Composition of active bacterial communities and presence of opportunistic pathogens in disinfected and non-disinfected drinking water distribution systems in Finland

Many factors, including microbiome structure and activity in the drinking water distribution system (DWDS), affect the colonization potential of opportunistic pathogens. The present study aims to describe the dynamics of active bacterial communities in DWDS and identify the factors that shape the community structures and activity in the selected DWDSs. Large-volume drinking water and hot water, biofilm, and water meter deposit samples were collected from five DWDSs. Total nucleic acids were extracted, and RNA was further purified and transcribed into its cDNA from a total of 181 water and biofilm samples originating from the DWDS of two surface water supplies (disinfected with UV and chlorine), two artificially recharged groundwater supplies (non-disinfected), and a groundwater supply (disinfected with UV and chlorine). In chlorinated DWDSs, concentrations of <0.02-0.97 mg/l free chlorine were measured. Bacterial communities in the RNA and DNA fractions were analysed using Illumina MiSeq sequencing with primer pair 341F-785R targeted to the 16S rRNA gene. The sequence libraries were analysed using QIIME pipeline, Program R, and MicrobiomeAnalyst. Not all bacterial cells were active based on their 16S rRNA content, and species richness was lower in the RNA fraction (Chao1 mean value 490) than in the DNA fraction (710). Species richness was higher in the two DWDSs distributing non-disinfected artificial groundwater (Chao1 mean values of 990 and 1 000) as compared to the two disinfected DWDSs using surface water (Chao1 mean values 190 and 460) and disinfected DWDS using ground water as source water (170). The difference in community structures between non-disinfected and disinfected water was clear in the beta-diversity analysis. Distance from the waterworks also affected the beta diversity of community structures, especially in disinfected distribution systems. The two most abundant bacteria in the active part of the community (RNA) and total bacterial community (DNA) belonged to the classes Alphaproteobacteria (RNA 28 %, DNA 44 %) and Gammaproteobacteria (RNA 32 %, DNA 30 %). The third most abundant and active bacteria class was Vampirovibrionia (RNA 15 %), whereas in the total community it was Paceibacteria (DNA 11 %). Class Nitrospiria was more abundant and active in both cold and hot water in DWDS that used chloramine disinfection compared to non-chlorinated or chlorine-using DWDSs. Thirty-eight operational taxonomic units (OTU) of Legionella, 30 of Mycobacterium, and 10 of Pseudomonas were detected among the sequences. The (RT)-qPCR confirmed the presence of opportunistic pathogens in the DWDSs studied as Legionella spp. was detected in 85 % (mean value 4.5 × 104 gene copies/100 ml), Mycobacterium spp. in 95 % (mean value 8.3 × 106 gene copies/100 ml), and Pseudomonas spp. in 78 % (mean value 1.6 × 105 gene copies/100 ml) of the water and biofilm samples. Sampling point inside the system (distance from the waterworks and cold/hot system) affected the active bacterial community composition. Chloramine as a chlorination method resulted in a recognizable community composition, with high abundance of bacteria that benefit from the excess presence of nitrogen. The results presented here confirm that each DWDS is unique and that opportunistic pathogens are present even in conditions when water quality is considered excellent.

Diagnostic yield of genetic testing in a multinational heterogeneous cohort of 2088 DCM patients

Background

Familial dilated cardiomyopathy (DCM) causes heart failure and may lead to heart transplantation. DCM is typically a monogenic disorder with autosomal dominant inheritance. Currently disease-causing variants have been reported in over 60 genes that encode proteins in sarcomeres, nuclear lamina, desmosomes, cytoskeleton, and mitochondria. Over half of the patients undergoing comprehensive genetic testing are left without a molecular diagnosis even when patient selection follows strict DCM criteria.

Methods and results

This study was a retrospective review of patients referred for genetic testing at Blueprint Genetics due to suspected inherited DCM. Next generation sequencing panels included 23-316 genes associated with cardiomyopathies and other monogenic cardiac diseases. Variants were considered diagnostic if classified as pathogenic (P) or likely pathogenic (LP). Of the 2,088 patients 514 (24.6%) obtained a molecular diagnosis; 534 LP/P variants were observed across 45 genes, 2.7% (14/514) had two diagnostic variants in dominant genes. Nine copy number variants were identified: two multigene and seven intragenic. Diagnostic variants were observed most often in TTN (45.3%), DSP (6.7%), LMNA (6.7%), and MYH7 (5.2%). Clinical characteristics independently associated with molecular diagnosis were: a lower age at diagnosis, family history of DCM, paroxysmal atrial fibrillation, absence of left bundle branch block, and the presence of an implantable cardioverter-defibrillator.

