Exome sequencing and characterization of 49,960 individuals in the UK Biobank.

The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world1. Here we describe the release of exome-sequence data for the first 49,960 study participants, revealing approximately 4 million coding variants (of which around 98.6% have a frequency of less than 1%). The data include 198,269 autosomal predicted loss-of-function (LOF) variants, a more than 14-fold increase compared to the imputed sequence. Nearly all genes (more than 97%) had at least one carrier with a LOF variant, and most genes (more than 69%) had at least ten carriers with a LOF variant. We illustrate the power of characterizing LOF variants in this population through association analyses across 1,730 phenotypes. In addition to replicating established associations, we found novel LOF variants with large effects on disease traits, including PIEZO1 on varicose veins, COL6A1 on corneal resistance, MEPE on bone density, and IQGAP2 and GMPR on blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical importance, and show that 2% of this population has a medically actionable variant. Furthermore, we characterize the penetrance of cancer in carriers of pathogenic BRCA1 and BRCA2 variants. Exome sequences from the first 49,960 participants highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community.

Rare GPR37L1 Variants Reveal Potential Association between GPR37L1 and Disorders of Anxiety and Migraine.

GPR37L1 is an orphan receptor that couples through heterotrimeric G-proteins to regulate physiological functions. Since its role in humans is not fully defined, we used an unbiased computational approach to assess the clinical significance of rare G-protein-coupled receptor 37-like 1 (GPR37L1) genetic variants found among 51,289 whole-exome sequences from the DiscovEHR cohort. Rare GPR37L1 coding variants were binned according to predicted pathogenicity and analyzed by sequence kernel association testing to reveal significant associations with disease diagnostic codes for epilepsy and migraine, among others. Since associations do not prove causality, rare GPR37L1 variants were functionally analyzed in SK-N-MC cells to evaluate potential signaling differences and pathogenicity. Notably, receptor variants exhibited varying abilities to reduce cAMP levels, activate mitogen-activated protein kinase (MAPK) signaling, and/or upregulate receptor expression in response to the agonist prosaptide (TX14(A)), as compared with the wild-type receptor. In addition to signaling changes, knock-out (KO) of GPR37L1 or expression of certain rare variants altered cellular cholesterol levels, which were also acutely regulated by administration of the agonist TX14(A) via activation of the MAPK pathway. Finally, to simulate the impact of rare nonsense variants found in the large patient cohort, a KO mouse line lacking Gpr37l1 was generated. Although KO animals did not recapitulate an acute migraine phenotype, the loss of this receptor produced sex-specific changes in anxiety-related disorders often seen in chronic migraineurs. Collectively, these observations define the existence of rare GPR37L1 variants associated with neuropsychiatric conditions in the human population and identify the signaling changes contributing to pathological processes.

Reduced penetrance of MODY-associated HNF1A/HNF4A variants but not GCK variants in clinically unselected cohorts.

The true prevalence and penetrance of monogenic disease variants are often not known because of clinical-referral ascertainment bias. We comprehensively assess the penetrance and prevalence of pathogenic variants in HNF1A, HNF4A, and GCK that account for >80% of monogenic diabetes. We analyzed clinical and genetic data from 1,742 clinically referred probands, 2,194 family members, clinically unselected individuals from a US health system-based cohort (n = 132,194), and a UK population-based cohort (n = 198,748). We show that one in 1,500 individuals harbor a pathogenic variant in one of these genes. The penetrance of diabetes for HNF1A and HNF4A pathogenic variants was substantially lower in the clinically unselected individuals compared to clinically referred probands and was dependent on the setting (32% in the population, 49% in the health system cohort, 86% in a family member, and 98% in probands for HNF1A). The relative risk of diabetes was similar across the clinically unselected cohorts highlighting the role of environment/other genetic factors. Surprisingly, the penetrance of pathogenic GCK variants was similar across all cohorts (89%-97%). We highlight that pathogenic variants in HNF1A, HNF4A, and GCK are not ultra-rare in the population. For HNF1A and HNF4A, we need to tailor genetic interpretation and counseling based on the setting in which a pathogenic monogenic variant was identified. GCK is an exception with near-complete penetrance in all settings. This along with the clinical implication of diagnosis makes it an excellent candidate for the American College of Medical Genetics secondary gene list.

