A joint NCBI and EMBL-EBI transcript set for clinical genomics and research.

Comprehensive genome annotation is essential to understand the impact of clinically relevant variants. However, the absence of a standard for clinical reporting and browser display complicates the process of consistent interpretation and reporting. To address these challenges, Ensembl/GENCODE1 and RefSeq2 launched a joint initiative, the Matched Annotation from NCBI and EMBL-EBI (MANE) collaboration, to converge on human gene and transcript annotation and to jointly define a high-value set of transcripts and corresponding proteins. Here, we describe the MANE transcript sets for use as universal standards for variant reporting and browser display. The MANE Select set identifies a representative transcript for each human protein-coding gene, whereas the MANE Plus Clinical set provides additional transcripts at loci where the Select transcripts alone are not sufficient to report all currently known clinical variants. Each MANE transcript represents an exact match between the exonic sequences of an Ensembl/GENCODE transcript and its counterpart in RefSeq such that the identifiers can be used synonymously. We have now released MANE Select transcripts for 97% of human protein-coding genes, including all American College of Medical Genetics and Genomics Secondary Findings list v3.0 (ref. 3) genes. MANE transcripts are accessible from major genome browsers and key resources. Widespread adoption of these transcript sets will increase the consistency of reporting, facilitate the exchange of data regardless of the annotation source and help to streamline clinical interpretation.

An adeno-associated viral labeling approach to visualize the meso- and microanatomy of mechanosensory afferents and autonomic innervation of the rat urinary bladder.

The urinary bladder is supplied by a rich network of sensory and autonomic axons, commonly visualized by immunolabeling for neural markers. This approach demonstrates overall network patterning but is less suited to understanding the structure of individual motor and sensory terminals within these complex plexuses. There is a further limitation visualizing the lightly myelinated (A-delta) class of sensory axons that provides the primary mechanosensory drive for initiation of voiding. Whereas most unmyelinated sensory axons can be revealed by immunolabeling for specific neuropeptides, to date no unique neural marker has been identified to immunohistochemically label myelinated visceral afferents. We aimed to establish a non-surgical method to visualize and map myelinated afferents in the bladder in rats. We found that in rats, the adeno-associated virus (AAV), AAV-PHP.S, which shows a high tropism for the peripheral nervous system, primarily transduced myelinated dorsal root ganglion neurons, enabling us to identify the structure and regional distribution of myelinated (mechanosensory) axon endings within the muscle and lamina propria of the bladder. We further identified the projection of myelinated afferents within the pelvic nerve and lumbosacral spinal cord. A minority of noradrenergic and cholinergic neurons in pelvic ganglia were transduced, enabling visualization and regional mapping of both autonomic and sensory axon endings within the bladder. Our study identified a sparse labeling approach for investigating myelinated sensory and autonomic axon endings within the bladder and provides new insights into the nerve-bladder interface.

The Importance of Equity Value Judgments and Estimator-Estimand Alignment in Measuring Disparity and Identifying Targets to Reduce Disparity.

The choice of which covariates to adjust for (so-called allowability designation (AD)) in health disparity measurements reflects value judgments about inequitable versus equitable sources of health differences, which is paramount for making inferences about disparity. Yet, many off-the-shelf estimators used in health disparity research are not designed with equity considerations in mind, and they imply different ADs. We demonstrated the practical importance of incorporating equity concerns in disparity measurements through simulations, motivated by the example of reducing racial disparities in hypertension control via interventions on disparities in treatment intensification. Seven causal decomposition estimators, each with a particular AD (with respect to disparities in hypertension control and treatment intensification), were considered to estimate the observed outcome disparity and the reduced/residual disparity under the intervention. We explored the implications for bias of the mismatch between equity concerns and the AD in the estimator under various causal structures (through altering racial differences in covariates or the confounding mechanism). The estimator that correctly reflects equity concerns performed well under all scenarios considered, whereas the other estimators were shown to have the risk of yielding large biases in certain scenarios, depending on the interaction between their ADs and the specific causal structure.

