Erratum: Corrigendum: Meta-analysis of 375,000 individuals identifies 38 susceptibility loci for migraine

Noncausal effects between tea intake and migraine risk: a Mendelian randomization study

Observational studies have yielded conflicting results regarding the relationship between tea intake and migraine risk. Residual confounders and potential reverse causality are unavoidable in traditional observational studies. To provide evidence for establishing viable disease screening and prevention strategies, a Mendelian randomization study (MR) was conducted to determine the causal inference between tea intake and migraine. We obtained 28 single-nucleotide polymorphisms (SNPs) for any migraine (AM), 25 SNPs for migraine with aura (MA), and 27 SNPs for migraine without aura (MO) associated with tea intake derived from a large genome-wide association study (GWAS) of the UK Biobank (UKBB) (containing 447,485 samples). The largest migraine GWAS performed by the International Headache Genetics Consortium (IHGC), including 29,209 cases and 172,931 controls, provided data on migraines and their subtypes (MA and MO). We used the method of inverse variance weighting (IVW) with fixed effects as the first-string MR selection. Sensitivity analysis and MR-pleiotropy residual sum and outlier (MR-PRESSO) method further assessed the robustness of the findings. Based on the conclusion of IVW in the fixed effects model, we found that tea intake had no causal relationship with AM risk (odds ratio (OR), 0.94; 95% confidence interval (CI), 0.70-1.25; P = 0.65), MA risk (OR, 0.93; 95% CI, 0.51-1.72; P = 0.83), or MO risk (OR, 0.90; 95% CI, 0.52-1.54; P = 0.69). Sensitivity analyses and MR-PRESSO showed no directional pleiotropy or heterogeneity. Our two-sample MR investigation found no causality between tea intake and migraine risk in European populations, implying that attempts to change tea drinking habits may not lead to a reduced risk of migraine.

Migraine: interactions between brain's trait and state

It is well established that migraine is a multifactorial disorder. A deep understanding of migraine should be based upon both the underlying traits and the current states affected by different physiological, psychological, and environmental factors. At this point, there is no framework fully meeting these criteria. Here, we describe a broader view of the migraine disorder defined as a dysfunctional brain state and trait interaction. In this model, we consider events that may enhance or diminish migraine responsivity based on an individual's trait and state. This could provide an expanded view for considering how migraine attacks are sometimes precipitated by "triggers" and sometimes not, how these factors only lead to migraine attacks in migraine patients, or how individuals with an increased risk for migraine do not show any symptoms at all. Summarizing recent studies and evidence that support the concept of migraine as a brain state-trait interaction can also contribute to improving patient care by highlighting the importance of precision medicine and applying measures that are able to capture how different traits and states work together to determine migraine.

Understanding Factors That Cause Tinnitus: A Mendelian Randomization Study in the UK Biobank

OBJECTIVES

To investigate the causal role of established risk factors and associated conditions to tinnitus and tinnitus severity in the UK Biobank.

DESIGN

The prospective cohort study with large dataset of >500,000 individuals. The analytical sample of 129,731 individuals in the UK Biobank of European descent. Participants were recruited from National Health Service registries, baseline age range between 37 and 73 years, response rate to baseline survey 6%. Participants were asked subjective questions about tinnitus and its severity. Previously observed associations (n = 23) were confirmed in the UK Biobank using logistic and ordinal regression models. Two-sample Mendelian randomization approaches were then used to test causal relationships between the 23 predictors and tinnitus and tinnitus severity. The main outcome measures were observational and genetic association between key demographics and determinants and two tinnitus outcomes (current tinnitus and tinnitus severity).

