Cerebrospinal fluid Presenilin-1 increases at asymptomatic stage in genetically determined Alzheimer’s disease

Background

Presenilin-1 (PS1), the active component of the intramembrane γ-secretase complex, can be detected as soluble heteromeric aggregates in cerebrospinal fluid (CSF). The aim of this study was to examine the different soluble PS1 complexes in the lumbar CSF (CSF-PS1) of individuals with Alzheimer’s disease (AD), particularly in both symptomatic and asymptomatic genetically determined AD, in order to evaluate their potential as early biomarkers.

Methods

Western blotting, differential centrifugation and co-immunoprecipitation served to determine and characterize CSF-PS1 complexes. We also monitored the assembly of soluble PS1 into complexes in a cell model, and the participation of Aβ in the dynamics and robustness of the stable PS1 complexes.

Results

There was an age-dependent increase in CSF-PS1 levels in cognitively normal controls, the different complexes represented in similar proportions. The total levels of CSF-PS1, and in particular the proportion of the stable 100–150 kDa complexes, increased in subjects with autosomal dominant AD that carried PSEN1 mutations (eight symptomatic and six asymptomatic ADAD) and in Down syndrome individuals (ten demented and ten non-demented DS), compared with age-matched controls (n?=?23), even prior to the appearance of symptoms of dementia. The proportion of stable CSF-PS1 complexes also increased in sporadic AD (n?=?13) and mild-cognitive impaired subjects (n?=?12), relative to age-matched controls (n?=?17). Co-immunoprecipitation demonstrated the association of Aβ oligomers with soluble PS1 complexes, particularly the stable complexes.

Conclusions

Our data suggest that CSF-PS1 complexes may be useful as an early biomarker for AD, reflecting the pathology at asymptomatic state.

     

Heart fatty acid binding protein and Aβ-associated Alzheimer’s neurodegeneration

Background

Epidemiological and molecular findings suggest a relationship between Alzheimer’s disease (AD) and dyslipidemia, although the nature of this association is not well understood.

Results

Using linear mixed effects models, we investigated the relationship between CSF levels of heart fatty acid binding protein (HFABP), a lipid binding protein involved with fatty acid metabolism and lipid transport, amyloid-β (Aβ), phospho-tau, and longitudinal MRI-based measures of brain atrophy among 295 non-demented and demented older individuals. Across all participants, we found a significant association of CSF HFABP with longitudinal atrophy of the entorhinal cortex and other AD-vulnerable neuroanatomic regions. However, we found that the relationship between CSF HABP and brain atrophy was significant only among those with low CSF Aβ_1–42 and occurred irrespective of phospho-tau_181p status.

Conclusions

Our findings indicate that Aβ-associated volume loss occurs in the presence of elevated HFABP irrespective of phospho-tau. This implicates a potentially important role for fatty acid binding proteins in Alzheimer’s disease neurodegeneration.

     

Metabolomic profiling of maternal hair suggests rapid development of intrahepatic cholestasis of pregnancy

Introduction

Intrahepatic cholestasis of pregnancy (ICP) is a common maternal liver disease; development can result in devastating consequences, including sudden fetal death and stillbirth. Currently, recognition of ICP only occurs following onset of clinical symptoms.

Objective

Investigate the maternal hair metabolome for predictive biomarkers of ICP.

Methods

The maternal hair metabolome (gestational age of sampling between 17 and 41 weeks) of 38 Chinese women with ICP and 46 pregnant controls was analysed using gas chromatography–mass spectrometry.

Results

Of 105 metabolites detected in hair, none were significantly associated with ICP.

Conclusion

Hair samples represent accumulative environmental exposure over time. Samples collected at the onset of ICP did not reveal any metabolic shifts, suggesting rapid development of the disease.

     

Optimization of fecal sample preparation for untargeted LC-HRMS based metabolomics

Introduction

Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.

Objectives

In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.

Methods

The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.

Results

A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.

Conclusion

The workflow generated repeatable and informative fingerprints for robust metabolome characterization.

     

A lost opportunity for science: journals promote data sharing in metabolomics but do not enforce it

Introduction

Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.

Objectives

(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.

Methods

A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.

Results

Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.

Conclusion

Further efforts are required to improve data sharing in metabolomics.