Evaluating Effects of Multilevel Interventions on Disparity in Health and Healthcare Decisions.

In this paper, we introduce an analytic approach for assessing effects of multilevel interventions on disparity in health outcomes and health-related decision outcomes (i.e., a treatment decision made by a healthcare provider). We outline common challenges that are encountered in interventional health disparity research, including issues of effect scale and interpretation, choice of covariates for adjustment and its impact on effect magnitude, and the methodological challenges involved with studying decision-based outcomes. To address these challenges, we introduce total effects of interventions on disparity for the entire sample and the treated sample, and corresponding direct effects that are relevant for decision-based outcomes. We provide weighting and g-computation estimators in the presence of study attrition and sketch a simulation-based procedure for sample size determinations based on precision (e.g., confidence interval width). We validate our proposed methods through a brief simulation study and apply our approach to evaluate the RICH LIFE intervention, a multilevel healthcare intervention designed to reduce racial and ethnic disparities in hypertension control.

Comparative effectiveness of omalizumab, mepolizumab, and dupilumab in asthma: A target trial emulation.

BACKGROUND: Multiple mAbs are currently approved for the treatment of asthma. However, there is limited evidence on their comparative effectiveness. OBJECTIVE: Our aim was to compare the effectiveness of omalizumab, mepolizumab, and dupilumab in individuals with moderate-to-severe asthma. METHODS: We emulated a hypothetical randomized trial using electronic health records from a large US-based academic health care system. Participants aged 18 years or older with baseline IgE levels between 30 and 700 IU/mL and peripheral eosinophil counts of at least 150 cells/µL were eligible for study inclusion. The study period extended from March 2016 to August 2021. Outcomes included the incidence of asthma-related exacerbations and change in baseline FEV1 value over 12 months of follow-up. RESULTS: In all, 68 individuals receiving dupilumab, 68 receiving omalizumab, and 65 receiving mepolizumab met the inclusion criteria. Over 12 months of follow-up, 31 exacerbations occurred over 68 person years (0.46 exacerbations per person year) in the dupilumab group, 63 over 68 person years (0.93 per person year) in the omalizumab group, and 86 over 65 person years (1.32 per person year) in the mepolizumab group (adjusted incidence rate ratios: dupilumab vs mepolizumab, 0.28 [95% CI = 0.09-0.84]; dupilumab vs omalizumab, 0.36 [95% CI = 0.12-1.09]; and omalizumab vs mepolizumab, 0.78 [95% CI = 0.32-1.91]). The differences in the change in FEV1 comparing patients who received the different biologics were as follows: 0.11 L (95% CI = -0.003 to 0.222 L) for dupilumab versus mepolizumab, 0.082 L (95% CI -0.040 to 0.204 L) for dupilumab versus omalizumab, and 0.026 L (95% CI -0.083 to 0.140 L) for omalizumab versus mepolizumab. CONCLUSIONS: Among patients with asthma and eosinophil counts of at least 150 cells/µL and IgE levels of 30 to 700 kU/L, dupilumab was associated with greater improvements in exacerbation and FEV1 value than omalizumab and mepolizumab.

Critical interactions between race and the highly granular area deprivation index in liver transplant evaluation.

Neighborhood socioeconomic deprivation may have important implications on disparities in liver transplant (LT) evaluation. In this retrospective cohort study, we constructed a novel dataset by linking individual patient-level data with the highly granular Area Deprivation Index (ADI), which is advantageous over other neighborhood measures due to: specificity of Census Block-Group (versus Census Tract, Zip code), scoring, and robust variables. Our cohort included 1377 adults referred to our center for LT evaluation 8/1/2016-12/31/2019. Using modified Poisson regression, we tested for effect measure modification of the association between neighborhood socioeconomic status (nSES) and LT evaluation outcomes (listing, initiating evaluation, and death) by race and ethnicity. Compared to patients with high nSES, those with low nSES were at higher risk of not being listed (aRR = 1.14; 95%CI 1.05-1.22; p < .001), of not initiating evaluation post-referral (aRR = 1.20; 95%CI 1.01-1.42; p = .03) and of dying without initiating evaluation (aRR = 1.55; 95%CI 1.09-2.2; p = .01). While White patients with low nSES had similar rates of listing compared to White patients with high nSES (aRR = 1.06; 95%CI .96-1.17; p = .25), Underrepresented patients from neighborhoods with low nSES incurred 31% higher risk of not being listed compared to Underrepresented patients from neighborhoods with high nSES (aRR = 1.31; 95%CI 1.12-1.5; p < .001). Interventions addressing neighborhood deprivation may not only benefit patients with low nSES but may address racial and ethnic inequities.