Germline Mutations in CIDEB and Protection against Liver Disease.

BACKGROUND: Exome sequencing in hundreds of thousands of persons may enable the identification of rare protein-coding genetic variants associated with protection from human diseases like liver cirrhosis, providing a strategy for the discovery of new therapeutic targets. METHODS: We performed a multistage exome sequencing and genetic association analysis to identify genes in which rare protein-coding variants were associated with liver phenotypes. We conducted in vitro experiments to further characterize associations. RESULTS: The multistage analysis involved 542,904 persons with available data on liver aminotransferase levels, 24,944 patients with various types of liver disease, and 490,636 controls without liver disease. We found that rare coding variants in APOB, ABCB4, SLC30A10, and TM6SF2 were associated with increased aminotransferase levels and an increased risk of liver disease. We also found that variants in CIDEB, which encodes a structural protein found in hepatic lipid droplets, had a protective effect. The burden of rare predicted loss-of-function variants plus missense variants in CIDEB (combined carrier frequency, 0.7%) was associated with decreased alanine aminotransferase levels (beta per allele, -1.24 U per liter; 95% confidence interval [CI], -1.66 to -0.83; P = 4.8×10-9) and with 33% lower odds of liver disease of any cause (odds ratio per allele, 0.67; 95% CI, 0.57 to 0.79; P = 9.9×10-7). Rare coding variants in CIDEB were associated with a decreased risk of liver disease across different underlying causes and different degrees of severity, including cirrhosis of any cause (odds ratio per allele, 0.50; 95% CI, 0.36 to 0.70). Among 3599 patients who had undergone bariatric surgery, rare coding variants in CIDEB were associated with a decreased nonalcoholic fatty liver disease activity score (beta per allele in score units, -0.98; 95% CI, -1.54 to -0.41 [scores range from 0 to 8, with higher scores indicating more severe disease]). In human hepatoma cell lines challenged with oleate, CIDEB small interfering RNA knockdown prevented the buildup of large lipid droplets. CONCLUSIONS: Rare germline mutations in CIDEB conferred substantial protection from liver disease. (Funded by Regeneron Pharmaceuticals.).

Pan-ancestry exome-wide association analyses of COVID-19 outcomes in 586,157 individuals.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), a respiratory illness that can result in hospitalization or death. We used exome sequence data to investigate associations between rare genetic variants and seven COVID-19 outcomes in 586,157 individuals, including 20,952 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome wide or when specifically focusing on (1) 13 interferon pathway genes in which rare deleterious variants have been reported in individuals with severe COVID-19, (2) 281 genes located in susceptibility loci identified by the COVID-19 Host Genetics Initiative, or (3) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, and results are publicly available through the Regeneron Genetics Center COVID-19 Results Browser.

Most Fanconi anemia heterozygotes are not at increased cancer risk: A genome-first DiscovEHR cohort population study.

PURPOSE: Fanconi anemia (FA) is a bone marrow failure and cancer predisposition syndrome caused primarily by biallelic pathogenic variants in 1 of 22 genes involved in DNA interstrand cross-link repair. An enduring question concerns cancer risk of those with a single pathogenic FA gene variant. To investigate all FA genes, this study utilized the DiscovEHR cohort of 170,503 individuals with exome sequencing and electronic health data. METHODS: 5822 subjects with a single pathogenic variant in an FA gene were identified. Two control groups were used in primary analysis deriving cancer risk signals. Secondary exploratory analysis was conducted using the UK Biobank and The Cancer Genome Atlas. RESULTS: Signals for elevated cancer risk were found in all 5 known cancer predisposition genes. Among the remaining 15 genes associated with autosomal recessive inheritance cancer risk signals were found for 4 cancers across 3 genes in the primary cohort but were not validated in secondary cohorts. CONCLUSION: To our knowledge, this is the first and largest FA heterozygote study to use genomic ascertainment and validates well-established cancer predispositions in 5 genes, whereas finding insufficient evidence of predisposition in 15 others. Our findings inform clinical surveillance given how common pathogenic FA variants are in the population.

