The association between circulating CD34+CD133+ endothelial progenitor cells and reduced risk of Alzheimer's disease in the Framingham Heart Study.

Aim: Endothelial dysfunction has been associated with both cerebrovascular pathology and Alzheimer's disease (AD). However, the connection between circulating endothelial cells and the risk of AD remains uncertain. The objective was to leverage data from the Framingham Heart Study to investigate various circulating endothelial subtypes and their potential correlations with the risk of AD. Methods: The study conducted data analyses using Cox proportional hazard regression and linear regression methods. Additionally, genome-wide association study (GWAS) was carried out to further explore the data. Results: Among the eleven distinct circulating endothelial subtypes, only circulating endothelial progenitor cells (EPCs) expressing CD34+CD133+ were found to be negatively and dose-dependently associated with reduced AD risk. This association persisted even after adjusting for age, sex, years of education, apolipoprotein E (APOE) ε4 status, and various vascular diseases. Particularly noteworthy was the significant association observed in individuals with hypertension and cerebral microbleeds. Consistently, positive associations were identified between CD34+CD133+ EPCs and specific brain regions, such as higher proportions of circulating CD34+CD133+ cells correlating with increased volumes of white matter and the hippocampus. Additionally, a GWAS study unveiled that CD34+CD133+ cells influenced AD risk specifically in individuals with homozygous genotypes for variants in two stem cell-related genes: kirre like nephrin family adhesion molecule 3 (KIRREL3, rs580382 CC and rs4144611 TT) and exocyst complex component 6B (EXOC6B, rs61619102 CC). Conclusions: The findings suggest that circulating CD34+CD133+ EPCs possess a protective effect and may offer a new therapeutic avenue for AD, especially in individuals with vascular pathology and those carrying specific genotypes of KIRREL3 and EXOC6B genes.

Hospital-treated infectious diseases, genetic susceptibility and risk of type 2 diabetes: A population-based longitudinal study.

BACKGROUND: The longitudinal association between infectious diseases and the risk of type 2 diabetes (T2D) remains unclear. METHODS: Based on the UK Biobank, the prospective cohort study included a total of 396,080 participants without diabetes at baseline. We determined the types and sites of infectious diseases and incident T2D using the International Classification of Diseases 10th Revision codes (ICD-10). Time-varying Cox proportional hazard model was used to assess the association. Infection burden was defined as the number of infection episodes over time and the number of co-occurring infections. Genetic risk score (GRS) for T2D consisted of 424 single nucleotide polymorphisms. RESULTS: During a median of 9.04 [IQR, 8.3-9.7] years of follow-up, hospital-treated infectious diseases were associated with a greater risk of T2D (adjusted HR [aHR] 1.54 [95 % CI 1.46-1.61]), with risk difference per 10,000 individuals equal to 154.1 [95 % CI 140.7-168.2]. The heightened risk persisted after 5 years following the index infection. Bacterial infection with sepsis had the strongest risk of T2D (aHR 2.95 [95 % CI 2.53-3.44]) among different infection types. For site-specific analysis, bloodstream infections posed the greatest risk (3.01 [95 % CI 2.60-3.48]). A dose-response association was observed between infection burden and T2D risk within each GRS tertile (p-trend <0.001). High genetic risk and infection synergistically increased the T2D risk. CONCLUSION: Infectious diseases were associated with an increased risk of subsequent T2D. The risk showed specificity according to types, sites, severity of infection and the period since infection occurred. A potential accumulative effect of infection was revealed.

Hospital-treated infectious diseases, infection burden and risk of Parkinson disease: An observational and Mendelian randomization study.

