Cluster Headache Genomewide Association Study and Meta-Analysis Identifies Eight Loci and Implicates Smoking as Causal Risk Factor.

OBJECTIVE: The objective of this study was to aggregate data for the first genomewide association study meta-analysis of cluster headache, to identify genetic risk variants, and gain biological insights. METHODS: A total of 4,777 cases (3,348 men and 1,429 women) with clinically diagnosed cluster headache were recruited from 10 European and 1 East Asian cohorts. We first performed an inverse-variance genomewide association meta-analysis of 4,043 cases and 21,729 controls of European ancestry. In a secondary trans-ancestry meta-analysis, we included 734 cases and 9,846 controls of East Asian ancestry. Candidate causal genes were prioritized by 5 complementary methods: expression quantitative trait loci, transcriptome-wide association, fine-mapping of causal gene sets, genetically driven DNA methylation, and effects on protein structure. Gene set and tissue enrichment analyses, genetic correlation, genetic risk score analysis, and Mendelian randomization were part of the downstream analyses. RESULTS: The estimated single nucleotide polymorphism (SNP)-based heritability of cluster headache was 14.5%. We identified 9 independent signals in 7 genomewide significant loci in the primary meta-analysis, and one additional locus in the trans-ethnic meta-analysis. Five of the loci were previously known. The 20 genes prioritized as potentially causal for cluster headache showed enrichment to artery and brain tissue. Cluster headache was genetically correlated with cigarette smoking, risk-taking behavior, attention deficit hyperactivity disorder (ADHD), depression, and musculoskeletal pain. Mendelian randomization analysis indicated a causal effect of cigarette smoking intensity on cluster headache. Three of the identified loci were shared with migraine. INTERPRETATION: This first genomewide association study meta-analysis gives clues to the biological basis of cluster headache and indicates that smoking is a causal risk factor. ANN NEUROL 2023;94:713-726.

Genetic Susceptibility Loci in Genomewide Association Study of Cluster Headache.

OBJECTIVE: Identifying common genetic variants that confer genetic risk for cluster headache. METHODS: We conducted a case-control study in the Dutch Leiden University Cluster headache neuro-Analysis program (LUCA) study population (n = 840) and unselected controls from the Netherlands Epidemiology of Obesity Study (NEO; n = 1,457). Replication was performed in a Norwegian sample of 144 cases from the Trondheim Cluster headache sample and 1,800 controls from the Nord-Trøndelag Health Survey (HUNT). Gene set and tissue enrichment analyses, blood cell-derived RNA-sequencing of genes around the risk loci and linkage disequilibrium score regression were part of the downstream analyses. RESULTS: An association was found with cluster headache for 4 independent loci (r2 < 0.1) with genomewide significance (p < 5 × 10-8 ), rs11579212 (odds ratio [OR] = 1.51, 95% confidence interval [CI] = 1.33-1.72 near RP11-815 M8.1), rs6541998 (OR = 1.53, 95% CI = 1.37-1.74 near MERTK), rs10184573 (OR = 1.43, 95% CI = 1.26-1.61 near AC093590.1), and rs2499799 (OR = 0.62, 95% CI = 0.54-0.73 near UFL1/FHL5), collectively explaining 7.2% of the variance of cluster headache. SNPs rs11579212, rs10184573, and rs976357, as proxy SNP for rs2499799 (r2  = 1.0), replicated in the Norwegian sample (p < 0.05). Gene-based mapping yielded ASZ1 as possible fifth locus. RNA-sequencing indicated differential expression of POLR1B and TMEM87B in cluster headache patients. INTERPRETATION: This genomewide association study (GWAS) identified and replicated genetic risk loci for cluster headache with effect sizes larger than those typically seen in complex genetic disorders. ANN NEUROL 2021;90:203-216.

Genome-Wide Association Study Identifies Risk Loci for Cluster Headache.