     

Multi factorial interactions in the pathogenesis pathway of Alzheimer’s disease: a new risk charts for prevention of dementia

Background

The population longitudinal study named “The Conselice Study” has been the focus of the present investigation. 65 years old or older participants of this population study on brain aging were followed up for 5 years: 937 subjects completed the follow-up. Relationships of 46 genetic, phenotypic, clinical and nutritional factors on incident cognitive decline and incident dementia cases were investigated.

Results

A new statistical approach, called the Auto Contractive Map (AutoCM) was applied to find relationship between variables and a possible hierarchy in the relevance of each variable with incident dementia. This method, based on an artificial adaptive system, was able to define the association strength of each variable with all the others. Moreover, few variables resulted to be aggregation points in the variable connectivity map related to cognitive decline and dementia. Gene variants and cognate phenotypic variables showed differential degrees of relevance to brain aging and dementia. A risk map for age associated cognitive decline and dementia has been constructed and will be presented and discussed.

Conclusion

This map of variables may be use to identify subjects with increased risk of developing cognitive decline end/or dementia and provide pivotal information for early intervention protocols for prevention of dementia.

     

Analysis of influencing factor of coexisting prediabetes and prehypertension in adult residents of Jilin Province

Background

To explore the risk factors of coexisting prediabetes and prehypertension, to provide theoretical basis for early intervention.

Methods

A multi-stage stratified random cluster sampling method was used to randomly select adult residents from Jilin Province in 2013 for questionnaire surveys, physical examinations, and laboratory tests.

Results

The prevalence of coexisting prediabetes and prehypertension in Jilin Province was 11.3%. The binary Logistic regression results showed that age, sex, education, triglyceride (TG), BMI, waist circumference and alcohol consumption were the effects of factor coexisting prediabetes and prehypertension.

Conclusion

It is important to pay attention to the early stage of hypertension and diabetes, control the transition from prehypertension and prediabetes to hypertension and diabetes, and improve the health of residents.

     

Serum metabolomic study for detecting biomarkers of non-traumatic osteonecrosis of the femoral head

Introduction

Non-traumatic osteonecrosis of the femoral head (NTONFH) is a progressive disease, always leading to hip dysfunction if no early intervention was applied. The difficulty for early diagnosis of NTONFH is due to the slight symptoms at early stages as well as the high cost for screening patients by using magnetic resonance imaging.

Objective

The aim was to detect biomarkers of early-stage NTONFH, which was beneficial to the exploration of a cost-effective approach for the early diagnose of the disease.

Methods

Metabolomic approaches were employed in this study to detect biomarkers of early-stage NTONFH (22 patients, 23 controls), based on the platform of ultra-performance liquid chromatography tandem quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) and the uses of multivariate statistic analysis, putative metabolite identification, metabolic pathway analysis and biomarker analysis.

Results

In total, 33 serum metabolites were found altered between NTONFH group and control group. In addition, glycerophospholipid metabolism and pyruvate metabolism were highly associated with the disease.

Conclusion

The combination of LysoPC (18:3), l-tyrosine and l-leucine proved to have a high diagnostic value for early-stage NTONFH. Our findings may contribute to the protocol for early diagnosis of NTONFH and further elucidate the underlying mechanisms of the disease.

     

Pseudo current density maps of electrophysiological heart,nerve or brain function and their physical basis

Background

In recent years the visualization of biomagnetic measurement data by so-called pseudo current density maps or Hosaka-Cohen (HC) transformations became popular.

Methods

The physical basis of these intuitive maps is clarified by means of analytically solvable problems.

Results

Examples in magnetocardiography, magnetoencephalography and magnetoneurography demonstrate the usefulness of this method.

Conclusion

Hardware realizations of the HC-transformation and some similar transformations are discussed which could advantageously support cross-platform comparability of biomagnetic measurements.

     

Untargeted metabolomics suffers from incomplete raw data processing

Introduction

Untargeted metabolomics is a powerful tool for biological discoveries. To analyze the complex raw data, significant advances in computational approaches have been made, yet it is not clear how exhaustive and reliable the data analysis results are.

Objectives

Assessment of the quality of raw data processing in untargeted metabolomics.

Methods

Five published untargeted metabolomics studies, were reanalyzed.

Results

Omissions of at least 50 relevant compounds from the original results as well as examples of representative mistakes were reported for each study.

Conclusion

Incomplete raw data processing shows unexplored potential of current and legacy data.

