobe (dmax  = -0.15). HY stage-specific analyses revealed a larger anterior lobule V bilaterally (dmax  = 0.28) in people with PD in HY stage 1 compared to controls. In contrast, smaller bilateral lobule VII volume in the posterior lobe was observed in HY stages 3, 4, and 5 (dmax  = -0.76), which was incrementally lower with higher disease stage. Within PD, cognitively impaired individuals had lower total cerebellar volume compared to cognitively normal individuals (d = -0.17).

CONCLUSIONS

We provide evidence of a dissociation between anterior "motor" lobe and posterior "non-motor" lobe cerebellar regions in PD. Whereas less severe stages of the disease are associated with larger motor lobe regions, more severe stages of the disease are marked by smaller non-motor regions. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The causal effects between selenium levels and the brain cortical structure: A two-sample Mendelian randomization study

Extensive research has demonstrated the critical role of selenium (Se) and selenoproteins in brain function and cognition. However, the impact of Se on brain cortical structure remains enigmatic. Therefore, this study used Mendelian randomization (MR) analysis to investigate the causal effect between Se levels and brain cortical structure.

METHODS

This study utilizes 11 genetic variants associated with Se level variations, extracted from a large-scale genome-wide association study (GWAS) encompassed circulating Se levels (n = 5477) and toenail Se levels (n = 4162) in the European population. Outcome data were sourced from the summary statistics of the ENIGMA Consortium, comprising GWAS data from 51,666 individuals. The variables include cortical surface area (SA), thickness (TH) at the global level, and 34 functional cortical regions evaluated by magnetic resonance imaging. The inverse-variance-weighted method was used as the primary estimate. Additionally, sensitivity analyses were conducted to detect potential violations of assumptions underlying MR.

RESULTS

At the global level, Se levels were not correlated with SA but showed a significant negative correlation with TH (β = -0.00485 mm, SE = 0.00192, p = .0115). Heterogeneity was observed across different brain regions, with positive correlations found between Se levels and the TH of the parahippocampal gyrus, superior frontal gyrus, and frontal pole, whereas negative correlations were found with the TH of the inferior parietal lobe and middle temporal lobe. Regarding SA, Se levels exhibit positive correlations with the pars triangularis, caudal anterior cingulate, inferior parietal lobe, and banks of the superior temporal sulcus. Conversely, negative correlations were observed with the medial orbitofrontal cortex, posterior cingulate gyrus, insula, and the middle, superior, and transverse gyrus of the temporal lobe. No pleiotropy was detected.

RESULTS

This MR study indicated that Se levels causally influence the brain cortical structure.

The molecular genetic landscape of human brain size variation

Human brain size changes dynamically through early development, peaks in adolescence, and varies up to 2-fold among adults. However, the molecular genetic underpinnings of interindividual variation in brain size remain unknown. Here, we leveraged postmortem brain RNA sequencing and measurements of brain weight (BW) in 2,531 individuals across three independent datasets to identify 928 genome-wide significant associations with BW. Genes associated with higher or lower BW showed distinct neurodevelopmental trajectories and spatial patterns that mapped onto functional and cellular axes of brain organization. Expression of BW genes was predictive of interspecies differences in brain size, and bioinformatic annotation revealed enrichment for neurogenesis and cell-cell communication. Genome-wide, transcriptome-wide, and phenome-wide association analyses linked BW gene sets to neuroimaging measurements of brain size and brain-related clinical traits. Cumulatively, these results represent a major step toward delineating the molecular pathways underlying human brain size variation in health and disease.

Unveiling the influence of daily dietary patterns on brain cortical structure: insights from bidirectional Mendelian randomization

Cognitive impairment is a significant concern in aging populations. This study utilized Mendelian randomization analysis to explore the impact of dietary habits and macro-nutrients on cortical structure. A bidirectional Mendelian randomization approach was employed, incorporating large-scale genetic data on dietary habits and brain cortical structure. The results did not reveal significant causal relationships between dietary factors and overall cortical structure and thickness. However, specific dietary factors showed associations with cortical structure in certain regions. For instance, fat intake affected six cortical regions, while milk, protein, fruits, and water were associated with changes in specific regions. Reverse analysis suggested that cortical thickness influenced the consumption of alcohol, carbohydrates, coffee, and fish. These findings contribute to understanding the potential mechanisms underlying the role of dietary factors in cognitive function changes and provide evidence supporting the existence of the gut-brain axis.

