Comparing migraine with and without aura to healthy controls using RNA sequencing

The Dawn and Advancement of the Knowledge of the Genetics of Migraine

Background: Migraine is a prevalent episodic brain disorder known for recurrent attacks of unilateral headaches, accompanied by complaints of photophobia, phonophobia, nausea, and vomiting. Two main categories of migraine are migraine with aura (MA) and migraine without aura (MO). Main body: Early twin and population studies have shown a genetic basis for these disorders, and efforts have been invested since to discern the genes involved. Many techniques, including candidate-gene association studies, loci linkage studies, genome-wide association, and transcription studies, have been used for this goal. As a result, several genes were pinned with concurrent and conflicting data among studies. It is important to understand the evolution of techniques and their findings. Conclusions: This review provides a chronological understanding of the different techniques used from the dawn of migraine genetic investigations and the genes linked with the migraine subtypes.

Migraine genetics: Status and road forward

BACKGROUND

Migraine is considered a multifactorial genetic disorder. Different platforms and methods are used to unravel the genetic basis of migraine. Initially, linkage analysis in multigenerational families followed by Sanger sequencing of protein-coding parts (exons) of genes in the genomic region shared by affected family members identified high-effect risk DNA mutations for rare Mendelian forms of migraine, foremost hemiplegic migraine. More recently, genome-wide association studies testing millions of DNA variants in large groups of patients and controls have proven successful in identifying many dozens of low-effect risk DNA variants for the more common forms of migraine with the number of associated DNA variants increasing steadily with larger sample sizes. Currently, next-generation sequencing, utilising whole exome and whole genome sequence data, and other omics data are being used to facilitate their functional interpretation and the discovery of additional risk factors. Various methods and analysis tools, such as genetic correlation and causality analysis, are used to further characterise genetic risk factors.

FINDINGS

We describe recent findings in genome-wide association studies and next-generation sequencing analysis in migraine. We show that the combined results of the two most recent and most powerful migraine genome-wide association studies have identified a total of 178 LD-independent (r² < 0.1) genome-wide significant single nucleotide polymorphisms (SNPs), of which 99 were unique to Hautakangas et al., 11 were unique to Choquet et al., and 68 were identified by both studies. When considering that Choquet et al. also identified three SNPs in a female-specific genome-wide association studies then these two recent studies identified 181 independent SNPs robustly associated with migraine. Cross-trait and causal analyses are beginning to identify and characterise specific biological factors that contribute to migraine risk and its comorbid conditions.

CONCLUSION

This review provides a timely update and overview of recent genetic findings in migraine.

Multi-omics to predict changes during cold pressor test

Background

The cold pressor test (CPT) is a widely used pain provocation test to investigate both pain tolerance and cardiovascular responses. We hypothesize, that performing multi-omic analyses during CPT gives the opportunity to home in on molecular mechanisms involved. Twenty-two females were phenotypically assessed before and after a CPT, and blood samples were taken. RNA-Sequencing, steroid profiling and untargeted metabolomics were performed. Each ‘omic level was analyzed separately at both single-feature and systems-level (principal component [PCA] and partial least squares [PLS] regression analysis) and all ‘omic levels were combined using an integrative multi-omics approach, all using the paired-sample design.

Results

We showed that PCA was not able to discriminate time points, while PLS did significantly distinguish time points using metabolomics and/or transcriptomic data, but not using conventional physiological measures. Transcriptomic and metabolomic data revealed at feature-, systems- and integrative- level biologically relevant processes involved during CPT, e.g. lipid metabolism and stress response.

Conclusion

Multi-omics strategies have a great potential in pain research, both at feature- and systems- level. Therefore, they should be exploited in intervention studies, such as pain provocation tests, to gain knowledge on the biological mechanisms involved in complex traits.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08981-z.

