Migraine: incorrect self-management for a disabling disease

Deep and unbiased proteomics, pathway enrichment analysis, and protein-protein interaction of biomarker signatures in migraine

Background

Currently, there are no biomarkers for migraine.

Objectives

We aimed to identify proteomic biomarker signatures for diagnosing, subclassifying, and predicting treatment response in migraine.

Design

This is a cross-sectional and longitudinal study of untargeted serum and cerebrospinal fluid (CSF) proteomics in episodic migraine (EM; n = 26), chronic migraine (CM; n = 26), and healthy controls (HC; n = 26).

Methods

We developed classification models for biomarker identification and natural clusters through unsupervised classification using agglomerative hierarchical clustering (AHC). Pathway analysis of differentially expressed proteins was performed.

Results

Of 405 CSF proteins, the top five proteins that discriminated between migraine patients and HC were angiotensinogen, cell adhesion molecule 3, immunoglobulin heavy variable (IGHV) V-III region JON, insulin-like growth factor binding protein 6 (IGFBP-6), and IGFBP-7. The top-performing classifier demonstrated 100% sensitivity and 75% specificity in differentiating the two groups. Of 229 serum proteins, the top five proteins in classifying patients with migraine were immunoglobulin heavy variable 3-74 (IGHV 3-74), proteoglycan 4, immunoglobulin kappa variable 3D-15, zinc finger protein (ZFP)-814, and mediator of RNA polymerase II transcription subunit 12. The best-performing classifier exhibited 94% sensitivity and 92% specificity. AHC separated EM, CM, and HC into distinct clusters with 90% success. Migraine patients exhibited increased ZFP-814 and calcium voltage-gated channel subunit alpha 1F (CACNA1F) levels, while IGHV 3-74 levels decreased in both cross-sectional and longitudinal serum analyses. ZFP-814 remained upregulated during the CM-to-EM reversion but was suppressed when CM persisted. CACNA1F was pronounced in CM persistence. Pathway analysis revealed immune, coagulation, glucose metabolism, erythrocyte oxygen and carbon dioxide exchange, and insulin-like growth factor regulation pathways.

Conclusion

Our data-driven study provides evidence for identifying novel proteomic biomarker signatures to diagnose, subclassify, and predict treatment responses for migraine. The dysregulated biomolecules affect multiple pathways, leading to cortical spreading depression, trigeminal nociceptor sensitization, oxidative stress, blood-brain barrier disruption, immune response, and coagulation cascades.

Trial registration

NCT03231241, ClincialTrials.gov.

Accuracy of migraine diagnosis and treatment by neurologists in the Baltic states: e-survey with clinical case challenge

BACKGROUND

Underdiagnosis of migraine causes a significant health burden, including lower quality of life, excessive medication use, and a delay in effective treatment. The purpose of this study was to evaluate migraine diagnosis accuracy and to review the treatment approaches used by neurologists in the Baltic states.

METHODS

The research was conducted as an anonymous e-survey with four cases in March and April 2021.

RESULTS

119 practicing adult neurologists have participated. The migraine diagnostic accuracy was 63.2%. The most commonly used diagnostic criteria were moderate/severe pain, unilateral pain, and disruption of daily activities. Diagnostic accuracy did not differ significantly between neurologists who always use ICHD-3 criteria and those who don't (68.4% vs. 58.5%, p = 0.167). It was higher in neurologists who were working in headache centers (91.7% vs. 60.9%, p = 0.012), and was related to a higher percentage of migraine diagnoses in all consulted headache patients (R2 = 0.202, adjusted R2 = 0.195, p < 0.001), prophylaxis with onabotulinumtoxin A [OR = 4.332, 95% Cl (1.588-11.814)], and anti-CGRP monoclonal antibodies [OR = 2.862, 95% Cl (1.186-6.907)].

CONCLUSIONS

Migraine diagnostic accuracy is improved through practical patient counseling and modern treatment prescription. Although the neurologists in the Baltic states follow current European guidelines, there is room for improvement in diagnostic accuracy to reduce migraine burden.

Use of Pharmacological and Non-Pharmacological Strategies by Community-Dwelling Adults to Manage Migraine: A Systematic Review

Migraine is a prevalent disease associated with high levels of disability and is often underdiagnosed and undertreated. This systematic literature review aimed to identify the types of pharmacological and non-pharmacological strategies that community-dwelling adults report using to manage migraine. A systematic literature review of relevant databases, grey literature, websites, and journals was conducted from 1 January 1989 to 21 December 2021. Study selection, data extraction, and risk of bias assessment were completed independently by multiple reviewers. Data were extracted on migraine management strategies and categorized as opioid and non-opioid medications and medical, physical, psychological, or self-initiated strategies. A total of 20 studies were included. The sample sizes ranged from 138 to 46,941, with a mean age of 34.7 to 79.9 years. The data were typically collected using self-administered questionnaires (nine studies), interviews (five studies), online surveys (three studies), paper-based surveys (two studies), and a retrospective database (one study). Community-dwelling adults with migraine reported they primarily used medications, specifically triptans (range 9-73%) and non-steroidal anti-inflammatory drugs (NSAIDs) (range 13-85%) to manage migraine. Except for medical strategies, the use of other non-pharmacological strategies was low. Common non-pharmacological strategies included consulting physicians (range 14-79%) and heat or cold therapy (35%).