Grey and white matter metrics demonstrate distinct and complementary prediction of differences in cognitive performance in children: Findings from ABCD (N= 11 876)

Individual differences in cognitive performance in childhood are a key predictor of significant life outcomes such as educational attainment and mental health. Differences in cognitive ability are governed in part by variations in brain structure. However, studies commonly focus on either grey or white matter metrics in humans, leaving open the key question as to whether grey or white matter microstructure play distinct or complementary roles supporting cognitive performance. To compare the role of grey and white matter in supporting cognitive performance, we used regularized structural equation models to predict cognitive performance with grey and white matter measures. Specifically, we compared how grey matter (volume, cortical thickness and surface area) and white matter measures (volume, fractional anisotropy and mean diffusivity) predicted individual differences in cognitive performance. The models were tested in 11,876 children (ABCD Study, 5680 female; 6196 male) at 10 years old. We found that grey and white matter metrics bring partly non-overlapping information to predict cognitive performance. The models with only grey or white matter explained respectively 15.4% and 12.4% of the variance in cognitive performance, while the combined model explained 19.0%. Zooming in we additionally found that different metrics within grey and white matter had different predictive power, and that the tracts/regions that were most predictive of cognitive performance differed across metric. These results show that studies focusing on a single metric in either grey or white matter to study the link between brain structure and cognitive performance are missing a key part of the equation.

Systematic druggable genome-wide Mendelian randomisation identifies therapeutic targets for Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is the leading cause of dementia. Currently, there are no effective disease-modifying treatments for AD. Mendelian randomisation (MR) has been widely used to repurpose licensed drugs and discover novel therapeutic targets. Thus, we aimed to identify novel therapeutic targets for AD and analyse their pathophysiological mechanisms and potential side effects.

METHODS

A two-sample MR integrating the identified druggable genes was performed to estimate the causal effects of blood and brain druggable expression quantitative trait loci (eQTLs) on AD. A repeat study was conducted using different blood and brain eQTL data sources to validate the identified genes. Using AD markers with available genome-wide association studies data, we evaluated the causal relationship between established AD markers to explore possible mechanisms. Finally, the potential side effects of the druggable genes for AD treatment were assessed using a phenome-wide MR.

RESULTS

Overall, 5883 unique druggable genes were aggregated; 33 unique potential druggable genes for AD were identified in at least one dataset (brain or blood), and 5 were validated in a different dataset. Among them, three prior druggable genes (epoxide hydrolase 2 (EPHX2), SERPINB1 and SIGLEC11) reached significant levels in both blood and brain tissues. EPHX2 may mediate the pathogenesis of AD by affecting the entire hippocampal volume. Further phenome-wide MR analysis revealed no potential side effects of treatments targeting EPHX2, SERPINB1 or SIGLEC11.

CONCLUSIONS

This study provides genetic evidence supporting the potential therapeutic benefits of targeting the three druggable genes for AD treatment, which will be useful for prioritising AD drug development.

Cerebral cortical structural alteration patterns across four major psychiatric disorders in 5549 individuals

According to the operational diagnostic criteria, psychiatric disorders such as schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and autism spectrum disorder (ASD) are classified based on symptoms. While its cluster of symptoms defines each of these psychiatric disorders, there is also an overlap in symptoms between the disorders. We hypothesized that there are also similarities and differences in cortical structural neuroimaging features among these psychiatric disorders. T1-weighted magnetic resonance imaging scans were performed for 5,549 subjects recruited from 14 sites. Effect sizes were determined using a linear regression model within each protocol, and these effect sizes were meta-analyzed. The similarity of the differences in cortical thickness and surface area of each disorder group was calculated using cosine similarity, which was calculated from the effect sizes of each cortical regions. The thinnest cortex was found in SZ, followed by BD and MDD. The cosine similarity values between disorders were 0.943 for SZ and BD, 0.959 for SZ and MDD, and 0.943 for BD and MDD, which indicated that a common pattern of cortical thickness alterations was found among SZ, BD, and MDD. Additionally, a generally smaller cortical surface area was found in SZ and MDD than in BD, and the effect was larger in SZ. The cosine similarity values between disorders were 0.945 for SZ and MDD, 0.867 for SZ and ASD, and 0.811 for MDD and ASD, which indicated a common pattern of cortical surface area alterations among SZ, MDD, and ASD. Patterns of alterations in cortical thickness and surface area were revealed in the four major psychiatric disorders. To our knowledge, this is the first report of a cross-disorder analysis conducted on four major psychiatric disorders. Cross-disorder brain imaging research can help to advance our understanding of the pathogenesis of psychiatric disorders and common symptoms.

Causal effects of nonalcoholic fatty liver disease on cerebral cortical structure: a Mendelian randomization analysis

Background

Previous studies have highlighted changes in the cerebral cortical structure and cognitive function among nonalcoholic fatty liver disease (NAFLD) patients. However, the impact of NAFLD on cerebral cortical structure and specific affected brain regions remains unclear. Therefore, we aimed to explore the potential causal relationship between NAFLD and cerebral cortical structure.

