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Worldwide trends to delay childbearing have increased parental ages at birth. Older parental age may harm offspring health, but mechanisms remain unclear. Alterations in offspring DNA methylation (DNAm) patterns could play a role as aging has been associated with methylation changes in gametes of older individuals. We meta-analyzed epigenome-wide associations of parental age with offspring blood DNAm of over 9500 newborns and 2000 children (5-10 years old) from the Pregnancy and Childhood Epigenetics consortium. In newborns, we identified 33 CpG sites in 13 loci with DNAm associated with maternal age (PFDR

PurposeTo describe the effects of estetrol (E4) 15 mg/drospirenone (DRSP) 3 mg on physical and emotional premenstrual and menstrual symptoms.Materials and methodsWe used Menstrual Distress Questionnaire (MDQ) data from a phase-3 trial (NCT02817828) in Europe and Russia with participants (18 - 50 years) using E4/DRSP for up to 13 cycles. We assessed mean changes in MDQ-t-scores from baseline to end of treatment in premenstrual (4 days before most recent flow) and menstrual (most recent flow) scores for 4 MDQ domains in starters and switchers (use of hormonal contraception in prior 3 months) and performed a shift analysis on individual symptoms within each domain.ResultsOf 1,553 treated participants, 1,398(90.0%), including 531(38%) starters, completed both MDQs. Starters reported improvements for premenstrual Pain (-1.4), Water Retention (-3.3) and Negative Affect (-2.5); and for menstrual Pain (-3.5), Water Retention (-3.4), and Negative Affect (-2.7) (all p 40% of participants for Cramps, Backache and Fatigue (domain Pain), Painful or Tender Breast and Swelling (domain Water Retention) and Mood Swings and Irritability (domain Negative Affect).ConclusionE4/DRSP starters experienced significant improvements in the domains Pain, Water Retention and Negative Affect particularly benefiting those with more severe baseline symptoms. Switchers showed minimal changes.

Traumatic brain injury (TBI) affects how the brain functions in the short and long term. Resulting patient outcomes across physical, cognitive, and psychological domains are complex and often difficult to predict. Major challenges to developing personalized treatment for TBI include distilling large quantities of complex data and increasing the precision with which patient outcome prediction (prognoses) can be rendered. We developed and applied interpretable machine learning methods to TBI patient data. We show that complex data describing TBI patients intake characteristics and outcome phenotypes can be distilled to smaller sets of clinically interpretable latent factors. We demonstrate that 19 clusters of TBI outcomes can be predicted from intake data, a ~ 6× improvement in precision over clinical standards. Finally, we show that 36% of the outcome variance across patients can be predicted. These results demonstrate the importance of interpretable machine learning applied to deeply characterized patients for data-driven distillation and precision prognosis.

BACKGROUND: Seasonal variations in environmental exposures at birth or during gestation are associated with numerous adult traits and health outcomes later in life. Whether DNA methylation (DNAm) plays a role in the molecular mechanisms underlying the associations between birth season and lifelong phenotypes remains unclear. METHODS: We carried out epigenome-wide meta-analyses within the Pregnancy And Childhood Epigenetic Consortium to identify associations of DNAm with birth season, both at differentially methylated probes (DMPs) and regions (DMRs). Associations were examined at two time points: at birth (21 cohorts, N = 9358) and in children aged 1-11 years (12 cohorts, N = 3610). We conducted meta-analyses to assess the impact of latitude on birth season-specific associations at both time points. RESULTS: We identified associations between birth season and DNAm (False Discovery Rate-adjusted p values

Although many novel gene-metabolite and gene-protein associations have been identified using high-throughput biochemical profiling, systematic studies that leverage human genetics to illuminate causal relationships between circulating proteins and metabolites are lacking. Here, we performed protein-metabolite association studies in 3,626 plasma samples from three human cohorts. We detected 171,800 significant protein-metabolite pairwise correlations between 1,265 proteins and 365 metabolites, including established relationships in metabolic and signaling pathways such as the protein thyroxine-binding globulin and the metabolite thyroxine, as well as thousands of new findings. In Mendelian randomization (MR) analyses, we identified putative causal protein-to-metabolite associations. We experimentally validated top MR associations in proof-of-concept plasma metabolomics studies in three murine knockout strains of key protein regulators. These analyses identified previously unrecognized associations between bioactive proteins and metabolites in human plasma. We provide publicly available data to be leveraged for studies in human metabolism and disease.

PurposeThe use of telemedicine (TM) has accelerated in recent years, yet research on the implementation and effectiveness of TM-delivered medication treatment for opioid use disorder (MOUD) has been limited. This study investigated the feasibility of implementing a care coordination model involving MOUD delivered via an external TM provider for the purpose of expanding access to MOUD for patients in rural settings.MethodsThe study tested a care coordination model in 6 rural primary care sites by establishing referral and coordination between the clinic and a TM company for MOUD. The intervention spanned approximately 6 months from July/August 2020 to January 2021, coinciding with the peak of the COVID-19 pandemic. Each clinic tracked patients with OUD in a registry during the intervention period. A pre-/post-intervention design (N = 6) was used to assess the clinic-level outcome as patient-days on MOUD based on patient electronic health records.FindingsAll clinics implemented critical components of the intervention, with an overall TM referral rate of 11.7% among patients in the registry. Five of the 6 sites showed an increase in patient-days on MOUD during the intervention period compared to the 6-month period before the intervention (mean increase per 1,000 patients: 132 days, P = .08, Cohen's d = 0.55). The largest increases occurred in clinics that lacked MOUD capacity or had a greater number of patients initiating MOUD during the intervention period.ConclusionsTo expand access to MOUD in rural settings, the care coordination model is most effective when implemented in clinics that have negligible or limited MOUD capacity.

HIV-1-associated nephropathy (HIVAN) is a severe complication of HIV-1 infection. To gain insight into the pathogenesis of kidney disease in the setting of HIV, a transgenic (Tg) mouse model [CD4C/HIV-negative regulator factor (Nef)] was used in which HIV-1 nef expression is under control of regulatory sequences (CD4C) of the human CD4 gene, thus allowing expression in target cells of the virus. These Tg mice develop a collapsing focal segmental glomerulosclerosis associated with microcystic dilatation, similar to human HIVAN. To identify kidney cells permissive to the CD4C promoter, CD4C reporter Tg lines were used. They showed preferential expression in glomeruli, mainly in mesangial cells. Breeding CD4C/HIV Tg mice on 10 different mouse backgrounds showed that HIVAN was modulated by host genetic factors. Studies of gene-deficient Tg mice revealed that the presence of B and T cells and that of several genes was dispensable for the development of HIVAN: those involved in apoptosis (Trp53, Tnfsf10, Tnf, Tnfrsf1b, and Bax), in immune cell recruitment (Ccl3, Ccl2, Ccr2, Ccr5, and Cx3cr1), in nitric oxide (NO) formation (Nos3 and Nos2), or in cell signaling (Fyn, Lck, and Hck/Fgr). However, deletion of Src partially and that of Hck/Lyn largely abrogated its development. These data suggest that Nef expression in mesangial cells through hematopoietic cell kinase (Hck)/Lck/Yes novel tyrosine kinase (Lyn) represents important cellular and molecular events for the development of HIVAN in these Tg mice.

