Practical causal mediation analysis: extending nonparametric estimators to accommodate multiple mediators and multiple intermediate confounders.

Mediation analysis is appealing for its ability to improve understanding of the mechanistic drivers of causal effects, but real-world data complexities challenge its successful implementation, including (i) the existence of post-exposure variables that also affect mediators and outcomes (thus, confounding the mediator-outcome relationship), that may also be (ii) multivariate, and (iii) the existence of multivariate mediators. All three challenges are present in the mediation analysis we consider here, where our goal is to estimate the indirect effects of receiving a Section 8 housing voucher as a young child on the risk of developing a psychiatric mood disorder in adolescence that operate through mediators related to neighborhood poverty, the school environment, and instability of the neighborhood and school environments, considered together and separately. Interventional direct and indirect effects (IDE/IIE) accommodate post-exposure variables that confound the mediator-outcome relationship, but currently, no readily implementable nonparametric estimator for IDE/IIE exists that allows for both multivariate mediators and multivariate post-exposure intermediate confounders. The absence of such an IDE/IIE estimator that can easily accommodate both multivariate mediators and post-exposure confounders represents a significant limitation for real-world analyses, because when considering each mediator subgroup separately, the remaining mediator subgroups (or a subset of them) become post-exposure intermediate confounders. We address this gap by extending a recently developed nonparametric estimator for the IDE/IIE to allow for easy incorporation of multivariate mediators and multivariate post-exposure confounders simultaneously. We apply the proposed estimation approach to our analysis, including walking through a strategy to account for other, possibly co-occurring intermediate variables when considering each mediator subgroup separately.

Quantification of mediation effects of white matter functional characteristics on cognitive decline in aging.

Cognitive decline with aging involves multifactorial processes, including changes in brain structure and function. This study focuses on the role of white matter functional characteristics, as reflected in blood oxygenation level-dependent signals, in age-related cognitive deterioration. Building on previous research confirming the reproducibility and age-dependence of blood oxygenation level-dependent signals acquired via functional magnetic resonance imaging, we here employ mediation analysis to test if aging affects cognition through white matter blood oxygenation level-dependent signal changes, impacting various cognitive domains and specific white matter regions. We used independent component analysis of resting-state blood oxygenation level-dependent signals to segment white matter into coherent hubs, offering a data-driven view of white matter's functional architecture. Through correlation analysis, we constructed a graph network and derived metrics to quantitatively assess regional functional properties based on resting-state blood oxygenation level-dependent fluctuations. Our analysis identified significant mediators in the age-cognition relationship, indicating that aging differentially influences cognitive functions by altering the functional characteristics of distinct white matter regions. These findings enhance our understanding of the neurobiological basis of cognitive aging, highlighting the critical role of white matter in maintaining cognitive integrity and proposing new approaches to assess interventions targeting cognitive decline in older populations.

The Legacy of Redlining: Increasing Childhood Asthma Disparities Through Neighborhood Poverty.

RATIONALE: Identifying the root causes of racial disparities in childhood asthma is critical for health equity. OBJECTIVES: To determine if the 1930's racist policy of redlining led to present-day disparities in childhood asthma by increasing community-level poverty and decreasing neighborhood socioeconomic position (SEP). METHODS: We categorized census tracts at birth of participants from the Children's Respiratory and Environmental Workgroup birth cohort consortium into A, B, C, or D categories as defined by the Home Owners Loan Corporation (HOLC), with D being the highest perceived risk. Surrogates of present-day neighborhood-level SEP were determined for each tract including the percentage of low-income households, the CDC's social vulnerability index (SVI), and other tract-level variables. We performed causal mediation analysis, which, under the assumption of no unmeasured confounding, estimates the direct and mediated pathways by which redlining may cause asthma disparities through census tract-level mediators adjusting for individual-level covariates. MEASUREMENTS AND MAIN RESULTS: Of 4,849 children, the cumulative incidence of asthma through age 11 was 26.6% and 13.2% resided in census tracts with a HOLC grade of D. In mediation analyses, residing in grade D tracts (aOR = 1.03 [95%CI 1.01,1.05]) was significantly associated with childhood asthma, with 79% of this increased risk mediated by percentage of low-income households; results were similar for SVI and other tract-level variables. CONCLUSIONS: The historical structural racist policy of redlining led to present-day asthma disparities in part through decreased neighborhood SEP. Policies aimed at reversing the effects of structural racism should be considered to create more just, equitable, and healthy communities.