OBJECTIVE: This study was undertaken to identify susceptibility loci for cluster headache and obtain insights into relevant disease pathways. METHODS: We carried out a genome-wide association study, where 852 UK and 591 Swedish cluster headache cases were compared with 5,614 and 1,134 controls, respectively. Following quality control and imputation, single variant association testing was conducted using a logistic mixed model for each cohort. The 2 cohorts were subsequently combined in a merged analysis. Downstream analyses, such as gene-set enrichment, functional variant annotation, prediction and pathway analyses, were performed. RESULTS: Initial independent analysis identified 2 replicable cluster headache susceptibility loci on chromosome 2. A merged analysis identified an additional locus on chromosome 1 and confirmed a locus significant in the UK analysis on chromosome 6, which overlaps with a previously known migraine locus. The lead single nucleotide polymorphisms were rs113658130 (p = 1.92 × 10-17 , odds ratio [OR] = 1.51, 95% confidence interval [CI] = 1.37-1.66) and rs4519530 (p = 6.98 × 10-17 , OR = 1.47, 95% CI = 1.34-1.61) on chromosome 2, rs12121134 on chromosome 1 (p = 1.66 × 10-8 , OR = 1.36, 95% CI = 1.22-1.52), and rs11153082 (p = 1.85 × 10-8 , OR = 1.30, 95% CI = 1.19-1.42) on chromosome 6. Downstream analyses implicated immunological processes in the pathogenesis of cluster headache. INTERPRETATION: We identified and replicated several genome-wide significant associations supporting a genetic predisposition in cluster headache in a genome-wide association study involving 1,443 cases. Replication in larger independent cohorts combined with comprehensive phenotyping, in relation to, for example, treatment response and cluster headache subtypes, could provide unprecedented insights into genotype-phenotype correlations and the pathophysiological pathways underlying cluster headache. ANN NEUROL 2021;90:193-202.

Investigating the relationships between unfavourable habitual sleep and metabolomic traits: evidence from multi-cohort multivariable regression and Mendelian randomization analyses.

BACKGROUND: Sleep traits are associated with cardiometabolic disease risk, with evidence from Mendelian randomization (MR) suggesting that insomnia symptoms and shorter sleep duration increase coronary artery disease risk. We combined adjusted multivariable regression (AMV) and MR analyses of phenotypes of unfavourable sleep on 113 metabolomic traits to investigate possible biochemical mechanisms linking sleep to cardiovascular disease. METHODS: We used AMV (N = 17,368) combined with two-sample MR (N = 38,618) to examine effects of self-reported insomnia symptoms, total habitual sleep duration, and chronotype on 113 metabolomic traits. The AMV analyses were conducted on data from 10 cohorts of mostly Europeans, adjusted for age, sex, and body mass index. For the MR analyses, we used summary results from published European-ancestry genome-wide association studies of self-reported sleep traits and of nuclear magnetic resonance (NMR) serum metabolites. We used the inverse-variance weighted (IVW) method and complemented this with sensitivity analyses to assess MR assumptions. RESULTS: We found consistent evidence from AMV and MR analyses for associations of usual vs. sometimes/rare/never insomnia symptoms with lower citrate (- 0.08 standard deviation (SD)[95% confidence interval (CI) - 0.12, - 0.03] in AMV and - 0.03SD [- 0.07, - 0.003] in MR), higher glycoprotein acetyls (0.08SD [95% CI 0.03, 0.12] in AMV and 0.06SD [0.03, 0.10) in MR]), lower total very large HDL particles (- 0.04SD [- 0.08, 0.00] in AMV and - 0.05SD [- 0.09, - 0.02] in MR), and lower phospholipids in very large HDL particles (- 0.04SD [- 0.08, 0.002] in AMV and - 0.05SD [- 0.08, - 0.02] in MR). Longer total sleep duration associated with higher creatinine concentrations using both methods (0.02SD per 1 h [0.01, 0.03] in AMV and 0.15SD [0.02, 0.29] in MR) and with isoleucine in MR analyses (0.22SD [0.08, 0.35]). No consistent evidence was observed for effects of chronotype on metabolomic measures. CONCLUSIONS: Whilst our results suggested that unfavourable sleep traits may not cause widespread metabolic disruption, some notable effects were observed. The evidence for possible effects of insomnia symptoms on glycoprotein acetyls and citrate and longer total sleep duration on creatinine and isoleucine might explain some of the effects, found in MR analyses of these sleep traits on coronary heart disease, which warrant further investigation.

Metabolic profile changes in serum of migraine patients detected using 1H-NMR spectroscopy.