Self-driving labs (SDLs) combine fully automated experiments with artificial intelligence (AI) that decides the next set of experiments. Taken to their ultimate expression, SDLs could usher a new paradigm of scientific research, where the world is probed, interpreted, and explained by machines for human benefit. While there are functioning SDLs in the fields of chemistry and materials science, we contend that synthetic biology provides a unique opportunity since the genome provides a single target for affecting the incredibly wide repertoire of biological cell behavior. However, the level of investment required for the creation of biological SDLs is only warranted if directed toward solving difficult and enabling biological questions. Here, we discuss challenges and opportunities in creating SDLs for synthetic biology.

Cortical thickness changes dramatically during development and is associated with adolescent drinking. However, previous findings have been inconsistent and limited by region-of-interest approaches that are underpowered because they do not conform to the underlying spatially heterogeneous effects of alcohol. In this study, adolescents (n = 657; 12-22 years at baseline) from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study who endorsed little to no alcohol use at baseline were assessed with structural magnetic resonance imaging and followed longitudinally at four yearly intervals. Seven unique spatial patterns of covarying cortical thickness were obtained from the baseline scans by applying an unsupervised machine learning method called non-negative matrix factorization (NMF). The cortical thickness maps of all participants' longitudinal scans were projected onto vertex-level cortical patterns to obtain participant-specific coefficients for each pattern. Linear mixed-effects models were fit to each pattern to investigate longitudinal effects of alcohol consumption on cortical thickness. We found in six NMF-derived cortical thickness patterns, the longitudinal rate of decline in no/low drinkers was similar for all age cohorts. Among moderate drinkers the decline was faster in the younger adolescent cohort and slower in the older cohort. Among heavy drinkers the decline was fastest in the younger cohort and slowest in the older cohort. The findings suggested that unsupervised machine learning successfully delineated spatially coordinated patterns of vertex-level cortical thickness variation that are unconstrained by neuroanatomical features. Age-appropriate cortical thinning is more rapid in younger adolescent drinkers and slower in older adolescent drinkers, an effect that is strongest among heavy drinkers.

INTRODUCTION: The SARS-CoV-2 pandemic represented a formidable scientific and technological challenge to public health due to its rapid spread and evolution. To meet these challenges and to characterize the virus over time, the State of California established the California SARS-CoV-2 Whole Genome Sequencing (WGS) Initiative, or California COVIDNet. This initiative constituted an unprecedented multi-sector collaborative effort to achieve large-scale genomic surveillance of SARS-CoV-2 across California to monitor the spread of variants within the state, to detect new and emerging variants, and to characterize outbreaks in congregate, workplace, and other settings. METHODS: California COVIDNet consists of 50 laboratory partners that include public health laboratories, private clinical diagnostic laboratories, and academic sequencing facilities as well as expert advisors, scientists, consultants, and contractors. Data management, sample sourcing and processing, and computational infrastructure were major challenges that had to be resolved in the midst of the pandemic chaos in order to conduct SARS-CoV-2 genomic surveillance. Data management, storage, and analytics needs were addressed with both conventional database applications and newer cloud-based data solutions, which also fulfilled computational requirements. RESULTS: Representative and randomly selected samples were sourced from state-sponsored community testing sites. Since March of 2021, California COVIDNet partners have contributed more than 450,000 SARS-CoV-2 genomes sequenced from remnant samples from both molecular and antigen tests. Combined with genomes from CDC-contracted WGS labs, there are currently nearly 800,000 genomes from all 61 local health jurisdictions (LHJs) in California in the COVIDNet sequence database. More than 5% of all reported positive tests in the state have been sequenced, with similar rates of sequencing across 5 major geographic regions in the state. DISCUSSION: Implementation of California COVIDNet revealed challenges and limitations in the public health system. These were overcome by engaging in novel partnerships that established a successful genomic surveillance program which provided valuable data to inform the COVID-19 public health response in California. Significantly, California COVIDNet has provided a foundational data framework and computational infrastructure needed to respond to future public health crises.

Metagenomics is a technique for genome-wide profiling of microbiomes; this technique generates billions of DNA sequences called reads. Given the multiplication of metagenomic projects, computational tools are necessary to enable the efficient and accurate classification of metagenomic reads without needing to construct a reference database. The program DL-TODA presented here aims to classify metagenomic reads using a deep learning model trained on over 3000 bacterial species. A convolutional neural network architecture originally designed for computer vision was applied for the modeling of species-specific features. Using synthetic testing data simulated with 2454 genomes from 639 species, DL-TODA was shown to classify nearly 75% of the reads with high confidence. The classification accuracy of DL-TODA was over 0.98 at taxonomic ranks above the genus level, making it comparable with Kraken2 and Centrifuge, two state-of-the-art taxonomic classification tools. DL-TODA also achieved an accuracy of 0.97 at the species level, which is higher than 0.93 by Kraken2 and 0.85 by Centrifuge on the same test set. Application of DL-TODA to the human oral and cropland soil metagenomes further demonstrated its use in analyzing microbiomes from diverse environments. Compared to Centrifuge and Kraken2, DL-TODA predicted distinct relative abundance rankings and is less biased toward a single taxon.

ObjectiveTo evaluate overall and subgroup efficacy of an estetrol (E4) 15 mg drospirenone (DRSP) 3 mg oral contraceptive in a 24/4-day regimen.Study designWe pooled efficacy outcomes from 2 pivotal phase 3 contraceptive trials with E4/DRSP conducted in the United States/Canada and Europe/Russia. We assessed Pearl Index (PI; pregnancies per 100 participant-years) and 13-cycle life-table pregnancy rates in at-risk cycles (confirmed intercourse and no other contraceptive use) among participants 16 to 35 years. We calculated PI by age and further subcategorization (contraceptive history and body mass index [BMI]). We performed multivariable analysis using Cox regression to assess impact of potential confounding factors.ResultsAnalyses included 3027 participants, of whom 451 (14.9%) had a BMI ≥30 kg/m2. The pooled PI was 1.52 (95% confidence interval 1.04-2.16) and the 13-cycle life-table pregnancy rate was 1.28% (0.83%-1.73%). We calculated unadjusted pooled PI in participants 16 to 25 years and 26 to 35 years of 1.61 (0.94-2.57) and 1.43 (0.78-2.40), respectively; in new starters and switchers of 1.88 (1.09-3.00) and 1.24 (0.68-2.08), respectively; and by BMI

ObjectivesTo evaluate tolerability and safety of estetrol (E4) 15 mg/drospirenone (DRSP) 3 mg oral contraceptive using pooled data from two, multicenter, phase 3 trials.Study designThe two trials enrolled participants aged 16-50 years with a body mass index ≤35.0 kg/m2 to use E4/DRSP in a 24/4-day regimen for up to 13 cycles. We pooled data from participants who used at least one E4/DRSP dose and had a follow-up assessment to analyze adverse events (AEs), vital signs, and laboratory parameters, including serum lipids, glucose, glycated hemoglobin, and potassium. We consolidated similar Medical Dictionary for Regulatory Activities preferred terms into groupings.ResultsOf 3725 participants enrolled, we included 3417 in the analyses of whom 1786 (52.3%) reported ≥1 AE. Most participants with reported AEs had AEs that investigators rated as mild or moderate (n = 1665, 93.2%); of participants reporting AEs, 1105 (61.9%) did so during cycles 1 to 3. In total, 981 (28.7%) participants experienced ≥1 treatment-related AE, most frequently related to bleeding complaints (n = 323, 9.5%), breast pain or tenderness (n = 136, 4.0%), acne (n = 113, 3.3%), and mood disturbance (n = 111, 3.2%). Discontinuation due to treatment-related AEs occurred in 272 participants (8.0%), with only bleeding complaints (n = 97, 2.8%) and mood disturbance (n = 38, 1.1%) at rates exceeding 1%. Three participants experienced serious AEs, which the site investigators considered treatment-related: one venous thromboembolism, one worsening of depression, and one ectopic pregnancy. We found no clinically relevant changes in weight, blood pressure, heart rate, or laboratory parameters during treatment.ConclusionsE4/DRSP is associated with a favorable tolerability and safety profile.Implications statementPooling data allowed for a robust assessment of tolerability and safety, including relatively infrequent events. Other than bleeding complaints and mood disturbance, no adverse event resulted in E4/DRSP discontinuation at rates >1%. Post-marketing surveillance studies are needed to evaluate long-term safety of the E4/DRSP COC and population-based venous thromboembolism risks.