Conclusions

Panel testing provides good diagnostic yield in patients with clinically suspected DCM. Causative variants were identified in 45 genes. In minority, two diagnostic variants were observed in dominant genes. Our results support the use of genetic panels in clinical settings in DCM patients with suspected genetic etiology.

GRINL1A Complex Transcription Unit Containing GCOM1, MYZAP, and POLR2M Genes Associates with Fully Penetrant Recessive Dilated Cardiomyopathy

Background: Familial dilated cardiomyopathy (DCM) is a monogenic disorder typically inherited in an autosomal dominant pattern. We have identified two Finnish families with familial cardiomyopathy that is not explained by a variant in any previously known cardiomyopathy gene. We describe the cardiac phenotype related to homozygous truncating GCOM1 variants. Methods and Results: This study included two probands and their relatives. All the participants are of Finnish ethnicity. Whole-exome sequencing was used to test the probands; bi-directional Sanger sequencing was used to identify the GCOM1 variants in probands' family members. Clinical evaluation was performed, medical records and death certificates were obtained. Immunohistochemical analysis of myocardial samples was conducted. A homozygous GCOM1 variant was identified altogether in six individuals, all considered to be affected. None of the nine heterozygous family members fulfilled any cardiomyopathy criteria. Heart failure was the leading clinical feature, and the patients may have had a tendency for atrial arrhythmias. Conclusions: This study demonstrates the significance of GCOM1 variants as a cause of human cardiomyopathy and highlights the importance of searching for new candidate genes when targeted gene panels do not yield a positive outcome.

Diverse and active archaea communities occur in non-disinfected drinking water systems-Less activity revealed in disinfected and hot water systems

The knowledge about the members of active archaea communities in DWDS is limited. The current understanding is based on high-throughput 16S ribosomal RNA gene (DNA-based) amplicon sequencing that reveals the diversity of active, dormant, and dead members of the prokaryote (bacteria, archaea) communities. The sequencing primers optimized for bacteria community analysis may underestimate the share of the archaea community. This study characterized archaea communities at five full-scale drinking water distribution systems (DWDS), representing a variety of drinking water production units (A-E); A&B use artificially recharged non-disinfected groundwater (ARG), the other DWDS's supplied water disinfected by using ultraviolet (UV) light and chlorine compounds, C&D were surface waterworks and E was a ground waterworks. For the first time for archaea community analyses, this study employed the archaea-specific high-throughput sequencing primers for 16S ribosomal RNA (rRNA) as a target (reverse-transcribed cDNA; an RNA-based approach) in addition to the previously used 16S rRNA gene target (rDNA; a DNA-based approach) to reveal the active fraction of the archaea present in DWDS. The archaea community structure in varying environmental conditions in the water and biofilm of the five DWDSs were investigated by taking into consideration the system properties (cold or hot water system) and water age (distance from the treatment plants) in samples from each season of one year. The RNA-based archaea amplicon reads were obtained mostly from cold water samples from DWDSs (A-B) distributing water without disinfection where the DNA-based and RNA-based analysis created separate clusters in a weighted beta-diversity analysis. The season and location in DWDS A further affected the diversity of these archaea communities as was seen by different clusters in beta-diversity plots. The recovery of archaea reads was not adequate for analysis in any of the disinfected samples in DWDSs C-E or non-disinfected hot water in DWDSs A-B when utilizing RNA-based template. The metabolically active archaea community of DWDSs thus seemed to be effectively controlled by disinfection of water and in the hot water systems by the temperature. All biofilms regardless of DWDS showed lower species richness values (mainly Nitrososphaeria class) than non-disinfected water from DWDSs A-B where several archaea classes occurred (e.g. Woesearchaeia, Nitrososphaeria, Micrarchaeia, Methanomicrobia, Iairchaeia, Bathyarchaeia) indicating only part of the archaea members were able to survive in biofilms. Thus, Archaea has been shown as a significant part of normal DWDS biota, and their role especially in non-disinfected DWDS may be more important than previously considered.

