Evidence supports a causal association between allele-specific vitamin D receptor binding and multiple sclerosis among Europeans.

Although evidence exists for a causal association between 25-hydroxyvitamin D (25(OH)D) serum levels, and multiple sclerosis (MS), the role of variation in vitamin D receptor (VDR) binding in MS is unknown. Here, we leveraged previously identified variants associated with allele imbalance in VDR binding (VDR-binding variant; VDR-BV) in ChIP-exo data from calcitriol-stimulated lymphoblastoid cell lines and 25(OH)D serum levels from genome-wide association studies to construct genetic instrumental variables (GIVs). GIVs are composed of one or more genetic variants that serve as proxies for exposures of interest. Here, GIVs for both VDR-BVs and 25(OH)D were used in a two-sample Mendelian Randomization study to investigate the relationship between VDR binding at a locus, 25(OH)D serum levels, and MS risk. Data for 13,598 MS cases and 38,887 controls of European ancestry from Kaiser Permanente Northern California, Swedish MS studies, and the UK Biobank were included. We estimated the association between each VDR-BV GIV and MS. Significant interaction between a VDR-BV GIV and a GIV for serum 25OH(D) was evidence for a causal association between VDR-BVs and MS unbiased by pleiotropy. We observed evidence for associations between two VDR-BVs (rs2881514, rs2531804) and MS after correction for multiple tests. There was evidence of interaction between rs2881514 and a 25(OH)D GIV, providing evidence of a causal association between rs2881514 and MS. This study is the first to demonstrate evidence that variation in VDR binding at a locus contributes to MS risk. Our results are relevant to other autoimmune diseases in which vitamin D plays a role.

Identifying covariate-related subnetworks for whole-brain connectome analysis.

Whole-brain connectome data characterize the connections among distributed neural populations as a set of edges in a large network, and neuroscience research aims to systematically investigate associations between brain connectome and clinical or experimental conditions as covariates. A covariate is often related to a number of edges connecting multiple brain areas in an organized structure. However, in practice, neither the covariate-related edges nor the structure is known. Therefore, the understanding of underlying neural mechanisms relies on statistical methods that are capable of simultaneously identifying covariate-related connections and recognizing their network topological structures. The task can be challenging because of false-positive noise and almost infinite possibilities of edges combining into subnetworks. To address these challenges, we propose a new statistical approach to handle multivariate edge variables as outcomes and output covariate-related subnetworks. We first study the graph properties of covariate-related subnetworks from a graph and combinatorics perspective and accordingly bridge the inference for individual connectome edges and covariate-related subnetworks. Next, we develop efficient algorithms to exact covariate-related subnetworks from the whole-brain connectome data with an $\ell_0$ norm penalty. We validate the proposed methods based on an extensive simulation study, and we benchmark our performance against existing methods. Using our proposed method, we analyze two separate resting-state functional magnetic resonance imaging data sets for schizophrenia research and obtain highly replicable disease-related subnetworks.

Microglial type I interferon signaling mediates chronic stress-induced synapse loss and social behavior deficits.

Inflammation and synapse loss have been associated with deficits in social behavior and are involved in pathophysiology of many neuropsychiatric disorders. Synapse loss, characterized by reduction in dendritic spines can significantly disrupt synaptic connectivity and neural circuitry underlying social behavior. Chronic stress is known to induce loss of spines and dendrites in the prefrontal cortex (PFC), a brain region implicated in social behavior. However, the underlying mechanisms are not well understood. In the present study, we investigated the role of type I Interferon (IFN-I) signaling in chronic unpredictable stress (CUS)-induced synapse loss and behavior deficits in mice. We found increased expression of type I IFN receptor (IFNAR) in microglia following CUS. Conditional knockout of microglial IFNAR in adult mice rescued CUS-induced social behavior deficits and synapse loss. Bulk RNA sequencing data show that microglial IFNAR deletion attenuated CUS-mediated changes in the expression of genes such as Keratin 20 (Krt20), Claudin-5 (Cldn5) and Nuclear Receptor Subfamily 4 Group A Member 1 (Nr4a1) in the PFC. Cldn5 and Nr4a1 are known for their roles in synaptic plasticity. Krt20 is an intermediate filament protein responsible for the structural integrity of epithelial cells. The reduction in Krt20 following CUS presents a novel insight into the potential contribution of cytokeratin in stress-induced alterations in neuroplasticity. Overall, these results suggest that microglial IFNAR plays a critical role in regulating synaptic plasticity and social behavior deficits associated with chronic stress conditions.

Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study.

Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenia's alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia.

Next-generation characterization of the Cancer Cell Line Encyclopedia.

Large panels of comprehensively characterized human cancer models, including the Cancer Cell Line Encyclopedia (CCLE), have provided a rigorous framework with which to study genetic variants, candidate targets, and small-molecule and biological therapeutics and to identify new marker-driven cancer dependencies. To improve our understanding of the molecular features that contribute to cancer phenotypes, including drug responses, here we have expanded the characterizations of cancer cell lines to include genetic, RNA splicing, DNA methylation, histone H3 modification, microRNA expression and reverse-phase protein array data for 1,072 cell lines from individuals of various lineages and ethnicities. Integration of these data with functional characterizations such as drug-sensitivity, short hairpin RNA knockdown and CRISPR-Cas9 knockout data reveals potential targets for cancer drugs and associated biomarkers. Together, this dataset and an accompanying public data portal provide a resource for the acceleration of cancer research using model cancer cell lines.

Reciprocal relationships between stress and depressive symptoms: the essential role of the nucleus accumbens.

BACKGROUND: Stress and depression have a reciprocal relationship, but the neural underpinnings of this reciprocity are unclear. We investigated neuroimaging phenotypes that facilitate the reciprocity between stress and depressive symptoms. METHODS: In total, 22 195 participants (52.0% females) from the population-based UK Biobank study completed two visits (initial visit: 2006-2010, age = 55.0 ± 7.5 [40-70] years; second visit: 2014-2019; age = 62.7 ± 7.5 [44-80] years). Structural equation modeling was used to examine the longitudinal relationship between self-report stressful life events (SLEs) and depressive symptoms. Cross-sectional data were used to examine the overlap between neuroimaging correlates of SLEs and depressive symptoms on the second visit among 138 multimodal imaging phenotypes. RESULTS: Longitudinal data were consistent with significant bidirectional causal relationship between SLEs and depressive symptoms. In cross-sectional analyses, SLEs were significantly associated with lower bilateral nucleus accumbal volume and lower fractional anisotropy of the forceps major. Depressive symptoms were significantly associated with extensive white matter hyperintensities, thinner cortex, lower subcortical volume, and white matter microstructural deficits, mainly in corticostriatal-limbic structures. Lower bilateral nucleus accumbal volume were the only imaging phenotypes with overlapping effects of depressive symptoms and SLEs (B = -0.032 to -0.023, p = 0.006-0.034). Depressive symptoms and SLEs significantly partially mediated the effects of each other on left and right nucleus accumbens volume (proportion of effects mediated = 12.7-14.3%, p < 0.001-p = 0.008). For the left nucleus accumbens, post-hoc seed-based analysis showed lower resting-state functional connectivity with the left orbitofrontal cortex (cluster size = 83 voxels, p = 5.4 × 10-5) in participants with high v. no SLEs. CONCLUSIONS: The nucleus accumbens may play a key role in the reciprocity between stress and depressive symptoms.

Genome-wide significant risk loci for mood disorders in the Old Order Amish founder population.

Genome-wide association studies (GWAS) of mood disorders in large case-control cohorts have identified numerous risk loci, yet pathophysiological mechanisms remain elusive, primarily due to the very small effects of common variants. We sought to discover risk variants with larger effects by conducting a genome-wide association study of mood disorders in a founder population, the Old Order Amish (OOA, n = 1,672). Our analysis revealed four genome-wide significant risk loci, all of which were associated with >2-fold relative risk. Quantitative behavioral and neurocognitive assessments (n = 314) revealed effects of risk variants on sub-clinical depressive symptoms and information processing speed. Network analysis suggested that OOA-specific risk loci harbor novel risk-associated genes that interact with known neuropsychiatry-associated genes via gene interaction networks. Annotation of the variants at these risk loci revealed population-enriched, non-synonymous variants in two genes encoding neurodevelopmental transcription factors, CUX1 and CNOT1. Our findings provide insight into the genetic architecture of mood disorders and a substrate for mechanistic and clinical studies.

A multivariate to multivariate approach for voxel-wise genome-wide association analysis.

