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

AI-Guided Cancer Therapy for Patients with Coexisting Migraines

Background: Cancer remains a leading cause of death worldwide. Progress in its effective treatment has been hampered by challenges in personalized therapy, particularly in patients with comorbid conditions. The integration of artificial intelligence (AI) into patient profiling offers a promising approach to enhancing individualized anticancer therapy. Objective: This narrative review explores the role of AI in refining anticancer therapy through personalized profiling, with a specific focus on cancer patients with comorbid migraine. Methods: A comprehensive literature search was conducted across multiple databases, including PubMed, Scopus, and Google Scholar. Studies were selected based on their relevance to AI applications in oncology and migraine management, with a focus on personalized medicine and predictive modeling. Key themes were synthesized to provide an overview of recent developments, challenges, and emerging directions. Results: AI technologies, such as machine learning (ML), deep learning (DL), and natural language processing (NLP), have become instrumental in the discovery of genetic and molecular biomarkers of cancer and migraine. These technologies also enable predictive analytics for assessing the impact of migraine on cancer therapy in comorbid cases, predicting outcomes and provide clinical decision support systems (CDSS) for real-time treatment adjustments. Conclusions: AI holds significant potential to improve the precision and effectiveness of the management and therapy of cancer patients with comorbid migraine. Nevertheless, challenges remain over data integration, clinical validation, and ethical consideration, which must be addressed to appreciate the full potential for the approach outlined herein.

Oxidative Stress and Migraine

The pathogenesis of migraine is not completely understood, but inflammation and oxidative stress seem to be involved, according to data from an experimental model of the disease. This narrative review summarizes data from studies on oxidative stress markers in migraine patients, case-control association studies on the possible association of candidate genes related to oxidative stress with the risk for migraine, studies showing the presence of oxidative stress in experimental models of migraine, and studies on the efficacy of antioxidant drugs in migraine therapy. Many studies have addressed the value of concentrations of prooxidant and antioxidant substances or the activity of antioxidant enzymes in different tissues (mainly in serum/plasma or in blood cells) as possible biomarkers for migraine, being thiobarbituric acid (TBA) reactive substances (TBARS) such as malonyl dialdehyde acid (MDA) and 4-hydroxynonenal, and nitric oxide (this at least during migraine attacks in patients with migraine with aura (MWA) the most reliable. In addition, the possible usefulness of antioxidant treatment is not well established, although preliminary short-term studies suggest a beneficial action of some of them such as Coenzyme Q10 and riboflavin. Both topics require further prospective, multicenter studies with a long-term follow-up period involving a large number of migraine patients and controls.

Identifying novel proteins for migraine by integrating proteomes from blood and CSF with genome-wide association data

BACKGROUND

Proteome-wide Mendelian randomization studies have been increasingly utilized to identify potential drug targets for diseases. We aimed to identify potential therapeutic targets for migraine and its subtypes through the application of Mendelian randomization and co-localization analysis methods.

METHODS

We utilized cis-protein quantitative trait loci data for 1378 plasma proteins available from two studies with 7213 individuals and 35,559 individuals, respectively. Summary data for migraine and its subtypes were obtained from a genetic study involving up to 1,339,303 individuals. Proteins that passed both the discovery and validation Mendelian randomization analysis, sensitivity analysis, heterogeneity test, and pleiotropy test, were associated with ≥2 outcomes, and received strong support from co-localization analysis (PP.H4.abf ≥0.80) and were classified as tier 1 proteins.

RESULTS

We identified three tier 1 proteins (LRP11, ITIH1, and ADGRF5), whose genes have not been previously identified as causal genes for migraine in genetic studies. LRP11 was significantly associated with the risk of any migraine (OR [odds ratio] = 0.968, 95% CI [confidence interval] = 0.955-0.981, p = 1.27 × 10-6) and significantly/suggestively associated with three migraine subtypes. ITIH1 was significantly associated with the risk of any migraine (OR = 1.044, 95% CI = 1.024-1.065, p = 1.08 × 10-5) and migraine with visual disturbances. ADGRF5 was significantly associated with the risk of any migraine (OR = 0.964, 95% CI = 0.946-0.982, p = 8.74 × 10-5) and suggestively associated with migraine with aura. The effects of LRP11 and ADGRF5 were further replicated using cerebrospinal fluid protein data. Apart from ADGRF5, there was no evidence of potential adverse consequences when modulating the plasma levels. We also identified another four proteins (PLCG1, ARHGAP25, CHGA, and MANBA) with no potential adverse consequences when modulating the plasma levels, and their genes were not reported by previous genetic studies.

CONCLUSIONS

We found compelling evidence for two proteins and suggestive evidence for four proteins that could be promising targets for migraine treatment without significant adverse consequences. The corresponding genes were not reported in previous genetic studies. Future studies are needed to confirm the causal role of these proteins and explore the underlying mechanisms.

