BACKGROUND: The study examined how plasma proteome indicators may explain the link between poor cardiovascular health (CVH) and dementia risk. METHODS: The present study involved 28,974 UK Biobank participants aged 50-74y at baseline (2006-2010) who were followed-up for ≤ 15 y for incidence of dementia. CVH was calculated using Life's Essential 8 (LE8) total scores. The scores were standardized and reverse coded to reflect poor CVH (LE8z_rev). OLINK proteomics was available on this sample (k = 1,463 plasma proteins). The study primarily tested the mediating effects of the plasma proteome in LE8z_rev-dementia effect. The total effect was decomposed into "mediation only" or pure indirect effect (PIE), "interaction only" or interaction referent (INTREF), "neither mediation nor interaction" or controlled direct effect (CDE), and "both mediation and interaction" or mediated interaction (INTMED). RESULTS: The study found poorer CVH assessed by LE8z_rev increased the risk of all-cause dementia by 11 % [per 1 SD, hazard ratio, (HR) = 1.11, 95 % CI: 1.03-1.20, p = 0.005). The study identified 11 plasma proteins with strong mediating effects, with GDF15 having the strongest association with dementia risk (per 1 SD, HR = 1.24, 95 % CI: 1.16, 1.33, P < 0.001 when LE8z_rev is set at its mean value) and the largest proportion mediated combining PIE and INTMED (62.6 %; 48 % of TE is PIE), followed by adrenomedullin or ADM. A first principal component with 10 top mediators (TNFRSF1A, GDF15, FSTL3, COL6A3, PLAUR, ADM, GFRAL, ACVRL1, TNFRSF6B, TGFA) mediated 53.6 % of the LE8z_rev-dementia effect. Using all the significant PIE (k = 526) proteins, we used OLINK Insight pathway analysis to identify key pathways, which revealed the involvement of the immune system, signal transduction, metabolism, disease, protein metabolism, hemostasis, membrane trafficking, extracellular matrix organization, developmental biology, and gene expression among others. STRING analysis revealed that five top consistent proteomic mediators were represented in two larger clusters reflecting numerous interconnected biological gene ontology pathways, most notably cytokine-mediated signaling pathway for GDF15 cluster (GO:0019221) and regulation of peptidyl-tyrosine phosphorylation for the ADM cluster (GO:0050730). CONCLUSION: Dementia is linked to poor CVH mediated by GDF15 and ADM among several key proteomic markers which collectively explained â¼ 54 % of the total effect.
Photodamage is one of the most common causes of skin injury. High molecular weight hyaluronic acid (HHA) has shown immense potential in the treatment of skin photodamage by virtue of its anti-inflammatory, reparative, and antioxidative properties. However, due to its large molecular structure of HHA, HHA solution could only form a protective film on the skin surface in conventional application, failing to effectively penetrate the skin, which necessitates the development of new delivery strategies. Liposomes, with a structure similar to biological membranes, have garnered extensive attention as transdermal drug delivery carriers because of their advantages in permeability, dermal compatibility, and biosafety. Herein, we have developed a HHA-liposome transdermal system (HHL) by embedding HHA into the liposome structure using reverse evaporation, high-speed homogenization, and micro-jet techniques. The effective penetration and long-term residence of HHA in skin tissue were multidimensionally verified, and the kinetics of HHA in the skin were extensively studied. Moreover, it was demonstrated that HHL significantly strengthened the activity of human keratinocytes and effectively inhibits photo-induced cellular aging in vitro. Furthermore, a murine model of acute skin injury induced by laser ablation was established, where the transdermal system showed significant anti-inflammatory and immunosuppressive properties, promoting skin proliferation and scar repair, thereby demonstrating immense potential in accelerating skin wound healing. Meanwhile, HHL significantly ameliorated skin barrier dysfunction caused by simulated sunlight exposure, inhibited skin erythema, inflammatory responses, and oxidative stress, and promoted collagen expression in a chronic photodamage skin model. Therefore, this transdermal delivery system with biocompatibility represents a promising new strategy for the non-invasive application of HHA in skin photodamage, revealing the significant potential for clinical translation and broad application prospects. STATEMENT OF SIGNIFICANCE: The transdermal system utilizing hyaluronic acid-based liposomes enhances skin permeability and retains high molecular weight hyaluronic acid (HHL). In vitro experiments with human keratinocytes demonstrate significant skin repair effects of HHL and its effective inhibition of cellular aging. In an acute photodamage model, HHL exhibits stronger anti-inflammatory and immunosuppressive properties, promoting skin proliferation and scar repair. In a chronic photodamage model, HHL significantly improves skin barrier dysfunction, reduces oxidative stress induced by simulated sunlight, and enhances collagen expression.
