Mendelian randomization analyses support causal relationships between brain imaging-derived phenotypes and risk of psychiatric disorders

Associations Between Temporomandibular Disorders and Brain Imaging-Derived Phenotypes

OBJECTIVE

Temporomandibular disorders (TMD) affect the temporomandibular joint and associated structures. Despite its prevalence and impact on quality of life, the underlying mechanisms of TMD remain unclear. Magnetic resonance imaging studies suggest brain abnormalities in patients with TMD. However, these lines of evidence are essentially observational and cannot infer a causal relationship. This study employs Mendelian randomisation (MR) to probe causal relationships between TMD and brain changes.

METHODS

Genome-wide association study (GWAS) summary statistics for TMD were collected, along with brain imaging-derived phenotypes (IDPs). Instrumental variables were selected from the GWAS summary statistics and used in bidirectional 2-sample MR analyses. The inverse-variance weighted analysis was chosen as the primary method. In addition, false discovery rate (FDR) correction of P value was used.

RESULTS

Eleven IDPs related to brain imaging alterations showed significant causal associations with TMD (P-FDR < .05), validated through sensitivity analysis. In forward MR, the mean thickness of left caudal middle frontal gyrus (OR, 0.76; 95% CI, 0.67-0.87; P-FDR = 1.15  ×  10-2) and the volume of right superior frontal gyrus (OR, 1.24; 95% CI, 1.10-1.39; P-FDR = 2.26  ×  10-2) exerted significant causal effects on TMD. In the reverse MR analysis, TMD exerted a significant causal effect on 9 IDPs, including the mean thickness of the left medial orbitofrontal cortex (β = -0.10; 95% CI, -0.13 to -0.08; P-FDR = 2.06 × 10-11), the volume of the left magnocellular nucleus (β = -0.15; 95% CI, -0.22 to -0.09; P-FDR = 3.26 × 10-4), the mean intensity of the right inferior-lateral ventricle (β = -0.09; 95% CI, -0.14 to -0.04; P-FDR = 2.23 × 10-2), the volume of grey matter in the anterior division of the left superior temporal gyrus (β = 0.09; 95% CI,  0.04-0.14; P-FDR = 1.69 × 10-2), and so forth.

CONCLUSIONS

This study provides genetic evidence supporting the bidirectional causal associations between TMD and brain IDPs, shedding light on potential neurobiological mechanisms underlying TMD development and its relationship with brain structure.

Genetic evidence supports a causal relationship between air pollution and brain imaging-derived phenotypes

BACKGROUND

Observational studies have reported associations between air pollutants and brain imaging-derived phenotypes (IDPs); however, whether this relationship is causal remains uncertain.

METHODS

We conducted bidirectional two-sample Mendelian randomization (MR) analyses to explore the causal relationships between 5 types of air pollutants (N=423,796 to 456,380 individuals) and 587 reliable IDPs (N=33,224 individuals). Two-step MR was also conducted to assess whether the identified effects are mediated through the modulation of circulating cytokines (N=8293).

RESULTS

We found genetic evidence supporting the association of nitrogen oxides (NOx) with mean intra-cellular volume fraction (ICVF) in the left uncinate fasciculus (IVW β=-0.42, 95 % CI -0.62 to -0.23, P=1.51×10-5) and mean fractional anisotropy (FA) in the left uncinate fasciculus (IVW β=-0.42, 95 % CI -0.62 to -0.21, P=4.89×10-5). In further two-step MR analyses, we did not find evidence that genetic predictions of any circulating cytokines mediated the association between NOx and IDPs.

CONCLUSION

This study provides evidence for the association between air pollutants and brain IDPs, emphasizing the importance of controlling air pollution to improve brain health.

Causal relationships involving brain imaging-derived phenotypes based on UKB imaging cohort: a review of Mendelian randomization studies

The UK Biobank (UKB) has the largest adult brain imaging dataset, which encompasses over 40,000 participants. A significant number of Mendelian randomization (MR) studies based on UKB neuroimaging data have been published to validate potential causal relationships identified in observational studies. Relevant articles published before December 2023 were identified following the PRISMA protocol. Included studies (n = 34) revealed that there were causal relationships between various lifestyles, diseases, biomarkers, and brain image-derived phenotypes (BIDPs). In terms of lifestyle habits and environmental factors, there were causal relationships between alcohol consumption, tea intake, coffee consumption, smoking, educational attainment, and certain BIDPs. Additionally, some BIDPs could serve as mediators between leisure/physical inactivity and major depressive disorder. Regarding diseases, BIDPs have been found to have causal relationships not only with Alzheimer's disease, stroke, psychiatric disorders, and migraine, but also with cardiovascular diseases, diabetes, poor oral health, osteoporosis, and ankle sprain. In addition, there were causal relationships between certain biological markers and BIDPs, such as blood pressure, LDL-C, IL-6, telomere length, and more.

Associations between brain imaging-derived phenotypes and cognitive functions

We aimed to evaluate the potential causal relationship between brain imaging-derived phenotypes and cognitive functions via Mendelian randomization analyses. Genetic instruments for 470 brain imaging-derived phenotypes were selected from a genome-wide association study based on the UK Biobank (n = 33,224). Statistics for cognitive functions were obtained from the genome-wide association study based on the UK Biobank. We used the inverse variance weighted Mendelian randomization method to investigate the associations between brain imaging-derived phenotypes and cognitive functions, and reverse Mendelian randomization analyses were performed for significant brain imaging-derived phenotypes to examine the reverse causation for the identified associations. We identified three brain imaging-derived phenotypes to be associated with verbal-numerical reasoning, including cortical surface area of the left fusiform gyrus (beta, 0.18 [95% confidence interval, 0.11 to 0.25], P = 4.74 × 10-7), cortical surface area of the right superior temporal gyrus (beta, 0.25 [95% confidence interval, 0.15 to 0.35], P = 6.30 × 10-7), and orientation dispersion in the left superior longitudinal fasciculus (beta, 0.14 [95% confidence interval, 0.09 to 0.20], P = 8.37 × 10-7). The reverse Mendelian randomization analysis indicated that verbal-numerical reasoning had no effect on these three brain imaging-derived phenotypes. This Mendelian randomization study identified cortical surface area of the left fusiform gyrus, cortical surface area of the right superior temporal gyrus, and orientation dispersion in the left superior longitudinal fasciculus as predictors of verbal-numerical reasoning.

