Hospital variation of outcomes in status epilepticus.

OBJECTIVE: Understanding factors driving variation in status epilepticus outcomes would be critical to improve care. We evaluated the degree to which patient and hospital characteristics explained hospital-to-hospital variability in intubation and postacute outcomes. METHODS: This was a retrospective cohort study of Medicare beneficiaries admitted with status epilepticus between 2009 and 2019. Outcomes included intubation, discharge to a facility, and 30- and 90-day readmissions and mortality. Multilevel models calculated percent variation in each outcome due to hospital-to-hospital differences. RESULTS: We included 29 150 beneficiaries. The median age was 68 years (interquartile range [IQR] = 57-78), and 18 084 (62%) were eligible for Medicare due to disability. The median (IQR) percentages of each outcome across hospitals were: 30-day mortality 25% (0%-38%), any 30-day readmission 14% (0%-25%), 30-day status epilepticus readmission 0% (0%-3%), 30-day facility stay 40% (25%-53%), and intubation 46% (20%-61%). However, after accounting for many hospitals with small sample size, hospital-to-hospital differences accounted for 2%-6% of variation in all unadjusted outcomes, and approximately 1%-5% (maximally 8% for 30-day readmission for status epilepticus) after adjusting for patient, hospitalization, and/or hospital characteristics. Although many characteristics significantly predicted outcomes, the largest effect size was cardiac arrest predicting death (odds ratio = 10.1, 95% confidence interval = 8.8-11.7), whereas hospital characteristics (e.g., staffing, accreditation, volume, setting, services) all had lesser effects. SIGNIFICANCE: Hospital-to-hospital variation explained little variation in studied outcomes. Rather, certain patient characteristics (e.g., cardiac arrest) had greater effects. Interventions to improve outcomes after status epilepticus may be better focused on individual or prehospital factors, rather than at the inpatient systems level.

Accuracy of Noncontrast T2 SPACE in Active MS Cord Lesion Detection.

BACKGROUND AND PURPOSE: The diagnosis of active MS lesions is often based on postgadolinium T1-weighted MR imaging. Recent studies suggest a risk of IV gadolinium to patients, predominantly based on gadolinium deposition in tissue. Noncontrast sequences have shown promise in MS diagnosis, but none differentiate acute from chronic MS lesions. We hypothesized that 3D T2 sampling perfection with application-optimized contrasts by using different flip angle evolution (SPACE) MR imaging can help detect and differentiate active-versus-chronic MS lesions without the need for IV contrast. MATERIALS AND METHODS: In this single-center retrospective study, 340 spinal MR imaging cases of MS were collected in a 24-month period. Two senior neuroradiologists blindly and independently reviewed postcontrast T1-weighted sagittal and T2-SPACE sagittal images for the presence of MS lesions, associated cord expansion/atrophy on T2-SPACE, and enhancement on postcontrast T1WI. Discrepancies were resolved by consensus between the readers. Sensitivity, specificity, and accuracy of T2-SPACE compared with postcontrast T1WI were computed, and interobserver agreement was calculated. RESULTS: The sensitivity of lesion detection on T2-SPACE was 85.71%, 95% CI, 63.66%-96.95%; with a specificity of 93.52%, 95% CI, 90.06%-96.05%; and an accuracy of 92.99%, 95% CI, 89.58%-95.56. Additionally, 16/21 (84.2%) acute enhancing cord lesions showed cord expansion on T2-SPACE. The interobserver agreement was 92%. CONCLUSIONS: Our study shows that T2-SPACE facilitates noncontrast detection of acute MS lesions with high accuracy compared with postcontrast T1WI and with high interobserver agreement. The lack of gadolinium use provides an advantage, bypassing any potential adverse effects of repetitive contrast administration.

Genome-wide analysis of anorexia nervosa and major psychiatric disorders and related traits reveals genetic overlap and identifies novel risk loci for anorexia nervosa.