BACKGROUND: Experimental and cross-sectional evidence has suggested a potential role of infection in the ethology of Parkinson's disease (PD). We aim to examine the longitudinal association of infections with the incidence of PD and to explore whether the increased risk is limited to specific infection type rather than infection burden. METHODS: Based on the UK Biobank, hospital-treated infectious diseases and incident PD were ascertained through record linkage to national hospital inpatient registers. Infection burden was defined as the sum of the number of infection episodes over time and the number of co-occurring infections. The polygenic risk score (PRS) for PD was calculated. The genome-wide association studies (GWAS) used in two-sample Mendelian Randomization (MR) were obtained from observational cohort participants of mostly European ancestry. RESULTS: Hospital-treated infectious diseases were associated with an increased risk of PD (adjusted HR [aHR] 1.35 [95 % CI 1.20-1.52]). This relationship persisted when analyzing new PD cases occurring more than 10 years post-infection (aHR 1.22 [95 % CI 1.04-1.43]). The greatest PD risk was observed in neurological/eye infection (aHR 1.72 [95 % CI 1.32-2.34]), with lower respiratory tract infection (aHR 1.43 [95 % CI 1.02-1.99]) ranked the second. A dose-response association was observed between infection burden and PD risk within each PD-PRS tertile (p-trend < 0.001). Multivariable MR showed that bacterial and viral infections increase the PD risk. CONCLUSIONS: Both observational and genetic analysis suggested a causal association between infections and the risk of developing PD. A dose-response relationship between infection burden and incident PD was revealed.

Association of hospital-treated infectious diseases and infection burden with cardiovascular diseases and life expectancy.

BACKGROUND: The association of a broad spectrum of infectious diseases with cardiovascular outcomes remains unclear. OBJECTIVES: We aim to provide the cardiovascular risk profiles associated with a wide range of infectious diseases and explore the extent to which infections reduce life expectancy. METHODS: We ascertained exposure to 900+ infectious diseases before cardiovascular disease (CVD) onset in 453,102 participants from the UK Biobank study. Time-varying Cox proportional hazard models were used. Life table was used to estimate the life expectancy of individuals aged ≥50 with different levels of infection burden (defined as the number of infection episodes over time and the number of co-occurring infections). RESULTS: Infectious diseases were associated with a greater risk of CVD events (adjusted HR [aHR] 1.79 [95% confidence interval {CI} 1.74-1.83]). For type-specific analysis, bacterial infection with sepsis had the strongest risk of CVD events [aHR 4.76 (4.35-5.20)]. For site-specific analysis, heart and circulation infections posed the greatest risk of CVD events [aHR 4.95 (95% CI 3.77-6.50)], whereas noncardiac infections also showed excess risk [1.77 (1.72-1.81)]. Synergistic interactions were observed between infections and genetic risk score. A dose-response relationship was found between infection burden and CVD risks (p-trend <0.001). Infection burden >1 led to a CVD-related life loss at age 50 by 9.3 years [95% CI 8.6-10.3]) for men and 6.6 years [5.5-7.8] for women. CONCLUSIONS: The magnitude of the infection-CVD association showed specificity in sex, pathogen type, infection burden, and infection site. High genetic risk and infection synergistically increased the CVD risk.

Does increasing forest age lead to greater trade-offs in ecosystem services? A study of a Robinia pseudoacacia artificial forest on the Loess Plateau, China.

Artificial forest ecosystems offer various ecosystem services (ES) and help mitigate climate change effects. Trade-offs or synergies exist among ES in artificial forests. Although forest age influences ES and ecosystem processes, the long-term dynamics of trade-offs among ES in artificial forests and during vegetation restorations remain unclear, complicating vegetation and sustainable management. We studied a Robinia pseudoacacia plantation on the Loess Plateau, China, with a restoration time of 10-44 years. The entropy weight method was used to assess five ES (carbon sequestration, water conservation, soil conservation, understory plant diversity, and runoff and sediment reduction) and investigate how ES change with forest age. The root mean square deviation (RMSD) was used to quantify the trade-offs among ES, and redundancy analysis (RDA) analysis was used to identify the key factors influencing the ES and trade-offs. The results showed that (1) as forest age increased, ES scores initially increased and then decreased. The optimal range for ES values was observed during the middle-aged to mature stages of the forest. (2) Before reaching maturity, the planted forests primarily delivered services related to water conservation and runoff and sediment reduction. (3) In young forests, ES showed a synergistic relationship (RMSD = 0.06), whereas trade-offs occurred in forests at other ages. The largest trade-off was observed in middle-aged forests. (4) The ES pairs with the dominant trade-offs in planted forests differed at different forest age stages. The largest trade-off occurred between carbon sequestration and water conservation (RMSD = 0.28). RDA analysis showed that understory vegetation coverage had a positive correlation with all ES. The ES indicators that significantly (P < 0.001) affected the water­carbon trade-off were tree carbon storage, soil organic carbon storage, soil total nitrogen, and soil total phosphorus. Thus, the water and carbon relationship must be balanced, and the key factors affecting ES trade-offs in forest management must be regulated to support ES multifunctionality.

