Cerebral microbleeds: Spatial distribution implications

Cerebral microbleeds are considered an imaging marker of cerebral small vessel disease. The location of microbleeds is thought to reflect the underlying pathology. Microbleeds in the deep and infratentorial region are thought to reflect hypertensive arteriopathy whereas lobar microbleeds are associated clinically with cerebral amyloid angiopathy (CAA). Aside from patient populations, microbleeds are frequently observed in seemingly asymptomatic populations. Moreover, many elderly, both in clinical and preclinical populations, have multiple coexisting pathologies in their brains, which complicates the interpretation of cerebral microbleeds, especially early in the clinical course. In this commentary, we discuss the influence of the strongest genetic risk factor for CAA, Apolipoprotein E (APOE), in the spatial distribution of microbleeds, and we additionally address issues in interpretation and implication of the location of microbleeds in clinical and asymptomatic populations

Prediagnostic adult body mass index change and esophageal adenocarcinoma survival

Background: We examined whether body mass index (BMI) changes in adulthood, prior to disease onset, are associated with overall survival among esophageal adenocarcinoma patients. Methods: We included 285 histologically confirmed patients with a complete baseline BMI questionnaire. Using extended Cox regression models, we obtained adjusted hazard ratios (HRs) for the associations between overall survival and BMI at diagnosis, BMI 6 months before diagnosis, self-reported average adult BMI, and ΔBMI (BMI 6 months before diagnosis minus average adult BMI), categorized into tertiles 25 and <35 kg/m2 was associated with better overall survival. Compared to patients with stable BMI in adulthood, patients who gained BMI throughout adulthood had 1.68 times the all-cause hazard of death (95% CI: 1.17-2.43; P <.01), independent of diagnosis BMI and percent weight loss 6 months before diagnosis. Compared to patients with average adult BMI < 27.5 who maintained stable adult BMI, patients with average adult BMI ≥ 27.5 kg/m2 who gained BMI had the worst survival (HR = 3.05; 95% CI 1.62-5.72; P <.01). Conclusion: Body mass index gain in adulthood is associated with poor overall survival, and maintaining a normal body weight throughout adulthood is associated with the best overall survival among esophageal adenocarcinoma patients, independent of BMI at diagnosis

A multi-omic study reveals BTG2 as a reliable prognostic marker for early-stage non-small cell lung cancer

B-cell translocation gene 2 (BTG2) is a tumour suppressor protein known to be downregulated in several types of cancer. In this study, we investigated a potential role for BTG2 in early-stage non-small cell lung cancer (NSCLC) survival. We analysed BTG2 methylation data from 1230 early-stage NSCLC patients from five international cohorts, as well as gene expression data from 3038 lung cancer cases from multiple cohorts. Three CpG probes (cg01798157, cg06373167, cg23371584) that detected BTG2 hypermethylation in tumour tissues were associated with lower overall survival. The prognostic model based on methylation could distinguish patient survival in the four cohorts [hazard ratio (HR) range, 1.51-2.21] and the independent validation set (HR=1.85). In the expression analysis, BTG2 expression was positively correlated with survival in each cohort (HR range, 0.28-0.68), which we confirmed with meta-analysis (HR=0.61, 95% CI 0.54-0.68). The three CpG probes were all negatively correlated with BTG2 expression. Importantly, an integrative model of BTG2 methylation, expression and clinical information showed better predictive ability in the training set and validation set. In conclusion, the methylation and integrated prognostic signatures based on BTG2 are stable and reliable biomarkers for early-stage NSCLC. They may have new applications for appropriate clinical adjuvant trials and personalized treatments in the future

Migraine Genetic Variants Influence Cerebral Blood Flow

Objective: To investigate the association of migraine genetic variants with cerebral blood flow (CBF). Background: Migraine is a common disorder with many genetic and non-genetic factors affecting its occurrence. The exact pathophysiological mechanisms underlying the disease remain unclear, but are known to involve hemodynamic and vascular disruptions. Recent genome-wide association studies have identified 44 genetic variants in 38 genetic loci that affect the risk of migraine, which provide the opportunity to further disentangle these mechanisms. Methods: We included 4665 participants of the population-based Rotterdam Study (mean age 65.0 ± 10.9 years, 55.6% women). Cross-sectional area (mm2), flow velocity (mm/s), and blood flow (mL/min) were measured in both carotids and the basilar artery using 2-dimensional phase-contrast magnetic resonance imaging. We analyzed 43 previously identified migraine variants separately and calculated a genetic risk score (GRS). To assess the association with CBF, we used linear regression models adjusted for age, sex, and total brain volume. Hierarchical clustering was performed based on the associations with CBF measures and tissue enrichment. Results: The rs67338227 risk allele was associated with higher flow velocity and smaller cross-sectional area in the carotids (Pminimum = 3.7 × 10−8). Other variants were related to CBF with opposite directions of effect, but not significantly after multiple testing adjustments (P < 1.4 × 10−4). The migraine GRS was not associated with CBF after multiple testing corrections. Migraine risk variants were found to be enriched for flow in the basilar artery (λ = 2.39). Conclusions: These findings show that genetic migraine risk is complexly associated with alterations in cerebral hemodynamics

