Migraine affects over a billion individuals worldwide but its genetic underpinning remains largely unknown. Here, we performed a genome-wide association study of 102,084 migraine cases and 771,257 controls and identified 123 loci, of which 86 are previously unknown. These loci provide an opportunity to evaluate shared and distinct genetic components in the two main migraine subtypes: migraine with aura and migraine without aura. Stratification of the risk loci using 29,679 cases with subtype information indicated three risk variants that seem specific for migraine with aura (in HMOX2, CACNA1A and MPPED2), two that seem specific for migraine without aura (near SPINK2 and near FECH) and nine that increase susceptibility for migraine regardless of subtype. The new risk loci include genes encoding recent migraine-specific drug targets, namely calcitonin gene-related peptide (CALCA/CALCB) and serotonin 1F receptor (HTR1F). Overall, genomic annotations among migraine-associated variants were enriched in both vascular and central nervous system tissue/cell types, supporting unequivocally that neurovascular mechanisms underlie migraine pathophysiology.

Genome-wide association analyses using high-throughput metabolomics platforms have led to novel insights into the biology of human metabolism^1–7. This detailed knowledge of the genetic determinants of systemic metabolism has been pivotal for uncovering how genetic pathways influence biological mechanisms and complex diseases^8–11. Here we present a genome-wide association study for 233 circulating metabolic traits quantified by nuclear magnetic resonance spectroscopy in up to 136,016 participants from 33 cohorts. We identify more than 400 independent loci and assign probable causal genes at two-thirds of these using manual curation of plausible biological candidates. We highlight the importance of sample and participant characteristics that can have significant effects on genetic associations. We use detailed metabolic profiling of lipoprotein- and lipid-associated variants to better characterize how known lipid loci and novel loci affect lipoprotein metabolism at a granular level. We demonstrate the translational utility of comprehensively phenotyped molecular data, characterizing the metabolic associations of intrahepatic cholestasis of pregnancy. Finally, we observe substantial genetic pleiotropy for multiple metabolic pathways and illustrate the importance of careful instrument selection in Mendelian randomization analysis, revealing a putative causal relationship between acetone and hypertension. Our publicly available results provide a foundational resource for the community to examine the role of metabolism across diverse diseases.

Background and Aims: Observational studies have suggested a bidirectional association between depression and inflammatory bowel disease [IBD], including Crohn’s disease [CD] and ulcerative colitis [UC]. However, it remains unclear whether the observed associations are causal due to the difficulties of determining sequential temporality. We investigated the association between depression and IBD by using bidirectional two-sample Mendelian randomization [MR]. Methods: Independent genetic variants for depression and IBD were selected as instruments from published genome-wide association studies [GWAS] among individuals of predominantly European ancestry. Summary statistics for instrument–outcome associations were retrieved from three separate databases for both depression [Psychiatric Genomics Consortium, FinnGen and UK Biobank] and IBD [the largest GWAS meta-analysis, FinnGen and UK Biobank], respectively. MR analyses included the inverse-variance-weighted method, weighted-median estimator, MR-Egger regression, and sensitivity analyses of Steiger filtering and MR PRESSO. From either direction, analyses were performed per outcome database and were subsequently meta-analysed using a fixed-effect model. Results: Genetically predicted depression [per log-odds ratio increase] was associated with a higher risk of IBD; odds ratios [95% confidence interval] for IBD, CD and UC were 1.20 [1.05, 1.36], 1.29 [1.07, 1.56] and 1.22 [1.01, 1.47] in a combined sample size of 693 183 [36 507 IBD cases], 212 172 [13 714 CD cases] and 219 686 [15 691 UC cases] individuals, respectively. In contrast, no association was observed between genetically influenced IBD and depression in 534 635 individuals [71 466 depression cases]. Conclusions: Our findings corroborated a causal association of depression on IBD, which may impact the clinical decision on the management of depression in patients with IBD. Though our results did not support a causal effect of IBD on depression, further investigations are needed to clarify the effect of IBD activity on depression [with different symptomology].

To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases.