A selective CutMix approach improves generalizability of deep learning-based grading and risk assessment of prostate cancer.

The Gleason score is an important predictor of prognosis in prostate cancer. However, its subjective nature can result in over- or under-grading. Our objective was to train an artificial intelligence (AI)-based algorithm to grade prostate cancer in specimens from patients who underwent radical prostatectomy (RP) and to assess the correlation of AI-estimated proportions of different Gleason patterns with biochemical recurrence-free survival (RFS), metastasis-free survival (MFS), and overall survival (OS). Training and validation of algorithms for cancer detection and grading were completed with three large datasets containing a total of 580 whole-mount prostate slides from 191 RP patients at two centers and 6218 annotated needle biopsy slides from the publicly available Prostate Cancer Grading Assessment dataset. A cancer detection model was trained using MobileNetV3 on 0.5 mm × 0.5 mm cancer areas (tiles) captured at 10× magnification. For cancer grading, a Gleason pattern detector was trained on tiles using a ResNet50 convolutional neural network and a selective CutMix training strategy involving a mixture of real and artificial examples. This strategy resulted in improved model generalizability in the test set compared with three different control experiments when evaluated on both needle biopsy slides and whole-mount prostate slides from different centers. In an additional test cohort of RP patients who were clinically followed over 30 years, quantitative Gleason pattern AI estimates achieved concordance indexes of 0.69, 0.72, and 0.64 for predicting RFS, MFS, and OS times, outperforming the control experiments and International Society of Urological Pathology system (ISUP) grading by pathologists. Finally, unsupervised clustering of test RP patient specimens into low-, medium-, and high-risk groups based on AI-estimated proportions of each Gleason pattern resulted in significantly improved RFS and MFS stratification compared with ISUP grading. In summary, deep learning-based quantitative Gleason scoring using a selective CutMix training strategy may improve prognostication after prostate cancer surgery.

Results From the Big Ten COVID-19 Cardiac Registry: Impact of SARS-COV-2 on Myocardial Involvement.

OBJECTIVE: COVID-19 has been associated with myocardial involvement in collegiate athletes. The first report from the Big Ten COVID-19 Cardiac Registry (Registry) was an ecological study that reported myocarditis in 37 of 1597 athletes (2.3%) based on local clinical diagnosis. Our objective was to assess the relationship between athlete and clinical characteristics and myocardial involvement. DESIGN: Cross-sectional study. SETTING: We analyzed data from 1218 COVID-19 positive Big Ten collegiate athletes who provided informed consent to participate in the Registry. PARTICIPANTS: 1218 athletes with a COVID-19-positive PCR test before June 1, 2021. ASSESSMENT OF INDEPENDENT VARIABLES: Demographic and clinical characteristics of athletes were obtained from the medical record. MAIN OUTCOME MEASURES: Myocardial involvement was diagnosed based on local clinical, cardiac magnetic resonance (CMR), electrocardiography, troponin assay, and echocardiography. We assessed the association of clinical factors with myocardial involvement using logistic regression and estimated the area under the receiver operating characteristic (ROC) curve. RESULTS: 25 of 1218 (2.0%) athletes met criteria for myocardial involvement. The logistic regression model used to predict myocardial involvement contained indicator variables for chest pain, new exercise intolerance, abnormal echocardiogram (echo), and abnormal troponin. The area under the ROC curve for these indicators was 0.714. The presence of any of these 4 factors in a collegiate athlete who tested positive for COVID-19 would capture 55.6% of cases. Among noncases without missing data, 86.9% would not be flagged for possible myocardial involvement. CONCLUSION: Myocardial involvement was infrequent. We predicted case status with good specificity but deficient sensitivity. A diagnostic approach for myocardial involvement based exclusively on symptoms would be less sensitive than one based on symptoms, echo, and troponin level evaluations. Abnormality of any of these evaluations would be an indication for CMR.

Genetic testing in early-onset atrial fibrillation.

Atrial fibrillation (AF) is a globally prevalent cardiac arrhythmia with significant genetic underpinnings, as highlighted by recent large-scale genetic studies. A prominent clinical and genetic overlap exists between AF, heritable ventricular cardiomyopathies, and arrhythmia syndromes, underlining the potential of AF as an early indicator of severe ventricular disease in younger individuals. Indeed, several recent studies have demonstrated meaningful yields of rare pathogenic variants among early-onset AF patients (∼4%-11%), most notably for cardiomyopathy genes in which rare variants are considered clinically actionable. Genetic testing thus presents a promising opportunity to identify monogenetic defects linked to AF and inherited cardiac conditions, such as cardiomyopathy, and may contribute to prognosis and management in early-onset AF patients. A first step towards recognizing this monogenic contribution was taken with the Class IIb recommendation for genetic testing in AF patients aged 45 years or younger by the 2023 American College of Cardiology/American Heart Association guidelines for AF. By identifying pathogenic genetic variants known to underlie inherited cardiomyopathies and arrhythmia syndromes, a personalized care pathway can be developed, encompassing more tailored screening, cascade testing, and potentially genotype-informed prognosis and preventive measures. However, this can only be ensured by frameworks that are developed and supported by all stakeholders. Ambiguity in test results such as variants of uncertain significance remain a major challenge and as many as ∼60% of people with early-onset AF might carry such variants. Patient education (including pretest counselling), training of genetic teams, selection of high-confidence genes, and careful reporting are strategies to mitigate this. Further challenges to implementation include financial barriers, insurability issues, workforce limitations, and the need for standardized definitions in a fast-moving field. Moreover, the prevailing genetic evidence largely rests on European descent populations, underscoring the need for diverse research cohorts and international collaboration. Embracing these challenges and the potential of genetic testing may improve AF care. However, further research-mechanistic, translational, and clinical-is urgently needed.

Single cell transcriptomes and multiscale networks from persons with and without Alzheimer's disease.

The emergence of single nucleus RNA sequencing (snRNA-seq) offers to revolutionize the study of Alzheimer's disease (AD). Integration with complementary multiomics data such as genetics, proteomics and clinical data provides powerful opportunities to link cell subpopulations and molecular networks with a broader disease-relevant context. We report snRNA-seq profiles from superior frontal gyrus samples from 101 well characterized subjects from the Banner Brain and Body Donation Program in combination with whole genome sequences. We report findings that link common AD risk variants with CR1 expression in oligodendrocytes as well as alterations in hematological parameters. We observed an AD-associated CD83(+) microglial subtype with unique molecular networks and which is associated with immunoglobulin IgG4 production in the transverse colon. Our major observations were replicated in two additional, independent snRNA-seq data sets. These findings illustrate the power of multi-tissue molecular profiling to contextualize snRNA-seq brain transcriptomics and reveal disease biology.

Consortium Profile: The Methylation, Imaging and NeuroDevelopment (MIND) Consortium.

Epigenetic processes, such as DNA methylation, show potential as biological markers and mechanisms underlying gene-environment interplay in the prediction of mental health and other brain-based phenotypes. However, little is known about how peripheral epigenetic patterns relate to individual differences in the brain itself. An increasingly popular approach to address this is by combining epigenetic and neuroimaging data; yet, research in this area is almost entirely comprised of cross-sectional studies in adults. To bridge this gap, we established the Methylation, Imaging and NeuroDevelopment (MIND) Consortium, which aims to bring a developmental focus to the emerging field of Neuroimaging Epigenetics by (i) promoting collaborative, adequately powered developmental research via multi-cohort analyses; (ii) increasing scientific rigor through the establishment of shared pipelines and open science practices; and (iii) advancing our understanding of DNA methylation-brain dynamics at different developmental periods (from birth to emerging adulthood), by leveraging data from prospective, longitudinal pediatric studies. MIND currently integrates 15 cohorts worldwide, comprising (repeated) measures of DNA methylation in peripheral tissues (blood, buccal cells, and saliva) and neuroimaging by magnetic resonance imaging across up to five time points over a period of up to 21 years (Npooled DNAm = 11,299; Npooled neuroimaging = 10,133; Npooled combined = 4,914). By triangulating associations across multiple developmental time points and study types, we hope to generate new insights into the dynamic relationships between peripheral DNA methylation and the brain, and how these ultimately relate to neurodevelopmental and psychiatric phenotypes.

Crystal structure determination and analyses of Hirshfeld surface, crystal voids, inter-molecular inter-action energies and energy frameworks of 1-benzyl-4-(methyl-sulfan-yl)-3a,7a-di-hydro-1H-pyrazolo-[3,4-d]pyrimidine.