Development of a Polygenic Risk Score to Predict Diverticulitis.

BACKGROUND: Despite its prevalence and associated morbidity, we remain limited in our ability to predict the course of a patient with diverticular disease. Although several clinical and genetic risk factors have been identified, we do not know how these factors relate to one another. OBJECTIVE: Our aim was to determine whether a polygenic risk score could improve risk prediction for diverticulitis and recurrent diverticulitis compared with a model using only clinical factors. DESIGN: This is an observational study. SETTING: The study examines the predictive ability of a polygenic risk score for diverticulitis developed using prior genome-wide association studies and validated using the MyCode biobank. PATIENTS: This study included patients of European ancestry in the Geisinger Health System who were enrolled in the MyCode Community Health biobanking program. MAIN OUTCOME MEASURES: The ability of a polygenic risk score to predict diverticulosis, diverticulitis, and recurrent diverticulitis was the main outcome measure of this study. RESULTS: A total of 60,861 patients were included, of whom 9912 (16.3%) had diverticulosis or diverticulitis (5015 with diverticulosis and 4897 with diverticulitis). When divided into deciles, our polygenic risk score stratified patients by risk of both diverticulosis and diverticulitis with a 2-fold difference in disease risk between the highest and lowest deciles for diverticulitis and a 4.8-fold difference for recurrent complicated diverticulitis. When compared with clinical factors alone, our polygenic risk score was able to improve risk prediction of recurrent diverticulitis. LIMITATIONS: Our population is largely located in a single geographic region and were classified by disease status, using international classification of diseases codes. CONCLUSIONS: This predictive model stratifies patients based on genetic risk for diverticular disease. The increased frequency of recurrent disease in our high-risk patients suggests that a polygenic risk score, in addition to other factors, may help guide the discussion regarding surgical intervention. See Video Abstract . DESARROLLO DE UNA PUNTUACIN DE RIESGO POLIGNICO PARA PREDECIR LA DIVERTICULITIS: ANTECEDENTES:A pesar de su prevalencia y morbilidad asociada, nuestra capacidad para predecir el curso en un paciente con enfermedad diverticular sigue siendo limitada. Si bien se han identificado varios factores de riesgo clínicos y genéticos, no sabemos cómo se relacionan estos factores entre sí.OBJETIVO:Determinar si una puntuación de riesgo poligénico podría mejorar la predicción del riesgo de diverticulitis y diverticulitis recurrente en comparación con un modelo que utiliza solo factores clínicos.DISEÑO:Un estudio observacional que examina la capacidad predictiva de una puntuación de riesgo poligénico para la diverticulitis desarrollada usando estudios previos de asociación amplia del genoma y validada usando el biobanco MyCode.ÁMBITOS Y PACIENTES:Pacientes de ascendencia europea en el Sistema de Salud Geisinger que estaban inscritos en el programa de biobancos MyCode Community Health.PRINCIPALES MEDIDAS DE VALORACIÓN:La capacidad de una puntuación de riesgo poligénico para predecir diverticulosis, diverticulitis y diverticulitis recurrente.RESULTADOS:Se incluyeron un total de 60.861 pacientes, de los cuales 9.912 (16,3%) presentaban diverticulosis o diverticulitis (5.015 con diverticulosis y 4.897 con diverticulitis). Cuando se dividió en deciles, nuestra puntuación de riesgo poligénico estratificó a los pacientes según el riesgo de diverticulosis y diverticulitis con una diferencia de 2 veces en el riesgo de enfermedad entre los deciles más alto y más bajo para diverticulitis y una diferencia de 4,8 veces para diverticulitis complicada recurrente. En comparación con los factores clínicos solos, nuestra puntuación de riesgo poligénico pudo mejorar la predicción del riesgo de diverticulitis recurrente.LIMITACIONES:Nuestra población se encuentra en gran parte en una sola región geográfica y se clasificó por estado de enfermedad utilizando códigos de clasificación internacional de enfermedades.CONCLUSIONES:Este modelo predictivo estratifica a los pacientes en función del riesgo genético de enfermedad diverticular. La mayor frecuencia de enfermedad recurrente en nuestros pacientes de alto riesgo sugiere que un puntaje de riesgo poligénico, además de otros factores, puede ayudar a guiar la discusión sobre la intervención quirúrgica. (Traducción- Dr. Ingrid Melo ).

