A genome-wide cross-phenotype meta-analysis of the association of blood pressure with migraine

DOI: https://doi.org/10.1038/s41467- 020- 17002- 0

large-scale

Abstract-Summary (Ncases/ Leveraging Ncontrols = 59,674/316,078) and BP (N = 757,601), we find positive genetic correla- tions of migraine with diastolic BP (DBP, rg = 0.11, p = 3.56 × 10−06) and systolic BP (SBP, rg = 0.06, p = 0.01), but not pulse pressure (PP, rg = −0.01, p = 0.75).

for migraine

summary

statistics

Cross-trait meta-analysis reveals 14 shared loci (p ≤ 5 × 10−08), nine of which rep-

licate (p < 0.05) in the UK Biobank.

Mendelian randomization reveals stronger instrumental estimates of DBP (OR [95% CI] = 1.20 [1.15–1.25]/10 mmHg; p = 5.57 × 10−25) on migraine than SBP (1.05 [1.03–1.07]/10 mmHg; p = 2.60 × 10−07) and a corresponding opposite effect for PP (0.92 [0.88–0.95]/10 mmHg; p = 3.65 × 10−07).

Extended: Cross-trait meta-analysis reveals shared loci between BP and migraine, some of which are also reinforced in gene-level analysis highlighting potential shared biological mechanisms.

The findings further our understanding of the long-standing debate about the role of BP in migraine susceptibility, reveal the prominent genetic-based role of DBP in migraine susceptibility, and identify shared genetic components including ADRA2B, all of which may provide insight into future migraine therapies.

Introduction Some studies have found associations between elevated systolic BP (SBP) or dia- stolic BP (DBP) and lower prevalence of migraine [150], whereas some have found inverse associations only for SBP [151, 152].

One study suggested that migraine was associated with higher DBP but lower

SBP [153].

Developed but widely accepted genetic methods leveraging only GWAS sum- mary statistics may be used to estimate global [154] and local genetic correlation [155] between BP measures (i.e. SBP, DBP, or PP) and migraine.

Additional genetic methods using GWAS summary statistics, including cross- trait meta-analysis [156] and transcriptome-wide association study (TWAS) [157], may be used to identify specific shared genetic components and pathophysiology between BP and migraine.

Our analysis identifies positive overall genetic correlations of migraine with DBP and SBP, but not PP, and evidence of local genetic overlap with BP at certain previously identified migraine loci after accounting for multiple testing.

Our results suggest a critical role of DBP in migraine susceptibility and shared

biological mechanisms between BP and migraine.

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Results Lead SNP rs6438857 (at chr3q21.2, PCPASSOC = 2.64 × 10−22, 1.77 × 10−23, 2.55 × 10−14 for DBP, SBP, and PP, respectively based on SHet statistic) implicating ITGB5 was the only locus that was shared between migraine and all the three BP measurements.

Reverse MR showed significant negative instrumental effects per doubling odds of migraine on SBP (estimate = 0.67 mmHg decrement, Wald test p = 1.01 × 10−10) and PP (estimate = 0.55 mmHg decrement, Wald test p = 3.21 × 10−15), but not DBP (estimate = 0.08 mmHg decrement, Wald test p = 0.45).

For significance thresholds of p < 5 × 10−8 or smaller, the instrumental effects of DBP and SBP for migraine were associated respectively with increased and decreased migraine susceptibility.

Discussion The conclusions from our genetic analyses were highly consistent and generally support observational associations of positive correlation between BP and migraine [158] but also qualify these associations in important ways.

Consistent with distinct effects of SBP and DBP, greater genetically determined PP was strongly associated with less susceptibility to migraine in the instrumental variable analysis.

Because we leveraged germline genetic variation as instrumental variables from large independent studies, our causal estimates will be less affected by reverse cau- sation and possibly also selection bias than inference about relationships between BP and migraine from observational epidemiology [159, 160].

To the results for the genetic effects of DBP and PP on migraine, the genetic association between BP and cardiovascular events was driven by SBP, consistent with the results from observational studies [161].

This study comprehensively investigates the genetic-based association between

migraine and BP.

Methods We used the most recent GWAS summary-level data from International Headache Genetics Consortium (IHGC) for migraine (any migraine and two subtypes of migraine: migraine with aura [MA] and migraine without aura [MO]) and from the International Consortium of Blood Pressure-Genome Wide Association Studies (ICBP) and UK Biobank (UKB) for three BP traits (SBP, DBP, and PP) [162, 163]. With TWAS, we compared gene-based models of genetic effects on tissue- specific gene expression from GTEx v.7 for migraine and the BP measures from the GWAS summary statistics to estimate strength of association between concordant gene-based genetic influences on gene expression on migraine or BP.