The pyrazolo-pyrimidine moiety in the title mol-ecule, C13H12N4S, is planar with the methyl-sulfanyl substituent lying essentially in the same plane. The benzyl group is rotated well out of this plane by 73.64 (6)°, giving the mol-ecule an approximate L shape. In the crystal, C-H⋯π(ring) inter-actions and C-H⋯S hydrogen bonds form tubes extending along the a axis. Furthermore, there are π-π inter-actions between parallel phenyl rings with centroid-to-centroid distances of 3.8418 (12) Å. A Hirshfeld surface analysis of the crystal structure indicates that the most important contributions to the crystal packing are from H⋯H (47.0%), H⋯N/N⋯H (17.6%) and H⋯C/C⋯H (17.0%) inter-actions. The volume of the crystal voids and the percentage of free space were calculated to be 76.45 Å3 and 6.39%, showing that there is no large cavity in the crystal packing. Evaluation of the electrostatic, dispersion and total energy frameworks indicate that the cohesion of the crystal structure is dominated by the dispersion energy contributions.

Quality Assurance Model for Breast Cancer Prognostication Using the Modified Magee Equations.

CONTEXT.­: The Oncotype DX recurrence score (RS) is a widely used test that provides prognostic information on the likelihood of disease recurrence and predictive information on the benefit of chemotherapy in early-stage, hormone receptor-positive breast cancer. Despite its widespread use, quality assurance of the RS does not receive the same level of scrutiny as other tests, such as human epidermal growth factor receptor 2 (HER2) immunohistochemistry. OBJECTIVE.­: To use modified Magee equations to calculate Magee score (MS) as a quality check of RS. DESIGN.­: The MS is an easily accessible prognostic model that uses histopathologic and immunohistochemical criteria. We identified cases where the RS and MS differed by 10 points or more or were in different risk categories. These instances were considered significant discordances. MS was presented along with RS at multidisciplinary tumor boards and all discrepancies were discussed to determine clinical significance and appropriate next steps. RESULTS.­: Twenty-five of 155 cases (16.1%) had discrepancies between RS and MS. Of these 25 cases, 3 (12%) had problems with either the RS or the histopathologic interpretation. Among the cases with concordant RS and MS, no RS or interpretive problems were identified. CONCLUSIONS.­: Use of the MS as a quality control check for the RS can help ensure appropriate treatment decisions in breast cancer patients. Pathologists can play a key role in ensuring the quality of molecular-based prognostic scores by using histopathologic models to ensure accurate risk stratification and improve clinical outcomes.

Synthesis, Crystal Structure, Hirshfeld Surface Analysis, and Computational Approach of a New Pyrazolo[3,4-g]isoquinoline Derivative as Potent against Leucine-Rich Repeat Kinase 2 (LRRK2).

Ethyl-2-((8-cyano-3,5,9a-trimethyl-1-(4-oxo-4,5-dihydrothiazol-2-yl)-4-phenyl-3a,4,9,9a-tetrahydro-1H-pyrazolo[3,4-g]isoquinolin-7-yl)thio)acetate (5) was synthesized, and its structure was characterized by IR, MS, and NMR (1H and 13C) and verified by a single-crystal X-ray structure determination. Compound 5 adopts a "pincer" conformation. In the crystal, the hydrogen bonds of -H···O, C-H···O, and O-H···S form thick layers of molecules that are parallel to (101). The layers are linked by C-H···π(ring) interactions. The Hirshfeld surface analysis shows that intermolecular hydrogen bonding plays a more important role than both intramolecular hydrogen bonding and π···π stacking in the crystal. The intramolecular noncovalent interactions in 5 were studied by QTAIM, NCI, and DFT-NBO calculations. Based on structural activity relationship studies, leucine-rich repeat kinase 2 (LRRK2) was found to bind 5 and was further subjected to molecular docking studies, molecular dynamics, and ADMET analysis to probe potential drug candidacy.

Associations between Computationally Derived Parent Emotional Sentiment Scores and Child ADHD and ODD Over Time.