Genetic overlap between temporomandibular disorders and primary headaches: A systematic review

Primary headache disorders (PHD), specifically migraine, are strongly associated with temporomandibular disorders (TMD), sharing some patterns of orofacial pain. Both disorders have significant genetic contributions already studied. PRISMA guidelines were followed to conduct this systematic review, which comprehensively summarize and discuss the genetic overlap between TMD and PHD to aid future research in potential therapy targets. This review included eight original articles published between 2015 and 2020, written in English and related to either TMD and/or PHD. The genes simultaneously assessed in PHD and TMD studies were COMT, MTHFR, and ESR1. COMT was proved to play a critical role in TMD pathogenesis, as all studies have concluded about its impact on the occurrence of the disease, although no association with PHD was found. No proof on the impact of MTHFR gene regulation on either TMD or PHD was found. The most robust results are concerning the ESR1 gene, which is present in the genetic profile of both clinical conditions. This novel systematic review highlights not only the need for a clear understanding of the role of ESR1 and COMT genes in pain pathogenesis, but it also evaluates their potential as a promising therapeutic target to treat both pathologies.

Role of Omics in Migraine Research and Management: A Narrative Review

Migraine is a neurological disorder defined by episodic attacks of chronic pain associated with nausea, photophobia, and phonophobia. It is known to be a complex disease with several environmental and genetic factors contributing to its susceptibility. Risk factors for migraine include head or neck injury (Arnold, Cephalalgia 38(1):1-211, 2018). Stress and high temperature are known to trigger migraine, while sleep disorders and anxiety are considered to be the comorbid conditions with migraine. Studies have reported various biomarkers, including genetic variants, proteins, and metabolites implicated in migraine's pathophysiology. Using the "omics" approach, which deals with genetics, transcriptomics, proteomics, and metabolomics, more specific biomarkers for various migraine can be identified. On account of its multifactorial nature, migraine is an ideal study model focusing on integrated omics approaches, including genomics, transcriptomics, proteomics, and metabolomics. The current review has been compiled with an aim to focus on the genomic alterations especially involved in the regulation of glutamatergic neurotransmission, cortical excitability, ion channels, solute carrier proteins, or receptors; their expression in migraine patients and also specific proteins and metabolites, including some inflammatory biomarkers that might represent the migraine phenotype at the molecular level. The systems biology approach holds the promise to understand the pathophysiology of the disease at length and also to identify the specific therapeutic targets for novel interventions.

A review of migraine genetics: gathering genomic and transcriptomic factors

Migraine is a common and complex neurologic disorder that affects approximately 15-18% of the general population. Although the cause of migraine is unknown, some genetic studies have focused on unravelling rare and common variants underlying the pathophysiological mechanisms of this disorder. This review covers the advances in the last decade on migraine genetics, throughout the history of genetic methodologies used, including recent application of next-generation sequencing techniques. A thorough review of the literature interweaves the genomic and transcriptomic factors that will allow a better understanding of the mechanisms underlying migraine pathophysiology, concluding with the clinical utility landscape of genetic information and future consideration to creating a new frontier toward advancing the field of personalized medicine.

Identification of disease- and headache-specific mediators and pathways in migraine using blood transcriptomic and metabolomic analysis

BACKGROUND

Recent data suggest that gene expression profiles of peripheral white blood cells can reflect changes in the brain. We aimed to analyze the transcriptome of peripheral blood mononuclear cells (PBMC) and changes of plasma metabolite levels of migraineurs in a self-controlled manner during and between attacks.

METHODS

Twenty-four patients with migraine were recruited and blood samples were collected in a headache-free (interictal) period and during headache (ictal) to investigate disease- and headache-specific alterations. Control samples were collected from 13 age- and sex-matched healthy volunteers. RNA was isolated from PBMCs and single-end 75 bp RNA sequencing was performed using Illumina NextSeq 550 instrument followed by gene-level differential expression analysis. Functional analysis was carried out on information related to the role of genes, such as signaling pathways and biological processes. Plasma metabolomic measurement was performed with the Biocrates MxP Quant 500 Kit.

RESULTS

We identified 144 differentially-expressed genes in PBMCs between headache and headache-free samples and 163 between symptom-free patients and controls. Network analysis revealed that enriched pathways included inflammation, cytokine activity and mitochondrial dysfunction in both headache and headache-free samples compared to controls. Plasma lactate, succinate and methionine sulfoxide levels were higher in migraineurs while spermine, spermidine and aconitate were decreased during attacks.

CONCLUSIONS

It is concluded that enhanced inflammatory and immune cell activity, and oxidative stress can play a role in migraine susceptibility and headache generation.