Mendelian randomization analyses reveal causal relationships between brain functional networks and risk of psychiatric disorders

Dysfunction of brain resting-state functional networks has been widely reported in psychiatric disorders. However, the causal relationships between brain resting-state functional networks and psychiatric disorders remain largely unclear. Here we perform bidirectional two-sample Mendelian randomization (MR) analyses to investigate the causalities between 191 resting-state functional magnetic resonance imaging (rsfMRI) phenotypes (n = 34,691 individuals) and 12 psychiatric disorders (n = 14,307 to 698,672 individuals). Forward MR identified 8 rsfMRI phenotypes causally associated with the risk of psychiatric disorders. For example, the increase in the connectivity of motor, subcortical-cerebellum and limbic network was associated with lower risk of autism spectrum disorder. In adddition, increased connectivity in the default mode and central executive network was associated with lower risk of post-traumatic stress disorder and depression. Reverse MR analysis revealed significant associations between 4 psychiatric disorders and 6 rsfMRI phenotypes. For instance, the risk of attention-deficit/hyperactivity disorder increases the connectivity of the attention, salience, motor and subcortical-cerebellum network. The risk of schizophrenia mainly increases the connectivity of the default mode and central executive network and decreases the connectivity of the attention network. In summary, our findings reveal causal relationships between brain functional networks and psychiatric disorders, providing important interventional and therapeutic targets for psychiatric disorders at the brain functional network level.

Revealing brain cell-stratified causality through dissecting causal variants according to their cell-type-specific effects on gene expression

The human brain has been implicated in the pathogenesis of several complex diseases. Taking advantage of single-cell techniques, genome-wide association studies (GWAS) have taken it a step further and revealed brain cell-type-specific functions for disease loci. However, genetic causal associations inferred by Mendelian randomization (MR) studies usually include all instrumental variables from GWAS, which hampers the understanding of cell-specific causality. Here, we developed an analytical framework, Cell-Stratified MR (csMR), to investigate cell-stratified causality through colocalizing GWAS signals with single-cell eQTL from different brain cells. By applying to obesity-related traits, our results demonstrate the cell-type-specific effects of GWAS variants on gene expression, and indicate the benefits of csMR to identify cell-type-specific causal effect that is often hidden from bulk analyses. We also found csMR valuable to reveal distinct causal pathways between different obesity indicators. These findings suggest the value of our approach to prioritize target cells for extending genetic causation studies.

Genetic evidence for the causal relationships between migraine, dementia, and longitudinal brain atrophy

BACKGROUND

Migraine is a neurological disease with a significant genetic component and is characterized by recurrent and prolonged episodes of headache. Previous epidemiological studies have reported a higher risk of dementia in migraine patients. Neuroimaging studies have also shown structural brain atrophy in regions that are common to migraine and dementia. However, these studies are observational and cannot establish causality. The present study aims to explore the genetic causal relationship between migraine and dementia, as well as the mediation roles of brain structural changes in this association using Mendelian randomization (MR).

METHODS

We collected the genome-wide association study (GWAS) summary statistics of migraine and its two subtypes, as well as four common types of dementia, including Alzheimer's disease (AD), vascular dementia, frontotemporal dementia, and Lewy body dementia. In addition, we collected the GWAS summary statistics of seven longitudinal brain measures that characterize brain structural alterations with age. Using these GWAS, we performed Two-sample MR analyses to investigate the causal effects of migraine and its two subtypes on dementia and brain structural changes. To explore the possible mediation of brain structural changes between migraine and dementia, we conducted a two-step MR mediation analysis.

RESULTS

The MR analysis demonstrated a significant association between genetically predicted migraine and an increased risk of AD (OR = 1.097, 95% CI = [1.040, 1.158], p = 7.03 × 10- 4). Moreover, migraine significantly accelerated annual atrophy of the total cortical surface area (-65.588 cm2 per year, 95% CI = [-103.112, -28.064], p = 6.13 × 10- 4) and thalamic volume (-9.507 cm3 per year, 95% CI = [-15.512, -3.502], p = 1.91 × 10- 3). The migraine without aura (MO) subtype increased the risk of AD (OR = 1.091, 95% CI = [1.059, 1.123], p = 6.95 × 10- 9) and accelerated annual atrophy of the total cortical surface area (-31.401 cm2 per year, 95% CI = [-43.990, -18.811], p = 1.02 × 10- 6). The two-step MR mediation analysis revealed that thalamic atrophy partly mediated the causal effect of migraine on AD, accounting for 28.2% of the total effect.

DISCUSSION

This comprehensive MR study provided genetic evidence for the causal effect of migraine on AD and identified longitudinal thalamic atrophy as a potential mediator in this association. These findings may inform brain intervention targets to prevent AD risk in migraine patients.

Unraveling the causal relationships between depression and brain structural imaging phenotypes: A bidirectional Mendelian Randomization study

BACKGROUND

Previous studies have revealed structural brain abnormalities in individuals with depression, but the causal relationship between depression and brain structure remains unclear.

METHODS

A genetic correlation analysis was conducted using summary statistics from the largest genome-wide association studies for depression (N = 674,452) and 1,265 brain structural imaging-derived phenotypes (IDPs, N = 33,224). Subsequently, a bidirectional two-sample Mendelian Randomization (MR) approach was employed to explore the causal relationships between depression and the IDPs that showed genetic correlations with depression. The main MR results were obtained using the inverse variance weighted (IVW) method, and other MR methods were further employed to ensure the reliability of the findings.