Pathways explaining racial/ethnic and socio-economic status (SES) disparities in white matter integrity (WMI) reflecting brain health, remain underexplored, particularly in the UK population. We examined racial/ethnic and SES disparities in diffusion tensor brain magnetic resonance imaging (dMRI) markers, namely global and tract-specific mean fractional anisotropy (FA), and tested total, direct and indirect effects through lifestyle, health-related and cognition factors using a structural equations modeling approach among 36,184 UK Biobank participants aged 40-70 y at baseline assessment (47% men). Multiple linear regression models were conducted, testing independent associations of race/ethnicity, socio-economic and other downstream factors in relation to global mean FA, while stratifying by Alzheimer's Disease polygenic Risk Score (AD PRS) tertiles. Race (Non-White vs. White) and lower SES predicted poorer WMI (i.e. lower global mean FA) at follow-up, with racial/ethnic disparities in FAmean involving multiple pathways and SES playing a central role in those pathways. Mediational patterns differed across tract-specific FA outcomes, with SES-FAmean total effect being partially mediated (41% of total effect = indirect effect). Furthermore, the association of poor cognition with FAmean was markedly stronger in the two uppermost AD PRS tertiles compared to the lower tertile (T2 and T3: ß±SE: -0.0009 ± 0.0001 vs. T1: ß±SE: -0.0005 ± 0.0001, P < 0.001), independently of potentially confounding factors. Race and lower SES were generally important determinants of adverse WMI outcomes, with partial mediation of socio-economic disparities in global mean FA through lifestyle, health-related and cognition factors. The association of poor cognition with lower global mean FA was stronger at higher AD polygenic risk.
Elephants have a unique auditory system that is larger than any other terrestrial mammal. To quantify the impact of larger middle ear (ME) structures, we measured 3D ossicular motion and ME sound transmission in cadaveric temporal bones from both African and Asian elephants in response to air-conducted (AC) tonal pressure stimuli presented in the ear canal (PEC). Results were compared to similar measurements in humans. Velocities of the umbo (VU) and stapes (VST) were measured using a 3D laser Doppler vibrometer in the 7-13,000 Hz frequency range, stapes velocity serving as a measure of energy entering the cochlea-a proxy for hearing sensitivity. Below the elephant ME resonance frequency of about 300 Hz, the magnitude of VU/PEC was an order of magnitude greater than in human, and the magnitude of VST/PEC was 5x greater. Phase of VST/PEC above ME resonance indicated that the group delay in elephant was approximately double that of human, which may be related to the unexpectedly high magnitudes at high frequencies. A boost in sound transmission across the incus long process and stapes near 9 kHz was also observed. We discuss factors that contribute to differences in sound transmission between these two large mammals.
Elephants , Animals , Humans , Ear, Middle/physiology , Sound , Stapes/physiology , Hearing/physiology , Vibration
The goal of this study is to investigate the association between chronic non-cancer pain (CNCP) and mild cognitive impairment (MCI)/Alzheimer's disease and related dementias (ADRDs) development among adults aged ≥50 using administrative claims data from a national commercial health insurance company during 2007-2017. To reduce selection bias, propensity-score matching was applied to select comparable CNCP and non-CNCP patients. Time-dependent Cox proportional-hazards regressions were conducted to estimate the hazard ratios (HRs) of incident MCI/ADRDs. Of 170,900 patients with/without CNCP, 0.61% developed MCI and 2.33% had been diagnosed with ADRDs during the follow-up period. Controlling for potential confounders, CNCP patients had a 123% increase in MCI risk (HR = 2.23; 95% CI = 1.92-2.58) and a 44% increase in ADRDs risk (HR = 1.44; 95% CI = 1.34-1.54) relative to non-CNCP patients. CNCP is a risk factor for MCI/ADRDs. Promoting awareness and improving early CNCP diagnosis in middle-aged and older adults should be incorporated into cognitive impairment and dementia prevention.
