Genetic causal relationship between immune diseases and migraine: a Mendelian randomization study

BackgroundMigraine has an increased prevalence in several immune disorders, but genetic cause-effect relationships remain unclear. Mendelian randomization (MR) was used in this study to explore whether immune diseases are causally associated with migraine and its subtypes.MethodsWe conducted a two-sample bidirectional multivariate Mendelian randomization study. Single-nucleotide polymorphisms (SNP) for six immune diseases, including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type 1 diabetes mellitus (T1D), allergic rhinitis (AR), asthma and psoriasis, were used as genetic instrumental variables. Summary statistics for migraine were obtained from 3 databases: the International Headache Genetics Consortium (IHGC), UK Biobank, and FinnGen study. MR analyses were performed per outcome database for each exposure and subsequently meta-analyzed. Reverse MR analysis was performed to determine whether migraine were risk factors for immune diseases. In addition, we conducted a genetic correlation to identify shared genetic variants for these two associations.ResultsNo significant causal relationship was found between immune diseases and migraine and its subtypes. These results were robust with a series of sensitivity analyses. Using the linkage disequilibrium score regression method (LDSC), we detected no genetic correlation between migraine and immune diseases.ConclusionThe evidence from our study does not support a causal relationship between immune diseases and migraine. The mechanisms underlying the frequent comorbidity of migraine and several immune diseases need to be further elucidated

Migraine polygenic risk score associates with efficacy of migraine-specific drugs

Objective To assess whether the polygenic risk score (PRS) for migraine is associated with acute and/or prophylactic migraine treatment response. Methods We interviewed 2,219 unrelated patients at the Danish Headache Center using a semistructured interview to diagnose migraine and assess acute and prophylactic drug response. All patients were genotyped. A PRS was calculated with the linkage disequilibrium pred algorithm using summary statistics from the most recent migraine genome-wide association study comprising ∼375,000 cases and controls. The PRS was scaled to a unit corresponding to a twofold increase in migraine risk, using 929 unrelated Danish controls as reference. The association of the PRS with treatment response was assessed by logistic regression, and the predictive power of the model by area under the curve using a case-control design with treatment response as outcome. Results A twofold increase in migraine risk associates with positive response to migraine-specific acute treatment (odds ratio [OR] = 1.25 [95% confidence interval (CI) = 1.05–1.49]). The association between migraine risk and migraine-specific acute treatment was replicated in an independent cohort consisting of 5,616 triptan users with prescription history (OR = 3.20 [95% CI = 1.26–8.14]). No association was found for acute treatment with non–migraine-specific weak analgesics and prophylactic treatment response. Conclusions The migraine PRS can significantly identify subgroups of patients with a higher-than-average likelihood of a positive response to triptans, which provides a first step toward genetics-based precision medicine in migraine

Sleep in psychotic disorders:results from nationwide SUPER Finland study

Abstract Objective: Characterizing sleep in patients with schizophrenia, schizoaffective disorder, bipolar disorder, and psychotic depression. Methods: This cross-sectional questionnaire study is based on the SUPER study sample, which is part of the Stanley Global Neuropsychiatric Genomics Initiative. The study is a multicentre, nationwide Finnish study consisting of patients (N = 8 623) both in primary and specialized health care. The main measurements were sleep duration, difficulties initiating sleep, early morning awakenings, and fatigue. These results were compared with a nationally representative sample of the Finnish population from the Health 2000 survey (N = 7 167) with frequency and logistic regression analyses. Results: Patients had more sleep problems compared with the general population, especially young and middle-aged patients (Difficulties initiating sleep in young patients odds ratio = 12.3, 95% CI 9.8–15.4). Long sleep duration was the most deviating property of the sleep characteristics, being particularly common among young patients with schizophrenia (odds ratio = 27.9, 95% CI 22.1–35.2, 47.4% vs 3.3% prevalence). All sleep problems were associated with worse subjective health. We also conducted a latent class analysis, resulting in a cluster relatively free of sleep problems (58% of patients), an insomnia symptom cluster (26%), and a hypersomnia symptom cluster (15%). Conclusions: In our sample, patients with psychotic disorders have more sleep problems—especially long sleep duration but also insomnia symptoms—compared with the general population. The patients can in a latent class analysis of their sleep symptoms be divided into groups with differing sleep profiles

Cohort profile:SUPER-Finland – the Finnish study for hereditary mechanisms of psychotic disorders

Abstract Purpose: SUPER-Finland is a large Finnish collection of psychosis cases. This cohort also represents the Finnish contribution to the Stanley Global Neuropsychiatric Genetics Initiative, which seeks to diversify genetic sample collection to include Asian, Latin American and African populations in addition to known population isolates, such as Finland. Participants: 10 474 individuals aged 18 years or older were recruited throughout the country. The subjects have been genotyped with a genome-wide genotyping chip and exome sequenced. A subset of 897 individuals selected from known population sub-isolates were selected for whole-genome sequencing. Recruitment was done between November 2015 and December 2018. Findings to date: 5757 (55.2%) had a diagnosis of schizophrenia, 944 (9.1%) schizoaffective disorder, 1612 (15.5%) type I or type II bipolar disorder, 532 (5.1 %) psychotic depression, 1047 (10.0%) other psychosis and for 530 (5.1%) self-reported psychosis at recruitment could not be confirmed from register data. Mean duration of schizophrenia was 22.0 years at the time of the recruitment. By the end of the year 2018, 204 of the recruited individuals had died. The most common cause of death was cardiovascular disease (n=61) followed by neoplasms (n=40). Ten subjects had psychiatric morbidity as the primary cause of death. Future plans: Compare the effects of common variants, rare variants and copy number variations (CNVs) on severity of psychotic illness. In addition, we aim to track longitudinal course of illness based on nation-wide register data to estimate how phenotypic and genetic differences alter it

Implementation of CYP2D6 copy-number imputation panel and frequency of key pharmacogenetic variants in Finnish individuals with a psychotic disorder

Abstract We demonstrate that CYP2D6 copy-number variation (CNV) can be imputed using existing imputation algorithms. Additionally, we report frequencies of key pharmacogenetic variants in individuals with a psychotic disorder from the genetically bottle-necked population of Finland. We combined GWAS chip and CYP2D6 CNV data from the Breast Cancer Pain Genetics study to construct an imputation panel (n = 902) for CYP2D6 CNV. The resulting data set was used as a CYP2D6 CNV imputation panel in 9262 non-related individuals from the SUPER-Finland study. Based on imputation of 9262 individuals we confirm the higher frequency of CYP2D6 ultrarapid metabolizers and a 22-fold enrichment of the UGT1A1 decreased function variant rs4148323 (UGT1A1*6) in Finland compared with non-Finnish Europeans. Similarly, the NUDT15 variant rs116855232 was highly enriched in Finland. We demonstrate that imputation of CYP2D6 CNV is possible and the methodology enables studying CYP2D6 in large biobanks with genome-wide data