     

Implementatie en (kosten-)effectiviteit van casemanagement voor mensen met dementie en hun mantelzorgers: resultaten van de COMPAS-studie

Background

Different forms of case management for dementia have emerged over the past few years. In the COMPAS study (Collaborative dementia care for patients and caregivers study), two prominent Dutch case management forms were studied: the linkage and the integrated care form.

Aim of study

Evaluation of the (cost)effectiveness of two dementia case management forms compared to usual care as well as factors that facilitated or impeded their implementation.

Methods

A mixed methods design with a) a prospective, observational controlled cohort study with 2 years follow-up among 521 dyads of people with dementia and their primary informal caregiver with and without case management; b) interviews with 22 stakeholders on facilitating and impeding factors of the implementation and continuity of the two case management models. Outcome measures were severity and frequency of behavioural problems (NPI) for the person with dementia and mental health complaints (GHQ-12) for the informal caregiver, total met and unmet care needs (CANE) and quality adjusted life years (QALYs).

Results

Outcomes showed a better quality of life of informal caregivers in the integrated model compared to the linkage model. Caregivers in the control group reported more care needs than those in both case management groups.The independence of the case management provider in the integrated model facilitated the implementation, while the rivalry between multiple providers in the linkage model impeded the implementation. The costs of care were lower in the linkage model (minus 22 %) and integrated care model (minus 33 %) compared to the control group.

Conclusion

The integrated care form was (very) cost-effective in comparison with the linkage form or no case management. The integrated care form is easy to implement.

     

Quantitative analysis of tetrahydrofolate metabolites from <Emphasis Type="Italic">clostridium autoethanogenum</Emphasis>

Introduction

Quantification of tetrahydrofolates (THFs), important metabolites in the Wood–Ljungdahl pathway (WLP) of acetogens, is challenging given their sensitivity to oxygen.

Objective

To develop a simple anaerobic protocol to enable reliable THFs quantification from bioreactors.

Methods

Anaerobic cultures were mixed with anaerobic acetonitrile for extraction. Targeted LC–MS/MS was used for quantification.

Results

Tetrahydrofolates can only be quantified if sampled anaerobically. THF levels showed a strong correlation to acetyl-CoA, the end product of the WLP.

Conclusion

Our method is useful for relative quantification of THFs across different growth conditions. Absolute quantification of THFs requires the use of labelled standards.

     

A methodology for elucidating regulatory mechanisms leading to changes in lipid profiles

Introduction

It is difficult to elucidate the metabolic and regulatory factors causing lipidome perturbations.

Objectives

This work simplifies this process.

Methods

A method has been developed to query an online holistic lipid metabolic network (of 7923 metabolites) to extract the pathways that connect the input list of lipids.

Results

The output enables pathway visualisation and the querying of other databases to identify potential regulators. When used to a study a plasma lipidome dataset of polycystic ovary syndrome, 14 enzymes were identified, of which 3 are linked to ELAVL1—an mRNA stabiliser.

Conclusion

This method provides a simplified approach to identifying potential regulators causing lipid-profile perturbations.

     

KniMet: a pipeline for the processing of chromatography–mass spectrometry metabolomics data

Introduction

Data processing is one of the biggest problems in metabolomics, given the high number of samples analyzed and the need of multiple software packages for each step of the processing workflow.

Objectives

Merge in the same platform the steps required for metabolomics data processing.

Methods

KniMet is a workflow for the processing of mass spectrometry-metabolomics data based on the KNIME Analytics platform.

Results

The approach includes key steps to follow in metabolomics data processing: feature filtering, missing value imputation, normalization, batch correction and annotation.

Conclusion

KniMet provides the user with a local, modular and customizable workflow for the processing of both GC–MS and LC–MS open profiling data.

     

Extraction of natural products from bark of <Emphasis Type="Italic">Betula pendula</Emphasis> using ionic liquids

Introduction

Aqueous–methanol mixtures have successfully been applied to extract a broad range of metabolites from plant tissue. However, a certain amount of material remains insoluble.

Objectives

To enlarge the metabolic compendium, two ionic liquids were selected to extract the methanol insoluble part of trunk from Betula pendula.

Methods

The extracted compounds were analyzed by LC/MS and GC/MS.

Results

The results show that 1-butyl-3-methylimidazolium acetate (IL-Ac) predominantly resulted in fatty acids, whereas 1-ethyl-3-methylimidazolium tosylate (IL-Tos) mostly yielded phenolic structures. Interestingly, bark yielded more ionic liquid soluble metabolites compared to interior wood.