RESULTS

Ninety structural IDPs were identified as being genetically correlated with depression and were included in the MR analyses. The IVW MR results indicated that reductions in the volume of several brain regions, including the bilateral subcallosal cortex, right medial orbitofrontal cortex, and right middle-posterior part of the cingulate cortex, were causally linked to an increased risk of depression. Additionally, decreases in surface area of the right middle temporal visual area, right middle temporal cortex, right inferior temporal cortex, and right middle-posterior part of the cingulate cortex were causally associated with a heightened risk of depression. Validation and sensitivity analyses supported the robustness of these findings. However, no evidence was found for a causal effect of depression on structural IDPs.

CONCLUSIONS

Our findings reveal the causal influence of specific brain structures on depression, providing evidence to consider brain structural changes in the etiology and treatment of depression.

Associations of systemic inflammatory regulators with CKD and kidney function: evidence from the bidirectional mendelian randomization study

BACKGROUND

Previous observational studies have reported that systemic inflammatory regulators are related to the development of chronic kidney disease (CKD); however, whether these associations are causal remains unclear. The current study aimed to investigate the potential causal relationships between systemic inflammatory regulators and CKD and kidney function.

METHOD

We performed bidirectional two-sample Mendelian randomization (MR) analyses to infer the underlying causal associations between 41 systemic inflammatory regulators and CKD and kidney function. The inverse-variance weighting (IVW) test was used as the primary analysis method. In addition, sensitivity analyses were executed via the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) test and the weighted median test.

RESULTS

The findings revealed 12 suggestive associations between 11 genetically predicted systemic inflammatory regulators and CKD or kidney function in the forward analyses, including 4 for CKD, 3 for blood urea nitrogen (BUN), 4 for eGFRcrea and 1 for eGFRcys. In the other direction, we identified 6 significant causal associations, including CKD with granulocyte-colony stimulating factor (GCSF) (IVW β = 0.145; 95% CI, 0.042 to 0.248; P = 0.006), CKD with stem cell factor (SCF) (IVW β = 0.228; 95% CI, 0.133 to 0.323; P = 2.40 × 10- 6), eGFRcrea with SCF (IVW β =-2.90; 95% CI, -3.934 to -1.867; P = 3.76 × 10- 8), eGFRcys with GCSF (IVW β =-1.382; 95% CI, -2.404 to -0.361; P = 0.008), eGFRcys with interferon gamma (IFNg) (IVW β =-1.339; 95% CI, -2.313 to -0.366; P = 0.007) and eGFRcys with vascular endothelial growth factor (VEGF) (IVW β =-1.709; 95% CI, -2.720 to -0.699; P = 9.13 × 10- 4).

CONCLUSIONS

Our findings support causal links between systemic inflammatory regulators and CKD or kidney function both in the forward and reverse MR analyses.

Unveiling Promising Neuroimaging Biomarkers for Schizophrenia Through Clinical and Genetic Perspectives

Schizophrenia is a complex and serious brain disorder. Neuroscientists have become increasingly interested in using magnetic resonance-based brain imaging-derived phenotypes (IDPs) to investigate the etiology of psychiatric disorders. IDPs capture valuable clinical advantages and hold biological significance in identifying brain abnormalities. In this review, we aim to discuss current and prospective approaches to identify potential biomarkers for schizophrenia using clinical multimodal neuroimaging and imaging genetics. We first described IDPs through their phenotypic classification and neuroimaging genomics. Secondly, we discussed the applications of multimodal neuroimaging by clinical evidence in observational studies and randomized controlled trials. Thirdly, considering the genetic evidence of IDPs, we discussed how can utilize neuroimaging data as an intermediate phenotype to make association inferences by polygenic risk scores and Mendelian randomization. Finally, we discussed machine learning as an optimum approach for validating biomarkers. Together, future research efforts focused on neuroimaging biomarkers aim to enhance our understanding of schizophrenia.

Genetic architecture of brain morphology and overlap with neuropsychiatric traits

Uncovering the genetic architectures of brain morphology offers valuable insights into brain development and disease. Genetic association studies of brain morphological phenotypes have discovered thousands of loci. However, interpretation of these loci presents a significant challenge. One potential solution is exploring the genetic overlap between brain morphology and disorders, which can improve our understanding of their complex relationships, ultimately aiding in clinical applications. In this review, we examine current evidence on the genetic associations between brain morphology and neuropsychiatric traits. We discuss the impact of these associations on the diagnosis, prediction, and treatment of neuropsychiatric diseases, along with suggestions for future research directions.

Alzheimer's disease as a causal risk factor for diabetic retinopathy: a Mendelian randomization study

Objectives

This study aims to investigate the causal relationship between Alzheimer's Disease (AD) and Diabetic Retinopathy (DR).

Methods

Employing Mendelian Randomization (MR), Generalized Summary-data-based Mendelian Randomization (GSMR), and the MR-Steiger test, this study scrutinizes the genetic underpinnings of the hypothesized causal association between AD and DR, as well as its Proliferative DR (PDR) and Non-Proliferative DR (NPDR) subtypes. Comprehensive data from Genome-Wide Association Studies (GWAS) were analyzed, specifically AD data from the Psychiatric Genomics Consortium (71,880 cases/383,378 controls), and DR, PDR, and NPDR data from both the FinnGen consortium (FinnGen release R8, DR: 5,988 cases/314,042 controls; PDR: 8,383 cases/329,756 controls; NPDR: 3,446 cases/314,042 controls) and the IEU OpenGWAS (DR: 14,584 cases/176,010 controls; PDR: 8,681 cases/204,208 controls; NPDR: 2,026 cases/204,208 controls). The study also incorporated Functional Mapping and Annotation (FUMA) for an in-depth analysis of the GWAS results.