Effect of Data-Processing Methods on Acceleration Summary Metrics of GNSS Devices in Elite Australian Football.

This study aimed to measure the differences in commonly used summary acceleration metrics during elite Australian football games under three different data processing protocols (raw, custom-processed, manufacturer-processed). Estimates of distance, speed and acceleration were collected with a 10-Hz GNSS tracking technology device from fourteen matches of 38 elite Australian football players from one team. Raw and manufacturer-processed data were exported from respective proprietary software and two common summary acceleration metrics (number of efforts and distance within medium/high-intensity zone) were calculated for the three processing methods. To estimate the effect of the three different data processing methods on the summary metrics, linear mixed models were used. The main findings demonstrated that there were substantial differences between the three processing methods; the manufacturer-processed acceleration data had the lowest reported distance (up to 184 times lower) and efforts (up to 89 times lower), followed by the custom-processed distance (up to 3.3 times lower) and efforts (up to 4.3 times lower), where raw data had the highest reported distance and efforts. The results indicated that different processing methods changed the metric output and in turn alters the quantification of the demands of a sport (volume, intensity and frequency of the metrics). Coaches, practitioners and researchers need to understand that various processing methods alter the summary metrics of acceleration data. By being informed about how these metrics are affected by processing methods, they can better interpret the data available and effectively tailor their training programs to match the demands of competition.

Classification of Force-Time Metrics Into Lower-Body Strength Domains.

ABSTRACT: Geneau, MC, Carey, DL, Gastin, PB, Robertson, S, and James, LP. Classification of force-time metrics into lower-body strength domains. J Strength Cond Res XX(X): 000-000, 2024-The purpose of this study was to classify force-time metrics into distinct lower-body strength domains using a systematic data reduction analysis. A cross-sectional design was used, whereby competitive field sport athletes (F = 39, M = 96) completed a series of drop jumps, squat jumps, countermovement jumps (CMJs), loaded CMJs, and 2 isometric tasks on portable force platforms, resulting in a total of 285 force-time performance metrics. The metrics were split into 4 test "families" and each was entered into a sparse principal component analysis (sPCA) model. A single metric from each component of each family-specific sPCA were selected based on the loading, reliability, and simplicity of the metric and entered into a second sPCA that included metrics across all tests. The final sPCA revealed 7 principal components each containing 2 metrics and explained a total of 53% variance of the dataset. The final principal components were interpreted as 7 lower-body strength domains: (a) dynamic force, (b) dynamic timing, (c) early isometric, (d) maximal isometric, (e) countermovement velocity, (f) reactive output, and (g) reactive timing. The findings demonstrate that a total of 7 metrics from a drop jump, CMJ, and isometric test can be used to represent ∼50% of variance in lower-body strength performance of field sport athletes. These results can help guide and simplify the lower-body strength diagnosis process in field sport athletes.

Familial Hypocalciuric Hypercalcemia Type 1 and Autosomal-Dominant Hypocalcemia Type 1: Prevalence in a Large Healthcare Population.