BACKGROUND: Migraine is a common brain disorder but reliable diagnostic biomarkers in blood are still lacking. Our aim was to identify, using proton nuclear magnetic resonance (1H-NMR) spectroscopy, metabolites in serum that are associated with lifetime and active migraine by comparing metabolic profiles of patients and controls. METHODS: Fasting serum samples from 313 migraine patients and 1512 controls from the Erasmus Rucphen Family (ERF) study were available for 1H-NMR spectroscopy. Data was analysed using elastic net regression analysis. RESULTS: A total of 100 signals representing 49 different metabolites were detected in 289 cases (of which 150 active migraine patients) and 1360 controls. We were able to identify profiles consisting of 6 metabolites predictive for lifetime migraine status and 22 metabolites predictive for active migraine status. We estimated with subsequent regression models that after correction for age, sex, BMI and smoking, the association with the metabolite profile in active migraine remained. Several of the metabolites in this profile are involved in lipid, glucose and amino acid metabolism. CONCLUSION: This study indicates that metabolic profiles, based on serum concentrations of several metabolites, including lipids, amino acids and metabolites of glucose metabolism, can distinguish active migraine patients from controls.

Gene co-expression analysis identifies brain regions and cell types involved in migraine pathophysiology: a GWAS-based study using the Allen Human Brain Atlas.

Migraine is a common disabling neurovascular brain disorder typically characterised by attacks of severe headache and associated with autonomic and neurological symptoms. Migraine is caused by an interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified over a dozen genetic loci associated with migraine. Here, we integrated migraine GWAS data with high-resolution spatial gene expression data of normal adult brains from the Allen Human Brain Atlas to identify specific brain regions and molecular pathways that are possibly involved in migraine pathophysiology. To this end, we used two complementary methods. In GWAS data from 23,285 migraine cases and 95,425 controls, we first studied modules of co-expressed genes that were calculated based on human brain expression data for enrichment of genes that showed association with migraine. Enrichment of a migraine GWAS signal was found for five modules that suggest involvement in migraine pathophysiology of: (i) neurotransmission, protein catabolism and mitochondria in the cortex; (ii) transcription regulation in the cortex and cerebellum; and (iii) oligodendrocytes and mitochondria in subcortical areas. Second, we used the high-confidence genes from the migraine GWAS as a basis to construct local migraine-related co-expression gene networks. Signatures of all brain regions and pathways that were prominent in the first method also surfaced in the second method, thus providing support that these brain regions and pathways are indeed involved in migraine pathophysiology.

Systematic re-evaluation of genes from candidate gene association studies in migraine using a large genome-wide association data set.

BACKGROUND: Before the genome-wide association (GWA) era, many hypothesis-driven candidate gene association studies were performed that tested whether DNA variants in genes that had been selected based on prior knowledge about migraine pathophysiology were associated with migraine. Most studies involved small sample sets without robust replication, thereby making the risk of false-positive findings high. Genome-wide marker data of thousands of migraine patients and controls from the International Headache Genetics Consortium provide a unique opportunity to re-evaluate key findings from candidate gene association studies (and other non-GWA genetic studies) in a much larger data set. METHODS: We selected 21 genes from published candidate gene association studies and six additional genes from other non-GWA genetic studies in migraine. Single nucleotide polymorphisms (SNPs) in these genes, as well as in the regions 500 kb up- and downstream, were inspected in IHGC GWAS data from 5175 clinic-based migraine patients with and without aura and 13,972 controls. RESULTS: None of the SNPs in or near the 27 genes, including the SNPs that were previously found to be associated with migraine, reached the Bonferroni-corrected significance threshold; neither when analyzing all migraine patients together, nor when analyzing the migraine with and without aura patients or males and females separately. CONCLUSION: The available migraine GWAS data provide no clear evidence for involvement of the previously reported most promising candidate genes in migraine.

Gene-based pleiotropy across migraine with aura and migraine without aura patient groups.