Unveiling the pathophysiology of restless legs syndrome through transcriptome analysis

The aim of this study was to analyze signaling pathways associated with differentially expressed messenger RNAs in people with restless legs syndrome (RLS). Seventeen RLS patients and 18 controls were enrolled. Coding RNA expression profiling of 12,857 gene transcripts by next-generation sequencing was performed. Enrichment analysis by pathfindR tool was carried-out, with p-adjusted ≤0.001 and fold-change ≥2.5. Nine main different network groups were significantly dysregulated in RLS: infections, inflammation, immunology, neurodegeneration, cancer, neurotransmission and biological, blood and metabolic mechanisms. Genetic predisposition plays a key role in RLS and evidence indicates its inflammatory nature; the high involvement of mainly neurotropic viruses and the TORCH complex might trigger inflammatory/immune reactions in genetically predisposed subjects and activate a series of biological pathways-especially IL-17, receptor potential channels, nuclear factor kappa-light-chain-enhancer of activated B cells, NOD-like receptor, mitogen-activated protein kinase, p53, mitophagy, and ferroptosis-involved in neurotransmitter mechanisms, synaptic plasticity, axon guidance, neurodegeneration, carcinogenesis, and metabolism.

Development and validation of non-invasive prediction models for migraine in Chinese adults

BACKGROUND

Migraine is a common disabling neurological disorder with severe physical and psychological damage, but there is a lack of convenient and effective non-invasive early prediction methods. This study aimed to develop a new series of non-invasive prediction models for migraine with external validation.

METHODS

A total of 188 and 94 subjects were included in the training and validation sets, respectively. A standardized professional questionnaire was used to collect the subjects' 9-item traditional Chinese medicine constitution (TCMC) scores, Pittsburgh Sleep Quality Index (PSQI) score, Zung's Self-rating Anxiety Scale and Self-rating Depression Scale scores. Logistic regression was used to analyze the risk predictors of migraine, and a series of prediction models for migraine were developed. Receiver operating characteristic (ROC) curve and calibration curve were used to assess the discrimination and calibration of the models. The predictive performance of the models were further validated using external datasets and subgroup analyses were conducted.

RESULTS

PSQI score and Qi-depression score were significantly and positively associated with the risk of migraine, with the area of the ROC curves (AUCs) predicting migraine of 0.83 (95% CI:0.77-0.89) and 0.76 (95% CI:0.68-0.84), respectively. Eight non-invasive predictive models for migraine containing one to eight variables were developed using logistic regression, with AUCs ranging from 0.83 (95% CI: 0.77-0.89) to 0.92 (95% CI: 0.89-0.96) for the training set and from 0.76 (95% CI: 0.66-0.85) to 0.83 (95% CI: 0.75-0.91) for the validation set. Subgroup analyses showed that the AUCs of the eight prediction models for predicting migraine in the training and validation sets of different gender and age subgroups ranged from 0.80 (95% CI: 0.63-0.97) to 0.95 (95% CI: 0.91-1.00) and 0.73 (95% CI: 0.64-0.84) to 0.93 (95% CI: 0.82-1.00), respectively.

CONCLUSIONS

This study developed and validated a series of convenient and novel non-invasive prediction models for migraine, which have good predictive ability for migraine in Chinese adults of different genders and ages. It is of great significance for the early prevention, screening, and diagnosis of migraine.

Towards precision medicine in migraine: Recent therapeutic advances and potential biomarkers to understand heterogeneity and treatment response

After 35 years since the introduction of the International Classification of Headache Disorders (ICHD), we are living in the era of the second great revolution in migraine therapies. First, discoveries of triptans provided a breakthrough in acute migraine treatment utilizing bench-to-bedside research results on the role of serotonin in migraine. Next, the discovery of the role of neuropeptides, more specifically calcitonin gene-related peptide (CGRP) in migraine attack led to the development of anti-CGRP therapies that are effective both in acute and preventive treatment, and are also able to reduce migraine-related burden. Here, we reviewed the most recent clinical studies and real-world data on available migraine-specific medications, including triptans, ditants, gepants and anti-CGRP monoclonal antibodies. Novel drug targets, such as PACAP and amylins were also discussed. To address the main challenges of migraine therapy, the high heterogeneity of people with migraine, the prevalent presence of various comorbid disorders, and the insufficient medical care of migraine patients were covered. Promising novel approaches from the fields of omics, blood and saliva biomarker, imaging and provocation studies might bring solutions for these challenges with the potential to identify further drug targets, distinguish more homogeneous patient subgroups, contribute to more optimal drug selection strategies, and detect biomarkers in association with headache features or predicting treatment efficacy. In the future, the combined analysis of data of different biomarker modalities with machine learning algorithms may serve precision medicine in migraine treatment.

Lack of Association between Common LAG3/CD4 Variants and Risk of Migraine

Several papers have been published suggesting a probable role of inflammatory factors in the etiopathogenesis of migraine. In this study, we investigated the possible association between common variants in the LAG3/CD4 genes (both genes, which are closely related, encode proteins involved in inflammatory and autoimmune responses) in the risk of migraine in a cohort of Caucasian Spanish participants. For this purpose, the frequencies of CD4 rs1922452, CD4 rs951818, and LAG3 rs870849 genotypes and allelic variants, using a specific TaqMan-based qPCR assay, were assessed in 290 patients diagnosed with migraine and in 300 healthy controls. The relationship of these variables with several clinical features of migraine was also analyzed. The frequencies of the analyzed LAG3/CD4 genotypes did not differ significantly between the two study groups and were not related to the sex, age at onset of migraine, family history of migraine, presence or absence of aura, or the triggering effect of ethanol on migraine episodes. These results suggest a lack of association between common variants in the LAG3/CD4 genes and the risk of developing migraine in the Caucasian Spanish population.