Biological Age, Chronological Age and Survival in Pulmonary Fibrosis: A Causal Mediation Analysis.

RATIONALE: Accelerated biological aging has been implicated in the development of interstitial lung disease (ILD) and other diseases of aging but remains poorly understood. OBJECTIVES: To identify plasma proteins that mediate the relationship between chronological age and survival association in patients with ILD. METHODS: Causal mediation analysis was performed to identify plasma proteins that mediated the chronological age-survival relationship in an idiopathic pulmonary fibrosis (IPF) discovery cohort. Proteins mediating this relationship after adjustment for false discovery were advanced for testing in an independent ILD validation cohort and explored in a chronic obstructive pulmonary disease (COPD) cohort. A proteomic-based measure of biological age was constructed and survival analysis performed assessing the impact of biological age and peripheral blood telomere length on the chronological age-survival relationship. RESULTS: Twenty-two proteins mediated the chronological age-survival relationship after adjustment for false discovery in the IPF discovery cohort (n=874), with nineteen remaining significant mediators of this relationship in the ILD validation cohort (n=983) and one mediating this relationship in the COPD cohort. Latent transforming growth factor beta binding protein 2 and ectodysplasin A2 receptor showed the strongest mediation across cohorts. A proteomic measure of biological age completely attenuated the chronological age-survival association and better discriminated survival than chronological age. Results were robust to adjustment for peripheral blood telomere length, which did not mediate the chronological age-survival relationship. CONCLUSIONS: Molecular measures of aging completely mediate the relationship between chronological age and survival, suggesting that chronological age has no direct effect on ILD survival.

Joint transcriptomic and cytometric study of children with peanut allergy reveals molecular and cellular cross talk in reaction thresholds.

BACKGROUND: Reaction thresholds in peanut allergy are highly variable. Elucidating causal relationships between molecular and cellular processes associated with variable thresholds could point to therapeutic pathways for raising thresholds. OBJECTIVE: The aim of this study was to characterize molecular and cellular systemic processes associated with reaction threshold in peanut allergy and causal relationships between them. METHODS: A total of 105 children aged 4 to 14 years with suspected peanut allergy underwent double-blind, placebo-controlled food challenge to peanut. The cumulative peanut protein quantity eliciting allergic symptoms was considered the reaction threshold for each child. Peripheral blood samples collected at 0, 2, and 4 hours after challenge start were used for RNA sequencing, whole blood staining, and cytometry. Statistical and network analyses were performed to identify associations and causal mediation between the molecular and cellular profiles and peanut reaction threshold. RESULTS: Within the cohort (N = 105), 81 children (77%) experienced allergic reactions after ingesting varying quantities of peanut, ranging from 43 to 9043 mg of cumulative peanut protein. Peripheral blood expression of transcripts (eg, IGF1R [false discovery rate (FDR) = 5.4e-5] and PADI4 [FDR = 5.4e-5]) and neutrophil abundance (FDR = 9.5e-4) were associated with peanut threshold. Coexpression network analyses revealed that the threshold-associated transcripts were enriched in modules for FcγR-mediated phagocytosis (FDR = 3.2e-3) and Toll-like receptor (FDR = 1.4e-3) signaling. Bayesian network, key driver, and causal mediation analyses identified key drivers (AP5B1, KLHL21, VASP, TPD52L2, and IGF2R) within these modules that are involved in bidirectional causal mediation relationships with neutrophil abundance. CONCLUSION: Key driver transcripts in FcγR-mediated phagocytosis and Toll-like receptor signaling interact bidirectionally with neutrophils in peripheral blood and are associated with reaction threshold in peanut allergy.

Investigating the causal relationship of gut microbiota with GERD and BE: a bidirectional mendelian randomization.