ObjectiveTo evaluate the bleeding patterns of a new combined oral contraceptive containing estetrol (E4) 15 mg/drospirenone (DRSP) 3 mg in a 24/4-day regimen.Study designWe pooled bleeding data from two parallel, open-label, 13-cycle phase 3 trials that enrolled participants 16 to 50 years old with body mass index (BMI) ≤35 kg/m2. Participants reported vaginal bleeding/spotting in daily diaries. For this bleeding analysis, we included participants with at least one evaluable cycle. We calculated mean frequencies of scheduled and unscheduled bleeding/spotting episodes and median duration of bleeding/spotting episodes, and assessed associations between treatment compliance, BMI and recent hormonal contraceptive use on bleeding/spotting outcomes.ResultsWe included 3409 participants with 33,815 cycles. Scheduled bleeding/spotting occurred in 87.2% to 90.4% of participants/cycle, with a median duration of 4 to 5 days. Unscheduled bleeding/spotting decreased from 27.1% in Cycle 1 to 20.6% in Cycle 2 to ≤17.5% from Cycle 5 onwards. Most (66.5%) unscheduled bleeding/spotting episodes were spotting-only. Between 5.8% and 7.8% of users/cycle experienced absence of any scheduled or unscheduled bleeding/spotting. Missing one or more active pills resulted in a higher occurrence of unscheduled bleeding/spotting (adjusted odds ratio [aOR] 2.13 [95% confidence interval 1.68-2.70]) and absence of scheduled bleeding/spotting (aOR 2.36 [1.82-3.07]). Participants with a BMI ≥30 kg/m2 reported more absence of scheduled bleeding/spotting (aOR 1.68 [1.37-2.05]). Switchers and starters reported similar frequencies of unscheduled bleeding/spotting (aOR 0.94 [0.83-1.07]) and absence of scheduled bleeding/spotting (aOR 1.00 [0.85-1.19]). Three percent of participants discontinued for a bleeding-related adverse event.ConclusionE4/DRSP use results in a predictable bleeding pattern with limited unscheduled bleeding/spotting. Noncompliance and BMI affect bleeding patterns.Implications statementMost estetrol/drospirenone users experience a predictable and regular bleeding pattern. Providers can educate patients about the expected bleeding patterns and should advise users that they may infrequently experience no scheduled bleeding/spotting. This information may improve user acceptability and continuation of this new oral contraceptive.

The neurophysiology of cells and tissues are monitored electrophysiologically and optically in diverse experiments and species, ranging from flies to humans. Understanding the brain requires integration of data across this diversity, and thus these data must be findable, accessible, interoperable, and reusable (FAIR). This requires a standard language for data and metadata that can coevolve with neuroscience. We describe design and implementation principles for a language for neurophysiology data. Our open-source software (Neurodata Without Borders, NWB) defines and modularizes the interdependent, yet separable, components of a data language. We demonstrate NWB's impact through unified description of neurophysiology data across diverse modalities and species. NWB exists in an ecosystem, which includes data management, analysis, visualization, and archive tools. Thus, the NWB data language enables reproduction, interchange, and reuse of diverse neurophysiology data. More broadly, the design principles of NWB are generally applicable to enhance discovery across biology through data FAIRness.

Mild Traumatic brain injury (mTBI) is a signature wound in military personnel, and repetitive mTBI has been linked to age-related neurogenerative disorders that affect white matter (WM) in the brain. However, findings of injury to specific WM tracts have been variable and inconsistent. This may be due to the heterogeneity of mechanisms, etiology, and comorbid disorders related to mTBI. Non-negative matrix factorization (NMF) is a data-driven approach that detects covarying patterns (components) within high-dimensional data. We applied NMF to diffusion imaging data from military Veterans with and without a self-reported TBI history. NMF identified 12 independent components derived from fractional anisotropy (FA) in a large dataset (n = 1,475) gathered through the ENIGMA (Enhancing Neuroimaging Genetics through Meta-Analysis) Military Brain Injury working group. Regressions were used to examine TBI- and mTBI-related associations in NMF-derived components while adjusting for age, sex, post-traumatic stress disorder, depression, and data acquisition site/scanner. We found significantly stronger age-dependent effects of lower FA in Veterans with TBI than Veterans without in four components (q

Rural populations continue to experience persistent cancer disparities compared with urban populations particularly in cancers that can be prevented or detected early through screening and vaccination. Although the National Cancer Institute and the larger cancer research community have identified rural community partnerships as the foundation for reducing the disparities, we have identified limited application of community-based participatory research in cancer prevention and control research. Guided by the Community-Based Participatory Research Conceptual Model and our collective experience, we provide a framework for a community-cancer center partnership that focuses on promoting health equity. In this commentary, we articulate that the partnership process must foster capacity for communities and cancer centers, strive for rural representation in clinical trials and biobanking, build a pipeline for dissemination and implementation research, and create a bidirectional flow of knowledge between communities and academic institutions. Authentic partnerships with rural communities should be the ultimate goal of cancer centers, and the process described in this commentary can serve as an initial platform to build capacity and continue to strive toward that goal.

IntroductionPhysical exercise and cognitive training have the potential to enhance cognitive function and mobility in older adults at risk of Alzheimer's disease and related dementia (ADRD), but little is known about the feasibility of delivering multidomain interventions in home settings of older adults at risk of ADRD. This study aims to assess the feasibility of home-based delivery of exercise and cognitive interventions, and to evaluate the relationship between participants' intervention preferences and their subsequent adherence. Secondary objectives include the effect of the interventions on ADRD risk factors, including frailty, mobility, sleep, diet and psychological health.Methods and analysisThe SYNchronising Exercises, Remedies in GaIt and Cognition at Home (SYNERGIC@Home) feasibility trial is a randomised control trial that follows a 2×2 factorial design, with a 16-week home-based intervention programme (3 sessions per week) of physical exercises and cognitive training. Participants will be randomised in blocks of four to one of the following four arms: (1) combined exercise (aerobic and resistance)+cognitive training (NEUROPEAK); (2) combined exercise+control cognitive training (web searching); (3) control exercise (balance and toning)+cognitive training; and (4) control exercise+control cognitive training. SYNERGIC@Home will be implemented through video conferencing. Baseline and post-intervention assessments at 4-month and 10-month follow-up will include measures of cognition, frailty, mobility, sleep, diet and psychological health. Primary feasibility outcome is adherence to the interventions. Primary analytic outcome is the relationship between pre-allocation preference for a given intervention and subsequent adherence to the allocated intervention. A series of secondary analytic outcomes examining the potential effect of the individual and combined interventions on cognitive, mobility and general well-being will be measured at baseline and follow-up.Ethics and disseminationEthics approval was granted by the relevant research ethics boards. Findings of the study will be presented to stakeholders and published in peer-reviewed journals and at provincial, national and international conferences.Trial registration numberNCT04997681, Pre-results.