RESULTS

Prevalence of tinnitus was 20% and severe tinnitus 3.8%. The observational results are consistent with the previous literature, with hearing loss, older age, male gender, high BMI, higher deprivation, higher blood pressure, smoking history, as well as numerous comorbidities being associated with higher odds of current tinnitus. Mendelian randomization results showed causal correlations with tinnitus. Current tinnitus was predicted by genetically instrumented hearing loss (odds ratio [OR]: 8.65 [95% confidence interval (CI): 6.12 to 12.23]), major depression (OR: 1.26 [95% CI: 1.06 to 1.50]), neuroticism (OR: 1.48 [95% CI: 1.28 to 1.71]), and higher systolic blood pressure (OR: 1.01 [95% CI:1.00 to 1.02]). Lower odds of tinnitus were associated with longer duration in education (OR: 0.74 [95% CI: 0.63 to 0.88]), higher caffeine intake (OR: 0.89 [95% CI: 0.83 to 0.95]) and being a morning person (OR: 0.94 [95% CI: 0.90 to 0.98]). Tinnitus severity was predicted by a higher genetic liability to neuroticism (OR: 1.15 [95% CI: 1.06 to 1.26]) and schizophrenia (OR: 1.02 [95% CI: 1.00 to 1.04]).

CONCLUSIONS

Tinnitus data from the UK Biobank confirm established associated factors in the literature. Genetic analysis determined causal relationships with several factors that expand the understanding of the etiology of tinnitus and can direct future pathways of clinical care and research.

Genetic identification of cell types underlying brain complex traits yields insights into the etiology of Parkinson's disease

Genome-wide association studies have discovered hundreds of loci associated with complex brain disorders, but it remains unclear in which cell types these loci are active. Here we integrate genome-wide association study results with single-cell transcriptomic data from the entire mouse nervous system to systematically identify cell types underlying brain complex traits. We show that psychiatric disorders are predominantly associated with projecting excitatory and inhibitory neurons. Neurological diseases were associated with different cell types, which is consistent with other lines of evidence. Notably, Parkinson's disease was genetically associated not only with cholinergic and monoaminergic neurons (which include dopaminergic neurons) but also with enteric neurons and oligodendrocytes. Using post-mortem brain transcriptomic data, we confirmed alterations in these cells, even at the earliest stages of disease progression. Our study provides an important framework for understanding the cellular basis of complex brain maladies, and reveals an unexpected role of oligodendrocytes in Parkinson's disease.

wtest: an integrated R package for genetic epistasis testing

BACKGROUND

With the increasing amount of high-throughput genomic sequencing data, there is a growing demand for a robust and flexible tool to perform interaction analysis. The identification of SNP-SNP, SNP-CpG, and higher order interactions helps explain the genetic etiology of human diseases, yet genome-wide analysis for interactions has been very challenging, due to the computational burden and a lack of statistical power in most datasets.

RESULTS

The wtest R package performs association testing for main effects, pairwise and high order interactions in genome-wide association study data, and cis-regulation of SNP and CpG sites in genome-wide and epigenome-wide data. The software includes a number of post-test diagnostic and analysis functions and offers an integrated toolset for genetic epistasis testing.

CONCLUSIONS

The wtest is an efficient and powerful statistical tool for integrated genetic epistasis testing. The package is available in CRAN: https://CRAN.R-project.org/package=wtest.

Pregnancy, Birth, Neonatal, and Postnatal Neurological Outcomes After Pregnancy With Migraine

BACKGROUND

Prevalence of migraine is high during the reproductive age. Although migraine often improves during pregnancy, the risk of adverse pregnancy, birth, neonatal, and neurological outcomes in mother and offspring remains poorly understood.

OBJECTIVE

To investigate the associations between maternal migraine and risks of adverse pregnancy outcomes in the mother, and birth, neonatal and postnatal outcomes in the offspring.

METHODS

We used Danish population registries to assemble a cohort of pregnancies among women with migraine and an age- and conception year-matched comparison cohort of pregnancies among women without migraine. The study period was 2005-2012. We computed adjusted prevalence ratios (aPRs) for pregnancy and birth outcomes and adjusted risk ratios (aRRs) for neonatal and postnatal outcomes, adjusting for age, preconception medical history, and preconception reproductive history.

