Background: Two-thirds of patients with migraine without aura (MwoA) complain ictal cutaneous allodynia (CA), clinical sign of central nociceptive pathway sensitization, and independent predictor for migraine chronification. Aim: We aimed to investigate whether functional abnormalities, structural, or microstructural changes of the main cognitive networks (default mode network [DMN], salience network [SN], and central executive network [CEN]) could predict the development of CA in patients with MwoA. Methods: Baseline 3-Tesla MRI images of 50 patients with MwoA were analyzed between 2009 and 2015. Over a three-year period, patients were then stratified into 2 groups based on CA development and compared with matched healthy controls (HC). Group-level independent components analysis was used to investigate intrinsic functional connectivity (FC) differences within the cognitive resting-state networks. Voxel-based morphometry (VBM) was used to assess whether group differences in cognitive network FC were related to structural differences. Tract-based spatial statistical analyses (TBSS) were conducted to assess the microstructural properties of white matter tracts. We also compared internetwork connectivity between patients. Finally, a logistic regression analysis was used to investigate baseline imaging predictors of CA development. Results and Discussion: We observed a significantly reduced FC of both DMN and CEN in patients with MwoA developing CA (MwoA dCA) when compared with both patients with MwoA not developing CA (MwoA ndCA) and HC. Within the DMN, the PCC/precuneus is a key hub aimed to anti-nociception and multisensory integration. The reduced intrinsic PCC/precuneus FC observed in patients with MwoA dCA could subtend abnormal inputs integration, from different sensory modalities, allowing the development of CA. On the other hand, within the CEN, a central role in pain modulation as well as in executive functions is played by ACC and MFG. Our finding of reduced ACC and MFG FC in MwoA dCA may represent the neuronal substrate of both subclinical impairment of complex executive functions and dysfunctional anti-nociceptive pathway, making these patients more prone to migraine chronification. TBSS analyses showed a statistically significant reduced corpus callosum (CC) FA in patients with MwoA dCA as previously demonstrated in migraine patients with other chronification factors such as medication overuse or affective disorders. No VBM differences in both global and local volumes were revealed between groups. No significant correlations have been found between the observed functional and microstructural changes and clinical parameters of disease severity. Logistic regression analysis indicated that the full model containing all predictors was statistically significant while the decreased ACC-FC was significantly associated with CA development. Conclusion: We suggest that DMN and CEN FC abnormalities as well as CC microstructural changes could represent a prognostic imaging biomarker able to identify migraine patients more prone to experiencing CA and therefore, more inclined to chronic migraine. In the new pharmacological scenario, it would be useful to address therapeutic resources to specific migraine populations with a high risk of more severe clinical phenotype.
Cognitive Networks Disarrangement in Patients With Migraine Predicts Cutaneous Allodynia
Russo A.;Silvestro M.;Trojsi F.;Bisecco A.;De Micco R.;Esposito F.;Tessitore A.;Tedeschi G.
2020
Abstract
Background: Two-thirds of patients with migraine without aura (MwoA) complain ictal cutaneous allodynia (CA), clinical sign of central nociceptive pathway sensitization, and independent predictor for migraine chronification. Aim: We aimed to investigate whether functional abnormalities, structural, or microstructural changes of the main cognitive networks (default mode network [DMN], salience network [SN], and central executive network [CEN]) could predict the development of CA in patients with MwoA. Methods: Baseline 3-Tesla MRI images of 50 patients with MwoA were analyzed between 2009 and 2015. Over a three-year period, patients were then stratified into 2 groups based on CA development and compared with matched healthy controls (HC). Group-level independent components analysis was used to investigate intrinsic functional connectivity (FC) differences within the cognitive resting-state networks. Voxel-based morphometry (VBM) was used to assess whether group differences in cognitive network FC were related to structural differences. Tract-based spatial statistical analyses (TBSS) were conducted to assess the microstructural properties of white matter tracts. We also compared internetwork connectivity between patients. Finally, a logistic regression analysis was used to investigate baseline imaging predictors of CA development. Results and Discussion: We observed a significantly reduced FC of both DMN and CEN in patients with MwoA developing CA (MwoA dCA) when compared with both patients with MwoA not developing CA (MwoA ndCA) and HC. Within the DMN, the PCC/precuneus is a key hub aimed to anti-nociception and multisensory integration. The reduced intrinsic PCC/precuneus FC observed in patients with MwoA dCA could subtend abnormal inputs integration, from different sensory modalities, allowing the development of CA. On the other hand, within the CEN, a central role in pain modulation as well as in executive functions is played by ACC and MFG. Our finding of reduced ACC and MFG FC in MwoA dCA may represent the neuronal substrate of both subclinical impairment of complex executive functions and dysfunctional anti-nociceptive pathway, making these patients more prone to migraine chronification. TBSS analyses showed a statistically significant reduced corpus callosum (CC) FA in patients with MwoA dCA as previously demonstrated in migraine patients with other chronification factors such as medication overuse or affective disorders. No VBM differences in both global and local volumes were revealed between groups. No significant correlations have been found between the observed functional and microstructural changes and clinical parameters of disease severity. Logistic regression analysis indicated that the full model containing all predictors was statistically significant while the decreased ACC-FC was significantly associated with CA development. Conclusion: We suggest that DMN and CEN FC abnormalities as well as CC microstructural changes could represent a prognostic imaging biomarker able to identify migraine patients more prone to experiencing CA and therefore, more inclined to chronic migraine. In the new pharmacological scenario, it would be useful to address therapeutic resources to specific migraine populations with a high risk of more severe clinical phenotype.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