Results

The MR analyses revealed that genetic susceptibility to AD significantly increases the risk of DR, as evidenced by GWAS data from the FinnGen consortium (OR: 2.5090; 95% confidence interval (CI):1.2102-5.2018, false discovery rate P-value (PFDR)=0.0201; GSMR: bxy=0.8936, bxy_se=0.3759, P=0.0174), NPDR (OR: 2.7455; 95% CI: 1.3178-5.7197, PFDR=0.0166; GSMR: bxy=0.9682, bxy_se=0.3802, P=0.0126), and PDR (OR: 2.3098; 95% CI: 1.2411-4.2986, PFDR=0.0164; GSMR: bxy=0.7962, bxy_se=0.3205, P=0.0129) using DR GWAS from FinnGen consortium. These results were corroborated by DR GWAS datasets from IEU OpenGWAS. The MR-Steiger test confirmed a significant association of all identified instrumental variables (IVs) with AD. While a potential causal effect of DR and its subtypes on AD was identified, the robustness of these results was constrained by a low power value. FUMA analysis identified OARD1, NFYA, TREM1 as shared risk genes between DR and AD, suggesting a potential genetic overlap between these complex diseases.

Discussion

This study underscores the contribution of AD to an increased risk of DR, as well as NPDR and PDR subtypes, underscoring the necessity of a holistic approach in the management of patients affected by these conditions.

Homotopic functional connectivity disruptions in schizophrenia and their associated gene expression

It has been revealed that abnormal voxel-mirrored homotopic connectivity (VMHC) is present in patients with schizophrenia, yet there are inconsistencies in the relevant findings. Moreover, little is known about their association with brain gene expression profiles. In this study, transcription-neuroimaging association analyses using gene expression data from Allen Human Brain Atlas and case-control VMHC differences from both the discovery (meta-analysis, including 9 studies with a total of 386 patients and 357 controls) and replication (separate group-level comparisons within two datasets, including a total of 258 patients and 287 controls) phases were performed to identify genes associated with VMHC alterations. Enrichment analyses were conducted to characterize the biological functions and specific expression of identified genes, and Neurosynth decoding analysis was performed to examine the correlation between cognitive-related processes and VMHC alterations in schizophrenia. In the discovery and replication phases, patients with schizophrenia exhibited consistent VMHC changes compared to controls, which were correlated with a series of cognitive-related processes; meta-regression analysis revealed that illness duration was negatively correlated with VMHC abnormalities in the cerebellum and postcentral/precentral gyrus. The abnormal VMHC patterns were stably correlated with 1287 genes enriched for fundamental biological processes like regulation of cell communication, nervous system development, and cell communication. In addition, these genes were overexpressed in astrocytes and immune cells, enriched in extensive cortical regions and wide developmental time windows. The present findings may contribute to a more comprehensive understanding of the molecular mechanisms underlying VMHC alterations in patients with schizophrenia.

Premorbid brain structure influences risk of amyotrophic lateral sclerosis

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a disease of the motor network associated with brain structure and functional connectivity alterations that are implicated in disease progression. Whether such changes have a causal role in ALS, fitting with a postulated influence of premorbid cerebral architecture on the phenotypes associated with neurodegenerative disorders is not known.

METHODS

This study considered causal effects and shared genetic risk of 2240 structural and functional MRI brain scan imaging-derived phenotypes (IDPs) on ALS using two sample Mendelian randomisation, with putative associations further examined with extensive sensitivity analysis. Shared genetic predisposition between IDPs and ALS was explored using genetic correlation analysis.

RESULTS

Increased white matter volume in the cerebral hemispheres was causally associated with ALS. Weaker causal associations were observed for brain stem grey matter volume, parieto-occipital white matter surface and volume of the left thalamic ventral anterior nucleus. Genetic correlation was observed between ALS and intracellular volume fraction and isotropic free water volume fraction within the posterior limb of the internal capsule.

CONCLUSIONS

This study provides evidence that premorbid brain structure, in particular white matter volume, contributes to the risk of ALS.

Causal Relationships Between Screen Use, Reading, and Brain Development in Early Adolescents

The rise of new media has greatly changed the lifestyles, leading to increased time on these platforms and less time spent reading. This shift has particularly profound impacts on early adolescents, who are in a critical stage of brain development. Previous studies have found associations between screen use and mental health, but it remains unclear whether screen use is the direct cause of the outcomes. Here, the Adolescent Brain Cognitive Development (ABCD) dataset is utlized to examine the causal relationships between screen use and brain development. The results revealed adverse causal effects of screen use on language ability and specific behaviors in early adolescents, while reading has positive causal effects on their language ability and brain volume in the frontal and temporal regions. Interestingly, increased screen use is identified as a result, rather than a cause, of certain behaviors such as rule-breaking and aggressive behaviors. Furthermore, the analysis uncovered an indirect influence of screen use, mediated by changes in reading habits, on brain development. These findings provide new evidence for the causal influences of screen use on brain development and highlight the importance of monitoring media use and related habit change in children.

Associations of the circulating levels of cytokines with risk of systemic sclerosis: a bidirectional Mendelian randomized study

Objective

Systemic sclerosis(SSc) remains unclear, studies suggest that inflammation may be linked to its pathogenesis. Hence, we conducted a bidirectional Mendelian randomization (MR) analysis to evaluate the association between cytokine and growth factor cycling levels and the risk of SSc onset.

Methods

In our study, the instrumental variables(IVs) for circulating cytokines were sourced from the genome-wide association study (GWAS) dataset of 8293 Finnish individuals. The SSc data comprised 302 cases and 213145 controls, and was included in the GWAS dataset. We employed four methods for the MR analysis: MR Egger, Inverse variance weighted (IVW), Weighted medium, and Weighted Mode, with IVW being the primary analytical method. Sensitivity analyses were performed using heterogeneity testing, horizontal pleiotropy testing, and the Leave One Out (LOO) method. We also conducted a reverse MR analysis to determine any reverse causal relationship between SSc and circulating cytokines.