BACKGROUND: Gut microbiota(GM) have been proven associated with lots of gastrointestinal diseases, but its causal relationship with Gastroesophageal reflux disease(GERD) and Barrett's esophagus(BE) hasn't been explored. We aimed to uncover the causal relation between GM and GERD/BE and potential mediators by utilizing Mendelian Randomization(MR) analysis. METHODS: Summary statistics of GM(comprising 301 bacteria taxa and 205 metabolism pathways) were extracted from MiBioGen Consortium(N = 18,340) and Dutch Microbiome Project(N = 7,738), GERD and BE from a multitrait meta-analysis(NGERD=602,604, NBE=56,429). Bidirectional two-sample MR analysis and linkage disequilibrium score regression(LDSC) were used to explore the genetic correlation between GM and GERD/BE. Mediation MR analysis was performed for the risk factors of GERD/BE, including Body mass index(BMI), weight, type 2 diabetes, major depressive disorder(MDD), smoking initiation, alcohol consumption, and dietary intake(including carbohydrate, sugar, fat, protein intake), to detect the potential mediators between GM and GERD/BE. RESULTS: 11 bacterial taxa and 13 metabolism pathways were found associated with GERD, and 18 taxa and 5 pathways exhibited causal relationship with BE. Mediation MR analysis suggested weight and BMI played a crucial role in these relationships. LDSC identified 1 taxon and 4 metabolism pathways related to GERD, and 1 taxon related to BE. Specie Faecalibacterium prausnitzii had a suggestive impact on both GERD(OR = 1.087, 95%CI = 1.01-1.17) and BE(OR = 1.388, 95%CI = 1.03-1.86) and LDSC had determined their correlation. Reverse MR indicated that BE impacted 10 taxa and 4 pathways. CONCLUSIONS: This study established a causal link between gut microbiota and GERD/BE, and identified the probable mediators. It offers new insights into the role of gut microbiota in the development and progression of GERD and BE in the host.

Evolving brain network dynamics in early childhood: Insights from modular graph metrics.

Modular dynamic graph theory metrics effectively capture the patterns of dynamic information interaction during human brain development. While existing research has employed modular algorithms to examine the overall impact of dynamic changes in community structure throughout development, there is a notable gap in understanding the cross-community dynamic changes within different functional networks during early childhood and their potential contributions to the efficiency of brain information transmission. This study seeks to address this gap by tracing the trajectories of cross-community structural changes within early childhood functional networks and modeling their contributions to information transmission efficiency. We analyzed 194 functional imaging scans from 83 children aged 2 to 8 years, who participated in passive viewing functional magnetic resonance imaging sessions. Utilizing sliding windows and modular algorithms, we evaluated three spatiotemporal metrics-temporal flexibility, spatiotemporal diversity, and within-community spatiotemporal diversity-and four centrality metrics: within-community degree centrality, eigenvector centrality, between-community degree centrality, and between-community eigenvector centrality. Mixed-effects linear models revealed significant age-related increases in the temporal flexibility of the default mode network (DMN), executive control network (ECN), and salience network (SN), indicating frequent adjustments in community structure within these networks during early childhood. Additionally, the spatiotemporal diversity of the SN also displayed significant age-related increases, highlighting its broad pattern of cross-community dynamic interactions. Conversely, within-community spatiotemporal diversity in the language network exhibited significant age-related decreases, reflecting the network's gradual functional specialization. Furthermore, our findings indicated significant age-related increases in between-community degree centrality across the DMN, ECN, SN, language network, and dorsal attention network, while between-community eigenvector centrality also increased significantly for the DMN, ECN, and SN. However, within-community eigenvector centrality remained stable across all functional networks during early childhood. These results suggest that while centrality of cross-community interactions in early childhood functional networks increases, centrality within communities remains stable. Finally, mediation analysis was conducted to explore the relationships between age, brain dynamic graph metrics, and both global and local efficiency based on community structure. The results indicated that the dynamic graph metrics of the SN primarily mediated the relationship between age and the decrease in global efficiency, while those of the DMN, language network, ECN, dorsal attention network, and SN primarily mediated the relationship between age and the increase in local efficiency. This pattern suggests a developmental trajectory in early childhood from global information integration to local information segregation, with the SN playing a pivotal role in this transformation. This study provides novel insights into the mechanisms by which early childhood brain functional development impacts information transmission efficiency through cross-community adjustments in functional networks.

Elucidating genetic and molecular basis of altered higher-order brain structure-function coupling in major depressive disorder.