Persistent infections, whether viral, bacterial or parasitic, including Helicobacter pylori infection, have been implicated in non-communicable diseases, including dementia and other neurodegenerative diseases. In this cross-sectional study, data on 635 cognitively normal participants from the UK Biobank study (2006-21, age range: 40-70 years) were used to examine whether H. pylori seropositivity (e.g. presence of antibodies), serointensities of five H. pylori antigens and a measure of total persistent infection burden were associated with selected brain volumetric structural MRI (total, white, grey matter, frontal grey matter (left/right), white matter hyperintensity as percent intracranial volume and bi-lateral sub-cortical volumes) and diffusion-weighted MRI measures (global and tract-specific bi-lateral fractional anisotropy and mean diffusivity), after an average 9-10 years of lag time. Persistent infection burden was calculated as a cumulative score of seropositivity for over 20 different pathogens. Multivariable-adjusted linear regression analyses were conducted, whereby selected potential confounders (all measures) and intracranial volume (sub-cortical volumes) were adjusted, with stratification by Alzheimer's disease polygenic risk score tertile when exposures were H. pylori antigen serointensities. Type I error was adjusted to 0.007. We report little evidence of an association between H. pylori seropositivity and persistent infection burden with various volumetric outcomes (P > 0.007, from multivariable regression models), unlike previously reported in past research. However, H. pylori antigen serointensities, particularly immunoglobulin G against the vacuolating cytotoxin A, GroEL and outer membrane protein antigens, were associated with poorer tract-specific white matter integrity (P < 0.007), with outer membrane protein serointensity linked to worse outcomes in cognition-related tracts such as the external capsule, the anterior limb of the internal capsule and the cingulum, specifically at low Alzheimer's disease polygenic risk. Vacuolating cytotoxin A serointensity was associated with greater white matter hyperintensity volume among individuals with mid-level Alzheimer's disease polygenic risk, while among individuals with the highest Alzheimer's disease polygenic risk, the urease serointensity was consistently associated with reduced bi-lateral caudate volumes and the vacuolating cytotoxin A serointensity was linked to reduced right putamen volume (P < 0.007). Outer membrane protein and urease were associated with larger sub-cortical volumes (e.g. left putamen and right nucleus accumbens) at middle Alzheimer's disease polygenic risk levels (P < 0.007). Our results shed light on the relationship between H. pylori seropositivity, H. pylori antigen levels and persistent infection burden with brain volumetric structural measures. These data are important given the links between infectious agents and neurodegenerative diseases, including Alzheimer's disease, and can be used for the development of drugs and preventive interventions that would reduce the burden of those diseases.
This study was designed to discern the effect of heavy scavenger metallothionein on glutathione (GSH) deprivation-evoked cardiac anomalies and mechanisms involved with an emphasis on ferroptosis. Wild-type and cardiac metallothionein transgenic mice received GSH synthase inhibitor buthionine sulfoximine (BSO; 30 mmol/L in drinking water) for 14 days before assessment of myocardial morphology and function. BSO evoked cardiac remodeling and contractile anomalies, including cardiac hypertrophy, interstitial fibrosis, enlarged left ventricular chambers, deranged ejection fraction, fraction shortening, cardiomyocyte contractile capacity, intracellular Ca2+ handling, sarcoplasmic reticulum Ca2+ reuptake, loss of mitochondrial integrity (mitochondrial swelling, loss of aconitase activity), mitochondrial energy deficit, carbonyl damage, lipid peroxidation, ferroptosis, and apoptosis. Metallothionein itself did not affect myocardial morphology and function, although it mitigated BSO-provoked myocardial anomalies, loss of mitochondrial integrity and energy, and ferroptosis. Immunoblotting revealed down-regulated sarco(endo)plasmic reticulum Ca2+-ATPase 2a, glutathione peroxidase 4, ferroptosis-suppressing CDGSH iron-sulfur domain 1 (CISD1), and mitochondrial regulating glycogen synthase kinase-3ß phosphorylation with elevated p53, myosin heavy chain-ß isozyme, IκB phosphorylation, and solute carrier family 7 member 11 (SLC7A11) as well as unchanged SLC39A1, SLC1A5, and ferroptosis-suppressing protein 1 following BSO challenge, all of which, except glutamine transporter SLC7A11 and p53, were abrogated by metallothionein. Inhibition of CISD1 using pioglitazone nullified GSH-offered benefit against BSO-induced cardiomyocyte ferroptosis and contractile and intracellular Ca2+ derangement. Taken together, these findings support a regulatory modality for CISD1 in the impedance of ferroptosis in metallothionein-offered protection against GSH depletion-evoked cardiac aberration.