BackgroundPlasma proteins are critical mediators of cardiovascular processes and are the targets of many drugs. Previous efforts to characterize the genetic architecture of the plasma proteome have been limited by a focus on individuals of European descent and leveraged genotyping arrays and imputation. Here we describe whole genome sequence analysis of the plasma proteome in individuals with greater African ancestry, increasing our power to identify novel genetic determinants.MethodsProteomic profiling of 1301 proteins was performed in 1852 Black adults from the Jackson Heart Study using aptamer-based proteomics (SomaScan). Whole genome sequencing association analysis was ascertained for all variants with minor allele count ≥5. Results were validated using an alternative, antibody-based, proteomic platform (Olink) as well as replicated in the Multi-Ethnic Study of Atherosclerosis and the HERITAGE Family Study (Health, Risk Factors, Exercise Training and Genetics).ResultsWe identify 569 genetic associations between 479 proteins and 438 unique genetic regions at a Bonferroni-adjusted significance level of 3.8×10-11. These associations include 114 novel locus-protein relationships and an additional 217 novel sentinel variant-protein relationships. Novel cardiovascular findings include new protein associations at the APOE gene locus including ZAP70 (sentinel single nucleotide polymorphism [SNP] rs7412-T, β=0.61±0.05, P=3.27×10-30) and MMP-3 (β=-0.60±0.05, P=1.67×10-32), as well as a completely novel pleiotropic locus at the HPX gene, associated with 9 proteins. Further, the associations suggest new mechanisms of genetically mediated cardiovascular disease linked to African ancestry; we identify a novel association between variants linked to APOL1-associated chronic kidney and heart disease and the protein CKAP2 (rs73885319-G, β=0.34±0.04, P=1.34×10-17) as well as an association between ATTR amyloidosis and RBP4 levels in community-dwelling individuals without heart failure.ConclusionsTaken together, these results provide evidence for the functional importance of variants in non-European populations, and suggest new biological mechanisms for ancestry-specific determinants of lipids, coagulation, and myocardial function.

Integrating genetic information with metabolomics has provided new insights into genes affecting human metabolism. However, gene-metabolite integration has been primarily studied in individuals of European Ancestry, limiting the opportunity to leverage genomic diversity for discovery. In addition, these analyses have principally involved known metabolites, with the majority of the profiled peaks left unannotated. Here, we perform a whole genome association study of 2,291 metabolite peaks (known and unknown features) in 2,466 Black individuals from the Jackson Heart Study. We identify 519 locus-metabolite associations for 427 metabolite peaks and validate our findings in two multi-ethnic cohorts. A significant proportion of these associations are in ancestry specific alleles including findings in APOE, TTR and CD36. We leverage tandem mass spectrometry to annotate unknown metabolites, providing new insight into hereditary diseases including transthyretin amyloidosis and sickle cell disease. Our integrative omics approach leverages genomic diversity to provide novel insights into diverse cardiometabolic diseases.

BackgroundAmong children, sex-specific differences in disease prevalence, age of onset, and susceptibility have been observed in health conditions including asthma, immune response, metabolic health, some pediatric and adult cancers, and psychiatric disorders. Epigenetic modifications such as DNA methylation may play a role in the sexual differences observed in diseases and other physiological traits.MethodsWe performed a meta-analysis of the association of sex and cord blood DNA methylation at over 450,000 CpG sites in 8438 newborns from 17 cohorts participating in the Pregnancy And Childhood Epigenetics (PACE) Consortium. We also examined associations of child sex with DNA methylation in older children ages 5.5-10 years from 8 cohorts (n = 4268).ResultsIn newborn blood, sex was associated at Bonferroni level significance with differences in DNA methylation at 46,979 autosomal CpG sites (p

Higher maternal pre-pregnancy body mass index (ppBMI) is associated with increased neonatal morbidity, as well as with pregnancy complications and metabolic outcomes in offspring later in life. The placenta is a key organ in fetal development and has been proposed to act as a mediator between the mother and different health outcomes in children. The overall aim of the present work is to investigate the association of ppBMI with epigenome-wide placental DNA methylation (DNAm) in 10 studies from the PACE consortium, amounting to 2631 mother-child pairs. We identify 27 CpG sites at which we observe placental DNAm variations of up to 2.0% per 10 ppBMI-unit. The CpGs that are differentially methylated in placenta do not overlap with CpGs identified in previous studies in cord blood DNAm related to ppBMI. Many of the identified CpGs are located in open sea regions, are often close to obesity-related genes such as GPX1 and LGR4 and altogether, are enriched in cancer and oxidative stress pathways. Our findings suggest that placental DNAm could be one of the mechanisms by which maternal obesity is associated with metabolic health outcomes in newborns and children, although further studies will be needed in order to corroborate these findings.

BackgroundEpigenome-wide association studies (EWAS) have provided opportunities to understand the role of epigenetic mechanisms in development and pathophysiology of many chronic diseases. However, an important limitation of conventional EWAS is that profiles of epigenetic variability are often obtained in samples of mixed cell types. Here, we aim to assess whether changes in cord blood DNA methylation (DNAm) associated with gestational diabetes mellitus (GDM) exposure and early childhood growth markers occur in a cell type-specific manner.ResultsWe analyzed 275 cord blood samples collected at delivery from a prospective pre-birth cohort with genome-wide DNAm profiled by the Illumina MethylationEPIC array. We estimated proportions of seven common cell types in each sample using a cord blood-specific DNAm reference panel. Leveraging a recently developed approach named CellDMC, we performed cell type-specific EWAS to identify CpG loci significantly associated with GDM, or 3-year-old body mass index (BMI) z-score. A total of 1410 CpG loci displayed significant cell type-specific differences in methylation level between 23 GDM cases and 252 controls with a false discovery rate

As of August 2021, there were three COVID-19 vaccines available in the United States for the prevention of coronavirus 2019 (COVID-19). The purpose of this narrative review is to examine the early experience from the Emergency Use Authorization (EUA) of BNT162b2 (Pfizer, Inc./BioNTech), mRNA-1273 (Moderna, Inc.), and Ad26.COV2.S (Johnson and Johnson/Janssen Global Services, LLC) through July 2021. The EUA data from the clinical trials have largely been corroborated by real-world effectiveness investigations post-authorization. These studies indicate that immunity is obtained within 2 weeks post-vaccination and may endure for 6 months. The immunity conferred by the vaccines may also be effective against SARS-CoV-2 variants of concern. Additionally, populations not included in the emergency use authorization studies may also benefit from vaccination. This look back at the initial clinical experience can be used by the global community to inform and develop COVID-19 vaccine programs.