The joint analysis of imaging-genetics data facilitates the systematic investigation of genetic effects on brain structures and functions with spatial specificity. We focus on voxel-wise genome-wide association analysis, which may involve trillions of single nucleotide polymorphism (SNP)-voxel pairs. We attempt to identify underlying organized association patterns of SNP-voxel pairs and understand the polygenic and pleiotropic networks on brain imaging traits. We propose a bi-clique graph structure (ie, a set of SNPs highly correlated with a cluster of voxels) for the systematic association pattern. Next, we develop computational strategies to detect latent SNP-voxel bi-cliques and an inference model for statistical testing. We further provide theoretical results to guarantee the accuracy of our computational algorithms and statistical inference. We validate our method by extensive simulation studies, and then apply it to the whole genome genetic and voxel-level white matter integrity data collected from 1052 participants of the human connectome project. The results demonstrate multiple genetic loci influencing white matter integrity measures on splenium and genu of the corpus callosum.

History of suicidal behavior and clozapine prescribing among people with schizophrenia in China: a cohort study.

BACKGROUND: Clozapine is an off-label drug used in most countries to prevent suicide in individuals with schizophrenia. However, few studies have reported real-world prescription practices. This study aimed to explore the association between a history of suicidal behavior and clozapine prescribing during eight weeks of hospitalization for individuals with early-stage schizophrenia. METHODS: This observational cohort study used routine health data collected from a mental health hospital in Beijing, China. The study included 1057 inpatients who had schizophrenia onset within 3 years. History of suicidal behavior was coded from reviewing medical notes according to the Columbia Suicide Severity Rating Scale. Information on antipsychotic use during hospitalization was extracted from the prescription records. Time to clozapine use was analyzed using Cox regression models adjusted for sociodemographic and clinical covariates. RESULTS: The prevalence rates of self-harm, suicidal behavior, and suicide attempt were 12.3%, 7.5%, and 5.4%, respectively. A history of self-harm history was positively associated with clozapine uses upon admission (4.1% vs. 0.8%, exact p = 0.009). Among those who had not used clozapine and had no clozapine contraindication, A history of suicidal behavior increased the possibility of switch to clozapine within 56 days after admission (Hazard Ratio[95% CI], 6.09[2.08-17.83]) or during hospitalization (4.18[1.62-10.78]). CONCLUSION: The use of clozapine for early-stage schizophrenia was more frequent among those with suicidal behavior than among those without suicidal behavior in China, although the drug instructions do not label its use for suicide risk.

Neglected Right Hemidiaphragmatic Angle Soft Tissue Shadow in a Renal Transplant Recipient Diagnosed as Lymphoma.

BACKGROUND: Post-transplant lymphoproliferative disorders are characterized by atypical clinical manifestations, high mortality, and missed diagnosis rates. METHODS: We report a case of renal transplantation in a patient with unexplained soft-tissue nodular shadows, and the type of the post-transplant abnormal soft-tissue shadows was clarified by puncture biopsy. RESULTS: The pathologic returns were consistent with the post-transplant lymphoproliferative disease, and the immunohistochemical returns supported a diffuse large B-cell lymphoma (non-growth center origin). CONCLUSIONS: In organ transplant patients, when unexplained soft tissue nodular shadows are present, the possibility of post-transplant lymphoproliferative disorders should be considered, and an aggressive puncture biopsy should be performed to clarify the diagnosis.

Organizing Pneumonia due to Secondary Invasive Pulmonary Mycosis and Cytomegalovirus Infection in a Patient with Lymphoma.

BACKGROUND: Reactivation of cytomegalovirus is more common in lymphoma patients undergoing hematopoietic stem cell transplantation, but reactivation of cytomegalovirus due to chemotherapy for lymphoma has rarely been reported. We report a case of a lymphoma patient with secondary pulmonary fungal infection and cytomegalovirus infection after chemotherapy, which ultimately led to organizing pneumonia. METHODS: Percutaneous lung biopsy, Next Generation Sequencing (NGS). RESULTS: NGS examination suggestive of cytomegalovirus infection, percutaneous lung biopsy suggests the presence of organizing pneumonia. The patient was discharged after a combination of antifungal and antiviral treatment with posaconazole, ganciclovir, and anti-inflammatory treatment with methylprednisolone. CONCLUSIONS: In patients with lymphoma, one should be alert for fungal and viral infections of the lungs when lung related clinical manifestations occur. Patients with persistent unrelieved symptoms after treatment should undergo lung biopsy or bronchoscopy to obtain pathologic tissue for definitive diagnosis.