Cardiomyopathies , Ferroptosis , Glutathione , Metallothionein , Mice, Transgenic , Animals , Ferroptosis/drug effects , Metallothionein/metabolism , Mice , Cardiomyopathies/metabolism , Cardiomyopathies/pathology , Glutathione/metabolism , Oxidative Stress/drug effects , Myocardium/metabolism , Myocardium/pathology , Myocytes, Cardiac/metabolism , Myocytes, Cardiac/pathology , Myocytes, Cardiac/drug effects , Male , Buthionine Sulfoximine/pharmacology
A substantial portion of dementia risk can be attributed to modifiable risk factors that can be affected by lifestyle changes. Identifying the contributors to dementia risk could prove valuable. Recently, machine learning methods have been increasingly applied to healthcare data. Several studies have attempted to predict dementia progression by using such techniques. This study aimed to compare the performance of different machine-learning methods in modeling associations between known cognitive risk factors and future dementia cases. A subset of the AGES-Reykjavik Study dataset was analyzed using three machine-learning methods: logistic regression, random forest, and neural networks. Data were collected twice, approximately five years apart. The dataset included information from 1,491 older adults who underwent a cognitive screening process and were considered to have healthy cognition at baseline. Cognitive risk factors included in the models were based on demographics, MRI data, and other health-related data. At follow-up, participants were re-evaluated for dementia using the same cognitive screening process. Various performance metrics for all three machine learning algorithms were assessed. The study results indicate that a random forest algorithm performed better than neural networks and logistic regression in predicting the association between cognitive risk factors and dementia. Compared to more traditional statistical analyses, machine-learning methods have the potential to provide more accurate predictions about which individuals are more likely to develop dementia than others.
Dementia , Humans , Aged , Dementia/diagnosis , Dementia/epidemiology , Dementia/etiology , Machine Learning , Risk Factors , Cognition , Logistic Models
BACKGROUND: Infection burden (IB), although linked to neurodegeneration, including Alzheimer's Disease (AD), has not been examined against neurite orientation, dispersion, and density imaging (NODDI) measures. METHODS: Among 38,803 UK Biobank adults (Age:40-70 years), we tested associations of total IB (IBtotal, 47.5 %) and hospital-treated IB (IBhosp, 9.7 %) with NODDI measures (5-15 years later), including volume fraction of Gaussian isotropic diffusion (ISOVF), intra-cellular volume fraction (ICVF) and orientation dispersion (OD) indices, using multiple linear regression models. RESULTS: Total and hospital-treated infection burdens (IBtotal and IBhosp) were associated with increased ISOVF, indicating increased free-water component. IBtotal was positively associated with OD, indicating that at higher IBtotal there was greater fanning of neurites. This was more evident in the lower cardiovascular health group. IBhosp was associated with higher OD, and lower ICVF at higher AD polygenic risk. Together, these findings indicate that both total and hospital-treated infections have effects on NODDI outcomes in the direction of poor brain health. These effects were largely homogeneous across cardiovascular health and AD polygenic risk groups, with some effects shown to be stronger at poor cardiovascular health and/or higher AD risk. CONCLUSIONS: Total and hospital-treated infections were associated with poorer white matter microstructure (higher ISOVF or OD or lower ICVF), with some heterogeneity across cardiovascular health and AD risk. Longitudinal studies with multiple repeats on neuroimaging markers in comparable samples are needed.