Family emotional climate is often assessed as expressed emotion (EE) using the five-minute speech sample (FMSS). Parent EE is related to child externalizing behavior, but the relationship with ADHD apart from externalizing is unclear. We report the largest ADHD-non-ADHD study of EE to date, introduce computational scoring of the FMSS to assay parent negative sentiment, and use this to evaluate reciprocal parent-child effects over time in ADHD while considering comorbid ODD. Parents of 810 children (nADHD = 509), aged 7-13 years old, completed the FMSS at three points. The FMSS was expert-coded for EE-Criticism at Time 1 and Time 2, negative sentiment was scored at all three time points. Sentiment and EE-Criticism were moderately correlated (r =.39, p <.001, 95% CI [0.32, 0.46]), and each was similarly correlated with baseline ADHD symptoms (r's range 0.31-0.33, p <.001) and ODD symptoms (r(ODD-EE) = 0.35, p <.001; r(ODD-sentiment = 0.28, p <.001). A longitudinal, cross-lagged panel model revealed that increases over time in parental negative sentiment scores led to increased ODD symptoms. Parent sex (namely fathers, but not mothers) showed an interaction effect of sentiment with ADHD. ADHD and ODD are independently and jointly associated with parental EE-Criticism and negative sentiment assessed by the FMSS cross-sectionally. A recursive effects model is supported for ODD, but for ADHD effects depend on which parent is assessed. For fathers, ADHD was related to negative sentiment in complex manners but for mothers, negative sentiment was related primarily to ODD.

A Retrospective Cohort Analysis of Analgosedation Requirements in COVID-19 Compared to Non-COVID-19 Extracorporeal Membrane Oxygenation Patients.

BACKGROUND: Reports have described increased sedation requirements in patients with acute respiratory distress syndrome (ARDS) while on extracorporeal membrane oxygenation (ECMO) and for intubated COVID-19 patients. Thus, the objective of this study was to assess the analgosedation requirements of COVID-19 patients receiving ECMO compared to non-COVID-19 ECMO patients. METHODS: This retrospective, observational cohort study included adult patients with ARDS requiring venovenous or venopulmonary arterial ECMO admitted to a single intensive care unit from January 2017 to December 2021. Patients were categorized as COVID-19 ECMO or non-COVID-19 ECMO. The primary outcome was median daily dosing of parenteral analgosedative medications. Pertinent secondary outcomes included incidence of extubation or tracheostomy and change in sedation following tracheostomy or addition of oral agents. RESULTS: A total of 109 patients were evaluated; 63 COVID-19 ECMO patients and 46 non-COVID ECMO patients. The primary outcome was statistically higher in the COVID-19 compared to non-COVID-19 patients for propofol (4131.0 mg vs 2704.8 mg, P < .001), dexmedetomidine (1581.4 mcg vs 1081.3 mcg, P = .016), and parenteral morphine equivalents ([PME], 209.3 mg vs 154.1 mg, P = .027), but only propofol remained significant after adjustment for weight (31.1 mcg/kg/day vs 37.7 mcg/kg/day, P = .014). COVID-19 was significantly associated with increased propofol and PME requirements after adjustment for confounders on linear regression analysis. COVID-19 patients had more days with non-zero dose for propofol (8 days vs 7 days), dexmedetomidine (13 days vs 8.5 days), and PME (17 days vs 8.5 days). The only interventions that were associated with reductions in propofol dose were tracheostomy and antipsychotics. CONCLUSIONS: COVID-19 patients on ECMO had significantly longer durations and higher doses of propofol, dexmedetomidine, and parenteral opioids over the first 28 days of cannulation. The only interventions that were associated with statistical reductions in propofol were antipsychotics and tracheostomy.

The Polygenic Score Catalog: new functionality and tools to enable FAIR research.

Polygenic scores (PGS) have transformed human genetic research and have multiple potential clinical applications, including risk stratification for disease prevention and prediction of treatment response. Here, we present a series of recent enhancements to the PGS Catalog (www.PGSCatalog.org), the largest findable, accessible, interoperable, and reusable (FAIR) repository of PGS. These include expansions in data content and ancestral diversity as well as the addition of new features. We further present the PGS Catalog Calculator (pgsc_calc, https://github.com/PGScatalog/pgsc_calc), an open-source, scalable and portable pipeline to reproducibly calculate PGS that securely democratizes equitable PGS applications by implementing genetic ancestry estimation and score normalization using reference data. With the PGS Catalog & calculator users can now quantify an individual's genetic predisposition for hundreds of common diseases and clinically relevant traits. Taken together, these updates and tools facilitate the next generation of PGS, thus lowering barriers to the clinical studies necessary to identify where PGS may be integrated into clinical practice.