An intersectional analysis of historical and contemporary structural racism on non-fatal shootings in Baltimore, Maryland.

Introduction Non-fatal shooting rates vary tremendously within cities in the USA. Factors related to structural racism (both historical and contemporary) could help explain differences in non-fatal shooting rates at the neighbourhood level. Most research assessing the relationship between structural racism and firearm violence only includes one dimension of structural racism. Our study uses an intersectional approach to examine how the interaction of two forms of structural racism is associated with spatial non-fatal shooting disparities in Baltimore, Maryland. Methods We present three additive interaction measures to describe the relationship between historical redlining and contemporary racialized economic segregation on neighbourhood-level non-fatal shootings. Results Our findings revealed that sustained disadvantage census tracts (tracts that experience contemporary socioeconomic disadvantage and were historically redlined) have the highest burden of non-fatal shootings. Sustained disadvantage tracts had on average 24 more non-fatal shootings a year per 10 000 residents compared with similarly populated sustained advantage tracts (tracts that experience contemporary socioeconomic advantage and were not historically redlined). Moreover, we found that between 2015 and 2019, the interaction between redlining and racialized economic segregation explained over one-third of non-fatal shootings (approximately 650 shootings) in sustained disadvantage tracts. Conclusion These findings suggest that the intersection of historical and contemporary structural racism is a fundamental cause of firearm violence inequities in Baltimore. Intersectionality can advance injury prevention research and practice by (1) serving as an analytical tool to expose inequities in injury-related outcomes and (2) informing the development and implementation of injury prevention interventions and policies that prioritise health equity and racial justice.

Comparative efficacy of mepolizumab, benralizumab, and dupilumab in eosinophilic asthma: A Bayesian network meta-analysis.

BACKGROUND: The comparative safety and efficacy of the biologics currently approved for asthma are unclear. OBJECTIVE: We compared the safety and efficacy of mepolizumab, benralizumab, and dupilumab in individuals with severe eosinophilic asthma. METHODS: We performed a systematic review of peer-reviewed literature published 2000 to 2021. We studied Bayesian network meta-analyses of exacerbation rates, prebronchodilator FEV1, the Asthma Control Questionnaire, and serious adverse events in individuals with eosinophilic asthma. RESULTS: Eight randomized clinical trials (n = 6461) were identified. We found in individuals with eosinophils ≥300 cells/µL the following: in reducing exacerbation rates compared to placebo: dupilumab (risk ratio [RR], 0.32; 95% credible interval [CI], 0.23 to 0.45), mepolizumab (RR, 0.37; 95% CI, 0.30 to 0.45), and benralizumab (RR, 0.49; 95% CI, 0.43 to 0.55); in improving FEV1: dupilumab (mean difference in milliliters [MD] 230; 95% CI, 160 to 300), benralizumab (MD, 150; 95% CI, 100 to 200), and mepolizumab (MD, 150; 95% CI, 66 to 220); and in reducing Asthma Control Questionnaire scores: mepolizumab (MD, -0.63; 95% CI, -0.81 to -0.45), dupilumab (MD, -0.48; 95% CI, -0.83 to -0.14), and benralizumab (MD, -0.32; 95% CI, -0.43 to -0.21). In individuals with eosinophils 150-299 cells/µL, benralizumab (RR, 0.62; 95% CI, 0.52 to 0.73) and dupilumab (RR, 0.60; 95% CI, 0.38 to 0.95) were associated with lower exacerbation rates; and only benralizumab (MD, 81; 95% CI, 8 to 150) significantly improved FEV1. These differences were minimal compared to clinically important thresholds. For serious adverse events in the overall population, mepolizumab (odds ratio, 0.67; 95% CI, 0.48 to 0.92) and benralizumab (odds ratio, 0.74; 95% CI, 0.59 to 0.93) were associated with lower odds of a serious adverse event, while dupilumab was not different from placebo (odds ratio, 1.0; 95% CI, 0.74 to 1.4). CONCLUSION: There are minimal differences in the efficacy and safety of mepolizumab, benralizumab, and dupilumab in eosinophilic asthma.

