Musculoskeletal pain is associated with restless legs syndrome in young adults

Background - In recent years, there is considerable evidence of a relationship between the sensorimotor disorder restless legs syndrome (RLS) and pain disorders, including migraine and fibromyalgia. An association between multi-site pain and RLS has been reported in adult women. In the current study, we explored the association between musculoskeletal (MSK) pain and RLS in a large cohort of young adults. Methods - Twenty two year olds (n = 1072), followed since birth of part of the Western Australian Pregnancy Cohort (Raine) Study, provided data on MSK pain (duration, severity, frequency, number of pain sites). RLS was considered present when 4 diagnostic criteria recommended by the International Restless Legs Syndrome Study Group were met (urge to move, dysaesthesia, relief by movement, worsening symptoms during the evening/night) and participants had these symptoms at least 5 times per month. Associations between MSK pain and RLS were analyzed by multivariable logistic regression with bias-corrected bootstrapped confidence intervals, with final models adjusted for sex, psychological distress and sleep quality. Results - The prevalence of RLS was 3.0 % and MSK pain was reported by 37.4 % of the participants. In multivariable logistic regression models, strong associations were found between RLS-diagnosis and long duration (three months or more) of MSK pain (odds ratio 3.6, 95 % confidence interval 1.4–9.2) and reporting three or more pain sites (4.9, 1.6–14.6). Conclusions - Different dimensions of MSK pain were associated with RLS in young adults, suggestive of shared pathophysiological mechanisms. Overlap between these conditions requires more clinical and research attention

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

Analysis of shared heritability in common disorders of the brain

Paroxysmal Cerebral Disorder

Pathogenic ischemic stroke phenotypes in the NINDS-Stroke Genetics Network

BACKGROUND AND PURPOSE: NINDS (National Institute of Neurological Disorders and Stroke)-SiGN (Stroke Genetics Network) is an international consortium of ischemic stroke studies that aims to generate high-quality phenotype data to identify the genetic basis of pathogenic stroke subtypes. This analysis characterizes the etiopathogenetic basis of ischemic stroke and reliability of stroke classification in the consortium. METHODS: Fifty-two trained and certified adjudicators determined both phenotypic (abnormal test findings categorized in major pathogenic groups without weighting toward the most likely cause) and causative ischemic stroke subtypes in 16 954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries using the web-based Causative Classification of Stroke System. Classification reliability was assessed with blinded readjudication of 1509 randomly selected cases. RESULTS: The distribution of pathogenic categories varied by study, age, sex, and race (P<0.001 for each). Overall, only 40% to 54% of cases with a given major ischemic stroke pathogenesis (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (κ 0.72; 95% confidence interval, 0.69-0.75) and phenotypic classifications (κ 0.73; 95% confidence interval, 0.70-0.75). CONCLUSIONS: This study demonstrates that pathogenic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes highlights the fact that the presence of an abnormality in a patient with stroke does not necessarily mean that it is the cause of stroke

Shared genetic basis for migraine and ischemic stroke: A genome-wide analysis of common variants

Objective: To quantify genetic overlap between migraine and ischemic stroke (IS) with respect to common genetic variation. Methods: We applied 4 different approaches to large-scale meta-analyses of genome-wide data on migraine (23,285 cases and 95,425 controls) and IS (12,389 cases and 62,004 controls). First, we queried known genome-wide significant loci for both disorders, looking for potential overlap of signals. We then analyzed the overall shared genetic load using polygenic scores and estimated the genetic correlation between disease subtypes using data derived from these models. We further interrogated genomic regions of shared risk using analysis of covariance patterns between the 2 phenotypes using cross-phenotype spatial mapping. Results: We found substantial genetic overlap between migraine and IS using all 4 approaches. Migraine without aura (MO) showed much stronger overlap with IS and its subtypes than migraine with aura (MA). The strongest overlap existed between MO and large artery stroke (LAS; p 6.4 × 10-28 for the LAS polygenic score in MO) and between MO and cardioembolic stroke (CE; p 2.7 × 10-20 for the CE score in MO). Conclusions: Our findings indicate shared genetic susceptibility to migraine and IS, with a particularly strong overlap between MO and both LAS and CE pointing towards shared mechanisms. Our observations on MA are consistent with a limited role of common genetic variants in this subtype