The Time-Varying Impact of COVID-19 on the Acute Kidney Disorders: A Historical Matched Cohort Study and Mendelian Randomization Analysis.

Background: This study aimed to explore the time-varying impact of COVID-19 on acute kidney disorders, including acute kidney injury and other acute kidney diseases. Methods: From the UK Biobank, 10,121 participants with COVID-19 were matched with up to 3 historically unexposed controls by age, sex, Townsend deprivation index, and the status of hospitalization or receiving critical care. We investigated the association between COVID-19 and incidence of acute kidney disorders, within the first 4 weeks after infection, using conditional and time-varying Cox proportional hazard regression. In addition, one-sample Mendelian randomization, utilizing the polygenic risk score for COVID-19 as an instrumental variable, was conducted to explore the potential causality of the association. Results: In the matched cohort study, we observed a significant association between COVID-19 and acute kidney disorders predominantly within the first 3 weeks. The impact of COVID-19 was time dependent, peaking in the second week (hazard ratio, 12.77; 95% confidence interval, 5.93 to 27.70) and decreasing by the fourth week (hazard ratio, 2.28; 95% confidence interval, 0.75 to 6.93). In subgroup analyses, only moderate to severe COVID-19 cases were associated with acute worsening of renal function in a time-dependent pattern. One-sample Mendelian randomization analyses further showed that COVID-19 might exert a "short-term" causal effect on the risk of acute kidney disorders, primarily confined to the first week after infection. Conclusions: The risk of acute kidney disorders following COVID-19 demonstrates a time-varying pattern. Hazard effects were observed only in patients with moderate or severe but not mild COVID-19.

Cardiovascular Disease, Genetic Susceptibility, and Risk of Psychiatric Disorders and Suicide Attempt: A Community-Based Matched Cohort Study Based on the UK Biobank.

BACKGROUND: The associations between cardiovascular disease (CVD) and multiple psychiatric disorders and suicide attempt, and whether different genetic susceptibilities affect such links, have not been investigated clearly. METHODS AND RESULTS: Based on the UK Biobank, we conducted a matched cohort study involving 63 923 patients who were first hospitalized with a CVD diagnosis between 1997 and 2020, and their 127 845 matched unexposed individuals. Cox models were used to examine the subsequent risk of psychiatric disorders and suicide attempt (ie, anxiety, depression, stress-related disorder, substance misuse, psychotic disorder, and suicide behaviors) following CVD. We further performed stratified analyses by polygenic risk score for each studied psychiatric condition to detect the possible effects of genetic susceptibility on the observed associations. We found an increased risk of any psychiatric disorders and suicide attempt among CVD patients, compared with matched unexposed individuals, particularly within 1 year following the CVD (fully adjusted hazard ratio [HR] within 1 year, 1.83 [95% CI, 1.58-2.12]; HR after 1 year, 1.24 [95% CI, 1.16-1.32]). By subtype, the risk elevations existed for any psychiatric disorders and suicide attempt following most categories of CVDs. Analyses stratified by polygenic risk score revealed little impact of genetic predisposition to studied psychiatric conditions on these observed links. CONCLUSIONS: Patients hospitalized for CVD were at increased subsequent risk of multiple types of psychiatric disorders and suicide attempt, especially in the first year after hospitalization, irrespective of their genetic susceptibilities to studied psychiatric conditions, and these findings underscore the necessity of developing timely psychological interventions for this vulnerable population.

Development of a microfluidic wearable electrochemical sensor for the non-invasive monitoring of oxidative stress biomarkers in human sweat.