A water quality prediction model based on signal decomposition and ensemble deep learning techniques.

Accurate water quality predictions are critical for water resource protection, and dissolved oxygen (DO) reflects overall river water quality and ecosystem health. This study proposes a hybrid model based on the fusion of signal decomposition and deep learning for predicting river water quality. Initially, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is employed to split the internal series of DO into numerous internal mode functions (IMFs). Subsequently, we employed multi-scale fuzzy entropy (MFE) to compute the entropy values for each IMF component. Time-varying filtered empirical mode decomposition (TVFEMD) is used to further extract features in high-frequency subsequences after linearly aggregating the high-frequency sequences. Finally, support vector machine (SVM) and long short-term memory (LSTM) neural networks are used to predict low- and high-frequency subsequences. Moreover, by comparing it with single models, models based on 'single layer decomposition-prediction-ensemble' and combination models using different methods, the feasibility of the proposed model in predicting water quality data for the Xinlian section of Fuhe River and the Chucha section of Ganjiang River was verified. As a result, the combined prediction approach developed in this work has improved generalizability and prediction accuracy, and it may be used to forecast water quality in complicated waters.

Dietary Supplement with Tribulus terrestris L. Extract Exhibits Protective Effects on Ischemic Stroke Rats.

SCOPE: Among herbal dietary supplements, the extract of Tribulus terrestris L. (TT) has been used as a commercially registered product in multiple studies. The previous studies demonstrate the protective effect of gross saponins of TT (GSTTF) on ischemic stroke. However, the mechanism by which GSTTF protects against ischemic stroke is still unclear. METHODS AND RESULTS: The study applies molecular biology and unbiased transcriptomics to explore the pathways and targets underlying the therapeutic impact of GSTTF in treating ischemic stroke. The mRNA of brain tissues from different groups is analyzed using a transcriptomics method. The data reveal that treatment with GSTTF significantly reduces elevated CRP, IL-6, and Ca2+ levels induced by middle cerebral artery occlusion (MCAO). A total of 61 differentially expressed genes (DEGs) are identified, GSTTF is found to effectively reverse the abnormal mRNA expression levels in rat brain tissues affected by ischemic stroke models. These positive effects of GSTTF are likely achieved through the suppression of calcium ion and the MyD88/IKK/NF-κB signaling pathway. CONCLUSIONS: This study uncovers the mechanisms behind the efficacy of GSTTF in treating ischemic stroke, which not only expands its potential medicinal applications but also confirmed its potential as a dietary supplement.

A literature review: mechanisms of antitumor pharmacological action of leonurine alkaloid.

Leonurine refers to the desiccated aerial portion of a plant in the Labiatae family. The primary bioactive constituent of Leonurine is an alkaloid, Leonurine alkaloid (Leo), renowned for its substantial therapeutic efficacy in the treatment of gynecological disorders, in addition to its broad-spectrum antineoplastic capabilities. Over recent years, the pharmacodynamic mechanisms of Leo have garnered escalating scholarly interest. Leo exhibits its anticancer potential by means of an array of mechanisms, encompassing the inhibition of neoplastic cell proliferation, induction of both apoptosis and autophagy, and the containment of oncogenic cell invasion and migration. The key signal transduction pathways implicated in these processes include the Tumor Necrosis Factor-Related Apoptosis-Inducing Ligand (TRAIL), the Phosphoinositide3-Kinase/Serine/Threonine Protein Kinase (PI3K/AKT), the Signal Transducer and Activator of Transcription 3 (STAT3), and the Mitogen-Activated Protein/Extracellular Signal-Regulated Kinase (MAP/ERK). This paper commences with an exploration of the principal oncogenic cellular behaviors influenced by Leo and the associated signal transduction pathways, thereby scrutinizing the mechanisms of Leo in the antineoplastic sequence of events. The intention is to offer theoretical reinforcement for the elucidation of more profound mechanisms underpinning Leo's anticancer potential and correlating pharmaceutical development.