INTRODUCTION: It is unclear whether patients diagnosed according to International Classification of Headache Disorders criteria for migraine with aura (MA) and migraine without aura (MO) experience distinct disorders or whether their migraine subtypes are genetically related. AIM: Using a novel gene-based (statistical) approach, we aimed to identify individual genes and pathways associated both with MA and MO. METHODS: Gene-based tests were performed using genome-wide association summary statistic results from the most recent International Headache Genetics Consortium study comparing 4505 MA cases with 34,813 controls and 4038 MO cases with 40,294 controls. After accounting for non-independence of gene-based test results, we examined the significance of the proportion of shared genes associated with MA and MO. RESULTS: We found a significant overlap in genes associated with MA and MO. Of the total 1514 genes with a nominally significant gene-based p value (pgene-based ≤ 0.05) in the MA subgroup, 107 also produced pgene-based ≤ 0.05 in the MO subgroup. The proportion of overlapping genes is almost double the empirically derived null expectation, producing significant evidence of gene-based overlap (pleiotropy) (pbinomial-test = 1.5 × 10(-4)). Combining results across MA and MO, six genes produced genome-wide significant gene-based p values. Four of these genes (TRPM8, UFL1, FHL5 and LRP1) were located in close proximity to previously reported genome-wide significant SNPs for migraine, while two genes, TARBP2 and NPFF separated by just 259 bp on chromosome 12q13.13, represent a novel risk locus. The genes overlapping in both migraine types were enriched for functions related to inflammation, the cardiovascular system and connective tissue. CONCLUSIONS: Our results provide novel insight into the likely genes and biological mechanisms that underlie both MA and MO, and when combined with previous data, highlight the neuropeptide FF-amide peptide encoding gene (NPFF) as a novel candidate risk gene for both types of migraine.

Gene-expression and in vitro function of mesenchymal stromal cells are affected in juvenile myelomonocytic leukemia.

An aberrant interaction between hematopoietic stem cells and mesenchymal stromal cells has been linked to disease and shown to contribute to the pathophysiology of hematologic malignancies in murine models. Juvenile myelomonocytic leukemia is an aggressive malignant disease affecting young infants. Here we investigated the impact of juvenile myelomonocytic leukemia on mesenchymal stromal cells. Mesenchymal stromal cells were expanded from bone marrow samples of patients at diagnosis (n=9) and after hematopoietic stem cell transplantation (n=7; from 5 patients) and from healthy children (n=10). Cells were characterized by phenotyping, differentiation, gene expression analysis (of controls and samples obtained at diagnosis) and in vitro functional studies assessing immunomodulation and hematopoietic support. Mesenchymal stromal cells from patients did not differ from controls in differentiation capacity nor did they differ in their capacity to support in vitro hematopoiesis. Deep-SAGE sequencing revealed differential mRNA expression in patient-derived samples, including genes encoding proteins involved in immunomodulation and cell-cell interaction. Selected gene expression normalized during remission after successful hematopoietic stem cell transplantation. Whereas natural killer cell activation and peripheral blood mononuclear cell proliferation were not differentially affected, the suppressive effect on monocyte to dendritic cell differentiation was increased by mesenchymal stromal cells obtained at diagnosis, but not at time of remission. This study shows that active juvenile myelomonocytic leukemia affects the immune response-related gene expression and function of mesenchymal stromal cells. In contrast, the differential gene expression of hematopoiesis-related genes could not be supported by functional data. Decreased immune surveillance might contribute to the therapy resistance and progression in juvenile myelomonocytic leukemia.

Cluster headache and the hypocretin receptor 2 reconsidered: a genetic association study and meta-analysis.

BACKGROUND: Cluster headache is a severe neurological disorder with a complex genetic background. A missense single nucleotide polymorphism (rs2653349; p.Ile308Val) in the HCRTR2 gene that encodes the hypocretin receptor 2 is the only genetic factor that is reported to be associated with cluster headache in different studies. However, as there are conflicting results between studies, we re-evaluated its role in cluster headache. METHODS: We performed a genetic association analysis for rs2653349 in our large Leiden University Cluster headache Analysis (LUCA) program study population. Systematic selection of the literature yielded three additional studies comprising five study populations, which were included in our meta-analysis. Data were extracted according to predefined criteria. RESULTS: A total of 575 cluster headache patients from our LUCA study and 874 controls were genotyped for HCRTR2 SNP rs2653349 but no significant association with cluster headache was found (odds ratio 0.91 (95% confidence intervals 0.75-1.10), p = 0.319). In contrast, the meta-analysis that included in total 1167 cluster headache cases and 1618 controls from the six study populations, which were part of four different studies, showed association of the single nucleotide polymorphism with cluster headache (random effect odds ratio 0.69 (95% confidence intervals 0.53-0.90), p = 0.006). The association became weaker, as the odds ratio increased to 0.80, when the meta-analysis was repeated without the initial single South European study with the largest effect size. CONCLUSIONS: Although we did not find evidence for association of rs2653349 in our LUCA study, which is the largest investigated study population thus far, our meta-analysis provides genetic evidence for a role of HCRTR2 in cluster headache. Regardless, we feel that the association should be interpreted with caution as meta-analyses with individual populations that have limited power have diminished validity.