National Institute of Mental Health Support for Cognitive Treatment Development in Schizophrenia: A Narrative Review.

For several decades the National Institute of Mental Health (NIMH) has supported basic and translational research into cognitive impairment in schizophrenia. This article describes the Institute's ongoing commitment to cognitive assessment and intervention research, as reflected by three signature initiatives-Measurement and Treatment Research to Improve Cognition in Schizophrenia; Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia; and Research Domain Criteria-and related funding announcements that span basic experimental studies, efficacy and comparative effectiveness trials, and implementation research designed to promote cognitive healthcare in real-world treatment settings. We discuss how trends in science and public health policy since the early 2000s have influenced NIMH treatment development activities, resulting in greater attention to (1) inclusive teams that reflect end-user perspectives on the utility of proposed studies; (2) measurement of discrete neurocognitive processes to inform targeted interventions; (3) clinical trials that produce useful information about putative illness mechanisms, promising treatment targets, and downstream clinical effects; and (4) "productive urgency" in pursuing feasible and effective cognitive interventions for psychosis. Programs employing these principles have catalyzed cognitive measurement, drug development, and behavioral intervention approaches that aim to improve neurocognition and community functioning among persons with schizophrenia. NIMH will maintain support for innovative and impactful investigator-initiated research that advances patient-centered, clinically effective, and continuously improving cognitive health care for persons with psychotic disorders.

A kinetic analysis of four high velocity, horizontally focused step-up variations for acceleration training.

Step-up variations are frequently used in sports performance to develop coordinated and powerful movements that transfer to running. This study aimed to quantify the kinetic characteristics of the first foot contact of four different step-up variations. Ten professional rugby league players participated in this study and performed the Barbell One Box Step-Up with Catch (BB1), Barbell Two Box Step-Up (BB2), Vest Two Box Run (VEST) and Step-Up Jump (JUMP) as part of routine in-season strength training sessions during one season. Peak force, total impulse and maximal rate of force development (RFD) were measured from first foot contact on the step-up box. Significantly greater peak force and RFD were observed in JUMP than any other variation (standardized mean difference; SMD: 3.9-5.5; p < 0.001). Total impulse was equal between JUMP and BB1, and significantly greater in JUMP than BB2 and VEST (SMD: 1.3-2.3; p < 0.001), and in BB1 than BB2 and VEST (SMD: 1.8-2.8; p < 0.001). Significantly larger peak force and RFD were observed in BB2 and VEST than BB1 (SMD: 0.6-0.7) and in total impulse in BB2 than VEST (SMD: 1.6) (p < 0.05). The results of this study highlight that step-up exercise variations maximize different kinetic characteristics, which may transfer differently to athlete running performance.

General Applicability of Existing College of American Pathologists Accreditation Requirements to Clinical Implementation of Machine Learning-Based Methods in Molecular Oncology Testing.

CONTEXT.­: The College of American Pathologists (CAP) accreditation requirements for clinical laboratory testing help ensure laboratories implement and maintain systems and processes that are associated with quality. Machine learning (ML)-based models share some features of conventional laboratory testing methods. Accreditation requirements that specifically address clinical laboratories' use of ML remain in the early stages of development. OBJECTIVE.­: To identify relevant CAP accreditation requirements that may be applied to the clinical adoption of ML-based molecular oncology assays, and to provide examples of current and emerging ML applications in molecular oncology testing. DESIGN.­: CAP accreditation checklists related to molecular pathology and general laboratory practices (Molecular Pathology, All Common and Laboratory General) were reviewed. Examples of checklist requirements that are generally applicable to validation, revalidation, quality management, infrastructure, and analytical procedures of ML-based molecular oncology assays were summarized. Instances of ML use in molecular oncology testing were assessed from literature review. RESULTS.­: Components of the general CAP accreditation framework that exist for traditional molecular oncology assay validation and maintenance are also relevant for implementing ML-based tests in a clinical laboratory. Current and emerging applications of ML in molecular oncology testing include DNA methylation profiling for central nervous system tumor classification, variant calling, microsatellite instability testing, mutational signature analysis, and variant prediction from histopathology images. CONCLUSIONS.­: Currently, much of the ML activity in molecular oncology is within early clinical implementation. Despite specific considerations that apply to the adoption of ML-based methods, existing CAP requirements can serve as general guidelines for the clinical implementation of ML-based assays in molecular oncology testing.