The impact of blood MCP-1 levels on Alzheimer's disease with genetic variation of UNC5C and NAV3 loci.

Background: Previous study shows that monocyte chemoattractant protein-1 (MCP-1), which is implicated in the peripheral proinflammatory cascade and blood-brain barrier (BBB) disruption, modulates the genetic risks of AD in established AD loci. Methods: In this study, we hypothesized that blood MCP-1 impacts the AD risk of genetic variants beyond known AD loci. We thus performed a genome-wide association study (GWAS) using the logistic regression via generalized estimating equations (GEE) and the Cox proportional-hazards models to examine the interactive effects between single nucleotide polymorphisms (SNPs) and blood MCP-1 level on AD in three cohorts: the Framingham Heart Study (FHS), Alzheimer's Disease Neuroimaging Initiative (ADNI) and Religious Orders Study/Memory and Aging Project (ROSMAP). Results: We identified SNPs in two genes, neuron navigator 3 (NAV3, also named Unc-53 Homolog 3, rs696468) (p < 7.55×10- 9) and Unc-5 Netrin Receptor C (UNC5C rs72659964) (p < 1.07×10- 8) that showed an association between increasing levels of blood MCP-1 and AD. Elevating blood MCP-1 concentrations increased AD risk and AD pathology in genotypes of NAV3 (rs696468-CC) and UNC5C (rs72659964-AT + TT), but did not influence the other counterpart genotypes of these variants. Conclusions: NAV3 and UNC5C are homologs and may increase AD risk through dysregulating the functions of neurite outgrowth and guidance. Overall, the association of risk alleles of NAV3 and UNC5C with AD is enhanced by peripheral MCP-1 level, suggesting that lowering the level of blood MCP-1 may reduce the risk of developing AD for people with these genotypes.

Association Between Glucosamine Use and the Risk of Incident Heart Failure: The UK Biobank Cohort Study and Mendelian Randomization Analysis.

OBJECTIVE: To evaluate the association between regular glucosamine intake and heart failure (HF) and to explore whether the association is mediated by relevant cardiovascular disease. PATIENTS AND METHODS: We included 479,650 participants with data available for supplement use and without HF at baseline from the UK Biobank study. Using 12 single-nucleotide polymorphisms linked to HF, a weighted genetic risk score was calculated. We evaluated the association between glucosamine use and HF by Cox regression models after inverse probability of treatment weighting. A validation and mediation analysis were performed through two-sample Mendelian randomization. The study was from May 18, 2006, to February 16, 2018. RESULTS: During a median follow-up of 9.0 (IQR, 8.3-9.8) years, we documented 5501 incident cases of HF. In multivariable analysis, the HR of glucosamine users for HF was 0.87 (95% CI, 0.81 to 0.94). The inverse associations were stronger in males and participants with unfavorable lifestyle (P<.05 for interaction). Genetic risk categories did not modify this association (P>.05 for interaction). Multivariable Mendelian randomization showed that taking glucosamine was protective against HF (HR, 0.92; 95% CI, 0.87 to 0.96). The mediated proportion of coronary heart disease and stroke were 10.5% (95% CI, 7.6% to 13.4%) and 14.4% (95% CI, 10.8% to 18.0%), respectively. The two-mediator combination accounted for 22.7% (95% CI, 17.2% to 28.2%) of the effect of glucosamine use. CONCLUSION: Regular glucosamine supplementation was associated with a lower risk of HF regardless of genetic risk status, and to a lesser extent, coronary heart disease and stroke mediated this effect. The results may inform novel pathway for prevention and intervention toward HF.

Association of regular glucosamine use with incident dementia: evidence from a longitudinal cohort and Mendelian randomization study.