Previous studies have shown that major depressive disorder (MDD) patients exhibit structural and functional impairments, but few studies have investigated changes in higher-order coupling between structure and function. Here, we systematically investigated the effect of MDD on higher-order coupling between structural connectivity (SC) and functional connectivity (FC). Each brain region was mapped into embedding vector by the node2vec algorithm. We used support vector machine (SVM) with the brain region embedding vector to distinguish MDD patients from health controls (HCs) and identify the most discriminative brain regions. Our study revealed that MDD patients had decreased higher-order coupling in connections between the most discriminative brain regions and local connections in rich-club organization and increased higher-order coupling in connections between the ventral attentional network and limbic network compared with HCs. Interestingly, transcriptome-neuroimaging association analysis demonstrated the correlations between regional rSC-FC coupling variations between MDD patients and HCs and α/ß-hydrolase domain-containing 6 (ABHD6), ß 1,3-N-acetylglucosaminyltransferase-9(ß3GNT9), transmembrane protein 45B (TMEM45B), the correlation between regional dSC-FC coupling variations and retinoic acid early transcript 1E antisense RNA 1(RAET1E-AS1), and the correlations between regional iSC-FC coupling variations and ABHD6, ß3GNT9, katanin-like 2 protein (KATNAL2). In addition, correlation analysis with neurotransmitter receptor/transporter maps found that the rSC-FC and iSC-FC coupling variations were both correlated with neuroendocrine transporter (NET) expression, and the dSC-FC coupling variations were correlated with metabotropic glutamate receptor 5 (mGluR5). Further mediation analysis explored the relationship between genes, neurotransmitter receptor/transporter and MDD related higher-order coupling variations. These findings indicate that specific genetic and molecular factors underpin the observed disparities in higher-order SC-FC coupling between MDD patients and HCs. Our study confirmed that higher-order coupling between SC and FC plays an important role in diagnosing MDD. The identification of new biological evidence for MDD etiology holds promise for the development of innovative antidepressant therapies.

Metabolomic landscape of overall and common cancers in the UK Biobank: A prospective cohort study.

Information about the NMR metabolomics landscape of overall, and common cancers is still limited. Based on a cohort of 83,290 participants from the UK Biobank, we used multivariate Cox regression to assess the associations between each of the 168 metabolites with the risks of overall cancer and 20 specific types of cancer. Then, we applied LASSO to identify important metabolites for overall cancer risk and obtained their associations using multivariate cox regression. We further conducted mediation analysis to evaluate the mediated role of metabolites in the effects of traditional factors on overall cancer risk. Finally, we included the 13 identified metabolites as predictors in prediction models, and compared the accuracies of our traditional models. We found that there were commonalities among the metabolic profiles of overall and specific types of cancer: the top 20 frequently identified metabolites for 20 specific types of cancer were all associated with overall cancer; most of the specific types of cancer had common identified metabolites. Meanwhile, the associations between the same metabolite with different types of cancer can vary based on the site of origin. We identified 13 metabolic biomarkers associated with overall cancer, and found that they mediated the effects of traditional factors. The accuracies of prediction models improved when we added 13 identified metabolites in models. This study is helpful to understand the metabolic mechanisms of overall and a wide range of cancers, and our results also indicate that NMR metabolites are potential biomarkers in cancer diagnosis and prevention.

Grandmaternal pre-pregnancy body mass index and infant birthweight: a mediation analysis of maternal pre-pregnancy body mass index.

The objectives of this study were to examine the total effect of grandmaternal [G0] pre-pregnancy body mass index (BMI) on infant [G2] birthweight z-score and to quantify the mediation role of maternal [G1] pre-pregnancy BMI. Data were extracted from the Nova Scotia 3G Multigenerational Cohort. The association between G0 pre-pregnancy BMI and G2 birthweight z-score and the mediated effect by G1 pre-pregnancy BMI were estimated using g-computation with adjustment for confounders identified using a directed acyclic graph and accounting for intermediate confounding. 20822 G1-G2 dyads from 18450 G0 were included. Relative to G0 normal weight, G0 underweight decreased mean G2 birthweight z-score (-0.11, 95% confidence interval (CI) -0.20, -0.030), while G0 overweight and obesity increased mean G2 birthweight z-score (0.091 [95% CI 0.034, 0.15] and 0.22 [95% CI 0.11, 0.33]). G1 pre-pregnancy BMI partly mediated the association, with the largest effect size observed for G0 obesity (0.11, 95% CI 0.080, 0.14). Estimates of the direct effect were close to the null. In conclusion, grandmaternal pre-pregnancy BMI was associated with infant birthweight z-score. Maternal pre-pregnancy BMI partly mediated the association, suggesting that factors related to BMI may play an important role in the transmission of weight across the maternal line.

Mediating pathways between neighborhood disadvantage and cardiovascular risk: Quasi-experimental evidence from a Danish refugee dispersal policy.