Diagnostic accuracy of an artificial intelligence online engine in migraine: A multi‐center study

Objective

This study assesses the concordance in migraine diagnosis between an online, self‐administered, Computer‐based, Diagnostic Engine (CDE) and semi‐structured interview (SSI) by a headache specialist, both using International Classification of Headache Disorders, 3rd edition (ICHD‐3) criteria.

Background

Delay in accurate diagnosis is a major barrier to headache care. Accurate computer‐based algorithms may help reduce the need for SSI‐based encounters to arrive at correct ICHD‐3 diagnosis.

Methods

Between March 2018 and August 2019, adult participants were recruited from three academic headache centers and the community via advertising to our cross‐sectional study. Participants completed two evaluations: phone interview conducted by headache specialists using the SSI and a web‐based expert questionnaire and analytics, CDE. Participants were randomly assigned to either the SSI followed by the web‐based questionnaire or the web‐based questionnaire followed by the SSI. Participants completed protocols a few minutes apart. The concordance in migraine/probable migraine (M/PM) diagnosis between SSI and CDE was measured using Cohen’s kappa statistics. The diagnostic accuracy of CDE was assessed using the SSI as reference standard.

Results

Of the 276 participants consented, 212 completed both SSI and CDE (study completion rate = 77%; median age = 32 years [interquartile range: 28–40], female:male ratio = 3:1). Concordance in M/PM diagnosis between SSI and CDE was: κ = 0.83 (95% confidence interval [CI]: 0.75–0.91). CDE diagnostic accuracy: sensitivity = 90.1% (118/131), 95% CI: 83.6%–94.6%; specificity = 95.8% (68/71), 95% CI: 88.1%–99.1%. Positive and negative predictive values = 97.0% (95% CI: 91.3%–99.0%) and 86.6% (95% CI: 79.3%–91.5%), respectively, using identified migraine prevalence of 60%. Assuming a general migraine population prevalence of 10%, positive and negative predictive values were 70.3% (95% CI: 43.9%–87.8%) and 98.9% (95% CI: 98.1%–99.3%), respectively.

Conclusion

The SSI and CDE have excellent concordance in diagnosing M/PM. Positive CDE helps rule in M/PM, through high specificity and positive likelihood ratio. A negative CDE helps rule out M/PM through high sensitivity and low negative likelihood ratio. CDE that mimics SSI logic is a valid tool for migraine diagnosis.

Headache changes after kidney transplant

Headache is considered as a possible complication of dialytic treatment in chronic kidney disease (CKD). The aim of this study was to evaluate possible change in headache characteristics after kidney transplantation in patients with CKD. During a 1-year period, we enrolled 110 subjects submitted to a kidney transplant in the previous 5 years. Headache characteristics before and after the transplant were investigated by a specific questionnaire. Possible effects of pharmacological therapies were also evaluated. 65.5% of patients complained of headache before the transplant (38.2% migraine and 14.5% dialysis headache). After transplant, 53.6% of patients reported changes in headache characteristics. In particular, 27.3% of the patients had a complete resolution, 19.1% presented a headache improvement and 7.2% showed a worsening. In both migraine and dialysis headache subgroups, steroids, beta-blockers and calcium channel blockers were associated with a significant improvement of headache. Kidney transplantation seems to impact significantly headache frequency and severity in patients with CKD. A careful evaluation and use of targeted treatments could improve both patients' compliance to therapies and quality of life.

Computerized migraine diagnostic tools: a systematic review

BACKGROUND

Computerized migraine diagnostic tools have been developed and validated since 1960. We conducted a systematic review to summarize and critically appraise the quality of all published studies involving computerized migraine diagnostic tools.

METHODS

We performed a systematic literature search using PubMed, Web of Science, Scopus, snowballing, and citation searching. Cutoff date for search was 1 June 2021. Published articles in English that evaluated a computerized/automated migraine diagnostic tool were included. The following summarized each study: publication year, digital tool name, development basis, sample size, sensitivity, specificity, reference diagnosis, strength, and limitations. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool was applied to evaluate the quality of included studies in terms of risk of bias and concern of applicability.

