Causal mediation analysis aims to investigate how an intermediary factor, called a mediator, regulates the causal effect of a treatment on an outcome. With the increasing availability of measurements on a large number of potential mediators, methods for selecting important mediators have been proposed. However, these methods often assume the absence of unmeasured mediator-outcome confounding. We allow for such confounding in a linear structural equation model for the outcome and further propose an approach to tackle the mediator selection issue. To achieve this, we firstly identify causal parameters by constructing a pseudo proxy variable for unmeasured confounding. Leveraging this proxy variable, we propose a partially penalized method to identify mediators affecting the outcome. The resultant estimates are consistent, and the estimates of nonzero parameters are asymptotically normal. Motivated by these results, we introduce a two-step procedure to consistently select active mediation pathways, eliminating the need to test composite null hypotheses for each mediator that are commonly required by traditional methods. Simulation studies demonstrate the superior performance of our approach compared to existing methods. Finally, we apply our approach to genomic data, identifying gene expressions that potentially mediate the impact of a genetic variant on mouse obesity.

This research note investigates citation bias using probabilities of zero citations, total citations, and citations per year since publication from Web of Science, Scopus, and Google Scholar for al...

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury1–4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries5. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction. A multi-ancestry meta-regression study analyses diverse genome-wide association studies and genome loci associated with tobacco and alcohol use.

<p>Immune-mediated thrombotic thrombocytopenic purpura (iTTP) is characterized by recurring episodes of thrombotic microangiopathy causing ischemic organ impairment. Blacks are overrepresented in iTTP cohorts in the United States but racial disparities in iTTP outcomes and response to therapy have not been studied. Using the United States Thrombotic Microangiopathy (USTMA) Consortium iTTP Registry, we evaluated the impact of race on mortality and relapse-free survival (RFS) in confirmed iTTP in the US from 1995 to 2020. We separately examined the impact of rituximab therapy and presentation with newly diagnosed (de novo) or relapsed iTTP on RFS by race. 645 participants with 1308 iTTP episodes were available for analysis. Acute iTTP mortality did not differ by race. When all episodes of iTTP were included, Black race was associated with shorter RFS [hazard ratio (HR) of 1.60 (95% CI 1.16-2.21)]; the addition of rituximab to corticosteroids improved RFS in White [HR 0.37 (95% CI 0.18-0.73)] but not Black patients [HR 0.96 (95% CI 0.71-1.31)]. In de novo iTTP, rituximab delayed relapse, but Blacks had shorter RFS than Whites regardless of treatment. In relapsed iTTP, rituximab significantly improved RFS in White but not Black patients. Race affects overall relapse risk and response to rituximab in iTTP. Black patients may require closer monitoring, earlier retreatment, and alternative immunosuppression following rituximab treatment. How race, racism, and the social determinants of health contribute to the disparity in relapse risk in iTTP deserve further study.</p>

Introduction: Obstructive sleep apnea (OSA) is a common disorder associated with increased risk for cardiovascular disease, diabetes, and premature mortality. There is strong clinical and epi-demio...

There is ample literature on interventions to reduce human immunodeficiency virus (HIV) stigma and discrimination and extant theory around intersectionality. However, the integration of intersectionality into the design and implementation of stigma reduction interventions is nascent. Using Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we reviewed 23 studies from six countries to examine the state of the evidence on interventions to reduce intersectional stigma in the context of HIV. Thirteen studies made explicit reference to intersectionality, 11 of which addressed all three stigma domains: drivers, facilitators, and manifestations. Most interventions were multilevel and multistrategy, yet only five included a structural component. Thirteen studies focused on four or more intersections (e.g., HIV, race, sexual identity, gender), five on three intersections, and five on two intersections. Twenty studies (87%) reported medium ( n = 5) to high ( n = 15) community engagement. The majority of studies (19/23) assessed HIV-related (e.g., antiretroviral therapy [ART] adherence) and/or empowerment-based outcomes (e.g., self-esteem, coping), with 91% reporting some positive intervention effects. Of 13 studies that measured stigma outcomes, only seven (54%) documented some improvement in the stigma measures assessed. Our review revealed a range of sophisticated, intersectionality-informed interventions that were mostly successful at improving HIV, sexual health, and empowerment-based outcomes, but less successful at reducing the aspects of stigma measured. Future research should encompass wider geographical regions, use validated measures of intersectional stigma, and test structural interventions and approaches that challenge the systems of power and oppression that fuel stigma, inequality, and poor health outcomes among multiply marginalized populations. (PsycInfo Database Record (c) 2022 APA, all rights reserved) (Source: journal abstract)