Diffusion Tensor Imaging , White Matter , Diffusion Tensor Imaging/methods , Neurites , Biological Specimen Banks , Brain , White Matter/diagnostic imaging , Diffusion Magnetic Resonance Imaging/methods
Human gliomas are lethal brain cancers. Emerging evidence revealed the regulatory role of long noncoding RNAs (lncRNAs) in tumors. Here, we performed a comprehensive analysis of the expression profiles of RNAs in histologically lower-grade glioma (LGG). Enrichment analysis revealed that glioma is influenced by immune-related signatures. Survival analysis further established the close correlation between network features and glioma prognosis. Subsequent experiments showed lncRNA RP11-770J1.4 regulates CTXN1 expression through hsa-miR-124-3p. Correlation analysis identified lncRNA RP11-770J1.4 was immune related, specifically involved in the cytosolic DNA sensing pathway. Downregulated lncRNA RP11-770J1.4 resulted in increased spontaneous gene expression of the cGAS-STING pathway. Single-cell RNA sequencing analysis, along with investigations in a glioblastoma stem cell model and patient sample analysis, demonstrated the predominant localization of CTXN1 within tumor cores rather than peripheral regions. Immunohistochemistry staining established a negative correlation between CTXN1 expression and infiltration of CD8+ T cells. In vivo, Ctxn1 knockdown in GL261 cells led to decreased tumor burden and improved survival while increasing infiltration of CD8+ T cells. These findings unveil novel insights into the lncRNA RP11-770J1.4-CTXN1 as a potential immune regulatory axis, highlighting its therapeutic implications for histologically LGGs.
Total saponins of Codonopsis (TSC) are a kind of critical bioactive substances in Codonopsis, which have anti-inflammatory, antioxidant, anti-ulcer, immunomodulatory effects, and protective effects on ulcerative enteritis. In this study, TSC (3.75 mL/kg, gavage) was administered once a day to 13-day gestation Kunming mice for 5 days. On day 13 of birth, the offspring were given Escherichia coli solution (0.15 mL/mouse, intraperitoneal injection) and senna leaf decoction (0.15 mL/mouse, gavage) once a day for 6 days. The results showed that gestation maternal administration of TSC effectively reduced the diarrhea index, increased the content of sIgA, IgG, SOD, and GSH, inhibited the TLR4/MyD88/NF-κB pathway in the intestine, reduced the expression of inflammatory factors, and alleviated intestinal injury in the littermates. The results provided a critical reference for the clinical application of TSC to control diarrhea in animal offspring.
Codonopsis , Saponins , Mice , Animals , Antioxidants , Diarrhea , Immunity , Saponins/pharmacology
Elephants have a unique auditory system that is larger than any other terrestrial mammal. To quantify the impact of larger middle ear (ME) structures, we measured 3D ossicular motion and ME sound transmission in cadaveric temporal bones from both African and Asian elephants in response to air-conducted (AC) tonal pressure stimuli presented in the ear canal (P EC ). Results were compared to similar measurements in humans. Velocities of the umbo (V U ) and stapes (V ST ) were measured using a 3D laser Doppler vibrometer in the 7-13,000 Hz frequency range, stapes velocity serving as a measure of energy entering the cochlea-a proxy for hearing sensitivity. Below the elephant ME resonance frequency of about 300 Hz, the magnitude of V U /P EC was an order of magnitude greater than in human, and the magnitude of V ST /P EC was 5x greater. Phase of V ST /P EC above ME resonance indicated that the group delay in elephant was approximately double that of human, which may be related to the unexpectedly high magnitudes at high frequencies. A boost in sound transmission across the incus long process and stapes near 9 kHz was also observed. We discuss factors that contribute to differences in sound transmission between these two large mammals.
BACKGROUND: Early identification of dementia is crucial for prompt intervention for high-risk individuals in the general population. External validation studies on prognostic models for dementia have highlighted the need for updated models. The use of machine learning in dementia prediction is in its infancy and may improve predictive performance. The current study aimed to explore the difference in performance of machine learning algorithms compared to traditional statistical techniques, such as logistic and Cox regression, for prediction of all-cause dementia. Our secondary aim was to assess the feasibility of only using clinically accessible predictors rather than MRI predictors. METHODS: Data are from 4,793 participants in the population-based AGES-Reykjavik Study without dementia or mild cognitive impairment at baseline (mean age: 76 years, % female: 59%). Cognitive, biometric, and MRI assessments (total: 59 variables) were collected at baseline, with follow-up of incident dementia diagnoses for a maximum of 12 years. Machine learning algorithms included elastic net regression, random forest, support vector machine, and elastic net Cox regression. Traditional statistical methods for comparison were logistic and Cox regression. Model 1 was fit using all variables and model 2 was after feature selection using the Boruta package. A third model explored performance when leaving out neuroimaging markers (clinically accessible model). Ten-fold cross-validation, repeated ten times, was implemented during training. Upsampling was used to account for imbalanced data. Tuning parameters were optimized for recalibration automatically using the caret package in R. RESULTS: 19% of participants developed all-cause dementia. Machine learning algorithms were comparable in performance to logistic regression in all three models. However, a slight added performance was observed in the elastic net Cox regression in the third model (c = 0.78, 95% CI: 0.78-0.78) compared to the traditional Cox regression (c = 0.75, 95% CI: 0.74-0.77). CONCLUSIONS: Supervised machine learning only showed added benefit when using survival techniques. Removing MRI markers did not significantly worsen our model's performance. Further, we presented the use of a nomogram using machine learning methods, showing transportability for the use of machine learning models in clinical practice. External validation is needed to assess the use of this model in other populations. Identifying high-risk individuals will amplify prevention efforts and selection for clinical trials.