Genetic Risk Score for Intracranial Aneurysms:Prediction of Subarachnoid Hemorrhage and Role in Clinical Heterogeneity

BACKGROUND: Recently, common genetic risk factors for intracranial aneurysm (IA) and aneurysmal subarachnoid hemorrhage (ASAH) were found to explain a large amount of disease heritability and therefore have potential to be used for genetic risk prediction. We constructed a genetic risk score to (1) predict ASAH incidence and IA presence (combined set of unruptured IA and ASAH) and (2) assess its association with patient characteristics. METHODS: A genetic risk score incorporating genetic association data for IA and 17 traits related to IA (so-called metaGRS) was created using 1161 IA cases and 407 392 controls from the UK Biobank population study. The metaGRS was validated in combination with risk factors blood pressure, sex, and smoking in 828 IA cases and 68 568 controls from the Nordic HUNT population study. Furthermore, we assessed association between the metaGRS and patient characteristics in a cohort of 5560 IA patients. RESULTS: Per SD increase of metaGRS, the hazard ratio for ASAH incidence was 1.34 (95% CI, 1.20-1.51) and the odds ratio for IA presence 1.09 (95% CI, 1.01-1.18). Upon including the metaGRS on top of clinical risk factors, the concordance index to predict ASAH hazard increased from 0.63 (95% CI, 0.59-0.67) to 0.65 (95% CI, 0.62-0.69), while prediction of IA presence did not improve. The metaGRS was statistically significantly associated with age at ASAH (β=-4.82×10(-3) per year [95% CI, -6.49×10(-3) to -3.14×10(-3)]; P=1.82×10(-8)), and location of IA at the internal carotid artery (odds ratio=0.92 [95% CI, 0.86-0.98]; P=0.0041). CONCLUSIONS: The metaGRS was predictive of ASAH incidence, although with limited added value over clinical risk factors. The metaGRS was not predictive of IA presence. Therefore, we do not recommend using this metaGRS in daily clinical care. Genetic risk does partly explain the clinical heterogeneity of IA warranting prioritization of clinical heterogeneity in future genetic prediction studies of IA and ASAH

Migraine, inflammatory bowel disease and celiac disease:A Mendelian randomization study

Objective: To assess whether migraine may be genetically and/or causally associated with inflammatory bowel disease (IBD) or celiac disease. Background: Migraine has been linked to IBD and celiac disease in observational studies, but whether this link may be explained by a shared genetic basis or could be causal has not been established. The presence of a causal association could be clinically relevant, as treating one of these medical conditions might mitigate the symptoms of a causally linked condition. Methods:Linkage disequilibrium score regression and two-sample bidirectional Mendelian randomization analyses were performed using summary statistics from cohort-based genome-wide association studies of migraine (59,674 cases; 316,078 controls), IBD (25,042 cases; 34,915 controls) and celiac disease (11,812 or 4533 cases; 11,837 or 10,750 controls). Migraine with and without aura were analyzed separately, as were the two IBD subtypes Crohn's disease and ulcerative colitis. Positive control analyses and conventional Mendelian randomization sensitivity analyses were performed.Results: Migraine was not genetically correlated with IBD or celiac disease. No evidence was observed for IBD (odds ratio [OR] 1.00, 95% confidence interval [CI] 0.99–1.02, p = 0.703) or celiac disease (OR 1.00, 95% CI 0.99–1.02, p = 0.912) causing migraine or migraine causing either IBD (OR 1.08, 95% CI 0.96–1.22, p = 0.181) or celiac disease (OR 1.08, 95% CI 0.79–1.48, p = 0.614) when all participants with migraine were analyzed jointly. There was some indication of a causal association between celiac disease and migraine with aura (OR 1.04, 95% CI 1.00–1.08, p = 0.045), between celiac disease and migraine without aura (OR 0.95, 95% CI 0.92–0.99, p = 0.006), as well as between migraine without aura and ulcerative colitis (OR 1.15, 95% CI 1.02–1.29, p = 0.025). However, the results were not significant after multiple testing correction. Conclusions: We found no evidence of a shared genetic basis or of a causal association between migraine and either IBD or celiac disease, although we obtained some indications of causal associations with migraine subtypes.</p

Cerebral small vessel disease genomics and its implications across the lifespan

White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.Peer reviewe

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Global wealth disparities drive adherence to COVID-safe pathways in head and neck cancer surgery

Peer reviewe