Improvement of antiretroviral therapy (ART) regimen switching practices and implementation of pretreatment drug resistance (PDR) testing are two potential approaches to improve health outcomes for children living with HIV. We developed a microsimulation model of disease progression and treatment focused on children with perinatally acquired HIV in sub-Saharan Africa who initiate ART at 3 years of age. We evaluated the cost-effectiveness of diagnostic-based strategies (improved switching and PDR testing), over a 10-year time horizon, in settings without and with pediatric dolutegravir (DTG) availability as first-line ART. The improved switching strategy increases the probability of switching to second-line ART when virologic failure is diagnosed through viral load testing. The PDR testing strategy involves a one-time PDR test prior to ART initiation to guide choice of initial regimen. When DTG is not available, PDR testing is dominated by the improved switching strategy, which has an incremental cost-effectiveness ratio (ICER) of USD 579/life-year gained (LY), relative to the status quo. If DTG is available, improved switching has a similar ICER (USD 591/LY) relative to the DTG status quo. Even when substantial financial investment is needed to achieve improved regimen switching practices, the improved switching strategy still has the potential to be cost-effective in a wide range of sub-Saharan African countries. Our analysis highlights the importance of strengthening existing laboratory monitoring systems to improve the health of children living with HIV.

Investigations of networked public spheres often examine the structures of online platforms by studying users' interactions. These works suggest that users' interactions can lead to cyberbalkani-zation when interlocutors form homophilous communities that typically have few connections to others with opposing ideologies. Yet, rather than assuming communities are isolated, this study examines community-level interactions to reveal how communities in online discourses are more interdependent than previously theorized. Specifically, we examine how such interactions influence the evolution of topics overtime in source and target communities. Our analysis found that (a) the size of a source community (the community that initiates interactions) and a target community (the community that receives interactions), (b) the stability of the source community, and (c) the volume of mentions from a source community to a target community predicts the level of influence one community has on another's discussion topics. We argue this has significant theoretical and practical implications. Lay Summary Political discussions online, especially those in the United States, seem to range between harmonious discussions of likeminded people and heated debates that end with few, if any, who have changed their minds. Researchers have often examined these balkanized/polarized situations by studying online communities as isolated echo chambers of opinion. Our study focuses on the interactions between online communities who have different worldviews. We examine communities engaged in the global refugee crisis. We consider how the inter-community interactions influence the agenda of the respective communities. Our longitudinal analysis on the one hand

Background: Body mass index (BMI), a well-known risk factor for poor cardiovascular outcomes, is associated with differential DNA methylation (DNAm). Similarly, metabolic health has also been associated with changes in DNAm. It is unclear how overall metabolic health outside of BMI may modify the relationship between BMI and methylation profiles, and what consequences this may have on downstream cardiovascular disease. The purpose of this study was to identify cytosine-phosphate-guanine (CpG) sites at which the association between BMI and DNAm could be modified by overall metabolic health. Results: The discovery study population was derived from three Women’s Health Initiative (WHI) ancillary studies (n = 3977) and two Atherosclerosis Risk in Communities (ARIC) ancillary studies (n = 3520). Findings were validated in the Multi-Ethnic Study of Atherosclerosis (MESA) cohort (n = 1200). Generalized linear models regressed methylation β values on the interaction between BMI and metabolic health Z score (BMI × MHZ) adjusted for BMI, MHZ, cell composition, chip number and location, study characteristics, top three ancestry principal components, smoking, age, ethnicity (WHI), and sex (ARIC). Among the 429,566 sites examined, differential associations between BMI × MHZ and DNAm were identified at 22 CpG sites (FDR q < 0.05), with one site replicated in MESA (cg18989722, in the TRAPPC9 gene). Three of the 22 sites were associated with incident coronary heart disease (CHD) in WHI. For each 0.01 unit increase in DNAm β value, the risk of incident CHD increased by 9% in one site and decreased by 6–10% in two sites over 25 years. Conclusions: Differential associations between DNAm and BMI by MHZ were identified at 22 sites, one of which was validated (cg18989722) and three of which were predictive of incident CHD. These sites are located in several genes related to NF-kappa-B signaling, suggesting a potential role for inflammation between DNA methylation and BMI-associated metabolic health.