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

Changes in the gene expression profile during spontaneous migraine attacks

Migraine attacks are delimited, allowing investigation of changes during and outside attack. Gene expression fluctuates according to environmental and endogenous events and therefore, we hypothesized that changes in RNA expression during and outside a spontaneous migraine attack exist which are specific to migraine. Twenty-seven migraine patients were assessed during a spontaneous migraine attack, including headache characteristics and treatment effect. Blood samples were taken during attack, two hours after treatment, on a headache-free day and after a cold pressor test. RNA-Sequencing, genotyping, and steroid profiling were performed. RNA-Sequences were analyzed at gene level (differential expression analysis) and at network level, and genomic and transcriptomic data were integrated. We found 29 differentially expressed genes between 'attack' and 'after treatment', after subtracting non-migraine specific genes, that were functioning in fatty acid oxidation, signaling pathways and immune-related pathways. Network analysis revealed mechanisms affected by changes in gene interactions, e.g. 'ion transmembrane transport'. Integration of genomic and transcriptomic data revealed pathways related to sumatriptan treatment, i.e. '5HT1 type receptor mediated signaling pathway'. In conclusion, we uniquely investigated intra-individual changes in gene expression during a migraine attack. We revealed both genes and pathways potentially involved in the pathophysiology of migraine and/or migraine treatment.

A Comprehensive Review on the Role of Genetic Factors in the Pathogenesis of Migraine

Migraine is a common neurovascular condition. This disorder has a complex genetic background. Several single-nucleotide polymorphisms (SNPs) or mutations within genes regulating glutamatergic neurotransmission, cortical excitability, ion channels, and solute carriers have been associated with polygenic and monogenic forms of migraine. SNPs within ACE, DBH, TRPM8, COMT, GABRQ, CALCA, TRPV1, and other genes have been reported to affect the risk of migraine or the associated clinical parameters. The distribution of some HLA alleles within the HLA-DRB1, HLA-DR2, HLA-B, and HLA-C regions have also been found to differ between migraineurs and healthy subjects. In addition, certain mitochondrial DNA changes and polymorphisms in this region have been shown to increase the risk of migraine. A few functional studies have investigated the molecular mechanisms contributing to these genetic factors in the development of migraine. Here we review studies evaluating the role of genetic polymorphisms and mRNA/miRNA dysregulation in migraine.

Weighted Gene Coexpression Network Analysis Identifies Specific Modules and Hub Genes Related to Major Depression

PURPOSE

Despite advances in characterizing the neurobiology of emotional disorders, there is still a significant lack of scientific understanding of the pathophysiological mechanisms governing major depressive disorder (MDD). This study attempted to elucidate the molecular circuitry of MDD and to identify more potential genes associated with the pathogenesis of the disease.

PATIENTS AND METHODS

Microarray data from the GSE98793 dataset were downloaded from the NCBI Gene Expression Omnibus (GEO) database, including 128 patients with MDD and 64 healthy controls. Weighted gene coexpression network analysis (WGCNA) was performed to find modules of differentially expressed genes (DEGs) with high correlations followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to obtain further biological insight into the top three key modules. The protein-protein interaction (PPI) network, the modules from the PPI network, and the gene annotation enrichment of modules were analyzed, as well.

RESULTS

We filtered 3276 genes that were considered significant DEGs for further WGCNA analysis. By performing WGCNA, we found that the turquoise, blue and brown functional modules were all strongly correlated with MDD development, including immune response, neutrophil degranulation, ribosome biogenesis, T cell activation, glycosaminoglycan biosynthetic process, and protein serine/threonine kinase activator activity. Hub genes were identified in the key functional modules that might have a role in the progression of MDD. Functional annotation showed that these modules primarily enriched such KEGG pathways as the TNF signaling pathway, T cell receptor signaling pathway, primary immunodeficiency, Th1, Th2 and Th17 cell differentiation, autophagy and RNA degradation and oxidative phosphorylation. These results suggest that these genes are closely related to autophagy and cellular immune function.

CONCLUSION

The results of this study may help to elucidate the pathophysiology of MDD development at the molecular level and explore the potential molecular mechanisms for new interventional strategies.