Neglected Mycobacterium Avium Complex Infection in a Patient with Prolonged Pneumonia.

BACKGROUND: Non-tuberculous mycobacterial pulmonary infections (NTM-PD) are becoming increasingly common in clinical practice, and early detection and accurate determination of the infecting pathogen is crucial for subsequent treatment. We report a case of NTM-PD in a healthy middle-aged female with Mycobacterium tuberculosis complex group (MAC) infection confirmed by mNGS examination. METHODS: Appropriate laboratory tests, chest CT scan, bronchoscopic alveolar lavage fluid (BALF) examination, and macrogenomic next-generation sequencing (mNGS) were performed to establish the diagnosis. RESULTS: Chest CT showed multiple inflammatory lesions in the right middle lobe, and BALF sent for mNGS finally confirmed the diagnosis of MAC infection. After symptomatic treatment with azithromycin combined with ethambutol and rifampicin, the patient improved and was discharged from the hospital. CONCLUSIONS: In patients with pulmonary infections, pathogens should be clarified early to determine the diagnosis. mNGS of BALF samples have high specificity in detecting pathogens of infectious diseases, especially complex mixed infectious disease pathogens.

Initial Misdiagnosis of Lung Cancer due to Elevated Carcinoembryonic Antigen in a Patient with Tuberculosis.

BACKGROUND: Tuberculosis often presents on imaging in the form of a solitary nodule, sometimes accompanied by elevated CEA, which is clinically difficult to differentiate from lung cancer and prone to misdiagnosis. METHODS: Lung tissue taken by lung biopsy and sent for NGS and Xpert MTB/RIF finally led to the definitive diag-nosis of nodular foci in the upper lobe of the left lung caused by tuberculosis. RESULTS: Enhanced CT of the chest showed nodular foci in the upper lobe of the left lung. Initially the nodules were thought to be malignant, but after a series of tests, were finally confirmed to be tuberculosis. CONCLUSIONS: In patients with lung disease, when chest imaging reveals a space-occupying lesion accompanied by an elevated CEA level, a comprehensive analysis of the type of lung disease, the patient's age, and comorbidities should be performed before final diagnosis to avoid misdiagnosis and delay in appropriate treatment.

Multiple Postoperative Lung Infections after Thymoma Surgery Diagnosed as Nontuberculous Mycobacterial Infection.

BACKGROUND: Thymomas are thymic epithelial-derived, most common primary anterior mediastinal masses. Non-tuberculous mycobacteria (NTM) are species that do not cause leprosy and belong to species outside the Mycobacterium tuberculosis complex. METHODS: With the clinical application of targeted next-generation sequencing (tNGS), we promptly confirmed a case of NTM infection combined with NTM infection after thymoma surgery, and we performed a joint literature analysis of the two diseases to improve clinicians' understanding and recognition of lung infections after thymoma surgery. RESULTS: Chest CT of both lungs showed multiple hyperdense shadows. Sputum bacterial culture and characterization detected Neisseria Dryad and Streptococcus Grass Green. The presence of Mycobacterium abscessus infection was confirmed by alveolar lavage fluid sent for second-generation macro gene sequencing. CONCLUSIONS: The body's immune function decreases after thymoma surgery. When empirical anti-infection treatment for recurrent pneumonia in the lungs is ineffective, we should be alerted to the possibility of the presence of pulmonary non-tuberculous mycobacterial infection, and next-generation sequencing should be performed promptly to arrive quickly at a diagnosis.

An in-depth association analysis of genetic variants within nicotine-related loci: Meeting in middle of GWAS and genetic fine-mapping.