Anorexia nervosa (AN) is a heritable eating disorder (50-60%) with an array of commonly comorbid psychiatric disorders and related traits. Although significant genetic correlations between AN and psychiatric disorders and related traits have been reported, their shared genetic architecture is largely understudied. We investigated the shared genetic architecture of AN and schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), mood instability (Mood), neuroticism (NEUR), and intelligence (INT). We applied the conditional false discovery rate (FDR) method to identify novel risk loci for AN, and conjunctional FDR to identify loci shared between AN and related phenotypes, to summarize statistics from relevant genome-wide association studies (GWAS). Individual GWAS samples varied from 72,517 to 420,879 participants. Using conditional FDR we identified 58 novel AN loci. Furthermore, we identified 38 unique loci shared between AN and major psychiatric disorders (SCZ, BIP, and MD) and 45 between AN and psychological traits (Mood, NEUR, and INT). In line with genetic correlations, the majority of shared loci showed concordant effect directions. Functional analyses revealed that the shared loci are involved in 65 unique pathways, several of which overlapped across analyses, including the "signal by MST1" pathway involved in Hippo signaling. In conclusion, we demonstrated genetic overlap between AN and major psychiatric disorders and related traits, and identified novel risk loci for AN by leveraging this overlap. Our results indicate that some shared characteristics between AN and related disorders and traits may have genetic underpinnings.

Efficient cleaning of a macro-structured micro-rough dental implant shoulder with a new coronal vertical groove design: A technical note.

This evaluation assessed the influence of a new implant shoulder design on cleanability using a now established in-vitro study model. Eight test (Botticelli, Di Meliora AG, Basel, Switzerland) and eight control implants (T3 Osseotite, ZimVie, Winterthur, Switzerland), were embedded in standardized defects in simulated bone. The implant surfaces were painted to be visually distinguishable and debrided with ultrasonic instruments (US) and an air powder waterjet device (AIR). Uncleaned implants served as positive controls. After the standardized cleaning, the implants were photographed and divided into three zones (upper marginal shoulder zone (A); lower marginal shoulder zone (B); fully threaded sub-shoulder zone (C)), and analyzed with an image processing software. On test implants, AIR was almost 100% efficacious compared to 80-90% with US, in both upper zones (A/B). In control implants, results of both AIR and US were almost 100% in zone A, but only 55-75% in zone B. In both implants, AIR showed statistically significant higher efficacy than US (P<0.05). Within the limitations of the present in-vitro model, a new macro-structured micro-rough dental implant shoulder with a new coronal vertical groove design shows similar cleanability in comparison to a smooth and machined surface.

Improved multimodal prediction of progression from MCI to Alzheimer's disease combining genetics with quantitative brain MRI and cognitive measures.

INTRODUCTION: There is a pressing need for non-invasive, cost-effective tools for early detection of Alzheimer's disease (AD). METHODS: Using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), Cox proportional models were conducted to develop a multimodal hazard score (MHS) combining age, a polygenic hazard score (PHS), brain atrophy, and memory to predict conversion from mild cognitive impairment (MCI) to dementia. Power calculations estimated required clinical trial sample sizes after hypothetical enrichment using the MHS. Cox regression determined predicted age of onset for AD pathology from the PHS. RESULTS: The MHS predicted conversion from MCI to dementia (hazard ratio for 80th versus 20th percentile: 27.03). Models suggest that application of the MHS could reduce clinical trial sample sizes by 67%. The PHS alone predicted age of onset of amyloid and tau. DISCUSSION: The MHS may improve early detection of AD for use in memory clinics or for clinical trial enrichment. HIGHLIGHTS: A multimodal hazard score (MHS) combined age, genetics, brain atrophy, and memory. The MHS predicted time to conversion from mild cognitive impairment to dementia. MHS reduced hypothetical Alzheimer's disease (AD) clinical trial sample sizes by 67%. A polygenic hazard score predicted age of onset of AD neuropathology.

A scoping review of randomized clinical trials for pain management in pediatric tonsillectomy and adenotonsillectomy.

