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

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

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Copia digital. España : Ministerio de Cultura y Deporte. Subdirección General de Coordinación Bibliotecaria, 201

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

Exploration of cannabis use and polygenic risk scores on the psychotic symptom progression of a FEP cohort

Cannabis use is highly prevalent in first-episode psychosis (FEP) and plays a critical role in its onset and prognosis, but the genetic underpinnings promoting both conditions are poorly understood. Current treatment strategies for cannabis cessation in FEP are clearly inefficacious. Here, we aimed to characterize the association between cannabis-related polygenic risk scores (PRS) on cannabis use and clinical course after a FEP. A cohort of 249 FEP individuals were evaluated during 12 months. Symptom severity was measured with the Positive and Negative Severity Scale and cannabis use with the EuropASI scale. Individual PRS for lifetime cannabis initiation (PRSCI) and cannabis use disorder (PRSCUD) were constructed. Current cannabis use was associated with increased positive symptoms. Cannabis initiation at younger ages conditioned the 12-month symptom progression. FEP patients with higher cannabis PRSCUD reported increased baseline cannabis use. PRSCI was associated with the course of negative and general symptomatology over follow-up. Cannabis use and symptom progression after a FEP were modulated by cannabis PRS, suggesting that lifetime initiation and use disorders may have partially independent genetic factors. These exploratory results may be the first step to identify those FEP patients more vulnerable to cannabis use and worse outcomes to ultimately develop tailored treatments

Quality of Maternal and Neonatal Care in Albania, Turkmenistan and Kazakhstan: A Systematic, Standard-Based, Participatory Assessment

BACKGROUND: Progress in maternal and neonatal mortality has been slow in many countries despite increasing access to institutional births, suggesting deficiencies in the quality of care. We carried out a systematic assessment of the quality of maternal and newborn care in three CEE/CIS countries, using an innovative approach to identify priority issues and promote action. METHODS: A standard-based tool, covering over 400 items grouped in 13 main areas ranging from support services to case management, was used to assess a sample of ten maternity hospitals in Albania, Kazakhstan and Turkmenistan. Sources of information were visit to services, medical records, observation of cases, and interviews with staff and mothers. A score (range 0 to 3) was attributed to each item and area of care. The assessment was carried out by a multidisciplinary team of international and national professionals. Local managers and staff provided the necessary information and were involved in discussing the findings and the priority actions. RESULTS: Quality of care was found to be substandard in all 13 areas. The lowest scores (between one and two) were obtained by: management of normal labour, delivery, obstetric complications and sick babies; infection prevention; use of guidelines and audits; monitoring and follow-up. Neonatal care as a whole scored better than obstetric care. Interviewed mothers identified lack of information, insufficient support during labour and lack of companionship as main issues. Actions to improve quality of care were identified at facility as well as at central level and framed according to main health system functions. CONCLUSIONS: Quality of care is a key issue to improve maternal and neonatal outcomes, particularly in countries such as CEE/CIS where access to institutional births is nearly universal. Approaches that involve health professionals and managers in comprehensive, action-oriented assessments of quality of care are promising and should be further supported

Interventions and approaches to integrating HIV and mental health services: a systematic review.

BACKGROUND: The frequency in which HIV and AIDS and mental health problems co-exist, and the complex bi-directional relationship between them, highlights the need for effective care models combining services for HIV and mental health. Here, we present a systematic review that synthesizes the literature on interventions and approaches integrating these services. METHODS: This review was part of a larger systematic review on integration of services for HIV and non-communicable diseases. Eligible studies included those that described or evaluated an intervention or approach aimed at integrating HIV and mental health care. We searched multiple databases from inception until October 2015, independently screened articles identified for inclusion, conducted data extraction, and assessed evaluative papers for risk of bias. RESULTS: Forty-five articles were eligible for this review. We identified three models of integration at the meso and micro levels: single-facility integration, multi-facility integration, and integrated care coordinated by a non-physician case manager. Single-site integration enhances multidisciplinary coordination and reduces access barriers for patients. However, the practicality and cost-effectiveness of providing a full continuum of specialized care on-site for patients with complex needs is arguable. Integration based on a collaborative network of specialized agencies may serve those with multiple co-morbidities but fragmented and poorly coordinated care can pose barriers. Integrated care coordinated by a single case manager can enable continuity of care for patients but requires appropriate training and support for case managers. Involving patients as key actors in facilitating integration within their own treatment plan is a promising approach. CONCLUSION: This review identified much diversity in integration models combining HIV and mental health services, which are shown to have potential in yielding positive patient and service delivery outcomes when implemented within appropriate contexts. Our review revealed a lack of research in low- and middle- income countries, and was limited to most studies being descriptive. Overall, studies that seek to evaluate and compare integration models in terms of long-term outcomes and cost-effectiveness are needed, particularly at the health system level and in regions with high HIV and AIDS burden

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