RESULTS

A total of 41 studies (median sample size: 288 participants, median age = 43 years; 77% women) were included. Most (60%) tools were developed based on International Classification of Headache Disorders criteria, half were self-administered, and 82% were evaluated using face-to-face interviews as reference diagnosis. Some of the automated algorithms and machine learning programs involved case-based reasoning, deep learning, classifier ensemble, ant-colony, artificial immune, random forest, white and black box combinations, and hybrid fuzzy expert systems. The median diagnostic accuracy was concordance = 89% [interquartile range (IQR) = 76-93%; range = 45-100%], sensitivity = 87% (IQR = 80-95%; range = 14-100%), and specificity = 90% (IQR = 77-96%; range = 65-100%). Lack of random patient sampling was observed in 95% of studies. Case-control designs were avoided in all studies. Most (76%) reference tests exhibited low risk of bias and low concern of applicability. Patient flow and timing showed low risk of bias in 83%.

CONCLUSION

Different computerized and automated migraine diagnostic tools are available with varying accuracies. Random patient sampling, head-to-head comparison among tools, and generalizability to other headache diagnoses may improve their utility.

Analysis of Genetic Variants in SCN1A, SCN2A, KCNK18, TRPA1 and STX1A as a Possible Marker of Migraine

Background

Migraine is a polygenetic disease, considered as a channelopathy. The dysregulation of ion functioning due to genetic changes may activate the trigeminovascular system and induce migraine attack both migraine with aura (MA) and without aura (MO).

Objectives

The aim of the study was to analyze the following variants of genes encoding ion channels and associated protein: c.3199G>A SCN1A, c.56G>A SCN2A, c.28A>G and c.328T>C KCNK18, c.3053A>G TRPA1, c.31-1811C>T STX1A in migraine patients.

Patients and Methods

The study included 170 migraine patients and 173 controls. HRMA and Sanger sequencing were used for genotyping. Meta-analysis was performed for c.28A>G, c.328T>C KCNK18, and c.31-1811C>T STX1A.

Results

AA genotype of c.56G>A SCN2A was found only in migraine patients. Patients with c.328T>C KCNK18 mutation had an increased risk of developing migraine before the age of 18. Moreover, individuals with AA/TC haplotype of KCNK18 had higher attack frequency than those with AA/TT (p<0.05). T allele of c.31-1811C>T STX1A was more frequent in MA patients than MO (p<0.05). The c.3053A>G TRPA1 polymorphism was more common in patients with migraine onset before the age of 15 (p<0.05), while c.31-1811C>T STX1A and c.3199G>A SCN1A before the age of 10 (p<0.01). Meta-analysis showed a significant association of c.31-1811C>T STX1A polymorphism with migraine overall (OR=1.22, p=0.0086), MA, and MO. No association was found for c.28A>G KCNK18, c.328T>C KCNK18, and migraine overall.

Conclusion

Changes in genes encoding ion channels or proteins regulating their functioning may increase the risk of migraines and correlate with clinical features of disease, e.g. age of onset and attack frequency.

Care Among Migraine Patients in a Commercially Insured Population

INTRODUCTION

Migraine management is characterized by the poor use of preventive therapy and the overuse of acute medications. An analysis of current treatment patterns in migraineurs is needed to improve care in this patient population. The aim of this study was to describe treatment patterns and healthcare utilization of newly diagnosed migraine patients.

METHODS

This was a retrospective observation study of newly diagnosed migraine patients (no indication of migraine in the past year) identified in the IBM MarketScan Commercial Claims and Encounters database from 1 January 2010 to 30 June 2014. The final study population comprised persons aged 18-64 years at index (new diagnosis of migraine) with 12 months of continuous enrollment in an insurance plan with medical and pharmacy benefits pre-index and post-index. Treatment patterns and healthcare resource utilization were assessed during the post-index period (at least 12-months).

RESULTS

Of the 1,588,666 migraine patients identified in the database as potentially eligible to participate in the study, 284,719 (17.9%) met the final inclusion criteria. Patients generally used acute and preventive therapies to manage migraine attacks, with most patients using preventive therapy (59.1%). However, 67.9% of those using preventive therapy discontinued the current therapy, with a median time to discontinuation of 5 months. Most of the patients who discontinued preventative therapy also used an acute treatment to manage migraine attacks after discontinuation (77.6%), generally in the year following discontinuation (68.4%). Patients on acute therapies were found to use triptans excessively (1.6%) and other non-migraine-specific acute medications for treatment (7.1%). Acute patients were also at risk of opioid dependence (12.0%) and commonly received opioids or barbiturates as first-line therapy (34.1%).

CONCLUSION

Newly diagnosed migraine patients are not being properly treated, as indicated by their excessive use of acute therapies and short time on preventive treatment before discontinuation of that treatment. Further study of the reasons why patients discontinue preventive therapy (adverse events, no response, etc.) and continue to excessively use acute treatments once their treatment regimen has been established is needed.