Objectives: To examine the volume, topics, and reporting trends in the published literature of randomized clinical trials for pharmacologic pain management of pediatric tonsillectomy and adenotonsillectomy and to identify areas requiring further research. Data Sources: PubMed (National Library of Medicine and National Institutes of Health), Scopus (Elsevier), CINAHL (EBSCO), and Cochrane Library (Wiley). Methods: A systematic search of four databases was conducted. Only randomized controlled or comparison trials examining pain improvement with a pharmacologic intervention in pediatric tonsillectomy or adenotonsillectomy were included. Data collected included demographics, pain-related outcomes, sedation scores, nausea/vomiting, postoperative bleeding, types of drug comparisons, modes of administration, timing of administration, and identities of the investigated drugs. Results: One hundred and eighty-nine studies were included for analysis. Most studies included validated pain scales, with the majority using visual-assisted scales (49.21%). Fewer studies examined pain beyond 24 h postoperation (24.87%), and few studies included a validated sedation scale (12.17%). Studies have compared several different dimensions of pharmacologic treatment, including different drugs, timing of administration, modes of administration, and dosages. Only 23 (12.17%) studies examined medications administered postoperatively, and only 29 (15.34%) studies examined oral medications. Acetaminophen only had four self-comparisons. Conclusion: Our work provides the first scoping review of pain and pediatric tonsillectomy. With drug safety profiles considered, the literature does not have enough data to determine which treatment regimen provides superior pain control in pediatric tonsillectomy. Even common drugs like acetaminophen and ibuprofen require further research for optimizing the treatment of posttonsillectomy pain. The heterogeneity in study design and comparisons weakens the conclusions of potential systematic reviews and meta-analyses. Future directions include more noninferiority studies of unique comparisons and more studies examining oral medications given postoperatively.

Auditory Outcomes in Children Who Undergo Cochlear Implantation Before 12 Months of Age: A Systematic Review.

OBJECTIVE: To systematically review the literature to determine auditory outcomes of cochlear implantation in children ≤12 months old. DATA SOURCE: PubMed, EMBASE, Medline, CINAHL, Cochrane, Scopus, and Web of Science databases were searched from inception to 9/1/2021 using PRISMA guidelines. REVIEW METHODS: Studies analyzing auditory outcomes after cochlear implantation (CI) in children ≤12 months of age were included. Non-English studies and case reports were excluded. Outcome measures included functional and objective auditory results. Two independent reviewers evaluated each abstract and article. Heterogeneity and bias across studies were evaluated. RESULTS: Of 305 articles identified, 17 met inclusion criteria. There were 642 children ages 2 to 12 months at CI. The most common etiologies of hearing loss were congenital CMV, meningitis, idiopathic hearing loss, and GJB2 mutations and other genetic causes. All studies concluded that early CI was safe. Overall, outcomes improved following early CI: IT-MAIS (9 studies), LittlEARS (4 studies), PTA (3 studies), CAP (3 studies), GASP (3 studies), and LNT (3 studies). Nine studies compared outcomes to an older implantation group (>12 months); of these (n = 450 early CI, n = 1189 late CI), 8 studies showed earlier CI achieved comparable or better auditory outcomes than later implantation, whereas 1 study (n = 120) concluded no differences in speech perception improvement. CONCLUSION: Auditory outcomes were overall improved in children ≤12 months old undergoing CI. Studies that compared early to late CI demonstrated similar or better auditory outcomes in early implantation group. Given the comparable safety profile and critical time period of speech and language acquisition, earlier CI should be considered for infants with hearing loss.

Vertebral Anomalies in Microtia Patients at a Tertiary Pediatric Care Center.

OBJECTIVE: Microtia is a congenital condition known to be associated with vertebral anomalies and congenital syndromes, most prominently hemifacial microsomia. There is controversy, however, on whether to screen with spinal imaging. Additionally, microtia ear reconstruction utilizes rib harvesting that could potentially worsen pre-existing vertebral and rib anomalies, specifically scoliosis. We report on the prevalence and characteristics of vertebral anomalies among microtia patients at a tertiary pediatric center. STUDY DESIGN: Retrospective case review with literature review. SETTING: Tertiary pediatric referral center. METHODS: A review of 425 children with microtia was conducted, characterized as either syndromic or nonsyndromic. Data included demographics, spinal imaging performed, indications, anomalies detected, and microtia repair. RESULTS: Among 425 microtia patients, 24.5% were syndromic with an average age of 9.7 years. Only 18.4% of all patients had spinal imaging performed (50% syndromic vs 8.1% nonsyndromic). Overall, 10.6% had a vertebral anomaly with a 57.7% detection rate (67.3% syndromic vs 38.5% nonsyndromic). The most common anomaly was scoliosis, with a prevalence of 7.8%. Fusion defects and rib deformities were the next most prominent. Microtia repair, most commonly with an autologous rib graft, was performed in 21.6% of the cohort. However, only 19.2% had spinal imaging and 16.7% with a vertebral anomaly. CONCLUSION: Children with microtia are at a greater risk of vertebral abnormalities. Scoliosis prevalence in isolated microtia is comparable to the general population (2%-3%) but greatly increased with genetic syndromes. Screening for vertebral anomalies should be considered when planning microtia reconstructions, especially in the syndromic population.