Recommendations for Using Causal Diagrams to Study Racial Health Disparities.

There have been calls for race to be denounced as a biological variable and for a greater focus on racism, instead of solely race, when studying racial health disparities in the United States. These calls are grounded in extensive scholarship and the rationale that race is not a biological variable, but instead socially constructed, and that structural/institutional racism is a root cause of race-related health disparities. However, there remains a lack of clear guidance for how best to incorporate these assertions about race and racism into tools, such as causal diagrams, that are commonly used by epidemiologists to study population health. We provide clear recommendations for using causal diagrams to study racial health disparities that were informed by these calls. These recommendations consider a health disparity to be a difference in a health outcome that is related to social, environmental, or economic disadvantage. We present simplified causal diagrams to illustrate how to implement our recommendations. These diagrams can be modified based on the health outcome and hypotheses, or for other group-based differences in health also rooted in disadvantage (e.g., gender). Implementing our recommendations may lead to the publication of more rigorous and informative studies of racial health disparities.

Female reproductive skew exacerbates the extinction risk from poaching in the eastern black rhino.

Variation in individual demographic rates can have large consequences for populations. Female reproductive skew is an example of structured demographic heterogeneity where females have intrinsic qualities that make them more or less likely to breed. The consequences of reproductive skew for population dynamics are poorly understood in non-cooperatively breeding mammals, especially when coupled with other drivers such as poaching. We address this knowledge gap with population viability analyses using an age-specific, female-only, individual-based, stochastic population model built with long-term data for three Kenyan populations of the Critically Endangered eastern black rhino (Diceros bicornis michaeli). There was substantial reproductive skew, with a high proportion of females not breeding or doing so at very low rates. This had a large impact on the projected population growth rate for the smaller population on Ol Jogi. Moreover, including female reproductive skew exacerbates the effects of poaching, increasing the probability of extinction by approximately 70% under a simulated poaching pressure of 5% offtake per year. Tackling the effects of reproductive skew depends on whether it is mediated by habitat or social factors, with potential strategies including habitat and biological management respectively. Investigating and tackling reproductive skew in other species requires long-term, individual-level data collection.

Multicenter study of racial and ethnic inequities in liver transplantation evaluation: Understanding mechanisms and identifying solutions.

Racial and ethnic disparities persist in access to the liver transplantation (LT) waiting list; however, there is limited knowledge about underlying system-level factors that may be responsible for these disparities. Given the complex nature of LT candidate evaluation, a human factors and systems engineering approach may provide insights. We recruited participants from the LT teams (coordinators, advanced practice providers, physicians, social workers, dieticians, pharmacists, leadership) at two major LT centers. From December 2020 to July 2021, we performed ethnographic observations (participant-patient appointments, committee meetings) and semistructured interviews (N = 54 interviews, 49 observation hours). Based on findings from this multicenter, multimethod qualitative study combined with the Systems Engineering Initiative for Patient Safety 2.0 (a human factors and systems engineering model for health care), we created a conceptual framework describing how transplant work system characteristics and other external factors may improve equity in the LT evaluation process. Participant perceptions about listing disparities described external factors (e.g., structural racism, ambiguous national guidelines, national quality metrics) that permeate the LT evaluation process. Mechanisms identified included minimal transplant team diversity, implicit bias, and interpersonal racism. A lack of resources was a common theme, such as social workers, transportation assistance, non-English-language materials, and time (e.g., more time for education for patients with health literacy concerns). Because of the minimal data collection or center feedback about disparities, participants felt uncomfortable with and unadaptable to unwanted outcomes, which perpetuate disparities. We proposed transplant center-level solutions (i.e., including but not limited to training of staff on health equity) to modifiable barriers in the clinical work system that could help patient navigation, reduce disparities, and improve access to care. Our findings call for an urgent need for transplant centers, national societies, and policy makers to focus efforts on improving equity (tailored, patient-centered resources) using the science of human factors and systems engineering.