Research has documented that neighborhood disadvantage is associated with increased cardiovascular disease risk, but it is unclear which mechanistic pathways mediate this association across the life course. Leveraging a natural experiment in which refugees to Denmark were quasi-randomly assigned to neighborhoods across the country during 1986-1998 and using 30 years of follow-up data from population and health registers, we assessed whether and how individual-level poverty, unstable employment, and poor mental health mediate the relation between neighborhood disadvantage and the risk of hypertension, hyperlipidemia, and type 2 diabetes among Danish refugees (N= 40,811). Linear probability models using the discrete time-survival framework showed that neighborhood disadvantage was associated with increased risk of hypertension (0.05 percentage points [pp] per year [95%CI -0.00, 0.10]); hyperlipidemia (0.03 pp per year [95%CI -0.01, 0.07]), and diabetes (0.01 pp per year (95%CI -0.02, 0.03)). The Baron-Kenny product-of-coefficients method for counterfactual mediation analysis indicated that cumulative income mediated 6%-28% of the disadvantage effect on these outcomes. We find limited evidence of mediation by unstable employment and poor mental health. This study informs our theoretical understanding of the pathways linking neighborhood disadvantage with cardiovascular disease risk and identifies income security as a promising point of intervention in future research.

Causal Effects of Competing Obstetrical Interventions: Mediators of Placental Abruption and Perinatal Mortality.

Placental abruption, the premature placental separation, confers increased perinatal mortality risk with preterm delivery as an important pathway through which the risk appears mediated. While pregnancies complicated by abruption are often delivered through an obstetrical intervention, many deliver spontaneously. We examined the contributions of clinician-initiated (PTDIND) and spontaneous (PTDSPT) preterm delivery at <37 weeks as competing causal mediators of the abruption-perinatal mortality association. Using the Consortium for Safe Labor (2002-2008) data (n = 203,990; 1.6% with abruption), we applied a potential outcomes-based mediation analysis to decompose the total effect into direct and mediator-specific indirect effects through PTDIND and PTDSPT. Each mediated effect describes the reduction in the counterfactual mortality risk if that preterm delivery subtype was shifted from its distribution under abruption to without abruption. The total effect risk ratio (RR) of abruption on perinatal mortality was 5.4 (95% confidence interval [CI] 4.6, 6.3). The indirect effect RRs for PTDIND and PTDSPT were 1.5 (95% CI: 1.4, 1.6) and 1.5 (95% CI: 1.5, 1.6), respectively; these corresponded to mediated proportions of 25% each. These findings underscore that spontaneous and clinician-initiated preterm deliveries each play essential roles in shaping perinatal mortality risks associated with placental abruption.

The mediating role of SARS-CoV-2 variants between income and hospitalisation due to COVID-19: A period-based mediation analysis.

The mechanisms facilitating the relationship between low income and COVID-19 severity have not been partitioned in the presence of SARS-CoV-2 variants of concern (VOC). To address this, we used causal mediation analysis to quantify the possible mediating role infection with VOC has on the relationship between neighbourhood income (exposure) and hospitalisation due to COVID-19 among cases (outcome). A population-based cohort of 65,629 individuals residing in British Columbia, Canada, was divided into three periods of VOC co-circulation in the 2021 calendar year whereby each period included co-circulation of an emerging and an established VOC. Each cohort was subjected to g-formula mediation techniques to decompose the relationship between exposure and outcome into total, direct and indirect effects. In the mediation analysis, the total effects indicated that low income was associated with increased odds of hospitalisation across all periods. Further decomposition of the effects revealed that income is directly and indirectly associated with hospitalisation. The resulting indirect effect through VOC accounted for approximately between 6 and 13% of the total effect of income on hospitalisation. This study underscores, conditional on the analysis, the importance of addressing underlying inequities to mitigate the disproportionate impact on historically marginalised communities by adopting an equity lens as central to pandemic preparedness and response from the onset.

Sex disparity in liver allocation within Eurotransplant.

In Eurotransplant, relatively more females than males die while waiting for liver transplantation, and relatively fewer females undergo transplantation. With adult liver transplantation candidates listed between 2007 and 2019 (n = 21 170), we study whether sex disparity is inherent to the model for end-stage liver disease (MELD) scoring system, or the indirect result of a small candidate body size limiting access to transplantation. Cox proportional hazard models are used to quantify the direct effect of sex on waitlist mortality, independent of the effect of sex through MELD scores, and the direct effect of sex on the transplantation rate, independent of the effect of sex through MELD and candidate body size. Adjusted waitlist mortality hazard ratios (HRs) for female sex are insignificant (HR: 1.03, 95% CI: 0.88-1.20). We thus lack evidence that MELD systematically underestimates waitlist mortality rates for females. Transplantation rates are 25% lower for females than males in unadjusted analyses (HR: 0.74, 95% CI: 0.71-0.77), but HRs become insignificant with adjustment for mediators (HR: 0.98, 95% CI: 0.93-1.04), most importantly candidate body size. Sex disparity in Eurotransplant thus appears to be largely a consequence of lower transplantation rates for females, which are explained by sex differences in body size.