Charting the Landscape of Genetic Overlap Between Mental Disorders and Related Traits Beyond Genetic Correlation.

OBJECTIVE: Mental disorders are heritable and polygenic, and genome-wide genetic correlations (rg) have indicated widespread shared genetic risk across multiple disorders and related traits, mirroring their overlapping clinical characteristics. However, rg may underestimate the shared genetic underpinnings of mental disorders and related traits because it does not differentiate mixtures of concordant and discordant genetic effects from an absence of genetic overlap. Using novel statistical genetics tools, the authors aimed to evaluate the genetic overlap between mental disorders and related traits when accounting for mixed effect directions. METHODS: The authors applied the bivariate causal mixture model (MiXeR) to summary statistics for four mental disorders, four related mental traits, and height from genome-wide association studies (Ns ranged from 53,293 to 766,345). MiXeR estimated the number of "causal" variants for a given trait ("polygenicity"), the number of variants shared between traits, and the genetic correlation of shared variants (rgs). Local rg was investigated using LAVA. RESULTS: Among mental disorders, ADHD was the least polygenic (5.6K "causal" variants), followed by bipolar disorder (8.6K), schizophrenia (9.6K), and depression (14.5K). Most variants were shared across mental disorders (4.4K-9.3K) and between mental disorders and related traits (5.2K-12.8K), but with disorder-specific variations in rg and rgs. Overlap with height was small (0.7K-1.1K). MiXeR estimates correlated with LAVA local rg (r=0.88, p<0.001). CONCLUSIONS: There is extensive genetic overlap across mental disorders and related traits, with mixed effect directions and few disorder-specific variants. This suggests that genetic risk for mental disorders is predominantly differentiated by divergent effect distributions of pleiotropic genetic variants rather than disorder-specific variants. This represents a conceptual advance in our understanding of the landscape of shared genetic architecture across mental disorders, which may inform genetic discovery, biological characterization, nosology, and genetic prediction.

Genetic overlap between mood instability and alcohol-related phenotypes suggests shared biological underpinnings.

Alcohol use disorder (AUD) is a pervasive and devastating mental illness with high comorbidity rates with other mental disorders. Understanding the genetic architecture of this comorbidity could be improved by focusing on intermediate traits that show positive genetic correlation with the disorders. Thus, we aimed to characterize the shared vs. unique polygenicity of AUD, alcohol consumption (AC) and mood instability (MOOD) -beyond genetic correlation, and boost discovery for jointly-associated loci. Summary statistics for MOOD (a binary measure of the tendency to report frequent mood swings), AC (number of standard drinks over a typical consumption week) and AUD GWASs (Ns > 200,000) were analyzed to characterize the cross-phenotype associations between MOOD and AC, MOOD and AUD and AC and AUD. To do so, we used a newly established pipeline that combines (i) the bivariate causal mixture model (MiXeR) to quantify polygenic overlap and (ii) the conjunctional false discovery rate (conjFDR) to discover specific jointly associated genomic loci, which were mapped to genes and biological functions. MOOD was highly polygenic (10.4k single nucleotide polymorphisms, SNPs, SD = 2k) compared to AC (4.9k SNPs, SD = 0.6k) and AUD (4.3k SNPs, SD = 2k). The polygenic overlap of MOOD and AC was twice that of MOOD and AUD (98% vs. 49%), with opposite genetic correlation (-0.2 vs. 0.23), as confirmed in independent samples. MOOD&AUD associated SNPs were significantly enriched for brain genes, conversely to MOOD&AC. Among 38 jointly associated loci, fifteen were novel for MOOD, AC and AUD. MOOD, AC and AUD were also strongly associated at the phenotypic level. Overall, using multilevel polygenic quantification, joint loci discovery and functional annotation methods, we evidenced that the polygenic overlap between MOOD and AC/AUD implicated partly shared biological underpinnings, yet, clearly distinct functional patterns between MOOD&AC and MOOD&AUD, suggesting new mechanisms for the comorbidity of AUD with mood disorders.