Flexible propensity score estimation strategies for clustered data in observational studies.

Existing studies have suggested superior performance of nonparametric machine learning over logistic regression for propensity score estimation. However, it is unclear whether the advantages of nonparametric propensity score modeling are carried to settings where there is clustering of individuals, especially when there is unmeasured cluster-level confounding. In this work we examined the performance of logistic regression (all main effects), Bayesian additive regression trees and generalized boosted modeling for propensity score weighting in clustered settings, with the clustering being accounted for by including either cluster indicators or random intercepts. We simulated data for three hypothetical observational studies of varying sample and cluster sizes. Confounders were generated at both levels, including a cluster-level confounder that is unobserved in the analyses. A binary treatment and a continuous outcome were generated based on seven scenarios with varying relationships between the treatment and confounders (linear and additive, nonlinear/nonadditive, nonadditive with the unobserved cluster-level confounder). Results suggest that when the sample and cluster sizes are large, nonparametric propensity score estimation may provide better covariate balance, bias reduction, and 95% confidence interval coverage, regardless of the degree of nonlinearity or nonadditivity in the true propensity score model. When the sample or cluster sizes are small, however, nonparametric approaches may become more vulnerable to unmeasured cluster-level confounding and thus may not be a better alternative to multilevel logistic regression. We applied the methods to the National Longitudinal Study of Adolescent to Adult Health data, estimating the effect of team sports participation during adolescence on adulthood depressive symptoms.

Sex-specific links between the social landscape and faecal glucocorticoid metabolites in semi-captive Asian elephants.

Although social behaviour is common in group-living mammals, our understanding of its mechanisms in long-lived animals is largely based on studies in human and non-human primates. There are health and fitness benefits associated with strong social ties, including increased life span, reproductive success, and lower disease risk, which are attributed to the proximate effects of lowered circulating glucocorticoid hormones. However, to deepen our understanding of health-social dynamics, we must explore species beyond the primate order. Here, using Asian elephants as a model species, we combine social data generated from semi-captive timber elephants in Myanmar with measurements of faecal glucocorticoid metabolite (FGM) concentrations. These data enable a "natural experiment" because individuals live in work groups with different demographic compositions. We examine sex-specific FGM concentrations for four different aspects of an individuals' social world: general sociality, work group size, sex ratio and the presence of immatures (<5 years) within the work group. Males experienced lower FGM concentrations when engaged in more social behaviours and residing in female-biased work groups. Surprisingly, females only exhibited lower FGM concentrations when residing with calves. Together, our findings highlight the importance of sociality on individual physiological function among elephants, which may have broad implications for the benefits of social interactions among mammals.

Scaling Interventions to Manage Chronic Disease: Innovative Methods at the Intersection of Health Policy Research and Implementation Science.