The calcium-sensing receptor (CaSR) regulates serum calcium concentrations. CASR loss- or gain-of-function mutations cause familial hypocalciuric hypercalcemia type 1 (FHH1) or autosomal-dominant hypocalcemia type 1 (ADH1), respectively, but the population prevalence of FHH1 or ADH1 is unknown. Rare CASR variants were identified in whole-exome sequences from 51,289 de-identified individuals in the DiscovEHR cohort derived from a single US healthcare system. We integrated bioinformatics pathogenicity triage, mean serum Ca concentrations, and mode of inheritance to identify potential FHH1 or ADH1 variants, and we used a Sequence Kernel Association Test (SKAT) to identify rare variant-associated diseases. We identified predicted heterozygous loss-of-function CASR variants (6 different nonsense/frameshift variants and 12 different missense variants) in 38 unrelated individuals, 21 of whom were hypercalcemic. Missense CASR variants were identified in two unrelated hypocalcemic individuals. Functional studies showed that all hypercalcemia-associated missense variants impaired heterologous expression, plasma membrane targeting, and/or signaling, whereas hypocalcemia-associated missense variants increased expression, plasma membrane targeting, and/or signaling. Thus, 38 individuals with a genetic diagnosis of FHH1 and two individuals with a genetic diagnosis of ADH1 were identified in the 51,289 cohort, giving a prevalence in this population of 74.1 per 100,000 for FHH1 and 3.9 per 100,000 for ADH1. SKAT combining all nonsense, frameshift, and missense loss-of-function variants revealed associations with cardiovascular, neurological, and other diseases. In conclusion, FHH1 is a common cause of hypercalcemia, with prevalence similar to that of primary hyperparathyroidism, and is associated with altered disease risks, whereas ADH1 is a major cause of non-surgical hypoparathyroidism.

Laterality indices consensus initiative (LICI): A Delphi expert survey report on recommendations to record, assess, and report asymmetry in human behavioural and brain research.

Laterality indices (LIs) quantify the left-right asymmetry of brain and behavioural variables and provide a measure that is statistically convenient and seemingly easy to interpret. Substantial variability in how structural and functional asymmetries are recorded, calculated, and reported, however, suggest little agreement on the conditions required for its valid assessment. The present study aimed for consensus on general aspects in this context of laterality research, and more specifically within a particular method or technique (i.e., dichotic listening, visual half-field technique, performance asymmetries, preference bias reports, electrophysiological recording, functional MRI, structural MRI, and functional transcranial Doppler sonography). Experts in laterality research were invited to participate in an online Delphi survey to evaluate consensus and stimulate discussion. In Round 0, 106 experts generated 453 statements on what they considered good practice in their field of expertise. Statements were organised into a 295-statement survey that the experts then were asked, in Round 1, to independently assess for importance and support, which further reduced the survey to 241 statements that were presented again to the experts in Round 2. Based on the Round 2 input, we present a set of critically reviewed key recommendations to record, assess, and report laterality research for various methods.

Discovery and Characterisation of Forward Line Formations at Centre Bounces in the Australian Football League.

The extent of player formation usage and the characteristics of player arrangements are not well understood in Australian football, unlike other team-based invasion sports. Using player location data from all centre bounces in the 2021 Australian Football League season; this study described the spatial characteristics and roles of players in the forward line. Summary metrics indicated that teams differed in how spread out their forward players were (deviation away from the goal-to-goal axis and convex hull area) but were similar with regard to the centroid of player locations. Cluster analysis, along with visual inspection of player densities, clearly showed the presence of different repeated structures or formations used by teams. Teams also differed in their choice of player role combinations in forward lines at centre bounces. New terminology was proposed to describe the characteristics of forward line formations used in professional Australian Football.

Estimated Prevalence and Clinical Manifestations of UBA1 Variants Associated With VEXAS Syndrome in a Clinical Population.