ObjectiveTo assess efficacy, cycle control, and safety of an oral contraceptive containing estetrol (E4) 15 mg and drospirenone (DRSP) 3 mg.Study designWomen aged 16 to 50 years with a body mass index ≤35 kg/m2 enrolled in this multicenter, open-label, 13-cycle, phase 3 trial evaluating E4/DRSP in a 24-active/4-placebo regimen. Follow-up was scheduled at Cycles 2, 4, 7, and 10 and within 3 weeks of completing Cycle 13. Participants used daily diaries to record pill use and vaginal bleeding. We evaluated efficacy outcomes in women 16 to 35 years and bleeding patterns and safety (adverse events [AEs]) in all participants. We assessed overall and method-failure pregnancy rates using the Pearl index (PI) and life-table analysis. Scheduled bleeding included spotting or bleeding starting during the 4-day placebo period or first 3 days of the next cycle.ResultsWe enrolled 1864 women of whom 1674 were 16 to 35 years. Women 16 to 35 years had a PI of 2.65 (95% CI 1.73-3.88), method-failure PI of 1.43 (95% CI 0.7-2.39) and 13-cycle life-table pregnancy rate of 2.1%. Scheduled bleeding occurred in 82.9% to 87.0% of women per cycle; median duration was 4.5 days. Unscheduled bleeding decreased from 30.3% in Cycle 1 to 21.3% to 22.1% during Cycles 2 to 4 and remained stable (15.5% to 19.2%) thereafter. The most frequently reported AEs were headache (5.0%) and metrorrhagia (4.6%). One-hundred thirty-two (7.1%) women discontinued the study early for an AE, most commonly for metrorrhagia (0.9%) and menorrhagia (0.8%). No thromboembolic events occurred.ConclusionE4/DRSP is an effective oral contraceptive with a predictable bleeding pattern for most women and low AE rates.Implications statementA new oral contraceptive with a novel estrogen, estetrol, combined with drospirenone has efficacy and safety within the range of other available oral contraceptives. Large phase 4 studies will be needed to confirm if this combination is associated with an improved adverse event profile or lower thrombosis risk.

Maternal smoking during pregnancy (MSDP) contributes to poor birth outcomes, in part through disrupted placental functions, which may be reflected in the placental epigenome. Here we present a meta-analysis of the associations between MSDP and placental DNA methylation (DNAm) and between DNAm and birth outcomes within the Pregnancy And Childhood Epigenetics (PACE) consortium (N = 1700, 344 with MSDP). We identify 443 CpGs that are associated with MSDP, of which 142 associated with birth outcomes, 40 associated with gene expression, and 13 CpGs are associated with all three. Only two CpGs have consistent associations from a prior meta-analysis of cord blood DNAm, demonstrating substantial tissue-specific responses to MSDP. The placental MSDP-associated CpGs are enriched for environmental response genes, growth-factor signaling, and inflammation, which play important roles in placental function. We demonstrate links between placental DNAm, MSDP and poor birth outcomes, which may better inform the mechanisms through which MSDP impacts placental function and fetal growth.

Human immunodeficiency virus (HIV) or simian immunodeficiency virus (SIV) infection causes myelodysplasia, anemia, and accumulation of inflammatory monocytes (CD14+ CD16+) through largely unknown cellular and molecular pathways. The mouse cells thought to be equivalent to human CD14+ CD16+ cells are CD11b+ Gr1+ myeloid-derived suppressor cells (MDSC). We used HIV transgenic (Tg) mouse models to study MDSC, namely, CD4C/Nef Tg mice expressing nef in dendritic cells (DC), pDC, CD4+ T, and other mature and immature myeloid cells and CD11c/Nef Tg mice with a more restricted expression, mainly in DC and pDC. Both Tg strains showed expansion of granulocytic and CD11b+ Gr1low/int cells with MDSC characteristics. Fetal liver cell transplantation revealed that this expansion was stroma-independent and abrogated in mixed Tg/non-Tg 50% chimera. Tg bone marrow (BM) erythroid progenitors were decreased and myeloid precursors increased, suggesting an aberrant differentiation likely driving CD11b+ Gr1+ cell expansion, apparently cell autonomously in CD4C/Nef Tg mice and likely through a bystander effect in CD11c/Nef Tg mice. Hck was activated in Tg spleen, and Nef-mediated CD11b+ Gr1+ cell expansion was abrogated in Hck/Lyn-deficient Nef Tg mice, indicating a requirement of Hck/Lyn for this Nef function. IL-17 and granulocyte colony-stimulating factor (G-CSF) were elevated in Nef Tg mice. Increased G-CSF levels were normalized in Tg mice treated with anti-IL-17 antibodies. Therefore, Nef expression in myeloid precursors causes severe BM failure, apparently cell autonomously. More cell-restricted expression of Nef in DC and pDC appears sufficient to induce BM differentiation impairment, granulopoiesis, and expansion of MDSC at the expense of erythroid maturation, with IL-17→G-CSF as one likely bystander contributor. IMPORTANCE HIV-1 and SIV infection often lead to myelodysplasia, anemia, and accumulation of inflammatory monocytes (CD14+ CD16+), with the latter likely involved in neuroAIDS. We found that some transgenic (Tg) mouse models of AIDS also develop accumulation of mature and immature cells of the granulocytic lineage, decreased erythroid precursors, and expansion of MDSC (equivalent to human CD14+ CD16+ cells). We identified Nef as being responsible for these phenotypes, and its expression in mouse DC appears sufficient for their development through a bystander mechanism. Nef expression in myeloid progenitors may also favor myeloid cell expansion, likely in a cell-autonomous way. Hck/Lyn is required for the Nef-mediated accumulation of myeloid cells. Finally, we identified G-CSF under the control of IL-17 as one bystander mediator of MDSC expansion. Our findings provide a framework to determine whether the Nef>Hck/Lyn>IL-17>G-CSF pathway is involved in human AIDS and whether it represents a valid therapeutic target.

BACKGROUND: β-adrenergic antagonists (BAAs) are used to treat cardiovascular disease such as ischemic heart disease, congestive heart failure, dysrhythmias, and hypertension. Poisoning from BAAs can lead to severe morbidity and mortality. We aimed to determine the utility of extracorporeal treatments (ECTRs) in BAAs poisoning. METHODS: We conducted systematic reviews of the literature, screened studies, extracted data, and summarized findings following published EXTRIP methods. RESULTS: A total of 76 studies (4 in vitro and 2 animal experiments, 1 pharmacokinetic simulation study, 37 pharmacokinetic studies on patients with end-stage kidney disease, and 32 case reports or case series) met inclusion criteria. Toxicokinetic or pharmacokinetic data were available on 334 patients (including 73 for atenolol, 54 for propranolol, and 17 for sotalol). For intermittent hemodialysis, atenolol, nadolol, practolol, and sotalol were assessed as dialyzable; acebutolol, bisoprolol, and metipranolol were assessed as moderately dialyzable; metoprolol and talinolol were considered slightly dialyzable; and betaxolol, carvedilol, labetalol, mepindolol, propranolol, and timolol were considered not dialyzable. Data were available for clinical analysis on 37 BAA poisoned patients (including 9 patients for atenolol, 9 for propranolol, and 9 for sotalol), and no reliable comparison between the ECTR cohort and historical controls treated with standard care alone could be performed. The EXTRIP workgroup recommends against using ECTR for patients severely poisoned with propranolol (strong recommendation, very low quality evidence). The workgroup offered no recommendation for ECTR in patients severely poisoned with atenolol or sotalol because of apparent balance of risks and benefits, except for impaired kidney function in which ECTR is suggested (weak recommendation, very low quality of evidence). Indications for ECTR in patients with impaired kidney function include refractory bradycardia and hypotension for atenolol or sotalol poisoning, and recurrent torsade de pointes for sotalol. Although other BAAs were considered dialyzable, clinical data were too limited to develop recommendations. CONCLUSIONS: BAAs have different properties affecting their removal by ECTR. The EXTRIP workgroup assessed propranolol as non-dialyzable. Atenolol and sotalol were assessed as dialyzable in patients with kidney impairment, and the workgroup suggests ECTR in patients severely poisoned with these drugs when aforementioned indications are present.