Putative metabolites involved in the beneficial effects of wholegrain cereal: Nontargeted metabolite profiling approach

BACKGROUND AND AIMS

Wholegrain cereals have been implicated in the reduction of lifestyle-related chronic diseases risk including cardiovascular diseases and type 2 diabetes. Molecular mechanisms responsible for the beneficial health effects are not entirely understood. The aims of this study were 1) to identify new potential plasma biomarker candidate metabolites of wholegrain cereal foods intake and 2) to examine whether some putative metabolites associated with wholegrain foods intake may play a role in the improvement of cardiometabolic risk factors.

METHODS AND RESULTS

Analysis have been conducted in 54 individuals with metabolic syndrome of both genders, age 40-65 years, randomly assigned to 2 dietary interventions lasting 12-week: 1) wholegrain enriched diet (n = 28), and 2) refined-wheat cereals diet (control diet) (n = 26). Nontargeted metabolite profiling analysis was performed on fasting plasma samples collected at baseline and at the end of the experimental diets. Our data show that, at the end of the intervention, a higher intake of wholegrain (tertile 3) was significantly associated with a marked increase in several lipid compounds, as PC (20:4/16:1), LPC (20:4), LPC (22:6), LPC (18:3), LPC (22:5), and a phenolic compound (P < .05 for all). In the wholegrain group, higher concentrations of these metabolites (tertile 3 vs tertile 1 of each metabolite) were significantly associated with lower postprandial insulin and triglyceride responses (P < .05) by 29% and 37%, respectively.

CONCLUSION

These observations suggest a possible role of lipid and polyphenol metabolites in the postprandial metabolic benefits of wholegrains in subjects at high risk of cardiovascular disease. In addition, they provide insight into the role of these metabolites as potential candidate biomarkers of wholegrain foods. The study was registered on ClinicalTrials.gov (identifier: NCT00945854).

Diagnostic yield of genetic testing in a heterogeneous cohort of 1376 HCM patients

Background

Genetic testing in hypertrophic cardiomyopathy (HCM) is a published guideline-based recommendation. The diagnostic yield of genetic testing and corresponding HCM-associated genes have been largely documented by single center studies and carefully selected patient cohorts. Our goal was to evaluate the diagnostic yield of genetic testing in a heterogeneous cohort of patients with a clinical suspicion of HCM, referred for genetic testing from multiple centers around the world.

Methods

A retrospective review of patients with a suspected clinical diagnosis of HCM referred for genetic testing at Blueprint Genetics was undertaken. The analysis included syndromic, myopathic and metabolic etiologies. Genetic test results and variant classifications were extracted from the database. Variants classified as pathogenic (P) or likely pathogenic (LP) were considered diagnostic.

Results

A total of 1376 samples were analyzed. Three hundred and sixty-nine tests were diagnostic (26.8%); 373 P or LP variants were identified. Only one copy number variant was identified. The majority of diagnostic variants involved genes encoding the sarcomere (85.0%) followed by 4.3% of diagnostic variants identified in the RASopathy genes. Two percent of diagnostic variants were in genes associated with a cardiomyopathy other than HCM or an inherited arrhythmia. Clinical variables that increased the likelihood of identifying a diagnostic variant included: an earlier age at diagnosis (p < 0.0001), a higher maximum wall thickness (MWT) (p < 0.0001), a positive family history (p < 0.0001), the absence of hypertension (p = 0.0002), and the presence of an implantable cardioverter-defibrillator (ICD) (p = 0.0004).

Conclusion

The diagnostic yield of genetic testing in this heterogeneous cohort of patients with a clinical suspicion of HCM is lower than what has been reported in well-characterized patient cohorts. We report the highest yield of diagnostic variants in the RASopathy genes identified in a laboratory cohort of HCM patients to date. The spectrum of genes implicated in this unselected cohort highlights the importance of pre-and post-test counseling when offering genetic testing to the broad HCM population.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-021-01927-5.

Biallelic loss-of-function in NRAP is a cause of recessive dilated cardiomyopathy

BACKGROUND

Familial dilated cardiomyopathy (DCM) is typically a monogenic disorder with dominant inheritance. Although over 40 genes have been linked to DCM, more than half of the patients undergoing comprehensive genetic testing are left without molecular diagnosis. Recently, biallelic protein-truncating variants (PTVs) in the nebulin-related anchoring protein gene (NRAP) were identified in a few patients with sporadic DCM.