BACKGROUND: Emerging data suggests the neuroprotective and anti-neuroinflammatory effects of glucosamine. We aimed to examine the association between regular glucosamine use and risk of incident dementia, including dementia subtypes. METHODS: We conducted large-scale observational and two-sample Mendelian randomization (MR) analyses. Participants in UK Biobank having accessible data for dementia incidence and who did not have dementia at baseline were included in the prospective cohort. Through the Cox proportional hazard model, we examined the risks of incident all-cause dementia, Alzheimer's disease (AD), and vascular dementia among glucosamine users and non-users. To further test the causal association between glucosamine use and dementia, we conducted a 2-sample MR utilizing summary statistics from genome-wide association studies (GWAS). The GWAS data were obtained from observational cohort participants of mostly European ancestry. RESULTS: During a median follow-up of 8.9 years, there were 2458 cases of all-cause dementia, 924 cases of AD, and 491 cases of vascular dementia. In multivariable analysis, the hazard ratios (HR) of glucosamine users for all-cause dementia, AD, and vascular dementia were 0.84 (95% CI 0.75-0.93), 0.83 (95% CI 0.71-0.98), and 0.74 (95% CI 0.58-0.95), respectively. The inverse associations between glucosamine use and AD appeared to be stronger among participants aged below 60 years than those aged above 60 years (p = 0.04 for interaction). The APOE genotype did not modify this association (p > 0.05 for interaction). Single-variable MR suggested a causal relationship between glucosamine use and lower dementia risk. Multivariable MR showed that taking glucosamine continued to protect against dementia after controlling for vitamin, chondroitin supplement use and osteoarthritis (all-cause dementia HR 0.88, 95% CI 0.81-0.95; AD HR 0.78, 95% CI 0.72-0.85; vascular dementia HR 0.73, 95% CI 0.57-0.94). Single and multivariable inverse variance weighted (MV-IVW) and MR-Egger sensitivity analyses produced similar results for these estimations. CONCLUSIONS: The findings of this large-scale cohort and MR analysis provide evidence for potential causal associations between the glucosamine use and lower risk for dementia. These findings require further validation through randomized controlled trials.

Pyroptosis-based risk score predicts prognosis and drug sensitivity in lung adenocarcinoma.

Pyroptosis is a recently identified form of programmed cell death; however, its role in lung adenocarcinoma (LUAD) remains unclear. Therefore, we set out to explore the prognostic potential of pyroptosis-related genes in LUAD. The pyroptosis-related risk score (PRRS) was developed by least absolute shrinkage and selection operator Cox regression and multivariate Cox regression. We found that PRRS was an independent prognostic factor for LUAD. LUAD patients in the high-PRRS group showed a significantly shorter overall survival (OS) and enriched in cell proliferation-related pathways. Then pathway enrichment analyses, mutation profile, tumor microenvironment, and drug sensitivity analysis were further studied in PRRS stratified LUAD patients. Tumor purity (TP) analyses revealed that L-PRRS LUAD patients had a lower TP, and patients in L-TP + L-PRRS subgroup had the most prolonged OS. Mutation analyses suggested that the L-PRRS LUAD patients had a lower tumor mutation burden (TMB), and patients in H-TMB + L-PRRS subgroup had the most prolonged OS. Drug sensitivity analyses showed that PRRS was significantly negatively correlated with the sensitivity of cisplatin, besarotene, etc., while it was significantly positively correlated with the sensitivity of kin001-135. Eventually, a nomogram was constructed based on PRRS and clinical characters of LUAD. Overall, the pyroptosis-related signature is helpful for prognostic prediction and in guiding treatment for LUAD patients.

ClusterSeg: A crowd cluster pinpointed nucleus segmentation framework with cross-modality datasets.