Evaluating Real-World Implementation of INFORM (Improving Nursing Home Care through Feedback on Performance Data): An Improvement Initiative in Canadian Nursing Homes.

BACKGROUND: INFORM (Improving Nursing Home Care through Feedback on Performance Data) was a research intervention that equipped nursing home managers with skills to conduct local improvement projects and supported them in improving performance through modifiable elements in their units. Prior reports have found positive and sustained outcomes from INFORM intervention. In this article, the authors report findings from a formative service evaluation of INFORM as modified for implementation in real-world settings. METHODS: INFORM was transformed for real-world implementation with an initial cohort of 26 nursing homes in British Columbia, Canada (INFORM BC). Three stakeholder groups were involved: nursing home teams, an academic team that modified INFORM for implementation, and a BC team that implemented INFORM and coached participating nursing home teams in applying it locally. Service evaluation was conducted drawing on participants from all three stakeholder groups, using convenience sampling, with numbers varying by data source. Using a mixed methods design, outcome data included qualitative and quantitative assessment of surveys, discussions, observations, and a review of documents and resources. RESULTS: The majority of nursing home teams reported positive outcomes relative to the usefulness and relevance of the initiative for local needs despite a number of operational challenges during implementation. A key factor in their success was combining targeted external support with the opportunity to set goals and measure success locally. Challenges included a lack of time at the nursing home level, COVID-19-related disruptions, and issues with role clarity and alignment of expectations among the academic and BC teams. CONCLUSION: INFORM BC advanced the processes of change planning and transferable learning among nursing home managers and their local teams. Success was facilitated externally but defined and achieved locally. Future iterations should probe outcome sustainability and how nursing home teams adapt the INFORM approach in practice.

Synthesis, crystal structure and Hirshfeld surface analysis of 1-[3-(2-oxo-3-phenyl-1,2-di-hydro-quinoxalin-1-yl)prop-yl]-3-phenyl-1,2-di-hydro-quinoxalin-2-one.

In the title compound, C31H24N4O2, the di-hydro-quinoxaline units are both essentially planar with the dihedral angle between their mean planes being 64.82 (4)°. The attached phenyl rings differ significantly in their rotational orientations with respect to the di-hydro-quinoxaline planes. In the crystal, one set of C-H⋯O hydrogen bonds form chains along the b-axis direction, which are connected in pairs by a second set of C-H⋯O hydrogen bonds. Two sets of π-stacking inter-actions and C-H⋯π(ring) inter-actions join the double chains into the final three-dimensional structure.

Ethyl 2-[(2-oxo-2H-chromen-6-yl)-oxy]acetate.

Ethyl 2-[(2-oxo-2H-chromen-6-yl)-oxy]acetate, C13H12O5, a member of the pharmacologically important class of coumarins, crystallizes in the monoclinic C2/c space group in the form of sheets, within which mol-ecules are related by inversion centers and 21 axes. Multiple C-H⋯O weak hydrogen-bonding inter-actions reinforce this pattern. The planes of these sheets are oriented in the approximate direction of the ac face diagonal. Inter-sheet inter-actions are a combination of coumarin system π-π stacking and additional C-H⋯O weak hydrogen bonds between ethyl acet-oxy groups.

Noninvasive assessment of organ-specific and shared pathways in multi-organ fibrosis using T1 mapping.

