Transient receptor potential canonical 5 channels plays an essential role in hepatic dyslipidemia associated with cholestasis.

Transient receptor potential canonical 5 (TRPC5), a calcium-permeable, non-selective cation channel is expressed in the periphery, but there is limited knowledge of its regulatory roles in vivo. Endogenous modulators of TRPC5 include a range of phospholipids that have an established role in liver disease, including lysophosphatidylcholine (LPC). Cholestasis is characterized by impairment of excretion of bile acids, leading to elevation of hepatic bile acids. We investigated the contribution of TRPC5 in a murine model of cholestasis. Wild-type (WT) and TRPC5 knock-out (KO) mice were fed a diet supplemented with 0.5% cholic acid (CA) for 21 days. CA-diet supplementation resulted in enlargement of the liver in WT mice, which was ameliorated in TRPC5 KO mice. Hepatic bile acid and lipid content was elevated in WT mice, with a reduction observed in TRPC5 KO mice. Consistently, liver enzymes were significantly increased in cholestatic WT mice and significantly blunted in TRPC5 KO mice. Localized dyslipidaemia, secondary to cholestasis, was investigated utilizing a selected lipid analysis. This revealed significant perturbations in the lipid profile following CA-diet feeding, with increased cholesterol, triglycerides and phospholipids, in WT, but not TRPC5 KO mice. Our results suggest that activation of TRPC5 contributes to the development of cholestasis and associated dyslipidemia. Modulation of TRPC5 activity may present as a novel therapeutic target for liver disease

Combating antimicrobial resistance in Singapore: a qualitative study exploring the policy context, challenges, facilitators, and proposed strategies

Antimicrobial resistance (AMR) is a global public health threat that warrants urgent attention. However, the multifaceted nature of AMR often complicates the development and implementation of comprehensive policies. In this study, we describe the policy context and explore experts' perspectives on the challenges, facilitators, and strategies for combating AMR in Singapore. We conducted semi-structured interviews with 21 participants. Interviews were transcribed verbatim and were analyzed thematically, adopting an interpretative approach. Participants reported that the Ministry of Health (MOH) has effectively funded AMR control programs and research in all public hospitals. In addition, a preexisting One Health platform, among MOH, Agri-Food & Veterinary Authority (restructured to form the Singapore Food Agency and the Animal & Veterinary Service under NParks in April 2019), National Environment Agency, and Singapore's National Water Agency, was perceived to have facilitated the coordination and formulation of Singapore's AMR strategies. Nonetheless, participants highlighted that the success of AMR strategies is compounded by various challenges such as surveillance in private clinics, resource constraints at community-level health facilities, sub-optimal public awareness, patchy regulation on antimicrobial use in animals, and environmental contamination. This study shows that the process of planning and executing AMR policies is complicated even in a well-resourced country such as Singapore. It has also highlighted the increasing need to address the social, political, cultural, and behavioral aspects influencing AMR. Ultimately, it will be difficult to design policy interventions that cater for the needs of individuals, families, and the community, unless we understand how all these aspects interact and shape the AMR response.This research is funded through the CoSTAR-HS and SPHERiC Collaborative Center Grants from the National Medical Research Council, Singapore

Mendelian randomization identifies blood metabolites previously linked to midlife cognition as causal candidates in Alzheimer's disease.

There are currently no disease-modifying treatments for Alzheimer's disease (AD), and an understanding of preclinical causal biomarkers to help target disease pathogenesis in the earliest phases remains elusive. Here, we investigated whether 19 metabolites previously associated with midlife cognition-a preclinical predictor of AD-translate to later clinical risk, using Mendelian randomization (MR) to tease out AD-specific causal relationships. Summary statistics from the largest genome-wide association studies (GWASs) for AD and metabolites were used to perform bidirectional univariable MR. Bayesian model averaging (BMA) was additionally performed to address high correlation between metabolites and identify metabolite combinations that may be on the AD causal pathway. Univariable MR indicated four extra-large high-density lipoproteins (XL.HDL) on the causal pathway to AD: free cholesterol (XL.HDL.FC: 95% CI = 0.78 to 0.94), total lipids (XL.HDL.L: 95% CI = 0.80 to 0.97), phospholipids (XL.HDL.PL: 95% CI = 0.81 to 0.97), and concentration of XL.HDL particles (95% CI = 0.79 to 0.96), significant at an adjusted P < 0.009. MR-BMA corroborated XL.HDL.FC to be among the top three causal metabolites, in addition to total cholesterol in XL.HDL (XL.HDL.C) and glycoprotein acetyls (GP). Both XL.HDL.C and GP demonstrated suggestive univariable evidence of causality (P < 0.05), and GP successfully replicated within an independent dataset. This study offers insight into the causal relationship between metabolites demonstrating association with midlife cognition and AD. It highlights GP in addition to several XL.HDLs-particularly XL.HDL.FC-as causal candidates warranting further investigation. As AD pathology is thought to develop decades prior to symptom onset, expanding on these findings could inform risk reduction strategies