Using Polygenic Hazard Scores to Predict Age at Onset of Alzheimer's Disease in Nordic Populations.

BACKGROUND: Polygenic hazard scores (PHS) estimate age-dependent genetic risk of late-onset Alzheimer's disease (AD), but there is limited information about the performance of PHS on real-world data where the population of interest differs from the model development population and part of the model genotypes are missing or need to be imputed. OBJECTIVE: The aim of this study was to estimate age-dependent risk of late-onset AD using polygenic predictors in Nordic populations. METHODS: We used Desikan PHS model, based on Cox proportional hazards assumption, to obtain age-dependent hazard scores for AD from individual genotypes in the Norwegian DemGene cohort (n = 2,772). We assessed the risk discrimination and calibration of Desikan model and extended it by adding new genotype markers (the Desikan Nordic model). Finally, we evaluated both Desikan and Desikan Nordic models in two independent Danish cohorts: The Copenhagen City Heart Study (CCHS) cohort (n = 7,643) and The Copenhagen General Population Study (CGPS) cohort (n = 10,886). RESULTS: We showed a robust prediction efficiency of Desikan model in stratifying AD risk groups in Nordic populations, even when some of the model SNPs were missing or imputed. We attempted to improve Desikan PHS model by adding new SNPs to it, but we still achieved similar risk discrimination and calibration with the extended model. CONCLUSION: PHS modeling has the potential to guide the timing of treatment initiation based on individual risk profiles and can help enrich clinical trials with people at high risk to AD in Nordic populations.

The shared genetic basis of mood instability and psychiatric disorders: A cross-trait genome-wide association analysis.

Recent genome-wide association studies of mood instability (MOOD) have found significant positive genetic correlation with major depression (DEP) and weak correlations with other psychiatric disorders. We investigated the polygenic overlap between MOOD and psychiatric disorders beyond genetic correlation to better characterize putative shared genetic determinants. GWAS summary statistics for schizophrenia (SCZ, n = 105,318), bipolar disorder (BIP, n = 413,466), DEP (n = 450,619), attention-deficit hyperactivity disorder (ADHD, n = 53,293), and MOOD (n = 363,705) were analyzed using the bivariate causal mixture model and conjunctional false discovery rate methods. MOOD correlated positively with all psychiatric disorders, but with wide variation in strength (rg = 0.10-0.62). Of 10.4 K genomic variants influencing MOOD, 4 K-9.4 K influenced psychiatric disorders. Furthermore, MOOD was jointly associated with DEP at 163 loci, SCZ at 110, BIP at 60 and ADHD at 25. Fifty-three jointly associated loci were overlapping across two or more disorders, seven of which had discordant effect directions on psychiatric disorders. Genes mapped to loci associated with MOOD and all four disorders were enriched in a single gene-set, "synapse organization." The extensive polygenic overlap indicates shared molecular underpinnings across MOOD and psychiatric disorders. However, distinct patterns of genetic correlation and effect directions may relate to differences in the core clinical features of each disorder.

Changes in the Use of Brand Name and Generic Medications and Total Prescription Cost Among Medicare Beneficiaries With Epilepsy.

OBJECTIVE: To characterize trends in antiseizure medication (ASM) fills and total prescription costs in people with epilepsy. METHODS: This was a retrospective cohort study of beneficiaries with epilepsy (ASM, plus International Classification of Diseases codes) in a 20% random Medicare sample, with continuous Fee-For-Service coverage (Parts A, B, and D) in 2008-2018. We summed the number of pill days and costs (adjusted to 2018 dollars) per person-year for each ASM. ASMs were categorized into brand versus generic, first- versus newer-generation, and enzyme-inducers versus non-inducers. RESULTS: There were 77,000-133,000 beneficiaries with epilepsy per year. The most common ASM was phenytoin in 2008, which shifted to levetiracetam in 2018 (2008: phenytoin 25%, levetiracetam 14%; 2018: phenytoin 9%, levetiracetam 27%). Brand name (2008: 56%; 2018: 14%), first-generation (2008: 55%; 2018: 32%), and enzyme-inducing ASMs (2008: 44%; 2018: 24%) each decreased over time as a proportion of pill days. The number of brand pill days per person-year initially decreased (e.g. 2008: 250; 2009: 121; 2010: 96), but then plateaued (2013-2018: between 66-69) given a notable increase in lacosamide pill days per person (2008: 0; 2018: 20). Total brand name costs per year initially decreased 2008-2010 (2008: $150 million; 2010: $72 million) but then increased after 2010 (2018: $256 million). In 2018 brand name ASMs represented 79% of costs despite representing only 14% of pill days, a one-year pill supply became 277% more expensive for brand name but 42% less expensive for generic medications over time (2008: brand ∼$2,800 versus generic ∼$800; 2018: brand ∼$10,700 versus generic ∼$460), and many common brand name ASMs cost approximately ten-fold more per pill day than their generic equivalents. CONCLUSIONS: First-generation and enzyme-inducing ASMs waned from 2008 to 2018. While brand name ASMs initially waned translating into lower costs and potentially higher value care, after 2010 brand name costs markedly increased due to increasing use of lacosamide plus a 277% increase in per-pill cost of brand name ASMs. Brand name ASMs represented a small minority of prescriptions, but the large majority of costs.