In the last two decades of Genome-wide association studies (GWAS), nicotine-dependence-related genetic loci (e.g., nicotinic acetylcholine receptor - nAChR subunit genes) are among the most replicable genetic findings. Although GWAS results have reported tens of thousands of SNPs within these loci, further analysis (e.g., fine-mapping) is required to identify the causal variants. However, it is computationally challenging for existing fine-mapping methods to reliably identify causal variants from thousands of candidate SNPs based on the posterior inclusion probability. To address this challenge, we propose a new method to select SNPs by jointly modeling the SNP-wise inference results and the underlying structured network patterns of the linkage disequilibrium (LD) matrix. We use adaptive dense subgraph extraction method to recognize the latent network patterns of the LD matrix and then apply group LASSO to select causal variant candidates. We applied this new method to the UK biobank data to identify the causal variant candidates for nicotine addiction. Eighty-one nicotine addiction-related SNPs (i.e.,-log(p) > 50) of nAChR were selected, which are highly correlated (average r2>0.8) although they are physically distant (e.g., >200 kilobase away) and from various genes. These findings revealed that distant SNPs from different genes can show higher LD r2 than their neighboring SNPs, and jointly contribute to a complex trait like nicotine addiction.

Association between brain similarity to severe mental illnesses and comorbid cerebral, physical, and cognitive impairments.

Severe mental illnesses (SMIs) are often associated with compromised brain health, physical comorbidities, and cognitive deficits, but it is incompletely understood whether these comorbidities are intrinsic to SMI pathophysiology or secondary to having SMIs. We tested the hypothesis that cerebral, cardiometabolic, and cognitive impairments commonly observed in SMIs can be observed in non-psychiatric individuals with SMI-like brain patterns of deviation as seen on magnetic resonance imaging. 22,883 participants free of common neuropsychiatric conditions from the UK Biobank (age = 63.4 ± 7.5 years, range = 45-82 years, 50.9% female) were split into discovery and replication samples. The regional vulnerability index (RVI) was used to quantify each participant's respective brain similarity to meta-analytical patterns of schizophrenia spectrum disorder, bipolar disorder, and major depressive disorder in gray matter thickness, subcortical gray matter volume, and white matter integrity. Cluster analysis revealed five clusters with distinct RVI profiles. Compared with a cluster with no RVI elevation, a cluster with RVI elevation across all SMIs and brain structures showed significantly higher volume of white matter hyperintensities (Cohen's d = 0.59, pFDR < 10-16), poorer cardiovascular (Cohen's d = 0.30, pFDR < 10-16) and metabolic (Cohen's d = 0.12, pFDR = 1.3 × 10-4) health, and slower speed of information processing (|Cohen's d| = 0.11-0.17, pFDR = 1.6 × 10-3-4.6 × 10-8). This cluster also had significantly higher level of C-reactive protein and alcohol use (Cohen's d = 0.11 and 0.28, pFDR = 4.1 × 10-3 and 1.1 × 10-11). Three other clusters with respective RVI elevation in gray matter thickness, subcortical gray matter volume, and white matter integrity showed intermediate level of white matter hyperintensities, cardiometabolic health, and alcohol use. Our results suggest that cerebral, physical, and cognitive impairments in SMIs may be partly intrinsic via shared pathophysiological pathways with SMI-related brain anatomical changes.

Brain deficit patterns of metabolic illnesses overlap with those for major depressive disorder: A new metric of brain metabolic disease.

Metabolic illnesses (MET) are detrimental to brain integrity and are common comorbidities in patients with mental illnesses, including major depressive disorder (MDD). We quantified effects of MET on standard regional brain morphometric measures from 3D brain MRI as well as diffusion MRI in a large sample of UK BioBank participants. The pattern of regional effect sizes of MET in non-psychiatric UKBB subjects was significantly correlated with the spatial profile of regional effects reported by the largest meta-analyses in MDD but not in bipolar disorder, schizophrenia or Alzheimer's disease. We used a regional vulnerability index (RVI) for MET (RVI-MET) to measure individual's brain similarity to the expected patterns in MET in the UK Biobank sample. Subjects with MET showed a higher effect size for RVI-MET than for any of the individual brain measures. We replicated elevation of RVI-MET in a sample of MDD participants with MET versus non-MET. RVI-MET scores were significantly correlated with the volume of white matter hyperintensities, a neurological consequence of MET and age, in both groups. Higher RVI-MET in both samples was associated with obesity, tobacco smoking and frequent alcohol use but was unrelated to antidepressant use. In summary, MET effects on the brain were regionally specific and individual similarity to the pattern was more strongly associated with MET than any regional brain structural metric. Effects of MET overlapped with the reported brain differences in MDD, likely due to higher incidence of MET, smoking and alcohol use in subjects with MDD.

