Human Microbiome Mixture Analysis Using Weighted Quantile Sum Regression

: Studies of the health effects of the microbiome often measure overall associations by using diversity metrics, and individual taxa associations in separate analyses, but do not consider the correlated relationships between taxa in the microbiome. In this study, we applied random subset weighted quantile sum regression with repeated holdouts (WQSRSRH), a mixture method successfully applied to 'omic data to account for relationships between many predictors, to processed amplicon sequencing data from the Human Microbiome Project. We simulated a binary variable associated with 20 operational taxonomic units (OTUs). WQSRSRH was used to test for the association between the microbiome and the simulated variable, adjusted for sex, and sensitivity and specificity were calculated. The WQSRSRH method was also compared to other standard methods for microbiome analysis. The method was further illustrated using real data from the Growth and Obesity Cohort in Chile to assess the association between the gut microbiome and body mass index. In the analysis with simulated data, WQSRSRH predicted the correct directionality of association between the microbiome and the simulated variable, with an average sensitivity and specificity of 75% and 70%, respectively, in identifying the 20 associated OTUs. WQSRSRH performed better than all other comparison methods. In the illustration analysis of the gut microbiome and obesity, the WQSRSRH analysis identified an inverse association between body mass index and the gut microbe mixture, identifying Bacteroides, Clostridium, Prevotella, and Ruminococcus as important genera in the negative association. The application of WQSRSRH to the microbiome allows for analysis of the mixture effect of all the taxa in the microbiome, while simultaneously identifying the most important to the mixture, and allowing for covariate adjustment. It outperformed other methods when using simulated data, and in analysis with real data found results consistent with other study findings

COVID-19 incidence and mortality in Lombardy, Italy: An ecological study on the role of air pollution, meteorological factors, demographic and socioeconomic variables

Lombardy, the most populated and industrialized Italian region, was the epicentre of the first wave (March and April 2020) of COVID-19 in Italy and it is among the most air polluted areas of Europe. We carried out an ecological study to assess the association between long-term exposure to particulate matter (PM) and nitrogen dioxide (NO2) on COVID-19 incidence and all-cause mortality after accounting for demographic, socioeconomic and meteorological variables. The study was based on publicly available data. Multivariable negative binomial mixed regression models were fitted, and results were reported in terms of incidence rate ratios (IRRs) and standardized mortality ratios (SMR). The effect of winter temperature and humidity was modelled through restricted cubic spline. Data from 1439 municipalities out of 1507 (95%) were included in the analyses, leading to a total of 61,377 COVID-19 cases and 40,401 deaths from all-causes collected from February 20th to April 16th and from March 1st to April 30th, 2020, respectively. Several demographic and socioeconomic variables resulted significantly associated with COVID-19 incidence and all-cause mortality in a multivariable fashion. An increase in average winter temperature was associated with a nonlinear decrease in COVID-19 incidence and all-cause mortality, while an opposite trend emerged for the absolute humidity. An increase of 10 μg/m3 in the mean annual concentrations of PM2.5 and PM10 over the previous years was associated with a 58% and 34% increase in COVID-19 incidence rate, respectively. Similarly, a 10 μg/m3 increase of annual mean PM2.5 concentration was associated with a 23% increase in all-cause mortality. An inverse association was found between NO2 levels and COVID-19 incidence and all-cause mortality. Our ecological study showed that exposure to PM was significantly associated with the COVID-19 incidence and excess mortality during the first wave of the outbreak in Lombardy, Italy

Non-alcoholic to metabolic associated fatty liver disease: Cardiovascular implications of a change in terminology in patients living with HIV