Polypharmacy composition and patient- and provider-related variation in patients with epilepsy.

OBJECTIVE: To describe polypharmacy composition, and the degree to which patients versus providers contribute to variation in medication fills, in people with epilepsy. METHODS: We performed a retrospective study of Medicare beneficiaries with epilepsy (antiseizure medication plus diagnostic codes) in 2014 (N = 78,048). We described total number of medications and prescribers, and specific medications. Multilevel models evaluated the percentage of variation in two outcomes (1. number of medications per patient-provider dyad, and 2. whether a medication was filled within thirty days of a visit) due to patient-to-patient differences versus provider-to-provider differences. RESULTS: Patients filled a median of 12 (interquartile range [IQR] 8-17) medications, from median of 5 (IQR 3-7) prescribers. Twenty-two percent filled an opioid, and 61% filled at least three central nervous system medications. Levetiracetam was the most common medication (40%), followed by hydrocodone/acetaminophen (27%). The strongest predictor of medications per patient was Charlson comorbidity index (7.5 [95% confidence interval (CI) 7.2-7.8] additional medications for index 8+ versus 0). Provider-to-provider variation explained 36% of variation in number of medications per patient, whereas patient-to-patient variation explained only 2% of variation. Provider-to-provider variation explained 57% of variation in whether a patient filled a medication within 30 days of a visit, whereas patient-to-patient variation explained only 30% of variation. CONCLUSION: Patients with epilepsy fill a large number of medications from a large number of providers, including high-risk medications. Variation in medication fills was substantially more related to provider-to-provider rather than patient-to-patient variation. The better understanding of drivers of high-prescribing practices may reduce avoidable medication-related harms.

Genetic Stratification of Age-Dependent Parkinson's Disease Risk by Polygenic Hazard Score.

BACKGROUND: Parkinson's disease (PD) is a highly age-related disorder, where common genetic risk variants affect both disease risk and age at onset. A statistical approach that integrates these effects across all common variants may be clinically useful for individual risk stratification. A polygenic hazard score methodology, leveraging a time-to-event framework, has recently been successfully applied in other age-related disorders. OBJECTIVES: We aimed to develop and validate a polygenic hazard score model in sporadic PD. METHODS: Using a Cox regression framework, we modeled the polygenic hazard score in a training data set of 11,693 PD patients and 9841 controls. The score was then validated in an independent test data set of 5112 PD patients and 5372 controls and a small single-study sample of 360 patients and 160 controls. RESULTS: A polygenic hazard score predicts the onset of PD with a hazard ratio of 3.78 (95% confidence interval 3.49-4.10) when comparing the highest to the lowest risk decile. Combined with epidemiological data on incidence rate, we apply the score to estimate genetically stratified instantaneous PD risk across age groups. CONCLUSIONS: We demonstrate the feasibility of a polygenic hazard approach in PD, integrating the genetic effects on disease risk and age at onset in a single model. In combination with other predictive biomarkers, the approach may hold promise for risk stratification in future clinical trials of disease-modifying therapies, which aim at postponing the onset of PD. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Dissecting the shared genetic basis of migraine and mental disorders using novel statistical tools.