Policy implementation is a key component of scaling effective chronic disease prevention and management interventions. Policy can support scale-up by mandating or incentivizing intervention adoption, but enacting a policy is only the first step. Fully implementing a policy designed to facilitate implementation of health interventions often requires a range of accompanying implementation structures, like health IT systems, and implementation strategies, like training. Decision makers need to know what policies can support intervention adoption and how to implement those policies, but to date research on policy implementation is limited and innovative methodological approaches are needed. In December 2021, the Johns Hopkins ALACRITY Center for Health and Longevity in Mental Illness and the Johns Hopkins Center for Mental Health and Addiction Policy convened a forum of research experts to discuss approaches for studying policy implementation. In this report, we summarize the ideas that came out of the forum. First, we describe a motivating example focused on an Affordable Care Act Medicaid health home waiver policy used by some US states to support scale-up of an evidence-based integrated care model shown in clinical trials to improve cardiovascular care for people with serious mental illness. Second, we define key policy implementation components including structures, strategies, and outcomes. Third, we provide an overview of descriptive, predictive and associational, and causal approaches that can be used to study policy implementation. We conclude with discussion of priorities for methodological innovations in policy implementation research, with three key areas identified by forum experts: effect modification methods for making causal inferences about how policies' effects on outcomes vary based on implementation structures/strategies; causal mediation approaches for studying policy implementation mechanisms; and characterizing uncertainty in systems science models. We conclude with discussion of overarching methods considerations for studying policy implementation, including measurement of policy implementation, strategies for studying the role of context in policy implementation, and the importance of considering when establishing causality is the goal of policy implementation research.

Enhanced method to select human oogonial stem cells for fertility research.

Alternative methods to obtain mature oocytes are still needed for women with premature ovarian failure (POF). Oogonial stem cells (OSCs), found in adult ovaries, have provided insight into potential paths to treating infertility. Previously, the DDX4 antibody marker alone was utilized to isolate OSCs; however, extensive debate over its location in OSCs versus resulting oocytes (transmembrane or intracytoplasmic) has raised doubt about the identity of these cells. Separate groups, however, have efficiently isolated OSCs using another antibody marker Ifitm3 which is consistently recognized to be transmembrane in location. We hypothesized that by using anti-DDX4 and anti-IFITM3 antibodies, in combination, with MACS, we would improve the yield of isolated OSCs versus using anti-DDX4 antibodies alone. Our study supports earlier findings of OSCs in ovaries during the entire female lifespan: from reproductive age through post-menopausal age. MACS sorting ovarian cells using a the two-marker combination yielded a ~ twofold higher percentage of OSCs from a given mass of ovarian tissue compared to existing single marker methods while minimizing the debate surrounding germline marker selection. During in vitro culture, isolated cells retained the germline phenotype expression of DDX4 and IFITM3 as confirmed by gene expression analysis, demonstrated characteristic germline stem cell self-assembly into embryoid bodies, and formed > 40 µm "oocyte-like" structures that expressed the early oocyte markers GDF9, DAZL, and ZP1. This enhanced and novel method is clinically significant as it could be utilized in the future to more efficiently produce mature, secondary oocytes, for use with IVF/ICSI to treat POF patients.

Optimized culture system to maximize ovarian cell growth and functionality in vitro.

Ovaries are the primary physiological source of female sex hormones, which play a crucial role in maintaining ovarian cycle, determining secondary sexual characteristics and preparing the endometrium for implantation. In vitro follicle engineering has been used to investigate follicle development, including ovarian hormone production and gamete maturation. To engineer functional follicles, culture and expansion of the primary ovarian cells are essential. However, the phenotypic and functional characteristics of primary ovarian cells are often lost during culture. The objective of this study is to develop an optimized culture system for maintaining ovarian cell growth and functionality. Granulosa cells (GCs) and theca cells (TCs) were isolated from female rats. The addition of follicle-stimulating hormone (FSH) or luteinizing hormone (LH) to the basal culture media significantly enhanced the secretion of estradiol from GCs and androstenedione from TCs. Serum concentrations of 5% and 10% had a similar role in promoting ovarian cell expansion and secretion of estradiol and androstenedione hormones from both types of cells. Growth differentiation factor 9 (GDF9), bone morphogenic protein 15 (BMP15), BMP7 and basic fibroblast growth factor (bFGF) enhanced GC proliferation and estradiol production, respectively. Among them, the effect of bFGF was most significant. bFGF also enhanced TC proliferation. When GCs and TCs were cultured in 5% serum, gonadotropin and bFGF-containing medium, they proliferated exponentially throughout the culture period of up to 40 days while maintaining their functional characteristics. Taken together, these results indicate that our medium formula is optimal for maximizing proliferation of functionally differentiated ovarian cells.