Are metabolites linked to midlife cognition on the causal pathway to Alzheimer's Disease? A Mendelian randomization study

There are currently no disease-modifying treatments for Alzheimer’s disease (AD), and an understanding of preclinical causal biomarkers to help target disease pathogenesis in the earliest phases remains elusive. Here, we investigated whether 19 metabolites previously associated with midlife cognition—a preclinical predictor of AD— translate to later clinical risk, using Mendelian randomization (MR) to tease out AD-specific causal relationships. Summary statistics from the largest genome-wide association studies (GWASs) for AD and metabolites were used to perform bidirectional univariable MR. Bayesian model averaging (BMA) was additionally performed to address high correlation between metabolites and identify metabolite combinations that may be on the AD causal pathway. Univariable MR indicated four extra-large high-density lipoproteins (XL.HDL) on the causal pathway to AD: free cholesterol (XL.HDL.FC: 95% CI = 0.78 to 0.94), total lipids (XL.HDL.L: 95% CI = 0.80 to 0.97), phospholipids (XL.HDL.PL: 95% CI = 0.81 to 0.97), and concentration of XL.HDL particles (95% CI = 0.79 to 0.96), significant at an adjusted P < 0.009. MR–BMA corroborated XL.HDL.FC to be among the top three causal metabolites, in addition to total cholesterol in XL.HDL (XL.HDL.C) and glycoprotein acetyls (GP). Both XL.HDL.C and GP demonstrated suggestive univariable evidence of causality (P < 0.05), and GP successfully replicated within an independent dataset. This study offers insight into the causal relationship between metabolites demonstrating association with midlife cognition and AD. It highlights GP in addition to several XL.HDLs—particularly XL.HDL.FC—as causal candidates warranting further investigation. As AD pathology is thought to develop decades prior to symptom onset, expanding on these findings could inform risk reduction strategies

Alpha-Synuclein in bio fluids and tissues as a potential biomarker for Parkinson’s disease

Background: Parkinson's disease (PD) is a chronic neurological disorder that impairs normal motor function and has no cure at present. Diagnosis of PD is clinical only; biopsies confirming the presence of the disease can only be done post-mortem. Furthermore, similarities in the manifestation of PD symptoms to other diseases such as Multiple System Atrophy (MSA), make early diagnosis difficult and ambiguous. As a result, there is a high demand for research investigating biomarkers for timely diagnosis of PD. Alpha-synuclein (α-SYN) is a protein found misfolded in the brain and other body tissues of PD patients. Its relevance and association to PD make it a prime biomarker candidate. However, reports in the literature suggest that the structural form and location of α-SYN are key to yield a reliable diagnosis. The aim of this Minireview is to highlight efforts made in studying α-SYN as a biomarker over the past decade. Key Findings: Based on the literature surveyed, α-SYN was indeed the most widely studied candidate biomarker for PD. Cerebrospinal fluid (CSF) and skin were promising sites for assessing α-SYN effectiveness in differentiating PD from MSA. Furthermore, gastro-intestinal α-SYN was suitable for early diagnosis of PD. A combination of total α-SYN and other forms including but not limited to phosphorylated α-SYN were the best predictors of the disease. Conclusion: Misdiagnosis of patients enrolled in clinical trials is a confounding factor for PD drug development. A robust biomarker for PD will help eradicate this problem. Identifying an accurate biomarker for PD will also ensure timely therapeutic intervention to manage symptoms better and improve the quality of life of patients. The promise α-SYN and its phosphorylated form show in different tissues is a step forward in this direction.published_or_final_versio

Integrated lipidomics and proteomics network analysis highlights lipid and immunity pathways associated with Alzheimer's disease