Traumatic brain injury (TBI) is common among military personnel and the civilian population and is often followed by a heterogeneous array of clinical, cognitive, behavioral, mood, and neuroimaging changes. Unlike many neurological disorders that have a characteristic abnormal central neurologic area(s) of abnormality pathognomonic to the disorder, a sufficient head impact may cause focal, multifocal, diffuse or combination of injury to the brain. This inconsistent presentation makes it difficult to establish or validate biological and imaging markers that could help improve diagnostic and prognostic accuracy in this patient population. The purpose of this manuscript is to describe both the challenges and opportunities when conducting military-relevant TBI research and introduce the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Military Brain Injury working group. ENIGMA is a worldwide consortium focused on improving replicability and analytical power through data sharing and collaboration. In this paper, we discuss challenges affecting efforts to aggregate data in this patient group. In addition, we highlight how "big data" approaches might be used to understand better the role that each of these variables might play in the imaging and functional phenotypes of TBI in Service member and Veteran populations, and how data may be used to examine important military specific issues such as return to duty, the late effects of combat-related injury, and alteration of the natural aging processes.

RNAcentral is a comprehensive database of non-coding RNA (ncRNA) sequences that provides a single access point to 44 RNA resources and >18 million ncRNA sequences from a wide range of organisms and RNA types. RNAcentral now also includes secondary (2D) structure information for >13 million sequences, making RNAcentral the world's largest RNA 2D structure database. The 2D diagrams are displayed using R2DT, a new 2D structure visualization method that uses consistent, reproducible and recognizable layouts for related RNAs. The sequence similarity search has been updated with a faster interface featuring facets for filtering search results by RNA type, organism, source database or any keyword. This sequence search tool is available as a reusable web component, and has been integrated into several RNAcentral member databases, including Rfam, miRBase and snoDB. To allow for a more fine-grained assignment of RNA types and subtypes, all RNAcentral sequences have been annotated with Sequence Ontology terms. The RNAcentral database continues to grow and provide a central data resource for the RNA community. RNAcentral is freely available at https://rnacentral.org.

When the COVID-19 pandemic began, formal frameworks to collect data about affected patients were lacking. The COVID-19 and Cancer Consortium (CCC19) was formed to collect granular data on patients with cancer and COVID-19 at scale and as rapidly as possible. CCC19 has grown from five initial institutions to 125 institutions with >400 collaborators. More than 5,000 cases with complete baseline data have been accrued. Future directions include increased electronic health record integration for direct data ingestion, expansion to additional domestic and international sites, more intentional patient involvement, and granular analyses of still-unanswered questions related to cancer subtypes and treatments.

BackgroundTumors comprise a complex microenvironment of interacting malignant and stromal cell types. Much of our understanding of the tumor microenvironment comes from in vitro studies isolating the interactions between malignant cells and a single stromal cell type, often along a single pathway.ResultTo develop a deeper understanding of the interactions between cells within human lung tumors, we perform RNA-seq profiling of flow-sorted malignant cells, endothelial cells, immune cells, fibroblasts, and bulk cells from freshly resected human primary non-small-cell lung tumors. We map the cell-specific differential expression of prognostically associated secreted factors and cell surface genes, and computationally reconstruct cross-talk between these cell types to generate a novel resource called the Lung Tumor Microenvironment Interactome (LTMI). Using this resource, we identify and validate a prognostically unfavorable influence of Gremlin-1 production by fibroblasts on proliferation of malignant lung adenocarcinoma cells. We also find a prognostically favorable association between infiltration of mast cells and less aggressive tumor cell behavior.ConclusionThese results illustrate the utility of the LTMI as a resource for generating hypotheses concerning tumor-microenvironment interactions that may have prognostic and therapeutic relevance.

In 2012, Kidney Disease: Improving Global Outcomes (KDIGO) published a guideline on the classification and management of acute kidney injury (AKI). The guideline was derived from evidence available through February 2011. Since then, new evidence has emerged that has important implications for clinical practice in diagnosing and managing AKI. In April of 2019, KDIGO held a controversies conference entitled Acute Kidney Injury with the following goals: determine best practices and areas of uncertainty in treating AKI; review key relevant literature published since the 2012 KDIGO AKI guideline; address ongoing controversial issues; identify new topics or issues to be revisited for the next iteration of the KDIGO AKI guideline; and outline research needed to improve AKI management. Here, we present the findings of this conference and describe key areas that future guidelines may address.

BackgroundData on patients with COVID-19 who have cancer are lacking. Here we characterise the outcomes of a cohort of patients with cancer and COVID-19 and identify potential prognostic factors for mortality and severe illness.MethodsIn this cohort study, we collected de-identified data on patients with active or previous malignancy, aged 18 years and older, with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection from the USA, Canada, and Spain from the COVID-19 and Cancer Consortium (CCC19) database for whom baseline data were added between March 17 and April 16, 2020. We collected data on baseline clinical conditions, medications, cancer diagnosis and treatment, and COVID-19 disease course. The primary endpoint was all-cause mortality within 30 days of diagnosis of COVID-19. We assessed the association between the outcome and potential prognostic variables using logistic regression analyses, partially adjusted for age, sex, smoking status, and obesity. This study is registered with ClinicalTrials.gov, NCT04354701, and is ongoing.FindingsOf 1035 records entered into the CCC19 database during the study period, 928 patients met inclusion criteria for our analysis. Median age was 66 years (IQR 57-76), 279 (30%) were aged 75 years or older, and 468 (50%) patients were male. The most prevalent malignancies were breast (191 [21%]) and prostate (152 [16%]). 366 (39%) patients were on active anticancer treatment, and 396 (43%) had active (measurable) cancer. At analysis (May 7, 2020), 121 (13%) patients had died. In logistic regression analysis, independent factors associated with increased 30-day mortality, after partial adjustment, were: increased age (per 10 years; partially adjusted odds ratio 1·84, 95% CI 1·53-2·21), male sex (1·63, 1·07-2·48), smoking status (former smoker vs never smoked: 1·60, 1·03-2·47), number of comorbidities (two vs none: 4·50, 1·33-15·28), Eastern Cooperative Oncology Group performance status of 2 or higher (status of 2 vs 0 or 1: 3·89, 2·11-7·18), active cancer (progressing vs remission: 5·20, 2·77-9·77), and receipt of azithromycin plus hydroxychloroquine (vs treatment with neither: 2·93, 1·79-4·79; confounding by indication cannot be excluded). Compared with residence in the US-Northeast, residence in Canada (0·24, 0·07-0·84) or the US-Midwest (0·50, 0·28-0·90) were associated with decreased 30-day all-cause mortality. Race and ethnicity, obesity status, cancer type, type of anticancer therapy, and recent surgery were not associated with mortality.InterpretationAmong patients with cancer and COVID-19, 30-day all-cause mortality was high and associated with general risk factors and risk factors unique to patients with cancer. Longer follow-up is needed to better understand the effect of COVID-19 on outcomes in patients with cancer, including the ability to continue specific cancer treatments.FundingAmerican Cancer Society, National Institutes of Health, and Hope Foundation for Cancer Research.