Migraine is three times more prevalent in people with bipolar disorder or depression. The relationship between schizophrenia and migraine is less certain although glutamatergic and serotonergic neurotransmission are implicated in both. A shared genetic basis to migraine and mental disorders has been suggested but previous studies have reported weak or non-significant genetic correlations and five shared risk loci. Using the largest samples to date and novel statistical tools, we aimed to determine the extent to which migraine's polygenic architecture overlaps with bipolar disorder, depression and schizophrenia beyond genetic correlation, and to identify shared genetic loci. Summary statistics from genome-wide association studies were acquired from large-scale consortia for migraine (n cases = 59 674; n controls = 316 078), bipolar disorder (n cases = 20 352; n controls = 31 358), depression (n cases = 170 756; n controls = 328 443) and schizophrenia (n cases = 40 675, n controls = 64 643). We applied the bivariate causal mixture model to estimate the number of disorder-influencing variants shared between migraine and each mental disorder, and the conditional/conjunctional false discovery rate method to identify shared loci. Loci were functionally characterized to provide biological insights. Univariate MiXeR analysis revealed that migraine was substantially less polygenic (2.8 K disorder-influencing variants) compared to mental disorders (8100-12 300 disorder-influencing variants). Bivariate analysis estimated that 800 (SD = 300), 2100 (SD = 100) and 2300 (SD = 300) variants were shared between bipolar disorder, depression and schizophrenia, respectively. There was also extensive overlap with intelligence (1800, SD = 300) and educational attainment (2100, SD = 300) but not height (1000, SD = 100). We next identified 14 loci jointly associated with migraine and depression and 36 loci jointly associated with migraine and schizophrenia, with evidence of consistent genetic effects in independent samples. No loci were associated with migraine and bipolar disorder. Functional annotation mapped 37 and 298 genes to migraine and each of depression and schizophrenia, respectively, including several novel putative migraine genes such as L3MBTL2, CACNB2 and SLC9B1. Gene-set analysis identified several putative gene sets enriched with mapped genes including transmembrane transport in migraine and schizophrenia. Most migraine-influencing variants were predicted to influence depression and schizophrenia, although a minority of mental disorder-influencing variants were shared with migraine due to the difference in polygenicity. Similar overlap with other brain-related phenotypes suggests this represents a pool of 'pleiotropic' variants that influence vulnerability to diverse brain-related disorders and traits. We also identified specific loci shared between migraine and each of depression and schizophrenia, implicating shared molecular mechanisms and highlighting candidate migraine genes for experimental validation.

Performance of African-ancestry-specific polygenic hazard score varies according to local ancestry in 8q24.

BACKGROUND: We previously developed an African-ancestry-specific polygenic hazard score (PHS46+African) that substantially improved prostate cancer risk stratification in men with African ancestry. The model consists of 46 SNPs identified in Europeans and 3 SNPs from 8q24 shown to improve model performance in Africans. Herein, we used principal component (PC) analysis to uncover subpopulations of men with African ancestry for whom the utility of PHS46+African may differ. MATERIALS AND METHODS: Genotypic data were obtained from the PRACTICAL consortium for 6253 men with African genetic ancestry. Genetic variation in a window spanning 3 African-specific 8q24 SNPs was estimated using 93 PCs. A Cox proportional hazards framework was used to identify the pair of PCs most strongly associated with the performance of PHS46+African. A calibration factor (CF) was formulated using Cox coefficients to quantify the extent to which the performance of PHS46+African varies with PC. RESULTS: CF of PHS46+African was strongly associated with the first and twentieth PCs. Predicted CF ranged from 0.41 to 2.94, suggesting that PHS46+African may be up to 7 times more beneficial to some African men than others. The explained relative risk for PHS46+African varied from 3.6% to 9.9% for individuals with low and high CF values, respectively. By cross-referencing our data set with 1000 Genomes, we identified significant associations between continental and calibration groupings. CONCLUSION: We identified PCs within 8q24 that were strongly associated with the performance of PHS46+African. Further research to improve the clinical utility of polygenic risk scores (or models) is needed to improve health outcomes for men of African ancestry.

Vertex-wise multivariate genome-wide association study identifies 780 unique genetic loci associated with cortical morphology.