Importance: VEXAS (vacuoles, E1-ubiquitin-activating enzyme, X-linked, autoinflammatory, somatic) syndrome is a disease with rheumatologic and hematologic features caused by somatic variants in UBA1. Pathogenic variants are associated with a broad spectrum of clinical manifestations. Knowledge of prevalence, penetrance, and clinical characteristics of this disease have been limited by ascertainment biases based on known phenotypes. Objective: To determine the prevalence of pathogenic variants in UBA1 and associated clinical manifestations in an unselected population using a genomic ascertainment approach. Design, Setting, and Participants: This retrospective observational study evaluated UBA1 variants in exome data from 163 096 participants within the Geisinger MyCode Community Health Initiative. Clinical phenotypes were determined from Geisinger electronic health record data from January 1, 1996, to January 1, 2022. Exposures: Exome sequencing was performed. Main Outcomes and Measures: Outcome measures included prevalence of somatic UBA1 variation; presence of rheumatologic, hematologic, pulmonary, dermatologic, and other findings in individuals with somatic UBA1 variation on review of the electronic health record; review of laboratory data; bone marrow biopsy pathology analysis; and in vitro enzymatic assays. Results: In 163 096 participants (mean age, 52.8 years; 94% White; 61% women), 11 individuals harbored likely somatic variants at known pathogenic UBA1 positions, with 11 of 11 (100%) having clinical manifestations consistent with VEXAS syndrome (9 male, 2 female). A total of 5 of 11 individuals (45%) did not meet criteria for rheumatologic and/or hematologic diagnoses previously associated with VEXAS syndrome; however, all individuals had anemia (hemoglobin: mean, 7.8 g/dL; median, 7.5 g/dL), which was mostly macrocytic (10/11 [91%]) with concomitant thrombocytopenia (10/11 [91%]). Among the 11 patients identified, there was a pathogenic variant in 1 male participant prior to onset of VEXAS-related signs or symptoms and 2 female participants had disease with heterozygous variants. A previously unreported UBA1 variant (c.1861A>T; p.Ser621Cys) was found in a symptomatic patient, with in vitro data supporting a catalytic defect and pathogenicity. Together, disease-causing UBA1 variants were found in 1 in 13 591 unrelated individuals (95% CI, 1:7775-1:23 758), 1 in 4269 men older than 50 years (95% CI, 1:2319-1:7859), and 1 in 26 238 women older than 50 years (95% CI, 1:7196-1:147 669). Conclusions and Relevance: This study provides an estimate of the prevalence and a description of the clinical manifestations of UBA1 variants associated with VEXAS syndrome within a single regional health system in the US. Additional studies are needed in unselected and genetically diverse populations to better define general population prevalence and phenotypic spectrum.

Association Between Position-Specific Impact and Movement Characteristics of Professional Rugby Union Players During Game Play.

ABSTRACT: Peek, RJ, Carey, DL, Middleton, KJ, Gastin, PB, and Clarke, AC. Association between position-specific impact and movement characteristics of professional rugby union players during game play. J Strength Cond Res 37(1): 161-166, 2023-The aim of this study was to understand the association between impact and movement characteristics during whole game and peak 1- to 10-minute rolling windows in professional rugby union. Maximal impact (impacts·min-1) and corresponding running (m·min-1) characteristics as well as maximal running (m·min-1) and corresponding impact (impacts·min-1) characteristics were obtained for 160 athletes from 4 teams across the 2018 and 2019 Super Rugby seasons. A linear mixed-effects model reported a positive association between whole-game running and impacts, where greater impact characteristics corresponded with greater running characteristics. The average 1-minute peak running characteristics (150-160 m·min-1) typically occurred when no impacts occurred. The average 1-minute peak impact characteristics (4-6 impacts·min-1) corresponded with an average relative distance of 90-100 m·min-1. Worst case scenario observed impact characteristics as large as 15 impacts·min-1 with a corresponding relative distance of 140 m·min-1. When training for peak period characteristics, running may be completed in isolation; however, peak impacts often occur in conjunction with moderate to high running movements. Given running and impact characteristics can appear concurrently within game play, this highlights the need to train them accordingly. As such, when prescribing training drills to replicate the peak characteristics in rugby union, consideration should be taken for both running and impact characteristics.

Human-Disease Phenotype Map Derived from PheWAS across 38,682 Individuals.

Phenome-wide association studies (PheWASs) have been a useful tool for testing associations between genetic variations and multiple complex traits or diagnoses. Linking PheWAS-based associations between phenotypes and a variant or a genomic region into a network provides a new way to investigate cross-phenotype associations, and it might broaden the understanding of genetic architecture that exists between diagnoses, genes, and pleiotropy. We created a network of associations from one of the largest PheWASs on electronic health record (EHR)-derived phenotypes across 38,682 unrelated samples from the Geisinger's biobank; the samples were genotyped through the DiscovEHR project. We computed associations between 632,574 common variants and 541 diagnosis codes. Using these associations, we constructed a "disease-disease" network (DDN) wherein pairs of diseases were connected on the basis of shared associations with a given genetic variant. The DDN provides a landscape of intra-connections within the same disease classes, as well as inter-connections across disease classes. We identified clusters of diseases with known biological connections, such as autoimmune disorders (type 1 diabetes, rheumatoid arthritis, and multiple sclerosis) and cardiovascular disorders. Previously unreported relationships between multiple diseases were identified on the basis of genetic associations as well. The network approach applied in this study can be used to uncover interactions between diseases as a result of their shared, potentially pleiotropic SNPs. Additionally, this approach might advance clinical research and even clinical practice by accelerating our understanding of disease mechanisms on the basis of similar underlying genetic associations.