EEG functional connectivity as a Riemannian mediator: An application to malnutrition and cognition.

Mediation analysis assesses whether an exposure directly produces changes in cognitive behavior or is influenced by intermediate "mediators". Electroencephalographic (EEG) spectral measurements have been previously used as effective mediators representing diverse aspects of brain function. However, it has been necessary to collapse EEG measures onto a single scalar using standard mediation methods. In this article, we overcome this limitation and examine EEG frequency-resolved functional connectivity measures as a mediator using the full EEG cross-spectral tensor (CST). Since CST samples do not exist in Euclidean space but in the Riemannian manifold of positive-definite tensors, we transform the problem, allowing for the use of classic multivariate statistics. Toward this end, we map the data from the original manifold space to the Euclidean tangent space, eliminating redundant information to conform to a "compressed CST." The resulting object is a matrix with rows corresponding to frequencies and columns to cross spectra between channels. We have developed a novel matrix mediation approach that leverages a nuclear norm regularization to determine the matrix-valued regression parameters. Furthermore, we introduced a global test for the overall CST mediation and a test to determine specific channels and frequencies driving the mediation. We validated the method through simulations and applied it to our well-studied 50+-year Barbados Nutrition Study dataset by comparing EEGs collected in school-age children (5-11 years) who were malnourished in the first year of life with those of healthy classmate controls. We hypothesized that the CST mediates the effect of malnutrition on cognitive performance. We can now explicitly pinpoint the frequencies (delta, theta, alpha, and beta bands) and regions (frontal, central, and occipital) in which functional connectivity was altered in previously malnourished children, an improvement to prior studies. Understanding the specific networks impacted by a history of postnatal malnutrition could pave the way for developing more targeted and personalized therapeutic interventions. Our methods offer a versatile framework applicable to mediation studies encompassing matrix and Hermitian 3D tensor mediators alongside scalar exposures and outcomes, facilitating comprehensive analyses across diverse research domains.

Resting-state brain activity as a biomarker of chronic pain impairment and a mediator of its association with pain resilience.

Past cross-sectional chronic pain studies have revealed aberrant resting-state brain activity in regions involved in pain processing and affect regulation. However, there is a paucity of longitudinal research examining links of resting-state activity and pain resilience with changes in chronic pain outcomes over time. In this prospective study, we assessed the status of baseline (T1) resting-state brain activity as a biomarker of later impairment from chronic pain and a mediator of the relation between pain resilience and impairment at follow-up. One hundred forty-two adults with chronic musculoskeletal pain completed a T1 assessment comprising a resting-state functional magnetic resonance imaging scan based on regional homogeneity (ReHo) and self-report measures of demographics, pain characteristics, psychological status, pain resilience, pain severity, and pain impairment. Subsequently, pain impairment was reassessed at a 6-month follow-up (T2). Hierarchical multiple regression and mediation analyses assessed relations of T1 ReHo and pain resilience scores with changes in pain impairment. Higher T1 ReHo values in the right caudate nucleus were associated with increased pain impairment at T2, after controlling for all other statistically significant self-report measures. ReHo also partially mediated associations of T1 pain resilience dimensions with T2 pain impairment. T1 right caudate nucleus ReHo emerged as a possible biomarker of later impairment from chronic musculoskeletal pain and a neural mechanism that may help to explain why pain resilience is related to lower levels of later chronic pain impairment. Findings provide empirical foundations for prospective extensions that assess the status of ReHo activity and self-reported pain resilience as markers for later impairment from chronic pain and targets for interventions to reduce impairment. PRACTITIONER POINTS: Resting-state markers of impairment: Higher baseline (T1) regional homogeneity (ReHo) values, localized in the right caudate nucleus, were associated with exacerbations in impairment from chronic musculoskeletal pain at a 6-month follow-up, independent of T1 demographics, pain experiences, and psychological factors. Mediating role of ReHo values: ReHo values in the right caudate nucleus also mediated the relationship between baseline pain resilience levels and later pain impairment among participants. Therapeutic implications: Findings provide empirical foundations for research extensions that evaluate (1) the use of resting-state activity in assessment to identify people at risk for later impairment from pain and (2) changes in resting-state activity as biomarkers for the efficacy of treatments designed to improve resilience and reduce impairment among those in need.

Childhood maltreatment and risk of endocrine diseases: an exploration of mediating pathways using sequential mediation analysis.

