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Data from: Large scale plasma metabolome analysis reveals alterations in HDL metabolism in migraine

Onderwater, Gerrit L.J., Leiden University Medical Center
Ligthart, Lannie, VU University Amsterdam
Bot, Mariska
Demirkan, Ayse, Leiden University Medical Center
Fu, Jingyuan, University Medical Center Groningen
van der Kallen, Carla J.H.
Vijfhuizen, Lisanne S., Leiden University Medical Center
Pool, René, VU University Amsterdam
Liu, Jun, Departments of Epidemiology and Neurology, Erasmus Medical Centre, Rotterdam
Vanmolkot, Floris H.M., Maastricht University Medical Centre
Beekman, Marian, VU University Medical Center
Wen, Hoyan
Amin, Najaf, Departments of Epidemiology and Neurology, Erasmus Medical Centre, Rotterdam
Thesing, Carisha S., VU University Medical Center
Pijpers, Judith A., Leiden University Medical Center
Kies, Dennis A., Leiden University Medical Center
Zielman, Ronald, Leiden University Medical Center
de Boer, Irene
van Greevenbroek, Marleen M.J.
Arts, Ilja C.W., Maastricht University
Milaneschi, Yuri, VU University Medical Center
Schram, Miranda T., Maastricht University
Dagnelie, Pieter C., Maastricht University
Franke, Lude, University Medical Center Groningen
Ikram, M. Arfan, Erasmus University Medical Center
Ferrari, Michel D., Leiden University Medical Center
Goeman, Jelle J., Leiden University Medical Center
Slagboom, P. Eline, Leiden University Medical Center
Wijmenga, Cisca, University Medical Center Groningen
Stehouwer, Coen D.A., Maastricht University
Boomsma, Dorret I., Amsterdam Neuroscience
van Duijn, Cornelia M.
Penninx, Brenda W., VU University Medical Center
’t Hoen, Peter A.C.
Terwindt, Gisela M., Leiden University Medical Center
van den Maagdenberg, Arn M.J.M.
Published Apr 08, 2019 on Dryad. https://doi.org/10.5061/dryad.p698mn7

Cite this dataset

Onderwater, Gerrit L.J. et al. (2019). Data from: Large scale plasma metabolome analysis reveals alterations in HDL metabolism in migraine [Dataset]. Dryad. https://doi.org/10.5061/dryad.p698mn7

Abstract

Objective: To identify a plasma metabolomic biomarker signature for migraine. Methods: Plasma samples from 8 Dutch cohorts (n = 10,153: 2,800 migraine patients and 7,353 controls) were profiled on a 1H-NMR-based metabolomics platform, to quantify 146 individual metabolites (e.g., lipids, fatty acids, and lipoproteins) and 79 metabolite ratios. Metabolite measures associated with migraine were obtained after single-metabolite logistic regression combined with a random-effects meta-analysis performed in a nonstratified and sex-stratified manner. Next, a global test analysis was performed to identify sets of related metabolites associated with migraine. The Holm procedure was applied to control the family-wise error rate at 5% in single-metabolite and global test analyses. Results: Decreases in the level of apolipoprotein A1 (β −0.10; 95% confidence interval [CI] −0.16, −0.05; adjusted p = 0.029) and free cholesterol to total lipid ratio present in small high-density lipoprotein subspecies (HDL) (β −0.10; 95% CI −0.15, −0.05; adjusted p = 0.029) were associated with migraine status. In addition, only in male participants, a decreased level of omega-3 fatty acids (β −0.24; 95% CI −0.36, −0.12; adjusted p = 0.033) was associated with migraine. Global test analysis further supported that HDL traits (but not other lipoproteins) were associated with migraine status. Conclusions: Metabolic profiling of plasma yielded alterations in HDL metabolism in migraine patients and decreased omega-3 fatty acids only in male migraineurs.

Usage notes

Methods_e-1_Cohort_background

Methods e-1 Cohort background, migraine assessment method, and sampling procedure.

Figure_e-1_Influence_of_Heritability

Figure e-1: Influence of heritability on metabolite estimates and log p-values in ERF and NTR.

Figure_e-2_Ratio_stratification_plots_migraine_smoking

Figure e-2: ApoA1 and S-HDL-FC ratio stratification plots for migraine and smoking in NESDA and LUMINA.

Figure_e-3_Ratio_stratification_plots_migraine_lipid_lowering_medication

Figure e-3: ApoA1 and S-HDL-FC ratio stratification plots for migraine and lipid lowering medication usage in NESDA and LUMINA.

Figure_e-4_Ratio_stratification_plots_migraine_fasting

Figure e-4: ApoA1 and S-HDL-FC ratio stratification plots for migraine and fasting in NESDA and LUMINA.

Figure_e-5_Ratio_stratification_plots_migraine_depression

Figure e-5: ApoA1 and S-HDL-FC ratio stratification plots for migraine and depression in NESDA and LUMINA.

Figure_e-6_Ratio_stratification_plots_migraine_body_mass_index

Figure e-6: ApoA1 and S-HDL-FC ratio stratification plots for migraine and body mass index in NESDA and LUMINA.

Figure_e-7_Metabolite_correlation_between_measurements_and_over_time

Figure e-7: Metabolite correlations between measurements and over time for apoA1 and the S-HDL-FC ratio.

Figure_e-8_HDL_feature_plots_for_all_individual_cohorts

Figure e-8: HDL feature plots for all individual cohorts.

Table_e-1_Included_metabolites_in_pathways

Table e-1: Included metabolites in (sub-)pathways

Table_e-2_Included_metabolite_ratios

Table e-2: Included metabolite ratio’s

Table_e-3_Results_from_logistic_regression_sex_age_migraine

Table e-3: Results from logistic regression with metabolite concentrations, sex, and age as independent variables and migraine status as dependent variable.

Table_e-4_Meta_analysis_results_of_the_logistic_regression

Table e-4: Meta-analysis results of the logistic regressions with sex, age, and metabolite concentrations as independent variables and migraine status as dependent variable.

Table_e-5_Results_logistic_regression_LLM_BMI_sex_age_migraine

Table e-5: Results logistic regression with metabolite concentrations, lipid lowering medication usage, body mass index, sex, and age as independent variables and migraine status as dependent variable.