BackgroundPreterm birth and shorter duration of pregnancy are associated with increased morbidity in neonatal and later life. As the epigenome is known to have an important role during fetal development, we investigated associations between gestational age and blood DNA methylation in children.MethodsWe performed meta-analysis of Illumina's HumanMethylation450-array associations between gestational age and cord blood DNA methylation in 3648 newborns from 17 cohorts without common pregnancy complications, induced delivery or caesarean section. We also explored associations of gestational age with DNA methylation measured at 4-18 years in additional pediatric cohorts. Follow-up analyses of DNA methylation and gene expression correlations were performed in cord blood. DNA methylation profiles were also explored in tissues relevant for gestational age health effects: fetal brain and lung.ResultsWe identified 8899 CpGs in cord blood that were associated with gestational age (range 27-42 weeks), at Bonferroni significance, P

The placenta participates in maternal insulin sensitivity changes during pregnancy; however, mechanisms remain unclear. We investigated associations between maternal insulin sensitivity and placental DNA methylation markers across the genome. We analyzed data from 430 mother-offspring dyads in the Gen3G cohort. All women underwent 75-g oral glucose tolerance tests at ∼26 weeks of gestation; we used glucose and insulin measures to estimate insulin sensitivity (Matsuda index). At delivery, we collected samples from placenta (fetal side) and measured DNA methylation using Illumina EPIC arrays. Using linear regression models to quantify associations at 720,077 cytosine-guanine dinucleotides (CpGs), with adjustment for maternal age, gravidity, smoking, BMI, child sex, and gestational age at delivery, we identified 188 CpG sites where placental DNA methylation was associated with Matsuda index (P < 6.94 × 10-8). Among genes annotated to these 188 CpGs, we found enrichment in targets for miRNAs, in histone modifications, and in parent-of-origin DNA methylation including the H19/MIR675 locus (paternally imprinted). We identified 12 known placenta imprinted genes, including KCNQ1 Mendelian randomization analyses revealed five loci where placenta DNA methylation may causally influence maternal insulin sensitivity, including the maternally imprinted gene DLGAP2. Our results suggest that placental DNA methylation is fundamentally linked to the regulation of maternal insulin sensitivity in pregnancy.

BackgroundEngaging diverse populations in biomedical research, including biospecimen donation, remains a national challenge. This study examined factors associated with an invitation to participate in biomedical research, intent to participate in biomedical research in the future, and participation in biomedical research and biospecimen donation among a diverse, multilingual, community-based sample across 3 distinct geographic areas.MethodsThree National Cancer Institute-designated cancer centers engaged in community partnerships to develop and implement population health assessments, reaching a convenience sample of 4343 participants spanning their respective catchment areas. Data harmonization, multiple imputation, and multivariable logistic modeling were used.ResultsAfrican Americans, Hispanic/Latinos, and other racial minority groups were more likely to be offered opportunities to participate in biomedical research compared to whites. Access to care, history of cancer, educational level, survey language, nativity, and rural residence also influenced opportunity, intent, and actual participation in biomedical research.ConclusionsTraditionally underserved racial and ethnic groups reported heightened opportunity and interest in participating in biomedical research. Well-established community partnerships and long-standing community engagement around biomedical research led to a diverse sample being reached at each site and may in part explain the current study findings. However, this study illustrates an ongoing need to establish trust and diversify biomedical research participation through innovative and tailored approaches. National Cancer Institute-designated cancer centers have the potential to increase opportunities for diverse participation in biomedical research through community partnerships and engagement. Additional work remains to identify and address system-level and individual-level barriers to participation in both clinical trials and biospecimen donation for research.

Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p

Changes in fetal DNA methylation (DNAm) of the leptin (LEP) gene have been associated with exposure to maternal hyperglycemia, but their links with childhood obesity risk are still unclear. We investigated the association between maternal hyperglycemia, placental LEP DNAm (25 5'-C-phosphate-G-3' (CpG) sites), neonatal leptinemia, and adiposity (i.e., BMI and skinfold thickness (ST) (subscapular (SS) + triceps (TR) skinfold measures, and the ratio of SS:TR) at 3-years-old, in 259 mother-child dyads, from Gen3G birth cohort. We conducted multivariate linear analyses adjusted for gestational age at birth, sex of the child, age at follow-up, and cellular heterogeneity. We assessed the causal role of DNAm in the association between maternal glycemia and childhood outcomes, using mediation analysis. We found three CpGs associated with neonatal leptinemia (p ≤ 0.002). Of these, cg05136031 and cg15758240 were also associated with BMI (β = -2.69, p = 0.05) and fat distribution (β = -0.581, p = 0.05) at 3-years-old, respectively. Maternal glycemia was associated with DNAm at cg15758240 (β = -0.01, p = 0.04) and neonatal leptinemia (β = 0.19, p = 0.004). DNAm levels at cg15758240 mediates 0.8% of the association between maternal glycemia and neonatal leptinemia (p < 0.001). Our results support that DNAm regulation of the leptin pathway in response to maternal glycemia might be involved in programming adiposity in childhood.

The aim of this study was to identify placental DNA methylation (DNAm) variations associated with adiposity at 3 years of age. We quantified placental DNAm using the Infinium MethylationEPIC BeadChips. We assessed associations between DNAm at single-CpGs and skinfold thickness using robust linear regression models adjusted for gestational age, child's sex, age at follow-up and cellular heterogeneity. We sought replication of DNAm association with child adiposity in an independent cohort. We quantified placental mRNA levels for annotated gene using qRT-PCR and tested for correlation with DNAm. Lower DNAm at cg22593959 and cg22436429 was associated with higher adiposity (β = -1.18, q = 0.002 and β = -0.82, q = 0.04). The cg22593959 is located in an intergenic region (chr7q31.3), whereas cg22436429 is within the TFAP2E gene (1p34.3). DNAm at cg22593959 and cg22436429 was correlated with mRNA levels at FAM3C (rs = -0.279, p = 0.005) and TFAP2E (rs = 0.216, p = 0.03). In an independent cohort, the association between placental DNAm at cg22593959 and childhood adiposity was of similar strength and direction (β = -3.8 ± 4.1, p = 0.36), yet non-significant. Four genomic regions were also associated with skinfold thickness within FMN1, MAGI2, SKAP2 and BMPR1B genes. We identified placental epigenetic variations associated with adiposity at 3 years of age suggesting that childhood fat accretion patterns might be established during fetal life.

Background: Antibiotics are prescribed to nearly onehalf of patients with viral respiratory tract infections (RTI) in outpatient settings. This use is ineffective and may cause undue harm and excess cost from unnecessary antibiotic exposure. We implemented a multifaceted intervention to address inappropriate antibiotic prescribing for viral RTI. Here, we discuss the impact over 4 years, before and during the SARS-CoV-2 pandemic. Methods: This observational study describes the implementation and initial impact of a multimodal stewardship intervention on inappropriate antibiotic prescribing for viral RTIs in outpatient care settings at a single centre. We tracked the rate of visits for viral RTI as well as antibiotic prescribing for viral RTIs in urgent care, primary care and the emergency department between January 2018 and March 2022. Data were collected 1 year prior to implementation and 3 years after implementation. The primary outcome – the rate of inappropriate antibiotics prescribed for viral RTIs – was described by calendar year (CY) to review changes after the stewardship intervention. Results: In CY2018, the year prior to implementation of targeted RTI antimicrobial stewardship, the rate of inappropriate RTI antibiotics prescribed was 10% in urgent care, 11% in primary care and 18% in the emergency department (ED). During the first CY of the intervention, rates were 8% in urgent care, 10% in primary care and 16% in the ED. In CY2020, the second year of the intervention, inappropriate RTI antibiotics were prescribed in 5% of urgent care and 3% primary care RTI visits and 15% of ED RTI visits. These rates were similar in CY2021 and the first 3 months of CY2022. Over 30,000 visits for RTIs were seen annually in CY2018 and CY2019. Annual RTI visits dropped to 20,222 in CY2020 and 14,172 in CY2021. Conclusion: Although total visits for non-COVID RTIs decreased by approximately 50% during the first 2 years of the SARS-CoV-2 pandemic, an antimicrobial stewardship intervention was associated with decreases in inappropriate antibiotic prescribing for RTIs. This was maintained throughout 2 years of the pandemic. This article is part of the Antibiotic stewardship Special Issue: https://www.drugsincontext.com/special_issues/antimicrobial-stewardship-a-focus-on-the-need-for-moderation