BACKGROUND: Adverse childhood experiences (ACEs), including childhood maltreatment, have been linked with increased risk of diabetes and obesity during adulthood. A comprehensive assessment on the associations between childhood maltreatment and all major endocrine diseases, as well as the relative importance of different proposed mechanistic pathways on these associations, is currently lacking. METHODS: Based on the UK Biobank, we constructed a cohort including 151,659 participants with self-reported data on childhood maltreatment who were 30 years of age or older on/after January 1, 1985. All participants were followed from the index date (i.e., January 1, 1985, or their 30th birthday, whichever came later) until the first diagnosis of any or specific (12 individual diagnoses and 9 subtypes) endocrine diseases, death, or the end of follow-up (December 31, 2019), whichever occurred first. We used Cox models to examine the association of childhood maltreatment, treated as continuous (i.e., the cumulative number of experienced childhood maltreatment), ordinal (i.e., 0, 1 and ≥ 2), or binary (< 2 and ≥ 2) variable, with any and specific endocrine diseases, adjusted for multiple covariates. We further examined the risk of having multiple endocrine diseases using Linear or Logistic Regression models. Then, sequential mediation analyses were performed to assess the contribution of four possible mechanisms (i.e., suboptimal socioeconomic status (SES), psychological adversities, unfavorable lifestyle, and biological alterations) on the observed associations. RESULTS: During an average follow-up of 30.8 years, 20,885 participants received a diagnosis of endocrine diseases. We observed an association between the cumulative number of experienced childhood maltreatment and increased risk of being diagnosed with any endocrine disease (adjusted hazard ratio (HR) = 1.10, 95% confidence interval 1.09-1.12). The HR was 1.26 (1.22-1.30) when comparing individuals ≥ 2 with those with < 2 experienced childhood maltreatment. We further noted the most pronounced associations for type 2 diabetes (1.40 (1.33-1.48)) and hypothalamic-pituitary-adrenal (HPA)-axis-related endocrine diseases (1.38 (1.17-1.62)), and the association was stronger for having multiple endocrine diseases, compared to having one (odds ratio (95% CI) = 1.24 (1.19-1.30), 1.35 (1.27-1.44), and 1.52 (1.52-1.53) for 1, 2, and ≥ 3, respectively). Sequential mediation analyses showed that the association between childhood maltreatment and endocrine diseases was consistently and most distinctly mediated by psychological adversities (15.38 ~ 44.97%), while unfavorable lifestyle (10.86 ~ 25.32%) was additionally noted for type 2 diabetes whereas suboptimal SES (14.42 ~ 39.33%) for HPA-axis-related endocrine diseases. CONCLUSIONS: Our study demonstrates that adverse psychological sequel of childhood maltreatment constitutes the main pathway to multiple endocrine diseases, particularly type 2 diabetes and HPA-axis-related endocrine diseases. Therefore, increased access to evidence-based mental health services may also be pivotal in reducing the risk of endocrine diseases among childhood maltreatment-exposed individuals.

The dynamics of B-cell reconstitution post allogeneic hematopoietic stem cell transplantation: A real-world study.

BACKGROUND: The immune reconstitution after allogeneic hematopoietic stem cell transplantation (allo-HSCT) is crucial for preventing infections and relapse and enhancing graft-versus-tumor effects. B cells play an important role in humoral immunity and immune regulation, but their reconstitution after allo-HSCT has not been well studied. METHODS: In this study, we analyzed the dynamics of B cells in 252 patients who underwent allo-HSCT for 2 years and assessed the impact of factors on B-cell reconstitution and their correlations with survival outcomes, as well as the development stages of B cells in the bone marrow and the subsets in the peripheral blood. RESULTS: We found that the B-cell reconstitution in the bone marrow was consistent with the peripheral blood (p = 0.232). B-cell reconstitution was delayed by the male gender, age >50, older donor age, the occurrence of chronic and acute graft-versus-host disease, and the infections of fungi and cytomegalovirus. The survival analysis revealed that patients with lower B cells had higher risks of death and relapse. More importantly, we used propensity score matching to obtain the conclusion that post-1-year B-cell reconstitution is better in females. Meanwhile, using mediation analysis, we proposed the age-B cells-survival axis and found that B-cell reconstitution at month 12 posttransplant mediated the effect of age on patient survival (p = 0.013). We also found that younger patients showed more immature B cells in the bone marrow after transplantation (p = 0.037). CONCLUSION: Our findings provide valuable insights for optimizing the management of B-cell reconstitution and improving the efficacy and safety of allo-HSCT.

