Heritability estimates for 361 blood metabolites across 40 genome-wide association studies

Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify >800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h2 total), and the proportion of heritability captured by known metabolite loci (h2 Metabolite-hits) for 309 lipids and

Sex differences in prevalence of migraine trigger factors: A cross-sectional study

Aim: To examine the effect of sex on migraine trigger factors. Methods: Prevalence of 11 frequently reported trigger factors was determined in a cross-sectional study among migraine patients from a validated migraine database (n = 5725 females and n = 1061 males). Female-to-male odds ratios were calculated for each trigger, using a logistic regression model with attack frequency and migraine subtype (with or without aura) as covariates. Additionally, the effect of sex on total number of triggers per individual was determined. Results: The top three most reported triggers in women were menstruation (78%), stress (77%), and bright light (69%). Men reported stress (69%), bright light (63%), and sleep deprivation (60%) most frequently as provoking factors. The following triggers were more often reported by women than men: Bright light (odds ratio 1.29 [95% CI 1.12–1.48]; p = 0.003), stress (1.47 [1.27–1.69]; p < 0.001), skipping a meal (1.24 [1.09–1.42]; p = 0.015), sleep deprivation (1.37 [1.20–1.57]; p < 0.001), high altitudes (1.70 [1.40–2.09]; p < 0.001), and weather changes (1.35 [1.18–1.55]; p < 0.001). Women reported more triggers than men, even when menstruation was disregarded (mean ± SD: 4.6 ± 2.3 and 4.3 ± 2.3; p < 0.001). Conclusion: Women report migraine trigger factors to be provocative of their attacks more frequently than men, which may be related to a lower migraine threshold due to sex hormonal changes

Prostaglandin-E2 levels over the course of glyceryl trinitrate provoked migraine attacks

Administration of glyceryl trinitrate (GTN), a donor of nitric oxide, can induce migraine-like attacks in subjects with migraine. Provocation with GTN typically follows a biphasic pattern; it induces immediate headache in subjects with migraine, as well as in healthy controls, whereafter only subjects with migraine may develop a migraine-like headache several hours later. Interestingly, intravenous infusion with prostaglandin-E2 (PGE2) can also provoke a migraine-like headache, but seems to have a more rapid onset compared to GTN. The aim of the study was to shed light on the mechanistic aspect PGE2 has in migraine attack development. Therefore, PGE2 plasma levels were measured towards the (pre)ictal state of an attack, which we provoked with GTN. Blood samples from women with migraine (n = 37) and age-matched female controls (n = 25) were obtained before and ∼ 140 min and ∼ 320 min after GTN infusion. PGE2 levels were measured using liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis. Data was analyzed using a generalized linear mixed-effect model. Immediate headache after GTN infusion occurred in 85 % of migraine participants and in 75 % of controls. A delayed onset migraine-like attack was observed in 82 % of migraine subjects and in none of the controls. PGE2 levels were not different between the interictal and preictal state (P = 0.527) nor between interictal and ictal state (defined as having migraine-like headache) (P = 0.141). Hence, no evidence was found that a rise in PGE2 is an essential step in the initiation of GTN-induced migraine-like attacks

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

Large-scale plasma metabolome analysis reveals alterations in HDL metabolism in migraine

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

Table_e-1_Included_metabolites_in_pathways

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

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

Figure_e-8_HDL_feature_plots_for_all_individual_cohorts

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

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-2_Included_metabolite_ratios

Table e-2: Included metabolite ratio’