Meaningful Causal Decompositions in Health Equity Research: Definition, Identification, and Estimation Through a Weighting Framework.

Causal decomposition analyses can help build the evidence base for interventions that address health disparities (inequities). They ask how disparities in outcomes may change under hypothetical intervention. Through study design and assumptions, they can rule out alternate explanations such as confounding, selection bias, and measurement error, thereby identifying potential targets for intervention. Unfortunately, the literature on causal decomposition analysis and related methods have largely ignored equity concerns that actual interventionists would respect, limiting their relevance and practical value. This article addresses these concerns by explicitly considering what covariates the outcome disparity and hypothetical intervention adjust for (so-called allowable covariates) and the equity value judgments these choices convey, drawing from the bioethics, biostatistics, epidemiology, and health services research literatures. From this discussion, we generalize decomposition estimands and formulae to incorporate allowable covariate sets (and thereby reflect equity choices) while still allowing for adjustment of non-allowable covariates needed to satisfy causal assumptions. For these general formulae, we provide weighting-based estimators based on adaptations of ratio-of-mediator-probability and inverse-odds-ratio weighting. We discuss when these estimators reduce to already used estimators under certain equity value judgments, and a novel adaptation under other judgments.

Meta-analysis of Total Effect Decomposition in the Presence of Multiple Mediators: The Example of Schizophrenia Treatment.

BACKGROUND: Causal mediation analysis addresses mechanistic questions by decomposing and quantifying effects operating through different pathways. Because most individual studies are underpowered to detect mediating effects, we outlined a parametric approach to meta-analyzing causal mediation and interaction analyses with multiple mediators, compared it with a bootstrap-based alternative, and discussed its limitations. METHODS: We employed fixed- and random-effects multivariate meta-analyses to integrate evidence on treatment-mediators and mediators-outcome associations across trials. We estimated path-specific effects as functions of meta-analyzed regression coefficients; we obtained standard errors using the delta method. We evaluated the performance of this approach in simulations and applied it to assess the mediating roles of positive symptoms of schizophrenia and weight gain in the treatment effect of paliperidone ER on negative symptoms across four efficacy trials. RESULTS: Both simulations and the application showed that the meta-analytic approaches increased statistical power. In the application, we observed substantial mediating effects of positive symptoms (proportions mediated from fixed-effects meta-analysis: (Equation is included in full-text article.)). Weight gain may have beneficial mediating effects; however, such benefit may disappear at high doses when metabolic side effects were excessive. CONCLUSIONS: Meta-analyzing causal mediation analysis combines evidence from multiple sources and improves power. Targeting positive symptoms may be an effective way to reduce negative symptoms that are challenging to treat. Future work should focus on extending the existing methods to allow for more flexible modeling of mediation.

Oxygen limitation fails to explain upper chronic thermal limits and the temperature size rule in mayflies.

An inability to adequately meet tissue oxygen demands has been proposed as an important factor setting upper thermal limits in ectothermic invertebrates (especially aquatic species) as well as explaining the observed decline in adult size with increased rearing temperature during the immature stages (a phenomenon known as the temperature size rule, or TSR). We tested this by rearing three aquatic insects (the mayflies Neocloeon triangulifer and two species of the Cloeon dipterum complex) through their entire larval life under a range of temperature and oxygen concentrations. Hyperoxia did not extend upper thermal limits, nor did it prevent the loss of size or fertility experienced near upper chronic thermal limits. At moderate temperatures, the TSR pattern was observed under conditions of hyperoxia, normoxia and hypoxia, suggesting little or no influence of oxygen on this trend. However, for a given rearing temperature, adults were smaller and less fecund under hypoxia as a result of a lowering of growth rates. These mayflies greatly increased the size of their gills in response to lower dissolved oxygen concentrations but not under oxygen-saturated conditions over a temperature range yielding the classic TSR response. Using ommatidium diameter as a proxy for cell size, we found the classic TSR pattern observed under moderate temperature conditions was due primarily to a change in the number of cells rather than cell size. We conclude overall that a failure to meet tissue oxygen demands is not a viable hypothesis for explaining either the chronic thermal limit or TSR pattern in these species.