Left-Handers Are Less Lateralized Than Right-Handers for Both Left and Right Hemispheric Functions.

Many neuroscientific techniques have revealed that more left- than right-handers will have unusual cerebral asymmetries for language. After the original emphasis on frequency in the aphasia and epilepsy literatures, most neuropsychology, and neuroimaging efforts rely on estimates of central tendency to compare these two handedness groups on any given measure of asymmetry. The inevitable reduction in mean lateralization in the left-handed group is often postulated as being due to reversed asymmetry in a small subset of them, but it could also be due to a reduced asymmetry in many of the left-handers. These two possibilities have hugely different theoretical interpretations. Using functional magnetic resonance imaging localizer paradigms, we matched left- and right-handers for hemispheric dominance across four functions (verbal fluency, face perception, body perception, and scene perception). We then compared the degree of dominance between the two handedness groups for each of these four measures, conducting t-tests on the mean laterality indices. The results demonstrate that left-handers with typical cerebral asymmetries are less lateralized for language, faces, and bodies than their right-handed counterparts. These results are difficult to reconcile with current theories of language asymmetry or of handedness.

Peak movement and impact characteristics of different training methods in professional rugby union.

The purpose of this study was to compare the peak periods (1- to 6-minute epochs) for three different training methods (game-based training - GBT; small-sided games - SSG; and conditioning training - CT) in elite male rugby union (RU) players. The peak movement (m·min-1) and impact (impact·min-1) characteristics of 42 players during in-season training were assessed. When comparing between training methods, SSG drills produced the greatest peak movement characteristics for all time epochs (1-minute average peak periods - SSG 195 m·min-1, GBT 160 m·min-1, and CT 144 m·min-1). The peak impact characteristics performed during training were 1-2 impact·min-1 for a 1-minute period and then decreased as the time period increased for all training methods. The greatest distribution of training time occurred at 30-39% (SSG and CT) and 40-49% (GBT) of peak movement intensity, with less than 5% of training performed at or above 80% peak intensity across all drill types. Findings from the current study show that the peak movement periods (m·min-1) in RU training from all three training methods match or exceed those which are previously reported in peak gameplay, yet their ability to replicate peak impact characteristics is questionable.

Comparison of player-dependent and independent high-speed running thresholds to model injury risk in football.

High-speed running (HSR) loads have been linked with non-contact injury risks in team-sports. This study investigated whether player-specific speed zones, reflecting individual fitness characteristics, impact the associations between non-contact injury and acute and chronic HSR loads. Semi-professional soccer players from two clubs (n = 47) were tracked over two seasons using 10 Hz GPS (5552 observations). HSR distances were calculated arbitrarily (≥5.5 m·s-1), and in an individualised fashion based on the final speed of the 30-15 intermittent fitness test. Cumulative running loads were represented by exponentially weighted moving averages with 7-(acute) and 28-day (chronic) decay parameters. Physiotherapists collected non-contact, lower-limb, time-loss injury data (n = 101). Injury models using session type (training vs matches), coach, as well as arbitrary or individualised running loads were constructed via mixed-effect logistic regression. Session type had the largest effect on injury (training vs match OR = 0.28; 95%CI:0.17-0.44). Variations in individualised or arbitrary acute and chronic HSR loads within the mid-range of the observed data had negligible effects on predicted injury risk. However, the uncertainty of estimated effects at extreme values of acute and chronic HSR loads prevented any conclusive findings. Therefore, the efficacy of using customised speed thresholds in quantifying load for injury risk mitigation purposes remains unclear.

Placental DNA methylation profiles in opioid-exposed pregnancies and associations with the neonatal opioid withdrawal syndrome.