Dementia , Machine Learning , Humans , Female , Aged , Male , Proof of Concept Study , Supervised Machine Learning , Algorithms , Dementia/diagnosis , Dementia/epidemiology
In search for SDHIs fungicides, twenty-five novel carboxamides containing a chalcone scaffold were designed, synthesized, and evaluated for antifungal activities against five pathogenic fungi. The results showed that compound 5 k exhibited outstanding antifungal activity against R.â solani with an EC50 value of 0.20â µg/mL, which was much better than that of commercial SDHIs Boscalid (EC50 =0.74â µg/mL). Moreover, compound 5 k also displayed promising antifungal activities against S.â sclerotiorum, B.â cinerea, and A.â alternate (IC50 =2.53-4.06â µg/mL), indicating that 5 k had broad-spectrum antifungal activity. Additionally, inâ vivo antifungal activities results showed that 5 k could significantly inhibit the growth of R.â solani in rice leaves with good protective efficacy (57.78 %) and curative efficacy (58.45 %) at 100â µg/mL, both of which were much better than those of Boscalid, indicating a promising application prospect. Moreover, SEM analysis showed that compound 5 k could remarkably disrupt the typical structure and morphology of R.â solani hyphae. Further SDH enzyme inhibition assay and molecular docking study revealed that lead compound 5 k had a similar mechanism of action as commercial SDHI Boscalid. These results indicated that compound 5 k showed potential as a SDHIs fungicide and deserved further investigation.
Chalcone , Chalcones , Fungicides, Industrial , Antifungal Agents/chemistry , Structure-Activity Relationship , Chalcones/pharmacology , Chalcone/pharmacology , Molecular Docking Simulation
A link between neurodegenerative diseases and infections has been previously reported. However, it is not clear to what extent such link is caused by confounding factors or to what extent it is intimately connected with the underlying conditions. Further, studies on the impact of infections on mortality risk following neurodegenerative diseases are rare. We analysed two data sets with different characteristics: (i) a community-based cohort from the UK Biobank with 2023 patients with multiple sclerosis, 2200 patients with Alzheimer's disease, 3050 patients with Parkinson's disease diagnosed before 1 March 2020 and 5 controls per case who were randomly selected and individually matched to the case; (ii) a Swedish Twin Registry cohort with 230 patients with multiple sclerosis, 885 patients with Alzheimer's disease and 626 patients with Parkinson's disease diagnosed before 31 December 2016 and their disease-free co-twins. The relative risk of infections after a diagnosis of neurodegenerative disease was estimated using stratified Cox models, with adjustment for differences in baseline characteristics. Causal mediation analyses of survival outcomes based on Cox models were performed to assess the impact of infections on mortality. Compared with matched controls or unaffected co-twins, we observed an elevated infection risk after diagnosis of neurodegenerative diseases, with a fully adjusted hazard ratio (95% confidence interval) of 2.45 (2.24-2.69) for multiple sclerosis, 5.06 (4.58-5.59) for Alzheimer's disease and 3.72 (3.44-4.01) for Parkinson's disease in the UK Biobank cohort, and 1.78 (1.21-2.62) for multiple sclerosis, 1.50 (1.19-1.88) for Alzheimer's disease and 2.30 (1.79-2.95) for Parkinson's disease in the twin cohort. Similar risk increases were observed when we analysed infections during the 5 years before diagnosis of the respective disease. Occurrence of infections after diagnosis had, however, relatively little impact on mortality, as mediation of infections on mortality (95% confidence interval) was estimated as 31.89% (26.83-37.11%) for multiple sclerosis, 13.38% (11.49-15.29%) for Alzheimer's disease and 18.85% (16.95-20.97%) for Parkinson's disease in the UK Biobank cohort, whereas it was 6.56% (-3.59 to 16.88%) for multiple sclerosis, -2.21% (-0.21 to 4.65%) for Parkinson's disease and -3.89% (-7.27 to -0.51%) for Alzheimer's disease in the twin cohort. Individuals with studied neurodegenerative diseases display an increased risk of infections independently of genetic and familial environment factors. A similar magnitude of risk increase is present prior to confirmed diagnosis, which may indicate a modulating effect of the studied neurological conditions on immune defences.