Large-scale genetic correlation studies explore the causal relationship and potential mechanism between gut microbiota and COVID-19-associated risks.

Recent observational studies suggest that gut microorganisms are involved in the onset and development of coronavirus disease 2019 (COVID-19), but the potential causal relationship behind them remains unclear. Exposure data were derived from the MiBioGen consortium, encompassing 211 gut microbiota (n = 18,340). The outcome data were sourced from the COVID-19 host genetics initiative (round 7), including COVID-19 severity (n = 1,086,211), hospitalization (n = 2,095,324), and susceptibility (n = 2,597,856). First, a two-sample Mendelian randomization (TSMR) was performed to investigate the causal effect between gut microbiota and COVID-19 outcomes. Second, a two-step MR was used to explore the potential mediators and underlying mechanisms. Third, several sensitivity analyses were performed to verify the robustness of the results. Five gut microbes were found to have a potential causality with COVID-19 severity, namely Betaproteobacteria (beta = 0.096, p = 0.034), Christensenellaceae (beta = -0.092, p = 0.023), Adlercreutzia (beta = 0.072, p = 0.048), Coprococcus 1 (beta = 0.089, p = 0.032), Eisenbergiella (beta = 0.064, p = 0.024). Seven gut microbes were found to have a potential causality with COVID-19 hospitalization, namely Victivallaceae (beta = 0.037, p = 0.028), Actinomyces (beta = 0.047, p = 0.046), Coprococcus 2 (beta = -0.061, p = 0.031), Dorea (beta = 0.067, p = 0.016), Peptococcus (beta = -0.035, p = 0.049), Rikenellaceae RC9 gut group (beta = 0.034, p = 0.018), and Proteobacteria (beta = -0.069, p = 0.035). Two gut microbes were found to have a potential causality with COVID-19 susceptibility, namely Holdemanella (beta = -0.024, p = 0.023) and Lachnospiraceae FCS020 group (beta = 0.026, p = 0.027). Multi-omics mediation analyses indicate that numerous plasma proteins, metabolites, and immune factors are critical mediators linking gut microbiota with COVID-19 outcomes. Sensitivity analysis suggested no significant heterogeneity or pleiotropy. These findings revealed the causal correlation and potential mechanism between gut microbiota and COVID-19 outcomes, which may improve our understanding of the gut-lung axis in the etiology and pathology of COVID-19 in the future.

Explaining International Trends in Mortality on Hemodialysis Through Changes in Hemodialysis Practices in the Dialysis Outcomes and Practice Patterns Study (DOPPS).

RATIONALE & OBJECTIVE: Case-mix adjusted hemodialysis mortality has decreased since 1998. Many factors that influence mortality may have contributed to this trend and these associations may differ by continental region. We studied changes in hemodialysis facility practices over time and their potential role in mediating changes in patient survival. STUDY DESIGN: Observational prospective cohort study. SETTING & PARTICIPANTS: Adult hemodialysis patients treated in hemodialysis 500 facilities participating in the Dialysis Outcomes Practice Patterns Study (DOPPS) between 1999 and 2015 in the US, Japan, and 4 four European countries: Germany, Italy, Spain, and UK. PREDICTORS: Four practice measures at each facility: the percentages of patients with Kt/V>1.2, interdialytic weight gain [IDWG]<5.7%, phosphorus<6 mg/dL, and using AV fistulae. OUTCOMES: Patient survival. ANALYTICAL APPROACH: Mediation analyses, adjusted for case mix, were conducted using 3-year study phase as the exposure and facility practice measures as potential mediators. RESULTS: In Europe, we observed a 13% improvement in overall case-mix adjusted survival per decade. Trends in facility practice measures, especially Kt/V and phosphorus, explained 10% improvement in case-mix survival per decade, representing 77% (10% explained of 13% improvement) of the observed improvement. In Japan, 73% of the observed 12%/decade improvement in case-mix adjusted survival could be attributed to facility practices, especially Kt/V and IDWG. In the US, 56% of the observed 47%/decade improvement in case-mix adjusted survival could be attributed to facility practices, especially AV fistula use and phosphorus control. LIMITATIONS: Unmeasured changes in the characteristics of the patient population over this period may confound the observed associations. CONCLUSION: The improvements in adjusted hemodialysis patient survival in Europe, Japan, and the US from 1999 to 2015 can be largely explained by improvements in specific facility practices. Future changes in patient survival may be responsive to further evolution in the implementation of common clinical practices.