RESULTS

We identified 22,841 pregnancies among women with migraine and 228,324 matched pregnancies among women without migraine. Migraine was associated with an increased risk of pregnancy-associated hypertension disorders (aPR: 1.50 [95% confidence interval (CI): 1.39-1.61]) and miscarriage (aPR: 1.10 [95% CI: 1.05-1.15]). Migraine was associated with an increased prevalence of low birth weight (aPR: 1.14 [95% CI: 1.06-1.23]), preterm birth (aPR: 1.21 [95% CI: 1.13-1.30]) and cesarean delivery (aPR: 1.20 [95% CI: 1.15-1.25]), but not of small for gestational age offspring (aPR: 0.94 [95% CI: 0.88-0.99]) and birth defects (aPR: 1.01 [95% CI: 0.93-1.09]). Offspring prenatally exposed to maternal migraine had elevated risks of several outcomes in the neonatal and postnatal period, including intensive care unit admission (aRR: 1.22 [95% CI: 1.03-1.45]), hospitalization (aRR: 1.12 [95% CI: 1.06-1.18]), dispensed prescriptions (aRR: 1.34 [95% CI: 1.24-1.45]), respiratory distress syndrome (aRR: 1.20 [95% CI: 1.02-1.42]), and febrile seizures (aRR: 1.27 [95% CI: 1.03-1.57), but not of death (aRR: 0.67 [95% CI: 0.43-1.04]) and cerebral palsy (aRR: 1.00 [95% CI: 0.51-1.94]).

CONCLUSIONS

Women with migraine and their offspring have greater risks of several adverse pregnancy outcomes than women without migraine.

Polygenic risk score: use in migraine research

BACKGROUND

The latest Genome-Wide Association Study identified 38 genetic variants associated with migraine. In this type of studies the significance level is very difficult to achieve (5 × 10^- 8) due to multiple testing. Thus, the identified variants only explain a small fraction of the genetic risk. It is expected that hundreds of thousands of variants also confer an increased risk but do not reach significance levels. One way to capture this information is by constructing a Polygenic Risk Score. Polygenic Risk Score has been widely used with success in genetics studies within neuropsychiatric disorders. The use of polygenic scores is highly relevant as data from a large migraine Genome-Wide Association Study are now available, which will form an excellent basis for Polygenic Risk Score in migraine studies.

RESULTS

Polygenic Risk Score has been used in studies of neuropsychiatric disorders to assess prediction of disease status in case-control studies, shared genetic correlation between co-morbid diseases, and shared genetic correlation between a disease and specific endophenotypes.

CONCLUSION

Polygenic Risk Score provides an opportunity to investigate the shared genetic risk between known and previously unestablished co-morbidities in migraine research, and may lead to better and personalized treatment of migraine if used as a clinical assistant when identifying responders to specific drugs. Polygenic Risk Score can be used to analyze the genetic relationship between different headache types and migraine endophenotypes. Finally, Polygenic Risk Score can be used to assess pharmacogenetic effects, and perhaps help to predict efficacy of the Calcitonin Gene-Related Peptide monoclonal antibodies that soon become available as migraine treatment.

Classification of common human diseases derived from shared genetic and environmental determinants

In this study, we used insurance claims for over one-third of the entire US population to create a subset of 128,989 families (481,657 unique individuals). We then used these data to (i) estimate the heritability and familial environmental patterns of 149 diseases and (ii) infer the genetic and environmental correlations for disease pairs from a set of 29 complex diseases. The majority (52 of 65) of our study's heritability estimates matched earlier reports, and 84 of our estimates appear to have been obtained for the first time. We used correlation matrices to compute environmental and genetic disease classifications and corresponding reliability measures. Among unexpected observations, we found that migraine, typically classified as a disease of the central nervous system, appeared to be most genetically similar to irritable bowel syndrome and most environmentally similar to cystitis and urethritis, all of which are inflammatory diseases.