Results

After Bonferroni correction, MR analysis revealed that the Interleukin-5 (IL-5) cycle level was associated with a reduced risk of SSc [odds ratio (OR)=0.48,95% confidence interval (CI): 0.27-0.84, P=0.01]. It also indicated that the Stem cell growth factor beta (SCGF-β) cycling level might elevate the risk of SSc (OR = 1.36, 95% CI: 1.01-1.83, P = 0.04). However, the reverse MR analysis did not establish a causal relationship between SSc and circulating cytokine levels. Additionally, sensitivity analysis outcomes affirm the reliability of our results.

Conclusion

Our MR study suggests potential causal relationships between IL-5, SCGF-β, and the risk of SSc. Further research is essential to determine how IL-5 and SCGF-β influence the development of SSc.

Changes in iron load in specific brain areas lead to neurodegenerative diseases of the central nervous system

The causes of neurodegenerative diseases remain largely elusive, increasing their personal and societal impacts. To reveal the causal effects of iron load on Parkinson's disease (PD), Alzheimer's disease (AD), amyotrophic lateral sclerosis and multiple sclerosis, we used Mendelian randomisation and brain imaging data from a UK Biobank genome-wide association study of 39,691 brain imaging samples (predominantly of European origin). Using susceptibility-weighted images, which reflect iron load, we analysed genetically significant brain regions. Inverse variance weighting was used as the main estimate, while MR Egger and weighted median were used to detect heterogeneity and pleiotropy. Nine clear associations were obtained. For AD and PD, an increased iron load was causative: the right pallidum for AD and the right caudate, left caudate and right accumbens for PD. However, a reduced iron load was identified in the right and left caudate for multiple sclerosis, the bilateral hippocampus for mixed vascular dementia and the left thalamus and bilateral accumbens for subcortical vascular dementia. Thus, changes in iron load in different brain regions have causal effects on neurodegenerative diseases. Our results are crucial for understanding the pathogenesis and investigating the treatment of these diseases.

Genetic analyses identify brain imaging-derived phenotypes associated with the risk of intracerebral hemorrhage

Previous observational studies have reported associations between brain imaging-derived phenotypes (IDPs) and intracerebral hemorrhage (ICH), but the causality between them remains uncertain. We aimed to investigate the potential causal relationship between IDPs and ICH by a two-sample Mendelian randomization (MR) study. We selected genetic instruments for 363 IDPs from a genome-wide association study (GWASs) based on the UK Biobank (n = 33,224). Summary-level data on ICH was derived from a European-descent GWAS with 1,545 cases and 1,481 controls. Inverse variance weighted MR method was applied in the main analysis to investigate the associations between IDPs and ICH. Reverse MR analyses were performed for significant IDPs to examine the reverse causation for the identified associations. Among the 363 IDPs, isotropic or free water volume fraction (ISOVF) in the anterior limb of the left internal capsule was identified to be associated with the risk of ICH (OR per 1-SD increase, 4.62 [95% CI, 2.18-9.81], P = 6.63 × 10-5). In addition, the reverse MR analysis indicated that ICH had no effect on ISOVF in the anterior limb of the left internal capsule (beta, 0.010 [95% CI, -0.010-0.030], P = 0.33). MR-Egger regression analysis showed no directional pleiotropy for the association between ISOVF and ICH, and sensitivity analyses with different MR models further confirmed these findings. ISOVF in the anterior limb of the left internal capsule might be a potential causal mediator of ICH, which may provide predictive guidance for the prevention of ICH. Further studies are warranted to replicate our findings and clarify the underlying mechanisms.

Genetic analyses identify brain imaging-derived phenotypes associated with the risk of amyotrophic lateral sclerosis

Brain imaging-derived phenotypes have been suggested to be associated with amyotrophic lateral sclerosis in observational studies, but whether these associations are causal remains unclear. We aimed to assess the potential bidirectional causal associations between imaging-derived phenotypes and amyotrophic lateral sclerosis using bidirectional 2-sample Mendelian randomization analyses. Summary statistics for 469 imaging-derived phenotypes (33,224 individuals) and amyotrophic lateral sclerosis (20,806 cases and 59,804 controls) were obtained from 2 large-scale genome-wide association studies of European ancestry. We used the inverse-variance weighted Mendelian randomization method in the main analysis to assess the bidirectional associations between imaging-derived phenotypes and amyotrophic lateral sclerosis, followed by several sensitivity analyses for robustness validation. In the forward Mendelian randomization analyses, we found that genetically determined high orientation dispersion index in the right cerebral peduncle was associated with the increased risk of amyotrophic lateral sclerosis (odds ratio = 1.30, 95% confidence interval = 1.16-1.45, P = 2.26 × 10-6). In addition, the reverse Mendelian randomization analysis indicated that amyotrophic lateral sclerosis had no effect on 469 imaging-derived phenotypes. Mendelian randomization-Egger regression analysis showed no directional pleiotropy for the association between high orientation dispersion index in the right cerebral peduncle and amyotrophic lateral sclerosis, and sensitivity analyses with different Mendelian randomization models further confirmed these findings. The present systematic bidirectional Mendelian randomization analysis showed that high orientation dispersion index in the right cerebral peduncle might be the potential causal mediator of amyotrophic lateral sclerosis, which may provide predictive guidance for the prevention of amyotrophic lateral sclerosis. Further studies are warranted to replicate our findings and clarify the underlying mechanisms.