Background: There is an urgent need to understand the pathways and processes underlying Alzheimer’s disease (AD) for early diagnosis and development of effective treatments. This study was aimed to investigate Alzheimer’s dementia using an unsupervised lipid, protein and gene multi-omics integrative approach. / Methods: A lipidomics dataset comprising 185 AD patients, 40 mild cognitive impairment (MCI) individuals and 185 controls, and two proteomics datasets (295 AD, 159 MCI and 197 controls) were used for weighted gene co-expression network analyses (WGCNA). Correlations of modules created within each modality with clinical AD diagnosis, brain atrophy measures and disease progression, as well as their correlations with each other, were analyzed. Gene ontology enrichment analysis was employed to examine the biological processes and molecular and cellular functions of protein modules associated with AD phenotypes. Lipid species were annotated in the lipid modules associated with AD phenotypes. The associations between established AD risk loci and the lipid/protein modules that showed high correlation with AD phenotypes were also explored. / Results: Five of the 20 identified lipid modules and five of the 17 identified protein modules were correlated with clinical AD diagnosis, brain atrophy measures and disease progression. The lipid modules comprising phospholipids, triglycerides, sphingolipids and cholesterol esters were correlated with AD risk loci involved in immune response and lipid metabolism. The five protein modules involved in positive regulation of cytokine production, neutrophil-mediated immunity, and humoral immune responses were correlated with AD risk loci involved in immune and complement systems and in lipid metabolism (the APOE ε4 genotype). / Conclusions: Modules of tightly regulated lipids and proteins, drivers in lipid homeostasis and innate immunity, are strongly associated with AD phenotypes

Disentangling independent and mediated causal relationships between blood metabolites, cognitive factors, and Alzheimer’s Disease

Background: Education and cognition demonstrate consistent inverse associations with Alzheimer’s disease (AD). The biological underpinnings, however, remain unclear. Blood metabolites reflect the end point of biological processes and are accessible and malleable. Identifying metabolites with etiological relevance to AD and disentangling how these relate to cognitive factors along the AD causal pathway could, therefore, offer unique insights into underlying causal mechanisms. // Methods: Using data from the largest metabolomics genome-wide association study (N ≈ 24,925) and three independent AD cohorts (N = 4725), cross-trait polygenic scores were generated and meta-analyzed. Metabolites genetically associated with AD were taken forward for causal analyses. Bidirectional two-sample Mendelian randomization interrogated univariable causal relationships between 1) metabolites and AD; 2) education and cognition; 3) metabolites, education, and cognition; and 4) education, cognition, and AD. Mediating relationships were computed using multivariable Mendelian randomization. // Results: Thirty-four metabolites were genetically associated with AD at p < .05. Of these, glutamine and free cholesterol in extra-large high-density lipoproteins demonstrated a protective causal effect (glutamine: 95% confidence interval [CI], 0.70 to 0.92; free cholesterol in extra-large high-density lipoproteins: 95% CI, 0.75 to 0.92). An AD-protective effect was also observed for education (95% CI, 0.61 to 0.85) and cognition (95% CI, 0.60 to 0.89), with bidirectional mediation evident. Cognition as a mediator of the education-AD relationship was stronger than vice versa, however. No evidence of mediation via any metabolite was found. // Conclusions: Glutamine and free cholesterol in extra-large high-density lipoproteins show protective causal effects on AD. Education and cognition also demonstrate protection, though education’s effect is almost entirely mediated by cognition. These insights provide key pieces of the AD causal puzzle, important for informing future multimodal work and progressing toward effective intervention strategies

Dysregulation of multiple metabolic networks related to brain transmethylation and polyamine pathways in Alzheimer disease: A targeted metabolomic and transcriptomic study.