Methods

We conducted a Mendelian randomization (MR) study using genetic predictors of alanine aminotransferase (ALT), NAFLD, and percent liver fat (PLF) and combined them with genome-wide association study (GWAS) summary statistics from the ENIGMA Consortium. Several methods were used to assess the effect of NAFLD on full cortex and specific brain regions, along with sensitivity analyses.

Results

At the global level, PLF nominally decreased SA of full cortex; at the functional level, ALT presented a nominal association with reduced SA of parahippocampal gyrus, TH of pars opercularis, TH of pars orbitalis, and TH of pericalcarine cortex. Besides, NAFLD presented a nominal association with reduced SA of parahippocampal gyrus, TH of pars opercularis, TH of pars triangularis and TH of pericalcarine cortex, but increased TH of entorhinal cortex, lateral orbitofrontal cortex and temporal pole. Furthermore, PLF presented a nominal association with reduced SA of parahippocampal gyrus, TH of pars opercularis, TH of cuneus and lingual gyrus, but increased TH of entorhinal cortex.

Conclusion

NAFLD is suggestively associated with atrophy in specific functional regions of the human brain.

The impact of early adversity on the cerebral cortex - a Mendelian randomization study

Background

The early adversity is associated with a series of negative outcomes in adulthood, and the impact on the cerebral cortex may be one of the fundamental causes of these adverse consequences in adulthood. In this study, we aim to investigate the causal relationship between early adversity and changes in cerebral cortex structure using Mendelian randomization (MR) analysis.

Methods

The GWAS summary statistics of 6 early adversity traits were obtained from individuals of European ancestry in the UK Biobank. The GWAS summary statistics of 34 known functional cortical regions were obtained from the ENIGMA Consortium. Causal relationships between the adversity factors and brain cortical structure were assessed using the inverse-variance weighted (IVW), MR-Egger, and weighted median methods, with IVW being the primary evaluation method. Cochran's Q-test, MR-PRESSO, leave-one-out analysis, and funnel plot examination were employed to detect potential heterogeneity and pleiotropy, as well as to identify and exclude outliers.

Results

At a global level, no causal relationship was found between early adversity and cortical thickness (TH) or surface area (SA) of the brain. However, at the regional level, early adversity was found to potentially influence the TH of the caudal anterior cingulate, superior temporal, entorhinal, paracentral, lateral occipital, banks of the superior temporal sulcus, and supramarginal regions, as well as the SA of the pars triangularis, lateral occipital, parahippocampal, medial orbitofrontal, and isthmus cingulate regions. All findings were nominally significant and passed sensitivity analyses, with no significant heterogeneity or pleiotropy detected.

Discussion

Our study provides evidence for the association between early adversity and alterations in brain cortical structure, which may serve as a foundation for certain mental disorders. Furthermore, magnetic resonance imaging (MRI) might be considered as a promising tool to aid healthcare professionals in identifying individuals with a history of adverse experiences, allowing for early interventions.

The pleiotropic contribution of genes in dopaminergic and serotonergic pathways to addiction and related behavioral traits

Introduction

Co-occurrence of substance use disorders (SUD) and other behavioral conditions, such as stress-related, aggressive or risk-taking behaviors, in the same individual has been frequently described. As dopamine (DA) and serotonin (5-HT) have been previously identified as key neurotransmitters for some of these phenotypes, we explored the genetic contribution of these pathways to SUD and these comorbid phenotypes in order to better understand the genetic relationship between them.

Methods

We tested the association of 275 dopaminergic genes and 176 serotonergic genes with these phenotypes by performing gene-based, gene-set and transcriptome-wide association studies in 11 genome-wide association studies (GWAS) datasets on SUD and related behaviors.

Results

At the gene-wide level, 68 DA and 27 5-HT genes were found to be associated with at least one GWAS on SUD or related behavior. Among them, six genes had a pleiotropic effect, being associated with at least three phenotypes: ADH1C, ARNTL, CHRNA3, HPRT1, HTR1B and DRD2. Additionally, we found nominal associations between the DA gene sets and SUD, opioid use disorder, antisocial behavior, irritability and neuroticism, and between the 5-HT-core gene set and neuroticism. Predicted gene expression correlates in brain were also found for 19 DA or 5-HT genes.

Discussion

Our study shows a pleiotropic contribution of dopaminergic and serotonergic genes to addiction and related behaviors such as anxiety, irritability, neuroticism and risk-taking behavior, highlighting a role for DA genes, which could explain, in part, the co-occurrence of these phenotypes.