The genetic architecture of the human hypothalamus and its involvement in neuropsychiatric behaviours and disorders

Despite its crucial role in the regulation of vital metabolic and neurological functions, the genetic architecture of the hypothalamus remains unknown. Here we conducted multivariate genome-wide association studies (GWAS) using hypothalamic imaging data from 32,956 individuals to uncover the genetic underpinnings of the hypothalamus and its involvement in neuropsychiatric traits. There were 23 significant loci associated with the whole hypothalamus and its subunits, with functional enrichment for genes involved in intracellular trafficking systems and metabolic processes of steroid-related compounds. The hypothalamus exhibited substantial genetic associations with limbic system structures and neuropsychiatric traits including chronotype, risky behaviour, cognition, satiety and sympathetic-parasympathetic activity. The strongest signal in the primary GWAS, the ADAMTS8 locus, was replicated in three independent datasets (N = 1,685-4,321) and was strengthened after meta-analysis. Exome-wide association analyses added evidence to the association for ADAMTS8, and Mendelian randomization showed lower ADAMTS8 expression with larger hypothalamic volumes. The current study advances our understanding of complex structure-function relationships of the hypothalamus and provides insights into the molecular mechanisms that underlie hypothalamic formation.

The potential role of gray matter volume differences in the association between smoking and depression: A narrative review

Tobacco use and major depression are both leading contributors to the global burden of disease and are also highly comorbid. Previous research indicates bi-directional causality between tobacco use and depression, but the mechanisms that underlie this causality are unclear, especially for the causality from tobacco use to depression. Here we narratively review the available evidence for a potential causal role of gray matter volume in the association. We summarize the findings of large existing neuroimaging meta-analyses, studies in UK Biobank, and the Enhancing NeuroImaging Genetics through MetaAnalysis (ENIGMA) consortium and assess the overlap in implicated brain areas. In addition, we review two types of methods that allow us more insight into the causal nature of associations between brain volume and depression/smoking: longitudinal studies and Mendelian Randomization studies. While the available evidence suggests overlap in the alterations in brain volumes implicated in tobacco use and depression, there is a lack of research examining the underlying pathophysiology. We conclude with recommendations on (genetically-informed) causal inference methods useful for studying these associations.

An augmented Mendelian randomization approach provides causality of brain imaging features on complex traits in a single biobank-scale dataset

Mendelian randomization (MR) is an effective approach for revealing causal risk factors that underpin complex traits and diseases. While MR has been more widely applied under two-sample settings, it is more promising to be used in one single large cohort given the rise of biobank-scale datasets that simultaneously contain genotype data, brain imaging data, and matched complex traits from the same individual. However, most existing multivariable MR methods have been developed for two-sample setting or a small number of exposures. In this study, we introduce a one-sample multivariable MR method based on partial least squares and Lasso regression (MR-PL). MR-PL is capable of considering the correlation among exposures (e.g., brain imaging features) when the number of exposures is extremely upscaled, while also correcting for winner's curse bias. We performed extensive and systematic simulations, and demonstrated the robustness and reliability of our method. Comprehensive simulations confirmed that MR-PL can generate more precise causal estimates with lower false positive rates than alternative approaches. Finally, we applied MR-PL to the datasets from UK Biobank to reveal the causal effects of 36 white matter tracts on 180 complex traits, and showed putative white matter tracts that are implicated in smoking, blood vascular function-related traits, and eating behaviors.

The genetic relationships between brain structure and schizophrenia

Genetic risks for schizophrenia are theoretically mediated by genetic effects on brain structure but it has been unclear which genes are associated with both schizophrenia and cortical phenotypes. We accessed genome-wide association studies (GWAS) of schizophrenia (N = 69,369 cases; 236,642 controls), and of three magnetic resonance imaging (MRI) metrics (surface area, cortical thickness, neurite density index) measured at 180 cortical areas (N = 36,843, UK Biobank). Using Hi-C-coupled MAGMA, 61 genes were significantly associated with both schizophrenia and one or more MRI metrics. Whole genome analysis with partial least squares demonstrated significant genetic covariation between schizophrenia and area or thickness of most cortical regions. Genetic similarity between cortical areas was strongly coupled to their phenotypic covariance, and genetic covariation between schizophrenia and brain phenotypes was strongest in the hubs of structural covariance networks. Pleiotropically associated genes were enriched for neurodevelopmental processes and positionally concentrated in chromosomes 3p21, 17q21 and 11p11. Mendelian randomization analysis indicated that genetically determined variation in a posterior cingulate cortical area could be causal for schizophrenia. Parallel analyses of GWAS on bipolar disorder, Alzheimer's disease and height showed that pleiotropic association with MRI metrics was stronger for schizophrenia compared to other disorders.

Mendelian randomization analysis implicates bidirectional associations between brain imaging-derived phenotypes and ischemic stroke

Brian imaging-derived phenotypes (IDPs) have been suggested to be associated with ischemic stroke, but the causality between them remains unclear. In this bidirectional two-sample Mendelian randomization (MR) study, we explored the potential causal relationship between 461 imaging-derived phenotypes (n = 33,224, UK Biobank) and ischemic stroke (n = 34,217 cases/406,111 controls, Multiancestry Genome-Wide Association Study of Stroke). Forward MR analyses identified five IDPs associated with ischemic stroke, including mean diffusivity (MD) in the right superior fronto-occipital fasciculus (1.22 [95% CI, 1.11-1.34]), MD in the left superior fronto-occipital fasciculus (1.30 [1.17-1.44]), MD in the anterior limb of the right internal capsule (1.36 [1.22-1.51]), MD in the right anterior thalamic radiation (1.17 [1.09-1.26]), and MD in the right superior thalamic radiation (1.23 [1.11-1.35]). In the reverse MR analyses, ischemic stroke was identified to be associated with three IDPs, including high isotropic or free water volume fraction in the body of corpus callosum (beta, 0.189 [95% confidence interval, 0.107-0.271]), orientation dispersion index in the pontine crossing tract (0.175 [0.093-0.257]), and volume of the third ventricle (0.219 [0.138-0.301]). This bidirectional two-sample MR study suggested five predictors and three diagnostic markers for ischemic stroke at the brain-imaging level. Further studies are warranted to replicate our findings and clarify underlying mechanisms.