METHODS AND RESULTS

We determined the frequency of rare NRAP variants in a cohort of DCM patients and control patients to further evaluate role of this gene in cardiomyopathies. A retrospective analysis of our internal variant database consisting of 31,639 individuals who underwent genetic testing (either panel or direct exome sequencing) was performed. The DCM group included 577 patients with either a confirmed or suspected DCM diagnosis. A control cohort of 31,062 individuals, including 25,912 individuals with non-cardiac (control group) and 5,150 with non-DCM cardiac indications (Non-DCM cardiac group). Biallelic (n = 6) or two (n = 5) NRAP variants (two PTVs or PTV+missense) were identified in 11 unrelated probands with DCM (1.9%) but none of the controls. None of the 11 probands had an alternative molecular diagnosis. Family member testing supports co-segregation. Biallelic or potentially biallelic NRAP variants were enriched in DCM vs. controls (OR 1052, p<0.0001). Based on the frequency of NRAP PTVs in the gnomAD reference population, and predicting full penetrance, biallelic NRAP variants could explain 0.25%-2.46% of all DCM cases.

CONCLUSION

Loss-of-function in NRAP is a cause for autosomal recessive dilated cardiomyopathy, supporting its inclusion in comprehensive genetic testing.

ThETA: transcriptome-driven efficacy estimates for gene-based TArget discovery

Summary

Estimating efficacy of gene–target-disease associations is a fundamental step in drug discovery. An important data source for this laborious task is RNA expression, which can provide gene–disease associations on the basis of expression fold change and statistical significance. However, the simply use of the log-fold change can lead to numerous false-positive associations. On the other hand, more sophisticated methods that utilize gene co-expression networks do not consider tissue specificity. Here, we introduce Transcriptome-driven Efficacy estimates for gene-based TArget discovery (ThETA), an R package that enables non-expert users to use novel efficacy scoring methods for drug–target discovery. In particular, ThETA allows users to search for gene perturbation (therapeutics) that reverse disease-gene expression and genes that are closely related to disease-genes in tissue-specific networks. ThETA also provides functions to integrate efficacy evaluations obtained with different approaches and to build an overall efficacy score, which can be used to identify and prioritize gene(target)–disease associations. Finally, ThETA implements visualizations to show tissue-specific interconnections between target and disease-genes, and to indicate biological annotations associated with the top selected genes.

Availability and implementation

ThETA is freely available for academic use at https://github.com/vittoriofortino84/ThETA.

Contact

vittorio.fortino@uef.fi

Supplementary information

Supplementary data are available at Bioinformatics online.

Detection of medications associated with Alzheimer's disease using ensemble methods and cooperative game theory

OBJECTIVE

To study the feasibility of evaluating feature importance with Shapley Values and ensemble methods in the context of pharmacoepidemiology and medication safety.

METHODS

We detected medications associated with Alzheimer's disease (AD) by examining the additive feature attribution with combined approach of Gradient Boosting and Shapley Values in the Medication use and Alzheimer's disease (MEDALZ) study, a nested case-control study of 70,719 verified AD cases in Finland. Our methodological approach is to do binary classification using Gradient boosting (an ensemble of weak classifiers) in a supervised learning manner. Then we apply Shapley Values (from cooperative game theory) to analyze how feature combinations affect the classification result. Medication use with a five to one year time-window before AD diagnosis was ascertained from Prescription register.

RESULTS

Antipsychotics with low or medium dose, antidepressants with medium to high dose, and cardiovascular medications with medium to high dose were identified as the contributing features for separating cases with AD from controls. Medium to high amount of irregularity in the purchase pattern were an indicating feature for separating AD cases from controls. The similarity of medication purchases between AD cases and controls made the feature evaluation challenging.

CONCLUSIONS

The combined approach of Gradient Boosting and feature evaluation with Shapley Values identified features that were consistent with findings from previous hypothesis-driven studies. Additionally, the results from the additive feature attribution identified new candidates for future studies on AD risk factors. Our approach also shows promise for studies based on observational studies, where feature identification and interactions in populations are of interest; and the applicability of using Shapley Values for evaluating feature relevance in pattern recognition tasks.