Background and Aims: It has recently been suggested that the definition of non-alcoholic fatty liver disease (NAFLD) be changed to Metabolic Associated FLD (MAFLD) to better reflect the complex metabolic aspects of this syndrome. We compared the ability of MAFLD and NAFLD to correctly identify high CV risk patients, sub-clinical atherosclerosis or a history of prior CV events (CVEs) in patients living with HIV (PWH). Methods: Single center, cross-sectional study of PWH on stable anti-retrovirals. NAFLD was diagnosed by transient liver elastography; published criteria were used to diagnose MAFLD (JHepatol.2020;73(1):202-209). Four mutually exclusive groups were considered: low (<7.5%) vs high (>7.5%) ASCVD risk, subclinical CVD (carotid IMT ≥1 mm and/or coronary calcium score >100), and prior CVEs. The association of NAFLD and MAFLD with the CVD risk groups was explored via a multinominal model adjusted for age, sex, liver fibrosis, HIV duration, nadir CD4 and current CD4 cell count. Results: We included 1249 PWH (mean age 55 years, 74% men, median HIV duration 24 years). Prevalence of overweight/obesity and diabetes was 40% and 18%. Prevalence of NAFLD and MAFLD and overlapping groups are shown in Fig 1A. Fig 1B shows distribution of NAFLD/MAFLD in the 4 patient categories (p-for-trend <0.001). Both MAFLD and NAFLD were significantly associated with an increased risk of CVD compared to the reference level (ASCVD<7.5%) (all p-values <0.004; Fig 2). Conclusions: NAFLD and MAFLD perform equally in detecting CVD or its risk. The proposed change in terminology may not help to identify PWH requiring enhanced surveillance and preventative interventions for cardiovascular disease

Relationships of Nutritional Factors and Agrochemical Exposure with Parkinson's Disease in the Province of Brescia, Italy

Environmental exposures to agrochemicals and nutritional factors may be associated with Parkinson's Disease (PD). None of the studies to date has examined the combined effects of diet and agricultural chemical exposure together. To address these research gaps, we aimed to assess the association of nutritional factors and agrochemical exposure with the risk of PD. A hospital-based case-control study was conducted. Multivariable logistic regressions were used to estimate the association of nutritional and agrochemical exposures with PD, adjusting for gender, age, socio-economic status, head injury, family history, smoking, metals exposure, and alpha-synuclein gene polymorphism. Weighted Quantile Sum (WQS) regression was applied to examine the effect of dietary components as a mixture. We recruited 347 cases and 389 controls. Parent history of PD (OR = 4.15, 95%CI: 2.10, 8.20), metals exposure (OR = 2.50, 95%CI: 1.61-3.89), SNCA rs356219 polymorphism (OR = 1.39, 95%CI: 1.04-1.87 for TC vs. TT; OR = 2.17, 95%CI: 1.43-3.28 for CC vs. TT), agrochemical exposures (OR = 2.11, 95%CI: 1.41-3.16), and being born in the Brescia province (OR = 1.83, 95%CI: 1.17-2.90) were significantly associated with PD. Conversely, fish intake and coffee consumption had a protective effect. The study confirmed the role of environmental exposures in the genesis of PD. Fish intake and coffee consumption are protective factors even when agricultural chemical exposures exist. Genetic factors and metals exposure were confirmed as risk factors for PD

Impact of COVID-19-Related Social Isolation on Behavioral Outcomes in Young Adults Residing in Northern Italy

: Social isolation affects our emotions, behavior and interactions. Worldwide, individuals experienced prolonged periods of isolation during the first wave of the COVID-19 pandemic when authorities-imposed restrictions to reduce the spread of the virus. In this study, we investigated the effects of social isolation on emotional and behavioral outcomes in young adults from Lombardy, Italy, a global hotspot of COVID-19. We leveraged baseline (pre-social isolation) and follow-up (mid- or post-isolation) data collected from young adults enrolled in the ongoing, longitudinal Public Health Impact of Metals Exposure (PHIME) study. At baseline, 167 participants completed the ASEBA questionnaires (ASR/YSR) by web link or in person; 65 completed the ASR 12-18 weeks after the onset of restrictions. Using the sign test and multiple linear regression models, we examined differences in ASR scores between baseline and follow-up adjusting for sex, age, pre-pandemic IQ and time with social restrictions (weeks). Further, we examined interactions between sex and time in social isolation. Participants completed the ASR after spending an average of 14 weeks in social isolation (range 12-18 weeks). Thought problems increased between baseline and follow-up (median difference 1.0; 1st, 3rd quartile: -1.0, 4.0; p = 0.049). Among males, a longer time in social isolation (≥14 weeks) was associated with increased rule-breaking behaviors of 2.8 points. These results suggest the social isolation related to COVID-19 adversely impacted mental health. In particular, males seem to externalize their condition. These findings might help future interventions and treatment to minimize the consequences of social isolation experience in young adults

ENIGMA—A Centralised Supervisory Controller for Enhanced Onboard Electrical Energy Management with Model in the Loop Demonstration