Macronutrient intake, the proportion of calories consumed from carbohydrate, fat, and protein, is an important risk factor for metabolic diseases with significant familial aggregation. Previous studies have identified two genetic loci for macronutrient intake, but incomplete coverage of genetic variation and modest sample sizes have hindered the discovery of additional loci. Here, we expanded the genetic landscape of macronutrient intake, identifying 12 suggestively significant loci (P

Proteins are effector molecules that mediate the functions of genes1,2 and modulate comorbidities3-10, behaviors and drug treatments11. They represent an enormous potential resource for personalized, systemic and data-driven diagnosis, prevention, monitoring and treatment. However, the concept of using plasma proteins for individualized health assessment across many health conditions simultaneously has not been tested. Here, we show that plasma protein expression patterns strongly encode for multiple different health states, future disease risks and lifestyle behaviors. We developed and validated protein-phenotype models for 11 different health indicators: liver fat, kidney filtration, percentage body fat, visceral fat mass, lean body mass, cardiopulmonary fitness, physical activity, alcohol consumption, cigarette smoking, diabetes risk and primary cardiovascular event risk. The analyses were prospectively planned, documented and executed at scale on archived samples and clinical data, with a total of ~85 million protein measurements in 16,894 participants. Our proof-of-concept study demonstrates that protein expression patterns reliably encode for many different health issues, and that large-scale protein scanning12-16 coupled with machine learning is viable for the development and future simultaneous delivery of multiple measures of health. We anticipate that, with further validation and the addition of more protein-phenotype models, this approach could enable a single-source, individualized so-called liquid health check.

Activation of T cells by antigen presenting cells (APCs) initiates their proliferation, cytokine production, and killing of infected or cancerous cells. We and others have shown that T-cell receptors require mechanical forces for triggering, and these forces arise during the interaction of T cells with APCs. Efficient activation of T cells in vitro is necessary for clinical applications. In this paper, we studied the impact of combining mechanical, oscillatory movements provided by an orbital shaker with soft, biocompatible, artificial APCs (aAPCs) of various sizes and amounts of antigen. We showed that these aAPCs allow for testing the strength of signal delivered to T cells, and enabled us to confirm that that absolute amounts of antigen engaged by the T cell are more important for activation than the density of antigen. We also found that when our aAPCs interact with T cells in the context of an oscillatory mechanoenvironment, they roughly double antigenic signal strength, compared to conventional, static culture. Combining these effects, our aAPCs significantly outperformed the commonly used Dynabeads. We finally demonstrated that tuning the signal strength down to a submaximal "sweet spot" allows for robust expansion of induced regulatory T cells. In conclusion, augmenting engineered aAPCs with mechanical forces offers a novel approach for tuning of T-cell activation and differentiation.

A fundamental challenge in neuroscience is to understand what structure in the world is represented in spatially distributed patterns of neural activity from multiple single-trial measurements. This is often accomplished by learning a simple, linear transformations between neural features and features of the sensory stimuli or motor task. While successful in some early sensory processing areas, linear mappings are unlikely to be ideal tools for elucidating nonlinear, hierarchical representations of higher-order brain areas during complex tasks, such as the production of speech by humans. Here, we apply deep networks to predict produced speech syllables from a dataset of high gamma cortical surface electric potentials recorded from human sensorimotor cortex. We find that deep networks had higher decoding prediction accuracy compared to baseline models. Having established that deep networks extract more task relevant information from neural data sets relative to linear models (i.e., higher predictive accuracy), we next sought to demonstrate their utility as a data analysis tool for neuroscience. We first show that deep network's confusions revealed hierarchical latent structure in the neural data, which recapitulated the underlying articulatory nature of speech motor control. We next broadened the frequency features beyond high-gamma and identified a novel high-gamma-to-beta coupling during speech production. Finally, we used deep networks to compare task-relevant information in different neural frequency bands, and found that the high-gamma band contains the vast majority of information relevant for the speech prediction task, with little-to-no additional contribution from lower-frequency amplitudes. Together, these results demonstrate the utility of deep networks as a data analysis tool for basic and applied neuroscience.

Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.

Birthweight is associated with health outcomes across the life course, DNA methylation may be an underlying mechanism. In this meta-analysis of epigenome-wide association studies of 8,825 neonates from 24 birth cohorts in the Pregnancy And Childhood Epigenetics Consortium, we find that DNA methylation in neonatal blood is associated with birthweight at 914 sites, with a difference in birthweight ranging from -183 to 178 grams per 10% increase in methylation (PBonferroni

OBJECTIVE:The aim of the study was to develop recommended techniques and quality assurance metrics for the practice of Digital Anal Rectal Examination (DARE). MATERIALS AND METHODS:The International Anal Neoplasia Society undertook a literature review and, using the AGREE II technique, developed guidelines for performing DARE. RESULTS:A consensus was formed regarding the optimum conditions and characteristics of DARE. Several Quality Assurance metrics were developed. CONCLUSIONS:Digital Anal Rectal Examination is a cheap and potentially universally available technique, which has the potential to facilitate the early diagnosis of anal cancers, when they are most amenable to treatment. These guidelines provide a basis for teaching the technique and may be used as for evaluation research.

ObjectiveFor tissue engineering, there is a need for quantitative methods to map cell density inside three-dimensional (3-D) bioreactors to assess tissue growth over time. The current cell mapping methods in 2-D cultures are based on optical microscopy. However, optical methods fail in 3-D due to increased opacity of the tissue. We present an approach for measuring the density of cells embedded in a hydrogel to generate quantitative maps of cell density in a living, 3-D tissue culture sample.MethodsQuantification of cell density was obtained by calibrating the 1H T2, magnetization transfer (MT) and diffusion-weighted nuclear magnetic resonance (NMR) signals to samples of known cell density. Maps of cell density were generated by weighting NMR images by these parameters post-calibration.ResultsThe highest sensitivity weighting arose from MT experiments, which yielded a limit of detection (LOD) of [Formula: see text] cells/mL/ √{Hz} in a 400 MHz (9.4 T) magnet.ConclusionThis mapping technique provides a noninvasive means of visualizing cell growth within optically opaque bioreactors.SignificanceWe anticipate that such readouts of tissue culture growth will provide valuable feedback for controlled cell growth in bioreactors.

The Brain Imaging Data Structure (BIDS) is a community-driven specification for organizing neuroscience data and metadata with the aim to make datasets more transparent, reusable, and reproducible. Intracranial electroencephalography (iEEG) data offer a unique combination of high spatial and temporal resolution measurements of the living human brain. To improve internal (re)use and external sharing of these unique data, we present a specification for storing and sharing iEEG data: iEEG-BIDS.