Parent-child similarity is a function of genetic and environmental transmission. In addition, genetic effects not transmitted to offspring may drive parental behavior, thereby affecting the rearing environment of the child. Measuring genetic proclivity directly, through polygenic risk scores (PRSs), provides a way to test for the effect of nontransmitted parental genotype, on offspring outcome, termed a genetic nurture effect-in other words, if and how parental genomes might affect their children through the environment. The current study used polygenic risk scores for smoking initiation, cigarettes per day, and drinks per week to predict substance use in a sample of 3,008 twins, assessed prospectively from age 17-29, and their parents, from the Minnesota Center for Twin and Family Research. Mixed-effects models were used to test for a genetic nurture effect whereby parental PRSs predict offspring tobacco and alcohol use after statistically adjusting for offspring's own PRS. Parental smoking initiation PRS predicted offspring cigarettes per day at age 24 (β = .103, 95% CI [.03, .17]) and alcohol use at age 17 (β = .091, 95% CI [.04, .14]) independent of shared genetics. There was also a suggestive independent association between the parent PRS and offspring smoking at age 17 (β = .096; 95% CI [.02, .17]). Mediation analyses provided some evidence for environmental effects of parental smoking, alcohol use, and family socioeconomic status. These findings, and more broadly the molecular genetic method used, have implications on the identification of environmental effects on developmental outcomes such as substance use. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Objective: : Developing clinical natural language processing systems often requires access to many clinical documents, which are not widely available to the public due to privacy and security concerns. To address this challenge, we propose to develop methods to generate synthetic clinical notes and evaluate their utility in real clinical natural language processing tasks. Materials and Methods: : We implemented 4 state-of-the-art text generation models, namely CharRNN, Seg-GAN, GPT-2, and CTRL, to generate clinical text for the History and Present Illness section. We then manually annotated clinical entities for randomly selected 500 History and Present Illness notes generated from the best-performing algorithm. To compare the utility of natural and synthetic corpora, we trained named entity recognition (NER) models from all 3 corpora and evaluated their performance on 2 independent natural corpora. Results: : Our evaluation shows GPT-2 achieved the best BLEU (bilingual evaluation understudy) score (with a BLEU-2 of 0.92). NER models trained on synthetic corpus generated by GPT-2 showed slightly better performance on 2 independent corpora: strict F1 scores of 0.709 and 0.748, respectively, when compared with the NER models trained on natural corpus (F1 scores of 0.706 and 0.737, respectively), indicating the good utility of synthetic corpora in clinical NER model development. In addition, we also demonstrated that an augmented method that combines both natural and synthetic corpora achieved better performance than that uses the natural corpus only. Conclusions: : Recent advances in text generation have made it possible to generate synthetic clinical notes that could be useful for training NER models for information extraction from natural clinical notes, thus lowering the privacy concern and increasing data availability. Further investigation is needed to apply this technology to practice.

Infectious disease epidemics are plaguing the world and a lot of research is focused on the development of models to reproduce disease dynamics for eco-environmental and biological investigation, and disease management. Leptospirosis is an example of a neglected zoonosis strongly mediated by ecohydrological dynamics with emerging endemic and epidemic patterns worldwide in both animal and human populations. By accounting for large heterogeneities of affected areas we show how exponential endemics and scale-free epidemics are largely predictable and linked to common socio-environmental features via scaling laws with different exponents that inform about vulnerability factors. This led to the development of a novel pattern-oriented integrated model that can be used as an early-warning signal (EWS) tool for endemic-epidemic regime classification, risk determinant attribution, and near real-time forecast of outbreaks. Forecasts are grounded on expected outbreak recurrence time dependent on exceedance probabilities and statistical EWS that sense outbreak onset. A stochastic spatially-explicit model is shown to comprehensively predict outbreak dynamics (early sensing, timing, magnitude, decay, and eco-environmental determinants) and derive a spreading factor characterizing endemics and epidemics, where average over maximum rainfall is the critical factor characterizing disease transitions. Dynamically, case cross-correlation considering neighboring communities senses 2-weeks in advance outbreaks. Eco-environmental scaling relationships highlight how predicted host suitability and topographic index can be used as epidemiological footprints to effectively distinguish and control Leptospirosis regimes and areas dependent on hydro-climatological dynamics as the main trigger. The spatio-temporal scale-invariance of epidemics – underpinning persistent criticality and neutrality or independence among areas – is emphasized by the high accuracy in reproducing sequence and magnitude of cases via reliable surveillance. Further investigations of robustness and universality of eco-environmental determinants are required; nonetheless a comprehensive and computationally simple EWS method for the full characterization of Leptospirosis is provided. The tool is extendable to other climate-sensitive zoonoses to define vulnerability factors and predict outbreaks useful for optimal disease risk prevention and control.