"notame": Workflow for Non-Targeted LC-MS Metabolic Profiling

Metabolomics analysis generates vast arrays of data, necessitating comprehensive workflows involving expertise in analytics, biochemistry and bioinformatics in order to provide coherent and high-quality data that enable discovery of robust and biologically significant metabolic findings. In this protocol article, we introduce notame, an analytical workflow for non-targeted metabolic profiling approaches, utilizing liquid chromatography-mass spectrometry analysis. We provide an overview of lab protocols and statistical methods that we commonly practice for the analysis of nutritional metabolomics data. The paper is divided into three main sections: the first and second sections introducing the background and the study designs available for metabolomics research and the third section describing in detail the steps of the main methods and protocols used to produce, preprocess and statistically analyze metabolomics data and, finally, to identify and interpret the compounds that have emerged as interesting.

Susceptibility to Cardiac Arrhythmias and Sympathetic Nerve Growth in VEGF-B Overexpressing Myocardium

VEGF-B gene therapy is a promising proangiogenic treatment for ischemic heart disease, but, unexpectedly, we found that high doses of VEGF-B promote ventricular arrhythmias (VAs). VEGF-B knockout, alpha myosin heavy-chain promoter (αMHC)-VEGF-B transgenic mice, and pigs transduced intramyocardially with adenoviral (Ad)VEGF- B186 were studied. Immunostaining showed a 2-fold increase in the number of nerves per field (76 vs. 39 in controls, p < 0.001) and an abnormal nerve distribution in the hypertrophic hearts of 11- to 20-month-old αMHC-VEGF-B mice. AdVEGF-B186 gene transfer (GT) led to local sprouting of nerve endings in pig myocardium (141 vs. 78 nerves per field in controls, p < 0.05). During dobutamine stress, 60% of the αMHC-VEGF-B hypertrophic mice had arrhythmias as compared to 7% in controls, and 20% of the AdVEGF-B186-transduced pigs and 100% of the combination of AdVEGF-B186- and AdsVEGFR-1-transduced pigs displayed VAs and even ventricular fibrillation. AdVEGF-B186 GT significantly increased the risk of sudden cardiac death in pigs when compared to any other GT with different VEGFs (hazard ratio, 500.5; 95% confidence interval [CI] 46.4-5,396.7; p < 0.0001). In gene expression analysis, VEGF-B induced the upregulation of Nr4a2, ATF6, and MANF in cardiomyocytes, molecules previously linked to nerve growth and differentiation. Thus, high AdVEGF-B186 overexpression induced nerve growth in the adult heart via a VEGFR-1 signaling-independent mechanism, leading to an increased risk of VA and sudden cardiac death.

An omics perspective on drug target discovery platforms

The drug discovery process starts with identification of a disease-modifying target. This critical step traditionally begins with manual investigation of scientific literature and biomedical databases to gather evidence linking molecular target to disease, and to evaluate the efficacy, safety and commercial potential of the target. The high-throughput and affordability of current omics technologies, allowing quantitative measurements of many putative targets (e.g. DNA, RNA, protein, metabolite), has exponentially increased the volume of scientific data available for this arduous task. Therefore, computational platforms identifying and ranking disease-relevant targets from existing biomedical data sources, including omics databases, are needed. To date, more than 30 drug target discovery (DTD) platforms exist. They provide information-rich databases and graphical user interfaces to help scientists identify putative targets and pre-evaluate their therapeutic efficacy and potential side effects. Here we survey and compare a set of popular DTD platforms that utilize multiple data sources and omics-driven knowledge bases (either directly or indirectly) for identifying drug targets. We also provide a description of omics technologies and related data repositories which are important for DTD tasks.

The Contribution of Staffing to Medication Administration Errors: A Text Mining Analysis of Incident Report Data

PURPOSE

(a) To describe trigger terms that can be used to identify reports of inadequate staffing contributing to medication administration errors, (b) to identify such reports, (c) to compare the degree of harm within incidents with and without those triggers, and (d) to examine the association between the most commonly reported inadequate staffing trigger terms and the incidence of omission errors and "no harm" terms.