BACKGROUND: There is growing evidence that Alzheimer disease (AD) is a pervasive metabolic disorder with dysregulation in multiple biochemical pathways underlying its pathogenesis. Understanding how perturbations in metabolism are related to AD is critical to identifying novel targets for disease-modifying therapies. In this study, we test whether AD pathogenesis is associated with dysregulation in brain transmethylation and polyamine pathways. METHODS AND FINDINGS: We first performed targeted and quantitative metabolomics assays using capillary electrophoresis-mass spectrometry (CE-MS) on brain samples from three groups in the Baltimore Longitudinal Study of Aging (BLSA) (AD: n = 17; Asymptomatic AD [ASY]: n = 13; Control [CN]: n = 13) (overall 37.2% female; mean age at death 86.118 ± 9.842 years) in regions both vulnerable and resistant to AD pathology. Using linear mixed-effects models within two primary brain regions (inferior temporal gyrus [ITG] and middle frontal gyrus [MFG]), we tested associations between brain tissue concentrations of 26 metabolites and the following primary outcomes: group differences, Consortium to Establish a Registry for Alzheimer's Disease (CERAD) (neuritic plaque burden), and Braak (neurofibrillary pathology) scores. We found significant alterations in concentrations of metabolites in AD relative to CN samples, as well as associations with severity of both CERAD and Braak, mainly in the ITG. These metabolites represented biochemical reactions in the (1) methionine cycle (choline: lower in AD, p = 0.003; S-adenosyl methionine: higher in AD, p = 0.005); (2) transsulfuration and glutathione synthesis (cysteine: higher in AD, p < 0.001; reduced glutathione [GSH]: higher in AD, p < 0.001); (3) polyamine synthesis/catabolism (spermidine: higher in AD, p = 0.004); (4) urea cycle (N-acetyl glutamate: lower in AD, p < 0.001); (5) glutamate-aspartate metabolism (N-acetyl aspartate: lower in AD, p = 0.002); and (6) neurotransmitter metabolism (gamma-amino-butyric acid: lower in AD, p < 0.001). Utilizing three Gene Expression Omnibus (GEO) datasets, we then examined mRNA expression levels of 71 genes encoding enzymes regulating key reactions within these pathways in the entorhinal cortex (ERC; AD: n = 25; CN: n = 52) and hippocampus (AD: n = 29; CN: n = 56). Complementing our metabolomics results, our transcriptomics analyses also revealed significant alterations in gene expression levels of key enzymatic regulators of biochemical reactions linked to transmethylation and polyamine metabolism. Our study has limitations: our metabolomics assays measured only a small proportion of all metabolites participating in the pathways we examined. Our study is also cross-sectional, limiting our ability to directly test how AD progression may impact changes in metabolite concentrations or differential-gene expression. Additionally, the relatively small number of brain tissue samples may have limited our power to detect alterations in all pathway-specific metabolites and their genetic regulators. CONCLUSIONS: In this study, we observed broad dysregulation of transmethylation and polyamine synthesis/catabolism, including abnormalities in neurotransmitter signaling, urea cycle, aspartate-glutamate metabolism, and glutathione synthesis. Our results implicate alterations in cellular methylation potential and increased flux in the transmethylation pathways, increased demand on antioxidant defense mechanisms, perturbations in intermediate metabolism in the urea cycle and aspartate-glutamate pathways disrupting mitochondrial bioenergetics, increased polyamine biosynthesis and breakdown, as well as abnormalities in neurotransmitter metabolism that are related to AD

The EMIF-AD Multimodal Biomarker Discovery study: design, methods and cohort characteristics.

There is an urgent need for novel, noninvasive biomarkers to diagnose Alzheimer's disease (AD) in the predementia stages and to predict the rate of decline. Therefore, we set up the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) study. In this report we describe the design of the study, the methods used and the characteristics of the participants. Participants were selected from existing prospective multicenter and single-center European studies. Inclusion criteria were having normal cognition (NC) or a diagnosis of mild cognitive impairment (MCI) or AD-type dementia at baseline, age above 50 years, known amyloid-beta (Aβ) status, availability of cognitive test results and at least two of the following materials: plasma, DNA, magnetic resonance imaging (MRI) or cerebrospinal fluid (CSF). Targeted and untargeted metabolomic and proteomic analyses were performed in plasma, and targeted and untargeted proteomics were performed in CSF. Genome-wide SNP genotyping, next-generation sequencing and methylation profiling were conducted in DNA. Visual rating and volumetric measures were assessed on MRI. Baseline characteristics were analyzed using ANOVA or chi-square, rate of decline analyzed by linear mixed modeling. We included 1221 individuals (NC n = 492, MCI n = 527, AD-type dementia n = 202) with a mean age of 67.9 (SD 8.3) years. The percentage Aβ+ was 26% in the NC, 58% in the MCI, and 87% in the AD-type dementia groups. Plasma samples were available for 1189 (97%) subjects, DNA samples for 929 (76%) subjects, MRI scans for 862 (71%) subjects and CSF samples for 767 (63%) subjects. For 759 (62%) individuals, clinical follow-up data were available. In each diagnostic group, the APOE ε4 allele was more frequent amongst Aβ+ individuals (p &lt; 0.001). Only in MCI was there a difference in baseline Mini Mental State Examination (MMSE) score between the A groups (p &lt; 0.001). Aβ+ had a faster rate of decline on the MMSE during follow-up in the NC (p &lt; 0.001) and MCI (p &lt; 0.001) groups. The characteristics of this large cohort of elderly subjects at various cognitive stages confirm the central roles of Aβ and APOE ε4 in AD pathogenesis. The results of the multimodal analyses will provide new insights into underlying mechanisms and facilitate the discovery of new diagnostic and prognostic AD biomarkers. All researchers can apply for access to the EMIF-AD MBD data by submitting a research proposal via the EMIF-AD Catalog