We investigated the heritability of educational attainment and how it differed between birth cohorts and cultural–geographic regions. A classical twin design was applied to pooled data from 28 cohorts representing 16 countries and including 193,518 twins with information on educational attainment at 25 years of age or older. Genetic factors explained the major part of individual differences in educational attainment (heritability: a2 = 0.43; 0.41–0.44), but also environmental variation shared by co-twins was substantial (c2 = 0.31; 0.30–0.33). The proportions of educational variation explained by genetic and shared environmental factors did not differ between Europe, North America and Australia, and East Asia. When restricted to twins 30 years or older to confirm finalized education, the heritability was higher in the older cohorts born in 1900–1949 (a2 = 0.44; 0.41–0.46) than in the later cohorts born in 1950–1989 (a2 = 0.38; 0.36–0.40), with a corresponding lower influence of common environmental factors (c2 = 0.31; 0.29–0.33 and c2 = 0.34; 0.32–0.36, respectively). In conclusion, both genetic and environmental factors shared by co-twins have an important influence on individual differences in educational attainment. The effect of genetic factors on educational attainment has decreased from the cohorts born before to those born after the 1950s.

Background: DNA methylation patterns associated with habitual diet have not been well studied. Methods: Diet quality was characterized using a Mediterranean-style diet score and the Alternative Healthy Eating Index score. We conducted ethnicity-specific and trans-ethnic epigenome-wide association analyses for diet quality and leukocyte-derived DNA methylation at over 400 000 CpGs (cytosine-guanine dinucleotides) in 5 population-based cohorts including 6662 European ancestry, 2702 African ancestry, and 360 Hispanic ancestry participants. For diet-associated CpGs identified in epigenome-wide analyses, we conducted Mendelian randomization (MR) analysis to examine their relations to cardiovascular disease risk factors and examined their longitudinal associations with all-cause mortality. Results: We identified 30 CpGs associated with either Mediterranean-style diet score or Alternative Healthy Eating Index, or both, in European ancestry participants. Among these CpGs, 12 CpGs were significantly associated with all-cause mortality (Bonferroni corrected P<1.6×10-3). Hypermethylation of cg18181703 (SOCS3) was associated with higher scores of both Mediterranean-style diet score and Alternative Healthy Eating Index and lower risk for all-cause mortality (P=5.7×10-15). Ten additional diet-associated CpGs were nominally associated with all-cause mortality (P<0.05). MR analysis revealed 8 putatively causal associations for 6 CpGs with 4 cardiovascular disease risk factors (body mass index, triglycerides, high-density lipoprotein cholesterol concentrations, and type 2 diabetes mellitus; Bonferroni corrected MR P<4.5×10-4). For example, hypermethylation of cg11250194 (FADS2) was associated with lower triglyceride concentrations (MR, P=1.5×10-14).and hypermethylation of cg02079413 (SNORA54; NAP1L4) was associated with body mass index (corrected MR, P=1×10-6). Conclusions: Habitual diet quality was associated with differential peripheral leukocyte DNA methylation levels of 30 CpGs, most of which were also associated with multiple health outcomes, in European ancestry individuals. These findings demonstrate that integrative genomic analysis of dietary information may reveal molecular targets for disease prevention and treatment.

Aim: We conducted a methylome-wide association study to examine associations between DNA methylation in whole blood and central adiposity and body fat distribution, measured as waist circumference, waist-to-hip ratio and waist-to-height ratio adjusted for body mass index, in 2684 African-American adults in the Atherosclerosis Risk in Communities study. Materials & methods: We validated significantly associated cytosine-phosphate-guanine methylation sites (CpGs) among adults using the Women's Health Initiative and Framingham Heart Study participants (combined n = 5743) and generalized associations in adolescents from The Raine Study (n = 820). Results & conclusion: We identified 11 CpGs that were robustly associated with one or more central adiposity trait in adults and two in adolescents, including CpG site associations near TXNIP, ADCY7, SREBF1 and RAP1GAP2 that had not previously been associated with obesity-related traits.

Fathers are more than social accidents. Research has demonstrated that fathers matter to children's development. Despite noted progress, challenges remain on how best to conceptualize and assess fathering and father–child relationships. The current monograph is the result of an SRCD-sponsored meeting of fatherhood scholars brought together to discuss these challenges and make recommendations for best practices for incorporating fathers in studies on parenting and children's development. The first aim of this monograph was to provide a brief update on the current state of research on fathering and to lay out a developmental ecological systems perspective as a conceptual framework for understanding the different spaces fathers inhabit in their children's lives. Because there is wide variability in fathers’ roles, the ecological systems perspective situates fathers, mothers, children, and other caregivers within an evolving network of interrelated social relationships in which children and their parents change over time and space (e.g., residence). The second aim was to present examples of empirical studies conducted by members of the international working group that highlighted different methods, data collection, and statistical analyses used to capture the variability in father–child relationships. The monograph ends with a commentary that elaborates on the ecological systems framework with a discussion of the broader macrosystem and social-contextual influences that impinge on fathers and their children. The collection of articles contributes to research on father–child relationships by advancing theory and presenting varied methods and analysis strategies that assist in understanding the father–child relationship and its impact on child development.