Oxidative stress is widely recognized as a pivotal factor contributing to numerous Central Nervous System (CNS) ailments. The concentrations of hydrogen peroxide (H2O2) and phosphorylated proteins within the human body serve as crucial indicators of oxidative stress. As such, the real-time monitoring of H2O2 and phosphorylated proteins in sweat is vital for the early identification, diagnosis, and management of diseases linked to oxidative stress. In this context, we present a novel microfluidic wearable electrochemical sensor by modifying the electrode with Prussian blue (PB) and loading sulfur-rich vacancy-containing molybdenum disulfide (MoS2-X) onto Multi-walled carbon nanotube (CNTs) to form coaxially layered CNTs/MoS2-X, which was then synthesized with highly dispersed titanium dioxide nanoparticles (TiO2) to synthesize CNTs/MoS2-X/TiO2 composites for the detection of human sweat H2O2 and phosphorylated proteins, respectively. This structure, with its sulfur vacancies and coaxial layering, significantly improved sensitivity of electrochemical sensors, allowing it to detect H2O2 in a range of 0.01-1 mM with a detection limit of 4.80 µM, and phosphoproteins in a range of 0.01-1 mg/mL with a threshold of 0.917 µg/mL. Furthermore, the miniature sensor demonstrates outstanding performance in detecting analytes in both simulated and real sweat. Comprehensive biosafety assessments have validated the compatibility of the electrode material, underscoring the potential of sensor as a reliable and non-invasive method for tracking biomarkers linked to CNS disorders. This microfluidic wearable electrochemical biosensor with high performance and biosafety features shows great promise for the development of cutting-edge wearable technology devices for tracking CNS disease indicators.

Causal association and mediating effect of blood biochemical metabolic traits and brain image-derived endophenotypes on Alzheimer's disease.

Background: Recent genetic evidence supports that circulating biochemical and metabolic traits (BMTs) play a causal role in Alzheimer's disease (AD), which might be mediated by changes in brain structure. Here, we leveraged publicly available genome-wide association study data to investigate the intrinsic causal relationship between blood BMTs, brain image-derived phenotypes (IDPs) and AD. Methods: Utilizing the genetic variants associated with 760 blood BMTs and 172 brain IDPs as the exposure and the latest AD summary statistics as the outcome, we analyzed the causal relationship between blood BMTs and brain IDPs and AD by using a two-sample Mendelian randomization (MR) method. Additionally, we used two-step/mediation MR to study the mediating effect of brain IDPs between blood BMTs and AD. Results: Twenty-five traits for genetic evidence supporting a causal association with AD were identified, including 12 blood BMTs and 13 brain IDPs. For BMTs, glutamine consistently reduced the risk of AD in 3 datasets. For IDPs, specific alterations of cortical thickness (atrophy in frontal pole and insular lobe, and incrassation in superior parietal lobe) and subcortical volume (atrophy in hippocampus and its subgroups, left accumbens and left choroid plexus, and expansion in cerebral white matter) are vulnerable to AD. In the two-step/mediation MR analysis, superior parietal lobe, right hippocampal fissure and left accumbens were identified to play a potential mediating role among three blood BMTs and AD. Conclusions: The results obtained in our study suggest that 12 circulating BMTs and 13 brain IDPs play a causal role in AD. Importantly, a subset of BMTs exhibit shared genetic architecture and potentially causal relationships with brain structure, which may contribute to the alteration of brain IDPs in AD.

Inspecting mother-to-infant microbiota transmission: disturbance of strain inheritance by cesarian section.

Introduction: The initial acquisition and subsequent development of the microbiota in early life is crucial to future health. Cesarean-section (CS) birth is considered to affect early microbial transmission from mother to infant. Methods: In this study, we collected fecal samples from 34 CS infants and their mothers from West China Second Hospital, Sichuan University to assess the microbiota developmental trajectory of mothers and infants. We explored mother-infant gut microbiome transmission via comparison with corresponding Finnish data. Results: Metagenomic analysis of gut microbiota profiles indicated that the communities of mothers and infants were distinct. The composition of the infant gut microbiome was highly variable but also followed predictable patterns in the early stages of life. Maternal communities were stable and mainly dominated by species from Bacteroidacea spp. We used PStrain to analyze and visualize strain transmission in each mother-infant pair. Excluding missing data, we included 32 mother-infant pairs for analysis of strain transmission. Most CS deliveries (65.6%, 21/32) did not demonstrate transmission of strains from mother to infant. To further explore the mother-infant strain transmission, we analyzed metagenomics data from Finnish mother-infant pairs. A total of 32 mother-infant pairs were included in the analysis, including 28 vaginal delivery (VD) infants and four CS infants. Strain transmission was observed in 30 infants, including 28 VD infants and two CS infants. All VD infants received transmitted stains from their mothers. Finally, a total of 193 strain transmission events were observed, comprising 131 strains and 45 species. Discussion: Taken together, our data suggested that delivery mode was an important factor influencing the mother-infant strain transmission.