The elephant in the family: Costs and benefits of elder siblings on younger offspring life-history trajectory in a matrilineal mammal.

Many mammals grow up with siblings, and interactions between them can influence offspring phenotype and fitness. Among these interactions, sibling competition between different-age offspring should lead to reproductive and survival costs on the younger sibling, while sibling cooperation should improve younger sibling's reproductive potential and survival. However, little is known about the consequences of sibling effects on younger offspring life-history trajectory, especially in long-lived mammals. We take advantage of a large, multigenerational demographic dataset from semi-captive Asian elephants to investigate how the presence and sex of elder siblings influence the sex, survival until 5 years old, body condition, reproductive success (i.e. age at first reproduction and lifetime reproductive success) and long-term survival of subsequent offspring. We find that elder siblings have heterogeneous effects on subsequent offspring life-history traits depending on their presence, their sex and the sex of the subsequent offspring (named focal calf). Overall, the presence of an elder sibling (either sex) strongly increased focal calf long-term survival (either sex) compared to sibling absence. However, elder sisters had higher impact on the focal sibling than elder brothers. Focal females born after a female display higher long-term survival, and decreased age at first reproduction when raised together with an elder sister rather than a brother. Focal males born after a female rather than a male showed lower survival but higher body weight when both were raised together. We did not detect any sibling effects on the sex of the focal calf sex, survival until 5 years old and lifetime reproductive success. Our results highlight the general complexity of sibling effects, but broadly that elder siblings can influence the life-history trajectory of subsequent offspring. We also stress the importance of considering all life stages when evaluating sibling effects on life trajectories.

Denombreux mammifères grandissent en fratrie, et les interactions au sein de lafratrie peuvent influencer le phénotype et la valeur sélective des jeunes.Parmi ces interactions, la compétition entre frères et sœurs d'âges différentspeut entraîner des coûts de reproduction et de survie pour le/la plus jeune,tandis que les interactions coopératives améliorent la reproduction et lasurvie du/de la plus jeune. Cependant, nous avons encore peu de connaissancessur l'influence de la fratrie sur la trajectoire de vie des frères et sœursplus jeunes, en particulier chez les mammifères longévifs. Grâce àun jeu de données démographique multigénérationnel d'éléphants d'Asiesemi-captifs, nous avons pu étudier comment la présence d'un frère aînéou d'une sœur aînée influence le sexe, la survie jusqu'à l'âge de cinqans, la masse corporelle, la reproduction (i.e. l'âge de première reproductionet le succès reproductif sur toute la vie) et la survie à long terme du jeunesuivant. Nousobservons que les frères et sœurs aînés ont des effets hétérogènes sur lestraits d'histoire de vie du jeune suivant et ce, en fonction de leur présence,et du sexe du jeune suivant (appelé focal). Dansl'ensemble, la présence d'un frère aîné oud'une sœur aînée augmente fortement la survie à long terme du jeune focal parrapport à leur absence. Cependant, il est à noter que les sœurs aînées ont unimpact plus important que les frères ainés sur le frère focal. Les femellesfocales présentent une survie à long terme plus élevée et un âge de premièrereproduction plus précoce lorsqu'elles sont élevées avec une sœur aînée plutôtqu'un frère. Les mâles focaux élevés avec une grande sœur plutôt qu'un grandfrère présentent une survie plus faible mais un poids corporel plus élevé. Nousn'avons détecté aucun effet des frères aînés ou sœurs aînées sur le sexe, la survie jusqu'àl'âge de cinq ans et le succès reproducteur sur toute la vie du jeune focal. Nosrésultats mettent en évidence la complexité des effets de la fratrie et, lefait que les frères et sœurs plus âgés peuvent influencer la trajectoire ducycle de vie des jeunes suivant. Nous soulignons également l'importance deconsidérer toutes les étapes de la vie lors de l'évaluation des effets de lafratrie sur les trajectoires de vie.