DESIGN AND SETTING

This was a retrospective study using descriptive statistical analysis, text mining, and manual analysis of free text descriptions of medication administration-related incident reports (N = 72,390) reported to the National Reporting and Learning System for England and Wales in 2016.

METHODS

Analysis included identifying terms indicating inadequate staffing (manual analysis), followed by text parsing, filtering, and concept linking (SAS Text Miner tool). IBM SPSS was used to describe the data, compare degree of harm for incidents with and without triggers, and to compare incidence of "omission errors" and "no harm" among the inadequate staffing trigger terms.

FINDINGS

The most effective trigger terms for identifying inadequate staffing were "short staffing" (n = 81), "workload" (n = 80), and "extremely busy" (n = 51). There was significant variation in omission errors across inadequate staffing trigger terms (Fisher's exact test = 44.11, p < .001), with those related to "workload" most likely to accompany a report of an omission, followed by terms that mention "staffing" and being "busy." Prevalence of "no harm" did not vary statistically between the trigger terms (Fisher's exact test = 11.45, p = 0.49), but the triggers "workload," "staffing level," "busy night," and "busy unit" identified incidents with lower levels of "no harm" than for incidents overall.

CONCLUSIONS

Inadequate staffing levels, workload, and working in haste may increase the risk for omissions and other types of error, as well as for patient harm.

CLINICAL RELEVANCE

This work lays the groundwork for creating automated text-analytical systems that could analyze incident reports in real time and flag or monitor staffing levels and related medication administration errors.

Identifying risks areas related to medication administrations - text mining analysis using free-text descriptions of incident reports

BACKGROUND

Some medications carry increased risk of patient harm when they are given in error. In incident reports, names of the medications that are involved in errors could be found written both in a specific medication field and/or within the free text description of the incident. Analysing only the names of the medications implicated in a specific unstructured medication field does not give information of the associated factors and risk areas, but when analysing unstructured free text descriptions, the information about the medication involved and associated risk factors may be buried within other non-relevant text. Thus, the aim of this study was to extract medication names most commonly used in free text descriptions of medication administration incident reports to identify terms most frequently associated with risk for each of these medications using text mining.

METHOD

Free text descriptions of medication administration incidents (n = 72,390) reported in 2016 to the National Reporting and Learning System for England and Wales were analysed using SAS® Text miner. Analysis included text parsing and filtering free text to identify most commonly mentioned medications, followed by concept linking, and clustering to identify terms associated with commonly mentioned medications and the associated risk areas.

RESULTS

The following risk areas related to medications were identified: 1. Allergic reactions to antibacterial drugs, 2. Intravenous administration of antibacterial drugs, 3. Fentanyl patches, 4. Checking and documenting of analgesic doses, 5. Checking doses of anticoagulants, 6. Insulin doses and blood glucose, 7. Administration of intravenous infusions.

CONCLUSIONS

Interventions to increase medication administration safety should focus on checking patient allergies and medication doses, especially for intravenous and transdermal medications. High-risk medications include insulin, analgesics, antibacterial drugs, anticoagulants, and potassium chloride. Text mining may be useful for analysing large free text datasets and should be developed further.

In Vitro and In Vivo Pipeline for Validation of Disease-Modifying Effects of Systems Biology-Derived Network Treatments for Traumatic Brain Injury-Lessons Learned

We developed a pipeline for the discovery of transcriptomics-derived disease-modifying therapies and used it to validate treatments in vitro and in vivo that could be repurposed for TBI treatment. Desmethylclomipramine, ionomycin, sirolimus and trimipramine, identified by in silico LINCS analysis as candidate treatments modulating the TBI-induced transcriptomics networks, were tested in neuron-BV2 microglial co-cultures, using tumour necrosis factor α as a monitoring biomarker for neuroinflammation, nitrite for nitric oxide-mediated neurotoxicity and microtubule associated protein 2-based immunostaining for neuronal survival. Based on (a) therapeutic time window in silico, (b) blood-brain barrier penetration and water solubility, (c) anti-inflammatory and neuroprotective effects in vitro (p < 0.05) and (d) target engagement of Nrf2 target genes (p < 0.05), desmethylclomipramine was validated in a lateral fluid-percussion model of TBI in rats. Despite the favourable in silico and in vitro outcomes, in vivo assessment of clomipramine, which metabolizes to desmethylclomipramine, failed to demonstrate favourable effects on motor and memory tests. In fact, clomipramine treatment worsened the composite neuroscore (p < 0.05). Weight loss (p < 0.05) and prolonged upregulation of plasma cytokines (p < 0.05) may have contributed to the worsened somatomotor outcome. Our pipeline provides a rational stepwise procedure for evaluating favourable and unfavourable effects of systems-biology discovered compounds that modulate post-TBI transcriptomics.