Exome sequencing of ATP1A3-negative cases of alternating hemiplegia of childhood reveals SCN2A as a novel causative gene.

Alternating hemiplegia of childhood (AHC) is a rare neurodevelopment disorder that is typically characterized by debilitating episodic attacks of hemiplegia, seizures, and intellectual disability. Over 85% of individuals with AHC have a de novo missense variant in ATP1A3 encoding the catalytic α3 subunit of neuronal Na+/K+ ATPases. The remainder of the patients are genetically unexplained. Here, we used next-generation sequencing to search for the genetic cause of 26 ATP1A3-negative index patients with a clinical presentation of AHC or an AHC-like phenotype. Three patients had affected siblings. Using targeted sequencing of exonic, intronic, and flanking regions of ATP1A3 in 22 of the 26 index patients, we found no ultra-rare variants. Using exome sequencing, we identified the likely genetic diagnosis in 9 probands (35%) in five genes, including RHOBTB2 (n = 3), ATP1A2 (n = 3), ANK3 (n = 1), SCN2A (n = 1), and CHD2 (n = 1). In follow-up investigations, two additional ATP1A3-negative individuals were found to have rare missense SCN2A variants, including one de novo likely pathogenic variant and one likely pathogenic variant for which inheritance could not be determined. Functional evaluation of the variants identified in SCN2A and ATP1A2 supports the pathogenicity of the identified variants. Our data show that genetic variants in various neurodevelopmental genes, including SCN2A, lead to AHC or AHC-like presentation. Still, the majority of ATP1A3-negative AHC or AHC-like patients remain unexplained, suggesting that other mutational mechanisms may account for the phenotype or that cases may be explained by oligo- or polygenic risk factors.

Whole Exome Sequencing of Hemiplegic Migraine Patients Shows an Increased Burden of Missense Variants in CACNA1H and CACNA1I Genes.

Hemiplegic migraine (HM) is a rare subtype of migraine with aura. Given that causal missense mutations in the voltage-gated calcium channel α1A subunit gene CACNA1A have been identified in a subset of HM patients, we investigated whether HM patients without a mutation have an increased burden of such variants in the "CACNA1x gene family". Whole exome sequencing data of an Australian cohort of unrelated HM patients (n = 184), along with public data from gnomAD, as controls, was used to assess the burden of missense variants in CACNA1x genes. We performed both a variant and a subject burden test. We found a significant burden for the number of variants in CACNA1E (p = 1.3 × 10-4), CACNA1H (p < 2.2 × 10-16) and CACNA1I (p < 2.2 × 10-16). There was also a significant burden of subjects with missense variants in CACNA1E (p = 6.2 × 10-3), CACNA1H (p < 2.2 × 10-16) and CACNA1I (p < 2.2 × 10-16). Both the number of variants and number of subjects were replicated for CACNA1H (p = 3.5 × 10-8; p = 0.012) and CACNA1I (p = 0.019, p = 0.044), respectively, in a Dutch clinical HM cohort (n = 32), albeit that CACNA1I did not remain significant after multiple testing correction. Our data suggest that HM, in the absence of a single causal mutation, is a complex trait, in which an increased burden of missense variants in CACNA1H and CACNA1I may contribute to the risk of disease.

Genome-wide analysis of 102,084 migraine cases identifies 123 risk loci and subtype-specific risk alleles.

Migraine affects over a billion individuals worldwide but its genetic underpinning remains largely unknown. Here, we performed a genome-wide association study of 102,084 migraine cases and 771,257 controls and identified 123 loci, of which 86 are previously unknown. These loci provide an opportunity to evaluate shared and distinct genetic components in the two main migraine subtypes: migraine with aura and migraine without aura. Stratification of the risk loci using 29,679 cases with subtype information indicated three risk variants that seem specific for migraine with aura (in HMOX2, CACNA1A and MPPED2), two that seem specific for migraine without aura (near SPINK2 and near FECH) and nine that increase susceptibility for migraine regardless of subtype. The new risk loci include genes encoding recent migraine-specific drug targets, namely calcitonin gene-related peptide (CALCA/CALCB) and serotonin 1F receptor (HTR1F). Overall, genomic annotations among migraine-associated variants were enriched in both vascular and central nervous system tissue/cell types, supporting unequivocally that neurovascular mechanisms underlie migraine pathophysiology.