Inferring the genetic relationship between brain imaging-derived phenotypes and risk of complex diseases by Mendelian randomization and genome-wide colocalization

Observational studies consistently disclose brain imaging-derived phenotypes (IDPs) as critical markers for early diagnosis of both brain disorders and cardiovascular diseases. However, it remains unclear about the shared genetic landscape between brain IDPs and the risk of brain disorders and cardiovascular diseases, restricting the applications of potential diagnostic techniques through brain IDPs. Here, we reported genetic correlations and putative causal relationships between 921 brain IDPs, 20 brain disorders and six cardiovascular diseases by leveraging their large-scale genome-wide association study (GWAS) summary statistics. Applications of Mendelian randomization (MR) identified significant putative causal effects of multiple region-specific brain IDPs in relation to the increased risks for amyotrophic lateral sclerosis (ALS), major depressive disorder (MDD), autism spectrum disorder (ASD) and schizophrenia (SCZ). We also found brain IDPs specifically from temporal lobe as a putatively causal consequence of hypertension. The genome-wide colocalization analysis identified three genomic regions in which MDD, ASD and SCZ colocalized with the brain IDPs, and two novel SNPs to be associated with ASD, SCZ, and multiple brain IDPs. Furthermore, we identified a list of candidate genes involved in the shared genetics underlying pairs of brain IDPs and MDD, ASD, SCZ, ALS and hypertension. Our results provide novel insights into the genetic relationships between brain disorders and cardiovascular diseases and brain IDP, which may server as clues for using brain IDPs to predict risks of diseases.

Timing of lifespan influences on brain and cognition

Modifiable risk and protective factors for boosting brain and cognitive development and preventing neurodegeneration and cognitive decline are embraced in neuroimaging studies. We call for sobriety regarding the timing and quantity of such influences on brain and cognition. Individual differences in the level of brain and cognition, many of which present already at birth and early in development, appear stable, larger, and more pervasive than differences in change across the lifespan. Incorporating early-life factors, including genetics, and investigating both level and change will reduce the risk of ascribing undue importance and causality to proximate factors in adulthood and older age. This has implications for both mechanistic understanding and prevention.

Sleep disorders causally affect the brain cortical structure: A Mendelian randomization study

BACKGROUND

s: Previous studies have reported that patients with sleep disorders have altered brain cortical structures. However, the causality has not been determined. We performed a two-sample Mendelian randomization (MR) to reveal the causal effect of sleep disorders on brain cortical structure.

METHODS

We included as exposures 11 phenotypes of sleep disorders including subjective and objective sleep duration, insomnia symptom and poor sleep efficiency, daytime sleepiness (narcolepsy)/napping, morning/evening preference, and four sleep breathing related traits from nine European-descent genome-wide association studies (GWASs). Further, outcome variables were provided by ENIGMA Consortium GWAS for full brain and 34 region-specific cortical thickness (TH) and surface area (SA) of grey matter. Inverse-variance weighted (IVW) was used as the primary estimate whereas alternative MR methods were implemented as sensitivity analysis approaches to ensure results robustness.

RESULTS

At the global level, both self-reported or accelerometer-measured shorter sleep duration decreases the thickness of full brain both derived from self-reported data (βIVW = 0.03 mm, standard error (SE) = 0.02, P = 0.038; βIVW = 0.02 mm, SE = 0.01, P = 0.010). At the functional level, there were 66 associations of suggestive evidence of causality. Notably, one robust evidence after multiple testing correction (1518 tests) suggests the without global weighted SA of superior parietal lobule was influenced significantly by sleep efficiency (βIVW = -285.28 mm2, SE = 68.59, P = 3.2 × 10-5).

CONCLUSIONS

We found significant evidence that shorter sleep duration, as estimated by self-reported interview and accelerometer measurements, was causally associated with atrophy in the entire human brain.

Correlations between schizophrenia and lichen planus: a two-sample bidirectional Mendelian randomization study

Background

Several existing studies have shown a correlation between schizophrenia and lichen planus (LP). However, the causality of this relationship remains uncertain. Thus, this study aimed to examine the causal association between schizophrenia and LP.

Methods

A two-sample Mendelian randomization (MR) study was carried out to investigate whether schizophrenia is causally related to LP and vice versa, and genetic variants in this study were taken from previous genome-wide association studies. We used the inverse variance weighted (IVW) method as the main analysis. Furthermore, several sensitivity analyses were performed to assess heterogeneity, horizontal pleiotropy, and stability.

Results

Our results show that schizophrenia has a protective effect on LP (OR = 0.881, 95%CI = 0.795-0.975, p = 0.015). Conversely, we observed no significant relationship between LP and schizophrenia in reverse MR analysis (OR = 0.934, 95%CI = 0.851-1.026, p = 0.156).

Conclusion

Our two-sample Mendelian randomization study supports a significant causal relationship between LP and schizophrenia and finds that schizophrenia can reduce the incidence of LP. This is in contrast to previous findings and provides new insights into the relationship between LP and schizophrenia, but the exact mechanism needs further investigation.

Mendelian randomization and transcriptomic analysis reveal an inverse causal relationship between Alzheimer's disease and cancer

BACKGROUND

Alzheimer's disease (AD) and cancer are common age-related diseases, and epidemiological evidence suggests an inverse relationship between them. However, investigating the potential mechanism underlying their relationship remains insufficient.

METHODS

Based on genome-wide association summary statistics for 42,034 AD patients and 609,951 cancer patients from the GWAS Catalog using the two-sample Mendelian randomization (MR) method. Moreover, we utilized two-step MR to identify metabolites mediating between AD and cancer. Furthermore, we employed colocalization analysis to identify genes whose upregulation is a risk factor for AD and demonstrated the genes' upregulation to be a favorable prognostic factor for cancer by analyzing transcriptomic data for 33 TCGA cancer types.