The detection and segmentation of individual cells or nuclei is often involved in image analysis across a variety of biology and biomedical applications as an indispensable prerequisite. However, the ubiquitous presence of crowd clusters with morphological variations often hinders successful instance segmentation. In this paper, nuclei cluster focused annotation strategies and frameworks are proposed to overcome this challenging practical problem. Specifically, we design a nucleus segmentation framework, namely ClusterSeg, to tackle nuclei clusters, which consists of a convolutional-transformer hybrid encoder and a 2.5-path decoder for precise predictions of nuclei instance mask, contours, and clustered-edges. Additionally, an annotation-efficient clustered-edge pointed strategy pinpoints the salient and error-prone boundaries, where a partially-supervised PS-ClusterSeg is presented using ClusterSeg as the segmentation backbone. The framework is evaluated with four privately curated image sets and two public sets with characteristic severely clustered nuclei across a variety range of image modalities, e.g., microscope, cytopathology, and histopathology images. The proposed ClusterSeg and PS-ClusterSeg are modality-independent and generalizable, and superior to current state-of-the-art approaches in multiple metrics empirically. Our collected data, the elaborate annotations to both public and private set, as well the source code, are released publicly at https://github.com/lu-yizhou/ClusterSeg.

Circulating Endothelial Progenitor Cells Reduce the Risk of Alzheimer's Disease.

Cerebrovascular damage coexists with Alzheimer's disease (AD) pathology and increases AD risk. However, it is unclear whether endothelial progenitor cells reduce AD risk via cerebrovascular repair. By using the Framingham Heart Study (FHS) offspring cohort, which includes data on different progenitor cells, the incidence of AD dementia, peripheral and cerebrovascular pathologies, and genetic data (n = 1,566), we found that elevated numbers of circulating endothelial progenitor cells with CD34+CD133+ co-expressions had a dose-dependent association with decreased AD risk (HR = 0.67, 95% CI: 0.46-0.96, p = 0.03) after adjusting for age, sex, years of education, and APOE ε4. With stratification, this relationship was only significant among those individuals who had vascular pathologies, especially hypertension (HTN) and cerebral microbleeds (CMB), but not among those individuals who had neither peripheral nor central vascular pathologies. We applied a genome-wide association study (GWAS) and found that the number of CD34+CD133+ cells impacted AD risk depending on the homozygous genotypes of two genes: KIRREL3 rs580382 CC carriers (HR = 0.31, 95% CI: 0.17-0.57, p<0.001), KIRREL3 rs4144611 TT carriers (HR = 0.29, 95% CI: 0.15-0.57, p<0.001), and EXOC6B rs61619102 CC carriers (HR = 0.49, 95% CI: 0.31-0.75, p<0.001) after adjusting for confounders. In contrast, the relationship did not exist in their counterpart genotypes, e.g. KIRREL3 TT/CT or GG/GT carriers and EXOC6B GG/GC carriers. Our findings suggest that circulating CD34+CD133+ endothelial progenitor cells can be therapeutic in reducing AD risk in the presence of cerebrovascular pathology, especially in KIRREL3 and EXOC6B genotype carriers.

Association of Diabetes Mellitus Status and Hyperglycemia With Symptomatic Knee Osteoarthritis.

OBJECTIVE: Emerging evidence indicates that hyperglycemia has an adverse impact on the knee joint which, in turn, may increase the risk of knee osteoarthritis (OA), but evidence from the real-life settings of large-scale cohort studies remains unclear. We sought to evaluate the association of glycemic control and the risk of symptomatic knee OA in a community-based cohort of older adults. METHODS: We conducted a prospective analysis of 10,730 participants without knee OA. Comprehensive blood biomarker data were obtained. Diabetes mellitus (DM) was defined mainly using a glycosylated hemoglobin (HbA1c ) level of ≥6.5%; poor glycemic control in individuals with DM was defined as an HbA1c level of ≥7%. We fit Cox regression models, stratified according to DM status. We evaluated the hazards associated with HbA1c and fasting blood glucose levels using a spline model. RESULTS: During a median follow-up of 5 years, knee OA developed in 1,089 participants (108 with DM and 971 without). Knee OA was related to DM (hazard ratio [HR] 1.29 [95% confidence interval (95% CI) 1.02-1.78]), bad glycemic regulation in DM patients (HR 1.41 [95% CI 1.05-2.09]), and long-term DM (≥5 versus <5 years; HR 1.49 [95% CI 1.02-2.17]). High levels of HbA1c (>7.7% and 61 mmoles/mole) and fasting blood glucose (>186 mg/dl) were significantly associated with higher risk of incident knee OA. CONCLUSION: DM, bad glycemic management, and long-term DM are potential risk factors of symptomatic knee OA independent of age and body mass index. Targeting blood glucose, in addition to bodyweight, may be an important avenue for prevention of knee OA.