Conclusion

From this one can conclude that the application of ionic liquids may expand the metabolic snapshot.

     

Sleeping posture recognition using fuzzy c-means algorithm

Background

Pressure sensors have been used for sleeping posture detection, which meet privacy requirements. Most of the existing techniques for sleeping posture recognition used force-sensitive resistor (FSR) sensors. However, lower limbs cannot be recognized accurately unless thousands of sensors are deployed on the bedsheet.

Method

We designed a sleeping posture recognition scheme in which FSR sensors were deployed on the upper part of the bedsheet to record the pressure distribution of the upper body. In addition, an infrared array sensor was deployed to collect data for the lower body. Posture recognition was performed using a fuzzy c-means clustering algorithm. Six types of sleeping body posture were recognized from the combination of the upper and lower body postures.

Results

The experimental results showed that the proposed method achieved an accuracy of above 88%. Moreover, the proposed scheme is cost-efficient and easy to deploy.

Conclusions

The proposed sleeping posture recognition system can be used for pressure ulcer prevention and sleep quality assessment. Compared to wearable sensors and cameras, FSR sensors and infrared array sensors are unobstructed and meet privacy requirements. Moreover, the proposed method provides a cost-effective solution for the recognition of sleeping posture.

     

Metabolic response of porcine colon explants to in vitro infection by <Emphasis Type="Italic">Brachyspira hyodysenteriae</Emphasis>: a leap into disease pathophysiology

Introduction

Swine dysentery caused by Brachyspira hyodysenteriae is a production limiting disease in pig farming. Currently antimicrobial therapy is the only treatment and control method available.

Objective

The aim of this study was to characterize the metabolic response of porcine colon explants to infection by B. hyodysenteriae.

Methods

Porcine colon explants exposed to B. hyodysenteriae were analyzed for histopathological, metabolic and pro-inflammatory gene expression changes.

Results

Significant epithelial necrosis, increased levels of l-citrulline and IL-1α were observed on explants infected with B. hyodysenteriae.

Conclusions

The spirochete induces necrosis in vitro likely through an inflammatory process mediated by IL-1α and NO.

     

Forecasting infectious disease emergence subject to seasonal forcing

Background

Despite high vaccination coverage, many childhood infections pose a growing threat to human populations. Accurate disease forecasting would be of tremendous value to public health. Forecasting disease emergence using early warning signals (EWS) is possible in non-seasonal models of infectious diseases. Here, we assessed whether EWS also anticipate disease emergence in seasonal models.

Methods

We simulated the dynamics of an immunizing infectious pathogen approaching the tipping point to disease endemicity. To explore the effect of seasonality on the reliability of early warning statistics, we varied the amplitude of fluctuations around the average transmission. We proposed and analyzed two new early warning signals based on the wavelet spectrum. We measured the reliability of the early warning signals depending on the strength of their trend preceding the tipping point and then calculated the Area Under the Curve (AUC) statistic.

Results

Early warning signals were reliable when disease transmission was subject to seasonal forcing. Wavelet-based early warning signals were as reliable as other conventional early warning signals. We found that removing seasonal trends, prior to analysis, did not improve early warning statistics uniformly.

Conclusions

Early warning signals anticipate the onset of critical transitions for infectious diseases which are subject to seasonal forcing. Wavelet-based early warning statistics can also be used to forecast infectious disease.

     

NMRProcFlow: a graphical and interactive tool dedicated to 1D spectra processing for NMR-based metabolomics

Introduction

Concerning NMR-based metabolomics, 1D spectra processing often requires an expert eye for disentangling the intertwined peaks.

Objectives

The objective of NMRProcFlow is to assist the expert in this task in the best way without requirement of programming skills.

Methods

NMRProcFlow was developed to be a graphical and interactive 1D NMR (¹H & ¹³C) spectra processing tool.

Results

NMRProcFlow (http://nmrprocflow.org), dedicated to metabolic fingerprinting and targeted metabolomics, covers all spectra processing steps including baseline correction, chemical shift calibration and alignment.

Conclusion

Biologists and NMR spectroscopists can easily interact and develop synergies by visualizing the NMR spectra along with their corresponding experimental-factor levels, thus setting a bridge between experimental design and subsequent statistical analyses.