RESULTS

Two-sample MR analysis revealed a significant causal influence for increased AD risk on reduced cancer risk. Two-step MR analysis identified very low-density lipoprotein (VLDL) as a key mediator of the negative cause-effect relationship between AD and cancer. Colocalization analysis uncovered PVRIG upregulation to be a risk factor for AD. Transcriptomic analysis showed that PVRIG expression had significant negative correlations with stemness scores, and positive correlations with antitumor immune responses and overall survival in pan-cancer and multiple cancer types.

CONCLUSION

AD may result in lower cancer risk. VLDL is a significant intermediate variable linking AD with cancer. PVRIG abundance is a risk factor for AD but a protective factor for cancer. This study demonstrates a causal influence for AD on cancer and provides potential molecular connections between both diseases.

Assessment of bidirectional relationships between brain imaging-derived phenotypes and stroke: a Mendelian randomization study

BACKGROUND

Stroke is a major cause of mortality and long-term disability worldwide. Whether the associations between brain imaging-derived phenotypes (IDPs) and stroke are causal is uncertain.

METHODS

We performed two-sample bidirectional Mendelian randomization (MR) analyses to explore the causal associations between IDPs and stroke. Summary data of 587 brain IDPs (up to 33,224 individuals) from the UK Biobank and five stroke types (sample size range from 301,663 to 446,696, case number range from 5,386 to 40,585) from the MEGASTROKE consortium were used.

RESULTS

Forward MR indicated 14 IDPs belong to projection fibers or association fibers were associated with stroke. For example, higher genetically determined mean diffusivity (MD) in the right external capsule was causally associated with an increased risk of small vessel stroke (IVW OR = 2.76, 95% CI 2.07 to 3.68, P = 5.87 × 10^-12). Reverse MR indicated that genetically determined higher risk of any ischemic stroke was associated with increased isotropic or free water volume fraction (ISOVF) in body of corpus callosum (IVW β = 0.23, 95% CI 0.14 to 0.33, P = 3.22 × 10^-7). This IDP is a commissural fiber and it is not included in the IDPs identified by forward MR.

CONCLUSIONS

We identified 14 IDPs with statistically significant evidence of causal effects on stroke or stroke subtypes. We also identified potential causal effects of stroke on one IDP of commissural fiber. These findings might guide further work toward identifying preventative strategies at the brain imaging levels.

Dissecting the causal association between social or physical inactivity and depression: a bidirectional two-sample Mendelian Randomization study

A growing body of research suggests that social or physical activity can affect the risk of Major depressive disorder (MDD). However, the bidirectional relationship between them remains to be clarified further, especially between inactivity and MDD. Here, we performed a two-sample Mendelian Randomization analysis using genetic variants associated with social/physical activities and MDD, and assessed the mediating effect of obesity-related measures and brain imaging phenotypes. The dataset on MDD, social activities, and physical activities included 500,199; 461,369; 460,376 individuals, respectively. Information regarding body mass index (BMI), body fat percentage (BFP), IDPs for 454,633; 461,460; 8,428 participants, respectively. We identified bidirectional causal relationships between sport clubs or gyms, strenuous sports, heavy do-it-youself, other exercises and MDD. We also observed that leisure/social inactivity (odds ratio [OR] = 1.64; P = 5.14 × 10^-5) or physical inactivity (OR = 3.67; P = 1.99 × 10^-5) caused an increased risk of MDD, which were partially mediated by BMI or BFP and masked by the weighted-mean orientation dispersion index of left acoustic radiation or volume of right caudate. Furthermore, we discovered that MDD increased the risk of leisure/social inactivity (OR = 1.03; P = 9.89 × 10^-4) or physical inactivity (OR = 1.01; P = 7.96 × 10^-4). In conclusions, we found that social/physical activities reduced the risk of MDD, while MDD in turn hindered social/physical activities. Inactivity may increase the risk of MDD, which was mediated or masked by brain imaging phenotypes. These results help to understand the manifestations of MDD and provide evidence and direction for the advancement of intervention and prevention.

Causal relationships between migraine and microstructural white matter: a Mendelian randomization study

BACKGROUND

Migraine is a disabling neurological disorder with the pathophysiology yet to be understood. The microstructural alteration in brain white matter (WM) has been suggested to be related to migraine in recent studies, but these evidence are observational essentially and cannot infer a causal relationship. The present study aims to reveal the causal relationship between migraine and microstructural WM using genetic data and Mendelian randomization (MR).

METHODS

We collected the Genome-wide association study (GWAS) summary statistics of migraine (48,975 cases / 550,381 controls) and 360 WM imaging-derived phenotypes (IDPs) (31,356 samples) that were used to measure microstructural WM. Based on instrumental variables (IVs) selected from the GWAS summary statistics, we conducted bidirectional two-sample MR analyses to infer bidirectional causal associations between migraine and microstructural WM. In forward MR analysis, we inferred the causal effect of microstructural WM on migraine by reporting the odds ratio (OR) that quantified the risk change of migraine for per 1 standard deviation (SD) increase of IDPs. In reverse MR analysis, we inferred the causal effect of migraine on microstructural WM by reporting the β value that represented SDs of changes in IDPs were caused by migraine.

RESULTS

Three WM IDPs showed significant causal associations (p < 3.29 × 10- 4, Bonferroni correction) with migraine and were proved to be reliable via sensitivity analysis. The mode of anisotropy (MO) of left inferior fronto-occipital fasciculus (OR = 1.76, p = 6.46 × 10- 5) and orientation dispersion index (OD) of right posterior thalamic radiation (OR = 0.78, p = 1.86 × 10- 4) exerted significant causal effects on migraine. Migraine exerted a significant causal effect on the OD of left superior cerebellar peduncle (β = - 0.09, p = 2.78 × 10- 4).

CONCLUSIONS

Our findings provided genetic evidence for the causal relationships between migraine and microstructural WM, bringing new insights into brain structure for the development and experience of migraine.