Random forest-based imputation outperforms other methods for imputing LC-MS metabolomics data: a comparative study

BACKGROUND

LC-MS technology makes it possible to measure the relative abundance of numerous molecular features of a sample in single analysis. However, especially non-targeted metabolite profiling approaches generate vast arrays of data that are prone to aberrations such as missing values. No matter the reason for the missing values in the data, coherent and complete data matrix is always a pre-requisite for accurate and reliable statistical analysis. Therefore, there is a need for proper imputation strategies that account for the missingness and reduce the bias in the statistical analysis.

RESULTS

Here we present our results after evaluating nine imputation methods in four different percentages of missing values of different origin. The performance of each imputation method was analyzed by Normalized Root Mean Squared Error (NRMSE). We demonstrated that random forest (RF) had the lowest NRMSE in the estimation of missing values for Missing at Random (MAR) and Missing Completely at Random (MCAR). In case of absent values due to Missing Not at Random (MNAR), the left truncated data was best imputed with minimum value imputation. We also tested the different imputation methods for datasets containing missing data of various origin, and RF was the most accurate method in all cases. The results were obtained by repeating the evaluation process 100 times with the use of metabolomics datasets where the missing values were introduced to represent absent data of different origin.

CONCLUSION

Type and rate of missingness affects the performance and suitability of imputation methods. RF-based imputation method performs best in most of the tested scenarios, including combinations of different types and rates of missingness. Therefore, we recommend using random forest-based imputation for imputing missing metabolomics data, and especially in situations where the types of missingness are not known in advance.

Varanto: variant enrichment analysis and annotation

SUMMARY

Genome-wide association studies (GWAS) aim to identify associations of genetic variations such as single-nucleotide polymorphisms (SNPs) to a specific trait or a disease. Identifying common themes such as pathways, biological processes and diseases associations is needed to further explore and interpret these results. Varanto is a novel web tool for annotating, visualizing and analyzing human genetic variations using diverse data sources. Varanto can be used to query a set of input variations, retrieve their associated variation and gene level annotations, perform annotation enrichment analysis and visualize the results.

AVAILABILITY AND IMPLEMENTATION

Varanto web app is developed with R and implemented as Shiny app with PostgreSQL database and is freely available at http://bioinformatics.uef.fi/varanto. Source code for the tool is available at https://github.com/oqe/varanto.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Active eukaryotes in drinking water distribution systems of ground and surface waterworks

BACKGROUND

Eukaryotes are ubiquitous in natural environments such as soil and freshwater. Little is known of their presence in drinking water distribution systems (DWDSs) or of the environmental conditions that affect their activity and survival.

METHODS

Eukaryotes were characterized by Illumina high-throughput sequencing targeting 18S rRNA gene (DNA) that estimates the total community and the 18S rRNA gene transcript (RNA) that is more representative of the active part of the community. DWDS cold water (N = 124), hot water (N = 40), and biofilm (N = 16) samples were collected from four cities in Finland. The sampled DWDSs were from two waterworks A-B with non-disinfected, recharged groundwater as source water and from three waterworks utilizing chlorinated water (two DWDSs of surface waterworks C-D and one of ground waterworks E). In each DWDS, samples were collected from three locations during four seasons of 1 year.

RESULTS

A beta-diversity analysis revealed that the main driver shaping the eukaryotic communities was the DWDS (A-E) (R = 0.73, P < 0.001, ANOSIM). The kingdoms Chloroplastida (green plants and algae), Metazoa (animals: rotifers, nematodes), Fungi (e.g., Cryptomycota), Alveolata (ciliates, dinoflagellates), and Stramenopiles (algae Ochrophyta) were well represented and active-judging based on the rRNA gene transcripts-depending on the surrounding conditions. The unchlorinated cold water of systems (A-B) contained a higher estimated total number of taxa (Chao1, average 380-480) than chlorinated cold water in systems C-E (Chao1 ≤ 210). Within each DWDS, unique eukaryotic communities were identified at different locations as was the case also for cold water, hot water, and biofilms. A season did not have a consistent impact on the eukaryotic community among DWDSs.

