Large-scale plasma metabolome analysis reveals alterations in HDL metabolism in migraine

Objective To identify a plasma metabolomic biomarker signature for migraine. Methods Plasma samples from 8 Dutch cohorts (n = 10,153: 2,800 migraine patients and 7,353 controls) were profiled on a 1H-NMR-based metabolomics platform, to quantify 146 individual metabolites (e.g., lipids, fatty acids, and lipoproteins) and 79 metabolite ratios. Metabolite measures associated with migraine were obtained after single-metabolite logistic regression combined with a random-effects meta-analysis performed in a nonstratified and sex-stratified manner. Next, a global test analysis was performed to identify sets of related metabolites associated with migraine. The Holm procedure was applied to control the family-wise error rate at 5% in single-metabolite and global test analyses. Results Decreases in the level of apolipoprotein A1 (β −0.10; 95% confidence interval [CI] −0.16, −0.05; adjusted p = 0.029) and free cholesterol to total lipid ratio present in small high-density lipoprotein subspecies (HDL) (β −0.10; 95% CI −0.15, −0.05; adjusted p = 0.029) were associated with migraine status. In addition, only in male participants, a decreased level of omega-3 fatty acids (β −0.24; 95% CI −0.36, −0.12; adjusted p = 0.033) was associated with migraine. Global test analysis further supported that HDL traits (but not other lipoproteins) were associated with migr

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

Migraine polygenic risk score associates with efficacy of migraine-specific drugs

Objective To assess whether the polygenic risk score (PRS) for migraine is associated with acute and/or prophylactic migraine treatment response. Methods We interviewed 2,219 unrelated patients at the Danish Headache Center using a semistructured interview to diagnose migraine and assess acute and prophylactic drug response. All patients were genotyped. A PRS was calculated with the linkage disequilibrium pred algorithm using summary statistics from the most recent migraine genome-wide association study comprising ∼375,000 cases and controls. The PRS was scaled to a unit corresponding to a twofold increase in migraine risk, using 929 unrelated Danish controls as reference. The association of the PRS with treatment response was assessed by logistic regression, and the predictive power of the model by area under the curve using a case-control design with treatment response as outcome. Results A twofold increase in migraine risk associates with positive response to migraine-specific acute treatment (odds ratio [OR] = 1.25 [95% confidence interval (CI) = 1.05–1.49]). The association between migraine risk and migraine-specific acute treatment was replicated in an independent cohort consisting of 5,616 triptan users with prescription history (OR = 3.20 [95% CI = 1.26–8.14]). No association was found for acute treatment with non–migraine-specific weak analgesics and prophylactic treatment response. Conclusions The migraine PRS can significantly identify subgroups of patients with a higher-than-average likelihood of a positive response to triptans, which provides a first step toward genetics-based precision medicine in migraine

Pleiotropy among common genetic loci identified for cardiometabolic disorders and C-reactive protein.

Pleiotropic genetic variants have independent effects on different phenotypes. C-reactive protein (CRP) is associated with several cardiometabolic phenotypes. Shared genetic backgrounds may partially underlie these associations. We conducted a genome-wide analysis to identify the shared genetic background of inflammation and cardiometabolic phenotypes using published genome-wide association studies (GWAS). We also evaluated whether the pleiotropic effects of such loci were biological or mediated in nature. First, we examined whether 283 common variants identified for 10 cardiometabolic phenotypes in GWAS are associated with CRP level. Second, we tested whether 18 variants identified for serum CRP are associated with 10 cardiometabolic phenotypes. We used a Bonferroni corrected p-value of 1.1×10-04 (0.05/463) as a threshold of significance. We evaluated the independent pleiotropic effect on both phenotypes using individual level data from the Women Genome Health Study. Evaluating the genetic overlap between inflammation and cardiometabolic phenotypes, we found 13 pleiotropic regions. Additional analyses showed that 6 regions (APOC1, HNF1A, IL6R, PPP1R3B, HNF4A and IL1F10) appeared to have a pleiotropic effect on CRP independent of the effects on the cardiometabolic phenotypes. These included loci where individuals carrying the risk allele for CRP encounter higher lipid levels and risk of type 2 diabetes. In addition, 5 regions (GCKR, PABPC4, BCL7B, FTO and TMEM18) had an effect on CRP largely mediated through the cardiometabolic phenotypes. In conclusion, our results show genetic pleiotropy among inflammation and cardiometabolic phenotypes. In addition to reverse causation, our data suggests that pleiotropic genetic variants partially underlie the association between CRP and cardiometabolic phenotypes

Meta-analysis of 375,000 individuals identifies 38 susceptibility loci for migraine