Fibrotic diseases affect multiple organs and are associated with morbidity and mortality. To examine organ-specific and shared biologic mechanisms that underlie fibrosis in different organs, we developed machine learning models to quantify T1 time, a marker of interstitial fibrosis, in the liver, pancreas, heart and kidney among 43,881 UK Biobank participants who underwent magnetic resonance imaging. In phenome-wide association analyses, we demonstrate the association of increased organ-specific T1 time, reflecting increased interstitial fibrosis, with prevalent diseases across multiple organ systems. In genome-wide association analyses, we identified 27, 18, 11 and 10 independent genetic loci associated with liver, pancreas, myocardial and renal cortex T1 time, respectively. There was a modest genetic correlation between the examined organs. Several loci overlapped across the examined organs implicating genes involved in a myriad of biologic pathways including metal ion transport (SLC39A8, HFE and TMPRSS6), glucose metabolism (PCK2), blood group antigens (ABO and FUT2), immune function (BANK1 and PPP3CA), inflammation (NFKB1) and mitosis (CENPE). Finally, we found that an increasing number of organs with T1 time falling in the top quintile was associated with increased mortality in the population. Individuals with a high burden of fibrosis in ≥3 organs had a 3-fold increase in mortality compared to those with a low burden of fibrosis across all examined organs in multivariable-adjusted analysis (hazard ratio = 3.31, 95% confidence interval 1.77-6.19; P = 1.78 × 10-4). By leveraging machine learning to quantify T1 time across multiple organs at scale, we uncovered new organ-specific and shared biologic pathways underlying fibrosis that may provide therapeutic targets.

Meta-Analysis of Genome-Wide Association Studies Reveals Genetic Mechanisms of Supraventricular Arrhythmias.

BACKGROUND: Substantial data support a heritable basis for supraventricular tachycardias, but the genetic determinants and molecular mechanisms of these arrhythmias are poorly understood. We sought to identify genetic loci associated with atrioventricular nodal reentrant tachycardia (AVNRT) and atrioventricular accessory pathways or atrioventricular reciprocating tachycardia (AVAPs/AVRT). METHODS: We performed multiancestry meta-analyses of genome-wide association studies to identify genetic loci for AVNRT (4 studies) and AVAP/AVRT (7 studies). We assessed evidence supporting the potential causal effects of candidate genes by analyzing relations between associated variants and cardiac gene expression, performing transcriptome-wide analyses, and examining prior genome-wide association studies. RESULTS: Analyses comprised 2384 AVNRT cases and 106 489 referents, and 2811 AVAP/AVRT cases and 1,483 093 referents. We identified 2 significant loci for AVNRT, which implicate NKX2-5 and TTN as disease susceptibility genes. A transcriptome-wide association analysis supported an association between reduced predicted cardiac expression of NKX2-5 and AVNRT. We identified 3 significant loci for AVAP/AVRT, which implicate SCN5A, SCN10A, and TTN/CCDC141. Variant associations at several loci have been previously reported for cardiac phenotypes, including atrial fibrillation, stroke, Brugada syndrome, and electrocardiographic intervals. CONCLUSIONS: Our findings highlight gene regions associated with ion channel function (AVAP/AVRT), as well as cardiac development and the sarcomere (AVAP/AVRT and AVNRT) as important potential effectors of supraventricular tachycardia susceptibility.

Adipokines measured during pregnancy and at birth are associated with infant negative affect.

BACKGROUND: Increased adiposity during pregnancy may be related to offspring risk for mental health disorders, although the biological mechanisms are poorly understood. One promising hypothesis is that factors secreted from adipocytes such as leptin and adiponectin may explain this association. The current study examined whether pregnancy or umbilical cord blood concentrations of leptin and/or adiponectin a) predict elevated infant negative affect at 6 months (an early life marker of risk for psychopathology); and b) help explain the association between pregnancy adiposity and increased infant negative affect. METHODS: Data came from a prospective cohort (N = 305) of pregnant individuals and their offspring. Second trimester adiposity was assessed using air displacement plethysmography. Concentrations of leptin and adiponectin were measured in second trimester plasma and umbilical cord plasma. Infant negative affect was assessed by standardized observation at 6 months. Second trimester inflammation was assessed using a comprehensive panel of cytokines. RESULTS: Lower second trimester adiponectin was associated with elevated infant negative affect, and mediated the effect of pregnancy adiposity on infant negative affect. This association was independent of the effect of second trimester inflammation. Umbilical cord leptin also predicted higher infant negative affect and mediated the association between pregnancy adiposity and infant negative affect. CONCLUSIONS: This is the first study to link pregnancy adiponectin or cord blood leptin to infant markers of risk for psychopathology, and the first to demonstrate that these adipokines mediate the association between pregnancy adiposity and offspring behavioral outcomes, suggesting novel markers of risk and potential mechanisms of effect.