BACKGROUND: Animal and human studies suggest the gut microbiome is linked to diabetes but additional data are needed on the associations of the gut microbiome to specific diabetes characteristics. The aim of this study was to examine the associations of gut microbiome composition to insulin resistance [Homeostatic Model Assessment of Insulin Resistance (HOMA-IR)], duration of diabetes, and 4 stages of diabetes [normoglycemia, pre-diabetes, and diabetes with (+) and without (-) medication for diabetes]. METHODS: Data are from a sub-sample (n = 605) of Black and White participants from the 30-year follow-up exam of the prospectively followed community-based Coronary Artery Risk Development in Young Adults cohort (2015-2016; aged 48-60 years). Stool samples were collected and sequenced using the 16S ribosomal RNA method. Microbial measures included: α diversity (within-person), ß diversity (between-person), and taxonomies. All analyses were adjusted for demographic, clinical, lifestyle factors, and use of relevant medications (full adjustment). Multivariate linear regression models were used to assess the association of diabetes characteristics with α diversity and genera abundance, while the association with ß diversity was analyzed using permutational multivariate analysis of variance. Statistical significance was set to p-value < 0.05 for α and ß diversity analyses and to q-value < 0.1 for genera abundance analyses. RESULTS: There were 16.7% of participants with pre-diabetes, and 14.4% with diabetes (9% diabetes+) with median (interquartile range) diabetes duration of 5 (5-10) years. In the fully adjusted models, compared to those with no diabetes, longer diabetes duration and the diabetes + group had a lower α diversity. There were significant differences in ß diversity across diabetes-related characteristics. A significantly reduced abundance of butyrate-producing genera was associated with higher HOMA-IR (ex., Anaerostipes and Lachnospiraceae_UCG.004), longer diabetes duration (ex., Agathobacter and Ruminococcus), and diabetes + (ex., Faecalibacterium and Romboutsia). CONCLUSIONS: Our results suggest that an adverse alteration of gut microbiome composition is related to higher insulin resistance, longer diabetes duration, and is present in those persons with diabetes using medications. These diabetes-related characteristics were also associated with lower levels of certain butyrate-producing bacteria that produce health-promoting short-chain fatty acids. Understanding the role of gut microbiota in glucose regulation may provide new strategies to reduce the burden of diabetes.
OBJECTIVES: Given the role of intraocular pressure in glaucoma, the patient's sleeping pattern might contribute to the development and progression of glaucoma. We performed a study to understand the association between sleep behaviours and glaucoma. DESIGN: Our study was a prospective cohort study. SETTING: This was a prospective cohort study in the UK Biobank. Self-reported data on five sleep behaviours were collected using a questionnaire at baseline. We identified four sleep patterns based on a cluster analysis of the sleep behaviours. PARTICIPANTS: In the UK Biobank, 409 053 participants were recruited between 2006 and 2010 and followed for a diagnosis of glaucoma. We identified glaucoma as any hospital admission with a diagnosis of glaucoma, based on UK Biobank inpatient hospital data. Individuals who withdrew from the UK Biobank, or were diagnosed with glaucoma before recruitment, or had self-reported surgery or laser treatment for glaucoma, or had no information on sleep behaviors were excluded. PRIMARY AND SECONDARY OUTCOME MEASURES: We estimated hazard ratios (HRs) with 95% confidence intervals (CI) using Cox proportional hazards models to estimate the associations of different sleep behaviors, as well as identified sleep patterns, with the risk of glaucoma, adjusting for multiple confounders. RESULTS: Compared with individuals who had a healthy sleep pattern, an excess risk of any glaucoma was observed among individuals with snoring and daytime sleepiness (HR 1.11, 95% CI 1.03 to 1.19) or insomnia and short/long sleep duration (HR 1.13, 95% CI 1.06 to 1.20), but not late chronotype sleep pattern (HR 0.98, 95% CI 0.93 to 1.03). CONCLUSION: Snoring, daytime sleepiness, insomnia, and short/long duration, individually or jointly, were all associated with the risk of glaucoma. These findings underscore the need for sleep intervention for individuals at high risk of glaucoma as well as potential ophthalmologic screening among individuals with chronic sleep problems for glaucoma prevention.