To evaluate separate effects of SBP and DBP on migraine, we performed condi- tional instrumental analysis using mtCOJO (multi-trait-based conditional and joint analysis), also within GSMR, with a two-step procedure requiring only the GWAS summary statistics [164].

2.2 Biology

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Acknowledgement A machine generated summary based on the work of Guo, Yanjun; Rist, Pamela M.; Daghlas, Iyas; Giulianini, Franco; Gormley, Padhraig; Anttila, Verneri; Winsvold, Bendik S.; Palta, Priit; Esko, Tonu; Pers, Tune H.; Farh, Kai-How; Cuenca-Leon, Ester; Muona, Mikko; Furlotte, Nicholas A.; Kurth, Tobias; Ingason, Andres; McMahon, George; Ligthart, Lannie; Terwindt, Gisela M.; Kallela, Mikko; Freilinger, Tobias M.; Ran, Caroline; Gordon, Scott G.; Stam, Anine H.; Steinberg, Stacy; Borck, Guntram; Koiranen, Markku; Quaye, Lydia; Adams, Hieab H.  H.; Lehtimäki, Terho; Sarin, Antti-Pekka; Wedenoja, Juho; Hinds, David A.; Buring, Julie E.; Schürks, Markus; Ridker, Paul M.; Hrafnsdottir, Maria Gudlaug; Stefansson, Hreinn; Ring, Susan M.; Hottenga, Jouke-Jan; Penninx, Brenda W. J. H.; Färkkilä, Markus; Artto, Ville; Kaunisto, Mari; Vepsäläinen, Salli; Malik, Rainer; Heath, Andrew C.; Madden, Pamela A. F.; Martin, Nicholas G.; Montgomery, Grant W.; Kurki, Mitja; Kals, Mart; Mägi, Reedik; Pärn, Kalle; Hämäläinen, Eija; Huang, Hailiang; Byrnes, Andrea E.; Franke, Lude; Huang, Jie; Stergiakouli, Evie; Lee, Phil H.; Sandor, Cynthia; Webber, Caleb; Cader, Zameel; Muller-Myhsok, Bertram; Schreiber, Stefan; Meitinger, Thomas; Eriksson, Johan G.; Salomaa, Veikko; Heikkilä, Kauko; Loehrer, Elizabeth; Uitterlinden, Andre G.; Hofman, Albert; van Duijn, Cornelia M.; Cherkas, Lynn; Pedersen, Linda M.; Stubhaug, Audun; Nielsen, Christopher S.; Männikkö, Minna; Mihailov, Evelin; Milani, Lili; Göbel, Hartmut; Esserlind, Ann-Louise; Christensen, Anne Francke; Hansen, Thomas Folkmann; Werge, Thomas; Kaprio, Jaakko; Aromaa, Arpo J.; Raitakari, Olli; Ikram, M. Arfan; Spector, Tim; Järvelin, Marjo-Riitta; Metspalu, Andres; Kubisch, Christian; Strachan, David P.; Ferrari, Michel D.; Belin, Andrea C.; Dichgans, Martin; Wessman, Maija; van den Maagdenberg, Arn M.  J. M.; Zwart, John-Anker; Boomsma, Dorret I.; Smith, George Davey; Stefansson, Kari; Eriksson, Nicholas; Daly, Mark J.; Neale, Benjamin M.; Olesen, Jes; Chasman, Daniel I.; Nyholt, Dale R.; Palotie, Aarno; Agee, Michelle; Auton, Adam; Bell, Robert K.; Bryc, Katarzyna; Elson, Sarah L.; Fontanillas, Pierre; Furlotte, Nicholas A.; Hinds, David A.; Huber, Karen E.; Kleinman, Aaron; Litterman, Nadia K.; McCreight, Jennifer C.; McIntyre, Matthew H.; Mountain, Joanna L.; Noblin, Elizabeth S.; Northover, Carrie A. M.; Pitts, Steven J.; Sathirapongsasuti, J.  Fah; Sazonova, Olga V.; Shelton, Janie F.; Shringarpure, Suyash; Tian, Chao; Tung, Joyce Y.; Vacic, Vladimir; Kurth, Tobias; Chasman, Daniel I. 2020 in Nature Communications.

2.2

Biology

Machine generated keywords: interictal, interictal period, phase, period, trigger, animal, vestibular, csd, phase migraine, migraineur, participant, aura, vestibular migraine, nucleus, cerebral

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Migraine Aura: Updates in Pathophysiology and Management