Brain morphology has been shown to be highly heritable, yet only a small portion of the heritability is explained by the genetic variants discovered so far. Here we extended the Multivariate Omnibus Statistical Test (MOSTest) and applied it to genome-wide association studies (GWAS) of vertex-wise structural magnetic resonance imaging (MRI) cortical measures from N=35,657 participants in the UK Biobank. We identified 695 loci for cortical surface area and 539 for cortical thickness, in total 780 unique genetic loci associated with cortical morphology robustly replicated in 8,060 children of mixed ethnicity from the Adolescent Brain Cognitive Development (ABCD) Study®. This reflects more than 8-fold increase in genetic discovery at no cost to generalizability compared to the commonly used univariate GWAS methods applied to region of interest (ROI) data. Functional follow up including gene-based analyses implicated 10% of all protein-coding genes and pointed towards pathways involved in neurogenesis and cell differentiation. Power analysis indicated that applying the MOSTest to vertex-wise structural MRI data triples the effective sample size compared to conventional univariate GWAS approaches. The large boost in power obtained with the vertex-wise MOSTest together with pronounced replication rates and highlighted biologically meaningful pathways underscores the advantage of multivariate approaches in the context of highly distributed polygenic architecture of the human brain.

Characterising the shared genetic determinants of bipolar disorder, schizophrenia and risk-taking.

Increased risk-taking is a central component of bipolar disorder (BIP) and is implicated in schizophrenia (SCZ). Risky behaviours, including smoking and alcohol use, are overrepresented in both disorders and associated with poor health outcomes. Positive genetic correlations are reported but an improved understanding of the shared genetic architecture between risk phenotypes and psychiatric disorders may provide insights into underlying neurobiological mechanisms. We aimed to characterise the genetic overlap between risk phenotypes and SCZ, and BIP by estimating the total number of shared variants using the bivariate causal mixture model and identifying shared genomic loci using the conjunctional false discovery rate method. Summary statistics from genome wide association studies of SCZ, BIP, risk-taking and risky behaviours were acquired (n = 82,315-466,751). Genomic loci were functionally annotated using FUMA. Of 8.6-8.7 K variants predicted to influence BIP, 6.6 K and 7.4 K were predicted to influence risk-taking and risky behaviours, respectively. Similarly, of 10.2-10.3 K variants influencing SCZ, 9.6 and 8.8 K were predicted to influence risk-taking and risky behaviours, respectively. We identified 192 loci jointly associated with SCZ and risk phenotypes and 206 associated with BIP and risk phenotypes, of which 68 were common to both risk-taking and risky behaviours and 124 were novel to SCZ or BIP. Functional annotation implicated differential expression in multiple cortical and sub-cortical regions. In conclusion, we report extensive polygenic overlap between risk phenotypes and BIP and SCZ, identify specific loci contributing to this shared risk and highlight biologically plausible mechanisms that may underlie risk-taking in severe psychiatric disorders.

Material recovery from electronic waste using pyrolysis: Emissions measurements and risk assessment.

Electronic waste (e-waste) generation has been growing in volume worldwide, and the diversity of its material composition is increasing. Sustainable management of this material is critical to achieving a circular-economy and minimizing environmental and public health risks. This study's objective was to investigate the use of pyrolysis as a possible technique to recover valuable materials and energy from different components of e-waste as an alternative approach for limiting their disposal to landfills. The study includes investigating the potential environmental impact of thermal processing of e-waste. The mass loss and change in e-waste chemicals during pyrolysis were also considered. The energy recovery from pyrolysis was made in a horizontal tube furnace under anoxic and isothermal conditions of selected temperatures of 300 °C, 400 °C, and 500 °C. Critical metals that include the rare earth elements and other metals (such as In, Co, Li) and valuable metals (Au, Ag, Pt group) were recovered from electronic components. Pyrolysis produced liquid and gas mixtures of organic compounds that can be used as fuels. Still, the process also emitted particulate matter and semi-volatile organic products, and the remaining ash contained leachable pollutants. Furthermore, toxicity characteristics leaching procedure (TCLP) of e-waste and partly oxidized products were conducted to measure the levels of pollutants leached before and after pyrolysis at selected temperatures. TCLP result revealed the presence of heavy metals like As, Cr, Cd, and Pd. Lead was found at 160 mg/L in PCBs leachate, which exceeded the toxicity characteristics (TC) limit of 5 mg/L. Liquid sample analysis from TCLP also showed the presence of C10-C19 components, including benzene. This study's results contribute to the development of practical recycling alternative approaches that could help reduce health risks and environmental problems and recover materials from e-waste. These results will also help assess the hazard risks that workers are exposed to semi-formal recycling centers.