Blood levels of MCP-1 modulate the genetic risks of Alzheimer's disease mediated by HLA-DRB1 and APOE for Alzheimer's disease.

INTRODUCTION: C-Reactive protein (CRP) and monocyte chemoattractant protein-1 (MCP-1) are both implicated in the peripheral proinflammatory cascade and blood-brain barrier (BBB) disruption. Since the blood CRP level increases Alzheimer's disease (AD) risk depending on the apolipoprotein E (APOE) genotype, we hypothesized that the blood MCP-1 level exerts different effects on the AD risk depending on the genotypes. METHODS: Using multiple regression analyses, data from the Framingham Heart Study (n = 2884) and Alzheimer's Disease Neuroimaging Initiative study (n = 231) were analyzed. RESULTS: An elevated blood MCP-1 level was associated with AD risk in major histocompatibility complex, Class II, DR beta 1 (HLA-DRB1) rs9271192-AC/CC (hazard ratio [HR] = 3.07, 95% confidence interval [CI] = 1.50-6.28, p = 0.002) and in APOE ε4 carriers (HR = 3.22, 95% CI = 1.59-6.53, p = 0.001). In contrast, among HLA-DRB1 rs9271192-AA and APOE ε4 noncarriers, blood MCP-1 levels were not associated with these phenotypes. DISCUSSION: Since HLA-DRB1 and APOE are expressed in the BBB, blood MCP-1 released in the peripheral inflammatory cascade may function as a mediator of the effects of HLA-DRB1 rs9271192-AC/CC and APOE ε4 genotypes on AD pathogenesis in the brain via the BBB pathways.

Interferon response and profiling of interferon response genes in peripheral blood of vaccine-naive COVID-19 patients.

Introduction: There is insufficient understanding on systemic interferon (IFN) responses during COVID-19 infection. Early reports indicated that interferon responses were suppressed by the coronavirus (SARS-CoV-2) and clinical trials of administration of various kinds of interferons had been disappointing. Expression of interferon-stimulated genes (ISGs) in peripheral blood (better known as interferon score) has been a well-established bioassay marker of systemic IFN responses in autoimmune diseases. Therefore, with archival samples of a cohort of COVID-19 patients collected before the availability of vaccination, we aimed to better understand this innate immune response by studying the IFN score and related ISGs expression in bulk and single cell RNAs sequencing expression datasets. Methods: In this study, we recruited 105 patients with COVID-19 and 30 healthy controls in Hong Kong. Clinical risk factors, disease course, and blood sampling times were recovered. Based on a set of five commonly used ISGs (IFIT1, IFIT2, IFI27, SIGLEC1, IFI44L), the IFN score was determined in blood leukocytes collected within 10 days after onset. The analysis was confined to those blood samples collected within 10 days after disease onset. Additional public datasets of bulk gene and single cell RNA sequencing of blood samples were used for the validation of IFN score results. Results: Compared to the healthy controls, we showed that ISGs expression and IFN score were significantly increased during the first 10 days after COVID infection in majority of patients (71%). Among those low IFN responders, they were more commonly asymptomatic patients (71% vs 25%). 22 patients did not mount an overall significant IFN response and were classified as low IFN responders (IFN score < 1). However, early IFN score or ISGs level was not a prognostic biomarker and could not predict subsequent disease severity. Both IFI27 and SIGLEC1 were monocyte-predominant expressing ISGs and IFI27 were activated even among those low IFN responders as defined by IFN score. In conclusion, a substantial IFN response was documented in this cohort of COVID-19 patients who experience a natural infection before the vaccination era. Like innate immunity towards other virus, the ISGs activation was observed largely during the early course of infection (before day 10). Single-cell RNA sequencing data suggested monocytes were the cell-type that primarily accounted for the activation of two highly responsive ISGs (IFI44L and IFI27). Discussion: As sampling time and age were two major confounders of ISG expression, they may account for contradicting observations among previous studies. On the other hand, the IFN score was not associated with the severity of the disease.