Metabolomics Profile in Depression: A Pooled Analysis of 230 Metabolic Markers in 5283 Cases With Depression and 10,145 Controls.

BACKGROUND: Depression has been associated with metabolic alterations, which adversely impact cardiometabolic health. Here, a comprehensive set of metabolic markers, predominantly lipids, was compared between depressed and nondepressed persons. METHODS: Nine Dutch cohorts were included, comprising 10,145 control subjects and 5283 persons with depression, established with diagnostic interviews or questionnaires. A proton nuclear magnetic resonance metabolomics platform provided 230 metabolite measures: 51 lipids, fatty acids, and low-molecular-weight metabolites; 98 lipid composition and particle concentration measures of lipoprotein subclasses; and 81 lipid and fatty acids ratios. For each metabolite measure, logistic regression analyses adjusted for gender, age, smoking, fasting status, and lipid-modifying medication were performed within cohort, followed by random-effects meta-analyses. RESULTS: Of the 51 lipids, fatty acids, and low-molecular-weight metabolites, 21 were significantly related to depression (false discovery rate q < .05). Higher levels of apolipoprotein B, very-low-density lipoprotein cholesterol, triglycerides, diglycerides, total and monounsaturated fatty acids, fatty acid chain length, glycoprotein acetyls, tyrosine, and isoleucine and lower levels of high-density lipoprotein cholesterol, acetate, and apolipoprotein A1 were associated with increased odds of depression. Analyses of lipid composition indicators confirmed a shift toward less high-density lipoprotein and more very-low-density lipoprotein and triglyceride particles in depression. Associations appeared generally consistent across gender, age, and body mass index strata and across cohorts with depressive diagnoses versus symptoms. CONCLUSIONS: This large-scale meta-analysis indicates a clear distinctive profile of circulating lipid metabolites associated with depression, potentially opening new prevention or treatment avenues for depression and its associated cardiometabolic comorbidity.

Search for Early Pancreatic Cancer Blood Biomarkers in Five European Prospective Population Biobanks Using Metabolomics.

Most patients with pancreatic cancer present with advanced disease and die within the first year after diagnosis. Predictive biomarkers that signal the presence of pancreatic cancer in an early stage are desperately needed. We aimed to identify new and validate previously found plasma metabolomic biomarkers associated with early stages of pancreatic cancer. Prediagnostic blood samples from individuals who were to receive a diagnosis of pancreatic cancer between 1 month and 17 years after sampling (N = 356) and age- and sex-matched controls (N = 887) were collected from five large population cohorts (HUNT2, HUNT3, FINRISK, Estonian Biobank, Rotterdam Study). We applied proton nuclear magnetic resonance-based metabolomics on the Nightingale platform. Logistic regression identified two interesting hits: glutamine (P = 0.011) and histidine (P = 0.012), with Westfall-Young family-wise error rate adjusted P values of 0.43 for both. Stratification in quintiles showed a 1.5-fold elevated risk for the lowest 20% of glutamine and a 2.2-fold increased risk for the lowest 20% of histidine. Stratification by time to diagnosis suggested glutamine to be involved in an earlier process (2 to 5 years before diagnosis), and histidine in a process closer to the actual onset (<2 years). Our data did not support the branched-chain amino acids identified earlier in several US cohorts as potential biomarkers for pancreatic cancer. Thus, although we identified glutamine and histidine as potential biomarkers of biological interest, our results imply that a study at this scale does not yield metabolomic biomarkers with sufficient predictive value to be clinically useful per se as prognostic biomarkers.

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 (ß -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) (ß -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 (ß -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 migraine status. CONCLUSIONS: Metabolic profiling of plasma yielded alterations in HDL metabolism in migraine patients and decreased omega-3 fatty acids only in male migraineurs.

Unstable TTTTA/TTTCA expansions in MARCH6 are associated with Familial Adult Myoclonic Epilepsy type 3.