Disorders of Excessive Somnolence , Glaucoma , Sleep Initiation and Maintenance Disorders , Sleep Wake Disorders , Humans , Snoring , Prospective Studies , Biological Specimen Banks , Sleep , United Kingdom
Background: Oxidative stress (OS) is associated with the development of acute myeloid leukemia (AML). However, there is lack of relevant research to confirm that OS-related genes can guide patients in risk stratification and predict their survival probability. Method: First, we Data from three public databases, respectively. Then, we use batch univariate Cox regression and machine learning to select important characteristic genes; next, we build the model and use receiver operating characteristic curve (ROC) to evaluate the accuracy. Moreover, GSEAs were performed to discover the molecular mechanism and conduct nomogram visualization. In addition, the relative importance value was used to identify the hub gene, and GSE9476 was to validate hub gene difference expression. Finally, we use symptom mapping to predict the candidate herbs, targeting the hub gene, and put these candidate herbs into Traditional Chinese Medicine Systems Pharmacology (TCMSP) to identify the main small molecular ingredients and then docking hub proteins with this small molecular. Results: A total of 313 candidate oxidative stress-related genes could affect patients' outcomes and machine learning to select six potential genes to construct a gene signature model to predict the overall survival (OS) of AML patients. Patients in a high group will obtain a short survival time when compared with the low-risk group (HR = 3.97, 95% CI: 2.48-6.36; p < 0.001). ROC results demonstrate the model has better prediction efficiency with AUC 0.873. GSEA suggests that this gene is enriched in several important signaling pathways. Nomogram is constructed and is robust. PLA2G4A is a hub gene of signature and associated with prognosis, and Nobiletin could target PLA2G4A for therapy AML. Conclusion: We use two different machine learning methods to build six oxidative stress-related gene signatures that could assist clinical decisions and identify PLA2G4A as a potential biomarker for AML. Nobiletin, targeting PLA2G4, may provide a third pathway for therapy AML.
Biomarkers, Tumor , Leukemia, Myeloid, Acute , Biomarkers, Tumor/metabolism , Humans , Leukemia, Myeloid, Acute/drug therapy , Leukemia, Myeloid, Acute/genetics , Machine Learning , Nomograms , Oxidative Stress/genetics
Background: Prior research provides suggestive evidence on an association between stress-related disorders and mortality. No previous study has however addressed the role of familial confounding on such association. Methods: We conducted a nationwide cohort study of 189,757 individuals with a first-onset stress-related disorder between January 1, 1981 and December 31, 2016 in Sweden (i.e., exposed patients), 1,896,352 matched unexposed individuals, and 207,479 unaffected full siblings of the exposed patients. Cox proportional hazards models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) of all-cause and cause-specific mortality. Findings: During a mean follow-up of 9.42 years, an elevated risk of all-cause mortality was observed during the entire follow-up among patients with stress-related disorders, compared with either unexposed individuals or their unaffected full siblings. Such excess risk was most pronounced within the first year after diagnosis of stress-related disorders (HR, 3.19 [95% CI, 2.87-3.54] in population-based comparison; HR, 3.21 [95% CI, 2.56-4.02] in sibling-based comparison). The excess risk decreased but remained statistically significant thereafter (HR, 1.64 [95% CI, 1.60-1.67] in population-based comparison; HR, 1.61 [95% CI, 1.54-1.68] in sibling-based comparison). An increased risk was observed for almost all cause-specific mortality, with greater risk increase for deaths from unnatural causes, especially suicide, and potentially avoidable causes. Interpretation: Stress-related disorders were associated with an increased risk of all-cause mortality and multiple cause-specific mortality, and the risk elevation was independent of familial confounding. The excess mortality attributable to unnatural causes and potentially avoidable causes highlights the importance of clinical surveillance of major health hazards among patients with stress-related disorders. Funding: EU Horizon 2020 Research and Innovation Action Grant, 1.3.5 Project for Disciplines of Excellence at West China Hospital of Sichuan University, National Natural Science Foundation of China, Icelandic Research Fund (Grant of Excellence), ERC Consolidator Grant, and Swedish Research Council.