Migraine is a debilitating neurological disorder affecting around one in seven people worldwide, but its molecular mechanisms remain poorly understood. There is some debate about whether migraine is a disease of vascular dysfunction or a result of neuronal dysfunction with secondary vascular changes. Genome-wide association (GWA) studies have thus far identified 13 independent loci associated with migraine. To identify new susceptibility loci, we carried out a genetic study of migraine on 59,674 affected subjects and 316,078 controls from 22 GWA studies. We identified 44 independent single-nucleotide polymorphisms (SNPs) significantly associated with migraine risk (P < 5 × 10−8) that mapped to 38 distinct genomic loci, including 28 loci not previously reported and a locus that to our knowledge is the first to be identified on chromosome X. In subsequent computational analyses, the identified loci showed enrichment for genes expressed in vascular and smooth muscle tissues, consistent with a predominant theory of migraine that highlights vascular etiologies

Aqueous phase reforming of glycerol over Re-promoted Pt and Rh catalysts

The potential of Re promotion for carbon-supported Pt and Rh nanoparticles was investigated for aqueous phase reforming (APR) of glycerol as a model compound for biobased feedstock. Upon alloying with Re, the overall conversion rate of glycerol was substantially increased for both metal catalysts. Whereas Pt/C is more active than Rh/C in glycerol APR, the RhRe/C catalyst outperforms PtRe/C. The overall APR catalytic performance strongly correlates with the activity trend for the gas-phase water–gas shift (WGS) reaction. RhRe/C exhibited the highest activity in APR and WGS reactions. A very strong synergy between Rh and Re and Pt and Re is observed in the model WGS reaction. The role of Re in the bimetallic catalysts is to facilitate water dissociation, effectively increasing the WGS activity. During APR, this results in lower steady-state CO coverage and increased glycerol conversion rates. In terms of selectivity, the yield of renewable hydrogen is increased. The use of Re as a promoter also results in significant changes in the product selectivities during glycerol APR. Although gas-phase acetaldehyde decomposition measurements evidenced that alloying with Re increased C–C bond cleavage activities of Pt/C and Rh/C, the increased acidity due to acidic hydroxyl groups bound to Re resulted in a more substantial increase of dehydration reactions. Whereas Rh/C is more selective for formation of products involving C–C bond cleavage than Pt/C, the product mixtures of their alloys with Re reflect a much increased ratio of C–O vs. C–C bond cleavage reaction rates

Influence of particle size on the activity and stability in steam methane reforming of supported Rh nanoparticles

The influence of Rh nanoparticle size and type of support on the catalytic performance in steam methane reforming has been investigated to clarify the nature of the rate-controlling step. A set of Rh catalysts was prepared using ZrO2, CeO2, CeZrO2 and SiO2 supports. The nature and dispersion of the active Rh metal phase was studied by H2-chemisorption, TEM and X-ray absorption spectroscopy. The particle size was varied between 1 and 9 nm. The degree of Rh reduction depends on the particle size and the support. Very small particles cannot be fully reduced, especially when ceria is the support. The intrinsic rate per surface metal atom increases linearly with the Rh metal dispersion and does not depend on the type of support. With the support of kinetic data, it is concluded that dissociative CH4 adsorption is the single rate-controlling step at least at reaction temperatures above 325 °C. This implies that the overall rate is controlled by the density of low-coordinated edge and corner metal atoms in the nanoparticles. These particles contain sufficient step edge sites to provide an easy reaction pathway for CO recombination reactions. Catalysts with Rh nanoparticles smaller than 2.5 nm deactivate more strongly than catalysts with larger nanoparticles. Characterization of spent catalysts by X-ray absorption spectroscopy shows that deactivation is due to the oxidation of very small particles under the steam methane reforming reaction conditions

Identification of step-edge sites on Rh nanoparticles for facile CO dissociation

Understanding the dependence of the rate of catalytic reactions on metal nanoparticle size remains one of the great challenges in heterogeneous catalysis. Especially, methods to probe step-edge sites on technical supported nanoparticle catalysts are needed to put structure–activity relations on a surer footing. Herein, we demonstrate that N2 is a useful IR probe for the semi-quantitative identification of step-edge sites on supported metallic Rh nanoparticles. The intensity of the strongly perturbed band at 2205 cm− 1 correlates with the CO bond dissociation rate under conditions relevant to the Fischer–Tropsch reaction. Due to the intermediate reactivity of Rh, step-edge sites are required to dissociate the strong CO bond. DFT calculations show that N2 prefers to adsorb on top of low-coordinated surface atoms such as steps, corners and edges. The occurrence of the intensity maximum at intermediate particle size is explained by the presence of surface overlayers on terraces that give rise to step-edges. These step-edge sites are important in the dissociation of di-atomic molecules such as CO, NO and N2