Familial Adult Myoclonic Epilepsy (FAME) is a genetically heterogeneous disorder characterized by cortical tremor and seizures. Intronic TTTTA/TTTCA repeat expansions in SAMD12 (FAME1) are the main cause of FAME in Asia. Using genome sequencing and repeat-primed PCR, we identify another site of this repeat expansion, in MARCH6 (FAME3) in four European families. Analysis of single DNA molecules with nanopore sequencing and molecular combing show that expansions range from 3.3 to 14 kb on average. However, we observe considerable variability in expansion length and structure, supporting the existence of multiple expansion configurations in blood cells and fibroblasts of the same individual. Moreover, the largest expansions are associated with micro-rearrangements occurring near the expansion in 20% of cells. This study provides further evidence that FAME is caused by intronic TTTTA/TTTCA expansions in distinct genes and reveals that expansions exhibit an unexpectedly high somatic instability that can ultimately result in genomic rearrangements.

Clinical spectrum of hemiplegic migraine and chances of finding a pathogenic mutation.

OBJECTIVE: To investigate whether the clinical characteristics of patients with hemiplegic migraine with and without autosomal dominant mutations in CACNA1A, ATP1A2, or SCN1A differ, and whether the disease may be caused by mutations in other genes. METHODS: We compared the clinical characteristics of 208 patients with familial (n = 199) or sporadic (n = 9) hemiplegic migraine due to a mutation in CACNA1A, ATP1A2, or SCN1A with those of 73 patients with familial (n = 49) or sporadic (n = 24) hemiplegic migraine without a mutation in these genes. In addition, 47 patients (familial: n = 33; sporadic: n = 14) without mutations in CACNA1A, ATP1A2, or SCN1A were scanned for mutations in novel genes using whole exome sequencing. RESULTS: Patients with mutations in CACNA1A, ATP1A2, or SCN1A had a lower age at disease onset, larger numbers of affected family members, and more often attacks (1) triggered by mild head trauma, (2) with extensive motor weakness, and (3) with brainstem features, confusion, and brain edema. Mental retardation and progressive ataxia were exclusively found in patients with a mutation. Whole exome sequencing failed to identify pathogenic mutations in new genes. CONCLUSIONS: Most patients with hemiplegic migraine without a mutation in CACNA1A, ATP1A2, or SCN1A display a mild phenotype that is more akin to that of common (nonhemiplegic) migraine. A major fourth autosomal dominant gene for hemiplegic migraine remains to be identified. Our observations might guide physicians in selecting patients for mutation screening and in providing adequate genetic counseling.

Identifying a gene expression signature of cluster headache in blood.

Cluster headache is a relatively rare headache disorder, typically characterized by multiple daily, short-lasting attacks of excruciating, unilateral (peri-)orbital or temporal pain associated with autonomic symptoms and restlessness. To better understand the pathophysiology of cluster headache, we used RNA sequencing to identify differentially expressed genes and pathways in whole blood of patients with episodic (n = 19) or chronic (n = 20) cluster headache in comparison with headache-free controls (n = 20). Gene expression data were analysed by gene and by module of co-expressed genes with particular attention to previously implicated disease pathways including hypocretin dysregulation. Only moderate gene expression differences were identified and no associations were found with previously reported pathogenic mechanisms. At the level of functional gene sets, associations were observed for genes involved in several brain-related mechanisms such as GABA receptor function and voltage-gated channels. In addition, genes and modules of co-expressed genes showed a role for intracellular signalling cascades, mitochondria and inflammation. Although larger study samples may be required to identify the full range of involved pathways, these results indicate a role for mitochondria, intracellular signalling and inflammation in cluster headache.

δ-Catenin (CTNND2) missense mutation in familial cortical myoclonic tremor and epilepsy.

OBJECTIVE: To identify the causative gene in a large Dutch family with familial cortical myoclonic tremor and epilepsy (FCMTE). METHODS: We performed exome sequencing for 3 patients of our FCMTE family. Next, we performed knock-down (shRNA) and rescue experiments by overexpressing wild-type and mutant human δ-catenin (CTNND2) proteins in cortical mouse neurons and compared the results with morphologic abnormalities in the postmortem FCMTE brain. RESULTS: We identified a missense mutation, p.Glu1044Lys, in the CTNND2 gene that cosegregated with the FCMTE phenotype. The knock-down of Ctnnd2 in cultured cortical mouse neurons revealed increased neurite outgrowth that was rescued by overexpression of wild-type, but not mutant, CTNND2 and was reminiscent of the morphologic abnormalities observed in cerebellar Purkinje cells from patients with FCMTE. CONCLUSIONS: We propose CTNND2 as the causal gene in FCMTE3. Functional testing of the mutant protein revealed abnormal neuronal sprouting, consistent with the abnormal cerebellar Purkinje cell morphology in patients with FCMTE.