Heterogeneous Graph Convolutional Neural Network via Hodge-Laplacian for Brain Functional Data.

This study proposes a novel heterogeneous graph convolutional neural network (HGCNN) to handle complex brain fMRI data at regional and across-region levels. We introduce a generic formulation of spectral filters on heterogeneous graphs by introducing the k-th Hodge-Laplacian (HL) operator. In particular, we propose Laguerre polynomial approximations of HL spectral filters and prove that their spatial localization on graphs is related to the polynomial order. Furthermore, based on the bijection property of boundary operators on simplex graphs, we introduce a generic topological graph pooling (TGPool) method that can be used at any dimensional simplices. This study designs HL-node, HL-edge, and HL-HGCNN neural networks to learn signal representation at a graph node, edge levels, and both, respectively. Our experiments employ fMRI from the Adolescent Brain Cognitive Development (ABCD; n=7693) to predict general intelligence. Our results demonstrate the advantage of the HL-edge network over the HL-node network when functional brain connectivity is considered as features. The HL-HGCNN outperforms the state-of-the-art graph neural networks (GNNs) approaches, such as GAT, BrainGNN, dGCN, BrainNetCNN, and Hypergraph NN. The functional connectivity features learned from the HL-HGCNN are meaningful in interpreting neural circuits related to general intelligence.

The impact of increasing levels of blood C-reactive protein on the inflammatory loci SPI1 and CD33 in Alzheimer's disease.

Apolipoprotein ε4 (APOE ε4) is the most significant genetic risk factor for late-onset Alzheimer's disease (AD). Elevated blood C-reactive protein (CRP) further increases the risk of AD for people carrying the APOE ε4 allele. We hypothesized that CRP, as a key inflammatory element, could modulate the impact of other genetic variants on AD risk. We selected ten single nucleotide polymorphisms (SNPs) in reported AD risk loci encoding proteins related to inflammation. We then tested the interaction effects between these SNPs and blood CRP levels on AD incidence using the Cox proportional hazards model in UK Biobank (n = 279,176 white participants with 803 incident AD cases). The five top SNPs were tested for their interaction with different CRP cutoffs for AD incidence in the Framingham Heart Study (FHS) Generation 2 cohort (n = 3009, incident AD = 156). We found that for higher concentrations of serum CRP, the AD risk increased for SNP genotypes in 3 AD-associated genes (SPI1, CD33, and CLU). Using the Cox model in stratified genotype analysis, the hazard ratios (HRs) for the association between a higher CRP level (≥10 vs. <10 mg/L) and the risk of incident AD were 1.94 (95% CI: 1.33-2.84, p < 0.001) for the SPI1 rs1057233-AA genotype, 1.75 (95% CI: 1.20-2.55, p = 0.004) for the CD33 rs3865444-CC genotype, and 1.76 (95% CI: 1.25-2.48, p = 0.001) for the CLU rs9331896-C genotype. In contrast, these associations were not observed in the other genotypes of these genes. Finally, two SNPs were validated in 321 Alzheimer's Disease Neuroimaging (ADNI) Mild Cognitive Impairment (MCI) patients. We observed that the SPI1 and CD33 genotype effects were enhanced by elevated CRP levels for the risk of MCI to AD conversion. Furthermore, the SPI1 genotype was associated with CSF AD biomarkers, including t-Tau and p-Tau, in the ADNI cohort when the blood CRP level was increased (p < 0.01). Our findings suggest that elevated blood CRP, as a peripheral inflammatory biomarker, is an important moderator of the genetic effects of SPI1 and CD33 in addition to APOE ε4 on AD risk. Monitoring peripheral CRP levels may be helpful for precise intervention and prevention of AD for these genotype carriers.