Genetic Influence on Gyral Peaks

Genetic mechanisms have been hypothesized to be a major determinant in the formation of cortical folding. Although there is an increasing number of studies examining the heritability of cortical folding, most of them focus on sulcal pits rather than gyral peaks. Gyral peaks, which reflect the highest local foci on gyri and are consistent across individuals, remain unstudied in terms of heritability. To address this knowledge gap, we used high-resolution data from the Human Connectome Project (HCP) to perform classical twin analysis and estimate the heritability of gyral peaks across various brain regions. Our results showed that the heritability of gyral peaks was heterogeneous across different cortical regions, but relatively symmetric between hemispheres. We also found that pits and peaks are different in a variety of anatomic and functional measures. Further, we explored the relationship between the levels of heritability and the formation of cortical folding by utilizing the evolutionary timeline of gyrification. Our findings indicate that the heritability estimates of both gyral peaks and sulcal pits decrease linearly with the evolution timeline of gyrification. This suggests that the cortical folds which formed earlier during gyrification are subject to stronger genetic influences than the later ones. Moreover, the pits and peaks coupled by their time of appearance are also positively correlated in respect of their heritability estimates. These results fill the knowledge gap regarding genetic influences on gyral peaks and significantly advance our understanding of how genetic factors shape the formation of cortical folding. The comparison between peaks and pits suggests that peaks are not a simple morphological mirror of pits but could help complete the understanding of folding patterns.

A single-cell multi-omic atlas spanning the adult rhesus macaque brain

Cataloging the diverse cellular architecture of the primate brain is crucial for understanding cognition, behavior, and disease in humans. Here, we generated a brain-wide single-cell multimodal molecular atlas of the rhesus macaque brain. Together, we profiled 2.58 M transcriptomes and 1.59 M epigenomes from single nuclei sampled from 30 regions across the adult brain. Cell composition differed extensively across the brain, revealing cellular signatures of region-specific functions. We also identified 1.19 M candidate regulatory elements, many previously unidentified, allowing us to explore the landscape of cis-regulatory grammar and neurological disease risk in a cell type-specific manner. Altogether, this multi-omic atlas provides an open resource for investigating the evolution of the human brain and identifying novel targets for disease interventions.

Interindividual variation in human cortical cell type abundance and expression

Single-cell transcriptomic studies have identified a conserved set of neocortical cell types from small postmortem cohorts. We extended these efforts by assessing cell type variation across 75 adult individuals undergoing epilepsy and tumor surgeries. Nearly all nuclei map to one of 125 robust cell types identified in the middle temporal gyrus. However, we found interindividual variance in abundances and gene expression signatures, particularly in deep-layer glutamatergic neurons and microglia. A minority of donor variance is explainable by age, sex, ancestry, disease state, and cell state. Genomic variation was associated with expression of 150 to 250 genes for most cell types. This characterization of cellular variation provides a baseline for cell typing in health and disease.

The overlapping genetic architecture of psychiatric disorders and cortical brain structure

Both psychiatric vulnerability and cortical structure are shaped by the cumulative effect of common genetic variants across the genome. However, the shared genetic underpinnings between psychiatric disorders and brain structural phenotypes, such as thickness and surface area of the cerebral cortex, remains elusive. In this study, we employed pleiotropy-informed conjunctional false discovery rate analysis to investigate shared loci across genome-wide association scans of regional cortical thickness, surface area, and seven psychiatric disorders in approximately 700,000 individuals of European ancestry. Aggregating regional measures, we identified 50 genetic loci shared between psychiatric disorders and surface area, as well as 26 genetic loci shared with cortical thickness. Risk alleles exhibited bidirectional effects on both cortical thickness and surface area, such that some risk alleles for each disorder increased regional brain size while other risk alleles decreased regional brain size. Due to bidirectional effects, in many cases we observed extensive pleiotropy between an imaging phenotype and a psychiatric disorder even in the absence of a significant genetic correlation between them. The impact of genetic risk for psychiatric disorders on regional brain structure did exhibit a consistent pattern across highly comorbid psychiatric disorders, with 80% of the genetic loci shared across multiple disorders displaying consistent directions of effect. Cortical patterning of genetic overlap revealed a hierarchical genetic architecture, with the association cortex and sensorimotor cortex representing two extremes of shared genetic influence on psychiatric disorders and brain structural variation. Integrating multi-scale functional annotations and transcriptomic profiles, we observed that shared genetic loci were enriched in active genomic regions, converged on neurobiological and metabolic pathways, and showed differential expression in postmortem brain tissue from individuals with psychiatric disorders. Cumulatively, these findings provide a significant advance in our understanding of the overlapping polygenic architecture between psychopathology and cortical brain structure.

CEGA: a method for inferring natural selection by comparative population genomic analysis across species

We developed maximum likelihood method for detecting positive selection or balancing selection using multilocus or genomic polymorphism and divergence data from two species. The method is especially useful for investigating natural selection in noncoding regions. Simulations demonstrate that the method outperforms existing methods in detecting both positive and balancing selection. We apply the method to population genomic data from human and chimpanzee. The list of genes identified under selection in the noncoding regions is prominently enriched in pathways related to the brain and nervous system. Therefore, our method will serve as a useful tool for comparative population genomic analysis.