CSF1R regulates schizophrenia-related stress response and vascular association of microglia/macrophages.

BACKGROUND: Microglia are known to regulate stress and anxiety in both humans and animal models. Psychosocial stress is the most common risk factor for the development of schizophrenia. However, how microglia/brain macrophages contribute to schizophrenia is not well established. We hypothesized that effector molecules expressed in microglia/macrophages were involved in schizophrenia via regulating stress susceptibility. METHODS: We recruited a cohort of first episode schizophrenia (FES) patients (n = 51) and age- and sex-paired healthy controls (HCs) (n = 46) with evaluated stress perception. We performed blood RNA-sequencing (RNA-seq) and brain magnetic resonance imaging, and measured plasma level of colony stimulating factor 1 receptor (CSF1R). Furthermore, we studied a mouse model of chronic unpredictable stress (CUS) combined with a CSF1R inhibitor (CSF1Ri) (n = 9 ~ 10/group) on anxiety behaviours and microglial biology. RESULTS: FES patients showed higher scores of perceived stress scale (PSS, p < 0.05), lower blood CSF1R mRNA (FDR = 0.003) and protein (p < 0.05) levels, and smaller volumes of the superior frontal gyrus and parahippocampal gyrus (both FDR < 0.05) than HCs. In blood RNA-seq, CSF1R-associated differentially expressed blood genes were related to brain development. Importantly, CSF1R facilitated a negative association of the superior frontal gyrus with PSS (p < 0.01) in HCs but not FES patients. In mouse CUS+CSF1Ri model, similarly as CUS, CSF1Ri enhanced anxiety (both p < 0.001). Genes for brain angiogenesis and intensity of CD31+-blood vessels were dampened after CUS-CSF1Ri treatment. Furthermore, CSF1Ri preferentially diminished juxta-vascular microglia/macrophages and induced microglia/macrophages morphological changes (all p < 0.05). CONCLUSION: Microglial/macrophagic CSF1R regulated schizophrenia-associated stress and brain angiogenesis.

Deciphering the causal relationship between blood pressure and regional white matter integrity: A two-sample Mendelian randomization study.

Elevated arterial blood pressure (BP) is a common risk factor for cerebrovascular and cardiovascular diseases, but no causal relationship has been established between BP and cerebral white matter (WM) integrity. In this study, we performed a two-sample Mendelian randomization (MR) analysis with individual-level data by defining two nonoverlapping sets of European ancestry individuals (genetics-exposure set: N = 203,111; mean age = 56.71 years, genetics-outcome set: N = 16,156; mean age = 54.61 years) from UK Biobank to evaluate the causal effects of BP on regional WM integrity, measured by fractional anisotropy of diffusion tensor imaging. Two BP traits: systolic and diastolic blood pressure were used as exposures. Genetic variant was carefully selected as instrumental variable (IV) under the MR analysis assumptions. We existing large-scale genome-wide association study summary data for validation. The main method used was a generalized version of inverse-variance weight method while other MR methods were also applied for consistent findings. Two additional MR analyses were performed to exclude the possibility of reverse causality. We found significantly negative causal effects (FDR-adjusted p < .05; every 10 mmHg increase in BP leads to a decrease in FA value by .4% ~ 2%) of BP traits on a union set of 17 WM tracts, including brain regions related to cognitive function and memory. Our study extended the previous findings of association to causation for regional WM integrity, providing insights into the pathological processes of elevated BP that might chronically alter the brain microstructure in different regions.

Buoyancy-Induced Convection Driven by Frontal Polymerization.

In this Letter, we study the interaction between a self-sustaining exothermic reaction front propagating in a direction perpendicular to that of gravity and the buoyancy-driven convective flow during frontal polymerization (FP) of a low-viscosity monomer resin. As the polymerization front transforms the liquid monomer into the solid polymer, the large thermal gradients associated with the propagating front sustain a natural convection of the fluid ahead of the front. The fluid convection in turn affects the reaction-diffusion (RD) dynamics and the shape of the front. Detailed multiphysics numerical analyses and particle image velocimetry experiments reveal this coupling between natural convection and frontal polymerization. The frontal Rayleigh (Ra) number affects the magnitude of the velocity field and the inclination of the front. A higher Ra number drives instability during FP, leading to the observation of thermal-chemical patterns with tunable wavelengths and magnitudes.