Opioid abuse during pregnancy can result in Neonatal Opioid Withdrawal Syndrome (NOWS). We investigated genome-wide methylation analyses of 96 placental tissue samples, including 32 prenatally opioid-exposed infants with NOWS who needed therapy (+Opioids/+NOWS), 32 prenatally opioid-exposed infants with NOWS who did not require treatment (+Opioids/-NOWS), and 32 prenatally unexposed controls (-Opioids/-NOWS, control). Statistics, bioinformatics, Artificial Intelligence (AI), including Deep Learning (DL), and Ingenuity Pathway Analyses (IPA) were performed. We identified 17 dysregulated pathways thought to be important in the pathophysiology of NOWS and reported accurate AI prediction of NOWS diagnoses. The DL had an AUC (95% CI) =0.98 (0.95-1.0) with a sensitivity and specificity of 100% for distinguishing NOWS from the +Opioids/-NOWS group and AUCs (95% CI) =1.00 (1.0-1.0) with a sensitivity and specificity of 100% for distinguishing NOWS versus control and + Opioids/-NOWS group versus controls. This study provides strong evidence of methylation dysregulation of placental tissue in NOWS development.

Exome Sequencing of a Clinical Population for Autosomal Dominant Polycystic Kidney Disease.

Importance: Most studies of autosomal dominant polycystic kidney disease (ADPKD) genetics have used kidney specialty cohorts, focusing on PKD1 and PKD2. These can lead to biased estimates of population prevalence of ADPKD-associated gene variants and their phenotypic expression. Objective: To determine the prevalence of ADPKD and contributions of PKD1, PKD2, and other genes related to cystic kidney disease in a large, unselected cohort. Design, Setting, and Participants: This retrospective observational study used an unselected health system-based cohort in central and northeast Pennsylvania with exome sequencing (enrolled from 2004 to 2020) and electronic health record data (up to October 2021). The genotype-first approach included the entire cohort and the phenotype-first approach focused on patients with ADPKD diagnosis codes, confirmed by chart and imaging review. Exposures: Loss-of-function (LOF) variants in PKD1, PKD2, and other genes associated with cystic kidney disease (ie, ALG8, ALG9, DNAJB11, GANAB, HNF1B, IFT140, SEC61B, PKHD1, PRKCSH, SEC63); likely pathogenic missense variants in PKD1 and PKD2. Main Outcomes and Measures: Genotype-first analysis: ADPKD diagnosis code (Q61.2, Q61.3, 753.13, 753.12); phenotype-first analysis: presence of a rare variant in PKD1, PKD2, or other genes associated with cystic kidney disease. Results: Of 174 172 patients (median age, 60 years; 60.6% female; 93% of European ancestry), 303 patients had ADPKD diagnosis codes, including 235 with sufficient chart review data for confirmation. In addition to PKD1 and PKD2, LOF variants in IFT140, GANAB, and HNF1B were associated with ADPKD diagnosis after correction for multiple comparisons. Among patients with LOF variants in PKD1, 66 of 68 (97%) had ADPKD; 43 of 43 patients (100%) with LOF variants in PKD2 had ADPKD. In contrast, only 24 of 77 patients (31.2%) with a PKD1 missense variant previously classified as "likely pathogenic" had ADPKD, suggesting misclassification or variable penetrance. Among patients with ADPKD diagnosis confirmed by chart review, 180 of 235 (76.6%) had a potential genetic cause, with the majority being rare variants in PKD1 (127 patients) or PKD2 (34 patients); 19 of 235 (8.1%) had variants in other genes associated with cystic kidney disease. Of these 235 patients with confirmed ADPKD, 150 (63.8%) had a family history of ADPKD. The yield for a genetic determinant of ADPKD was higher for those with a family history of ADPKD compared with those without family history (91.3% [137/150] vs 50.6% [43/85]; difference, 40.7% [95% CI, 29.2%-52.3%]; P < .001). Previously unreported PKD1, PKD2, and GANAB variants were identified with pedigree data suggesting pathogenicity, and several PKD1 missense variants previously reported as likely pathogenic appeared to be benign. Conclusions and Relevance: This study demonstrates substantial genetic and phenotypic variability in ADPKD among patients within a regional health system in the US.