A centralised smart supervisor (CSS) controller with enhanced electrical energy management (E2-EM) capability has been developed for an Iron Bird Electrical Power Generation and Distribution System (EPGDS) within the Clean Sky 2 ENhanced electrical energy MAnagement (ENIGMA) project. The E2-EM strategy considers the potential for eliminating the 5 min overload capability of the generators to achieve a substantial reduction in the mass of the EPGDS. It ensures optimal power and energy sharing within the EPGDS by interfacing the CSS with the smart grid network (SGN), the energy storage and regeneration system (ESRS), and the programmable load bank 1 secondary distribution board (PLB1 SDU) during power overloads and failure conditions. The CSS has been developed by formalizing E2-EM logic as an algorithm operating in real time and by following safety and reliability rules. The CSS undergoes initial verification using model-in-the-loop (MIL) testing. This paper describes the EPGDS simulated for the MIL testing and details the E2-EM strategy, the algorithms, and logic developed for the ENIGMA CSS design. The CSS was subjected to two test cases using MIL demonstration, and based on the test results, the performance of the ENIGMA CSS is verified and validated

Topological network properties of resting-state functional connectivity patterns are associated with metal mixture exposure in adolescents

IntroductionAdolescent exposure to neurotoxic metals adversely impacts cognitive, motor, and behavioral development. Few studies have addressed the underlying brain mechanisms of these metal-associated developmental outcomes. Furthermore, metal exposure occurs as a mixture, yet previous studies most often consider impacts of each metal individually. In this cross-sectional study, we investigated the relationship between exposure to neurotoxic metals and topological brain metrics in adolescents. MethodsIn 193 participants (53% females, ages: 15-25 years) enrolled in the Public Health Impact of Metals Exposure (PHIME) study, we measured concentrations of four metals (manganese, lead, copper, and chromium) in multiple biological media (blood, urine, hair, and saliva) and acquired resting-state functional magnetic resonance imaging scans. Using graph theory metrics, we computed global and local efficiency (global:GE; local:LE) in 111 brain areas (Harvard Oxford Atlas). We used weighted quantile sum (WQS) regression models to examine association between metal mixtures and each graph metric (GE or LE), adjusted for sex and age. ResultsWe observed significant negative associations between the metal mixture and GE and LE [beta GE = -0.076, 95% CI (-0.122, -0.031); beta LE= -0.051, 95% CI (-0.095, -0.006)]. Lead and chromium measured in blood contributed most to this association for GE, while chromium measured in hair contributed the most for LE. DiscussionOur results suggest that exposure to this metal mixture during adolescence reduces the efficiency of integrating information in brain networks at both local and global levels, informing potential neural mechanisms underlying the developmental toxicity of metals. Results further suggest these associations are due to combined joint effects to different metals, rather than to a single metal

The clinical effectiveness of an integrated multidisciplinary evidence-based program to prevent intraoperative pressure injuries in high-risk children undergoing long-duration surgical procedures: a quality improvement study

The prevention of hospital-acquired pressure injuries (HAPIs) in children undergoing long-duration surgical procedures is of critical importance due to the potential for catastrophic sequelae of these generally preventable injuries for the child and their family. Long-duration surgical procedures in children have the potential to result in high rates of HAPI due to physiological factors and the difficulty or impossibility of repositioning these patients intraoperatively. We developed and implemented a multi-modal, multi-disciplinary translational HAPI prevention quality improvement program at a large European Paediatric University Teaching Hospital. The intervention comprised the establishment of wound prevention teams, modified HAPI risk assessment tools, specific education, and the use of prophylactic dressings and fluidized positioners during long-duration surgical procedures. As part of the evaluation of the effectiveness of the program in reducing intraoperative HAPI, we conducted a prospective cohort study of 200 children undergoing long-duration surgical procedures and compared their outcomes with a matched historical cohort of 200 children who had undergone similar surgery the previous year. The findings demonstrated a reduction in HAPI in the intervention cohort of 80% (p < 0.01) compared to the comparator group when controlling for age, pathology, comorbidity, and surgical duration. We believe that the findings demonstrate that it is possible to significantly decrease HAPI incidence in these highly vulnerable children by using an evidence-based, multi-modal, multidisciplinary HAPI prevention strategy