{"title":"A study of changes in hematologic parameters in patients with migraine.","authors":"Jiaonan Wu, Lulan Fu, Ziru Deng, Hanli Li, Linyan Zhong, Rupan Gao, Wei Gui","doi":"10.1093/cei/uxae113","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>To evaluate the characteristics of hematological parameters and peripheral inflammatory markers in migraine, including chronic migraine (CM) and episodic migraine (EM), and to explore their underlying mechanisms.</p><p><strong>Method: </strong>A total of 88 subjects were enrolled, 58 with migraine (28 with chronic migraine and 30 with episodic migraine) and 30 healthy controls. All subjects were matched for age, gender and body mass index (BMI), and peripheral blood was collected. Hematological parameters and peripheral inflammatory markers (PIMs) were compared between migraineurs and healthy controls. The patients underwent hematological laboratory testing and calculated the PIMs. PIMs included neutrophil/lymphocyte ratio (NLR), lymphocyte/monocyte ratio (LMR), neutrophil/monocyte ratio (NMR), platelet/lymphocyte ratio (PLR), and platelet/monocyte ratio (PMR) ratio.</p><p><strong>Result: </strong>Monocyte counts in migraine patients were significantly lower compared to healthy controls, while LMR and PMR were significantly higher. Statistically significant differences were observed in monocyte counts, LMR, and PMR among the three groups of CM, EM and HC patients. Post hoc Bonferroni t-test showed that monocyte counts were significantly lower in the EM group compared to the HC group, while LMR and PMR were significantly higher. Comparison between the EM and CM groups showed that LMR was significantly higher in the EM group. Differences in monocyte counts, LMR and PMR between the CM and HC groups were not statistically significant. Receiver operating characteristic (ROC) curve analysis indicated that the area under the curve (AUC) for the diagnosing migraine using the combination of Mon, LMR and PMR was 0.707, and the AUC for the diagnosis of EM was 0.758. The AUC value of PMR for diagnosing CM was 0.669, while the AUC for the combination of LMR and PLR in distinguishing CM and EM was 0.705.</p><p><strong>Conclusion: </strong>Our findings indicate that migraine and its subtypes exhibit abnormalities in monocyte counts and PIMs, which possess diagnostic predictive value for differentiating migraine and its subtypes. This suggests that systemic inflammation may play a role in the pathogenesis of migraine.</p>","PeriodicalId":10268,"journal":{"name":"Clinical and experimental immunology","volume":" ","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical and experimental immunology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/cei/uxae113","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: To evaluate the characteristics of hematological parameters and peripheral inflammatory markers in migraine, including chronic migraine (CM) and episodic migraine (EM), and to explore their underlying mechanisms.
Method: A total of 88 subjects were enrolled, 58 with migraine (28 with chronic migraine and 30 with episodic migraine) and 30 healthy controls. All subjects were matched for age, gender and body mass index (BMI), and peripheral blood was collected. Hematological parameters and peripheral inflammatory markers (PIMs) were compared between migraineurs and healthy controls. The patients underwent hematological laboratory testing and calculated the PIMs. PIMs included neutrophil/lymphocyte ratio (NLR), lymphocyte/monocyte ratio (LMR), neutrophil/monocyte ratio (NMR), platelet/lymphocyte ratio (PLR), and platelet/monocyte ratio (PMR) ratio.
Result: Monocyte counts in migraine patients were significantly lower compared to healthy controls, while LMR and PMR were significantly higher. Statistically significant differences were observed in monocyte counts, LMR, and PMR among the three groups of CM, EM and HC patients. Post hoc Bonferroni t-test showed that monocyte counts were significantly lower in the EM group compared to the HC group, while LMR and PMR were significantly higher. Comparison between the EM and CM groups showed that LMR was significantly higher in the EM group. Differences in monocyte counts, LMR and PMR between the CM and HC groups were not statistically significant. Receiver operating characteristic (ROC) curve analysis indicated that the area under the curve (AUC) for the diagnosing migraine using the combination of Mon, LMR and PMR was 0.707, and the AUC for the diagnosis of EM was 0.758. The AUC value of PMR for diagnosing CM was 0.669, while the AUC for the combination of LMR and PLR in distinguishing CM and EM was 0.705.
Conclusion: Our findings indicate that migraine and its subtypes exhibit abnormalities in monocyte counts and PIMs, which possess diagnostic predictive value for differentiating migraine and its subtypes. This suggests that systemic inflammation may play a role in the pathogenesis of migraine.
期刊介绍：
Clinical & Experimental Immunology (established in 1966) is an authoritative international journal publishing high-quality research studies in translational and clinical immunology that have the potential to transform our understanding of the immunopathology of human disease and/or change clinical practice.
The journal is focused on translational and clinical immunology and is among the foremost journals in this field, attracting high-quality papers from across the world. Translation is viewed as a process of applying ideas, insights and discoveries generated through scientific studies to the treatment, prevention or diagnosis of human disease. Clinical immunology has evolved as a field to encompass the application of state-of-the-art technologies such as next-generation sequencing, metagenomics and high-dimensional phenotyping to understand mechanisms that govern the outcomes of clinical trials.
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