CONCLUSIONS

This study comprehensively characterized the eukaryotic community members within the DWDS of well-maintained ground and surface waterworks providing good quality water. The study gives an indication that each DWDS houses a unique eukaryotic community, mainly dependent on the raw water source and water treatment processes in place at the corresponding waterworks. In particular, disinfection as well as hot water temperature seemed to represent a strong selection pressure that controlled the number of active eukaryotic species.

Healthy Nordic Diet Modulates the Expression of Genes Related to Mitochondrial Function and Immune Response in Peripheral Blood Mononuclear Cells from Subjects with Metabolic Syndrome-A SYSDIET Sub-Study

SCOPE

To explore the effect of a healthy Nordic diet on the global transcriptome profile in peripheral blood mononuclear cells (PBMCs) of subjects with metabolic syndrome.

METHODS AND RESULTS

Subjects with metabolic syndrome undergo a 18/24 week randomized intervention study comparing an isocaloric healthy Nordic diet with an average habitual Nordic diet served as control (SYSDIET study). Altogether, 68 participants are included. PBMCs are obtained before and after intervention and total RNA is subjected to global transcriptome analysis. 1302 probe sets are differentially expressed between the diet groups (p-value < 0.05). Twenty-five of these are significantly regulated (FDR q-value < 0.25) and are mainly involved in mitochondrial function, cell growth, and cell adhesion. The list of 1302 regulated probe sets is subjected to functional analyses. Pathways and processes involved in the mitochondrial electron transport chain, immune response, and cell cycle are downregulated in the healthy Nordic diet group. In addition, gene transcripts with common motifs for 42 transcription factors, including NFR1, NFR2, and NF-κB, are downregulated in the healthy Nordic diet group.

CONCLUSION

These results suggest that benefits of a healthy diet may be mediated by improved mitochondrial function and reduced inflammation.

Interrelationship between the Levels of C9orf72 and Amyloid-β Protein Precursor and Amyloid-β in Human Cells and Brain Samples

A subset of C9orf72 repeat expansion-carrying frontotemporal dementia patients display an Alzheimer-like decrease in cerebrospinal fluid amyloid-β (Aβ) biomarker levels. We report that downregulation of C9orf72 in non-neuronal human cells overexpressing amyloid-β protein precursor (AβPP) resulted in increased levels of secreted AβPP fragments and Aβ, while levels of AβPP or its C-terminal fragments (CTFs) remained unchanged. In neuronal cells, AβPP and C83 CTF levels were decreased upon C9orf72 knockdown, but those of secreted AβPP fragments or Aβ remained unchanged. C9orf72 protein levels significantly increased in human brain with advancing neurofibrillary pathology and positively correlated with brain Aβ42 levels. Our data suggest that altered C9orf72 levels may lead to cell-type specific alterations in AβPP processing, but warrant further studies to clarify the underlying mechanisms.

Digitally supported program for type 2 diabetes risk identification and risk reduction in real-world setting: protocol for the StopDia model and randomized controlled trial

BACKGROUND

The StopDia study is based on the convincing scientific evidence that type 2 diabetes (T2D) and its comorbidities can be prevented by a healthy lifestyle. The need for additional research is based on the fact that the attempts to translate scientific evidence into actions in the real-world health care have not led to permanent and cost-effective models to prevent T2D. The specific aims of the StopDia study following the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework are to 1) improve the Reach of individuals at increased risk, 2) evaluate the Effectiveness and cost-effectiveness of the digital lifestyle intervention and the digital and face-to-face group lifestyle intervention in comparison to routine care in a randomized controlled trial (RCT), and 3) evaluate the Adoption and Implementation of the StopDia model by the participants and the health care organizations at society level. Finally, we will address the Maintenance of the lifestyle changes at participant level and that of the program at organisatory level after the RCT.

METHODS

The StopDia study is carried out in the primary health care system as part of the routine actions of three provinces in Finland, including Northern Savo, Southern Carelia, and Päijät-Häme. We estimate that one fifth of adults aged 18-70 years living in these areas are at increased risk of T2D. We recruit the participants using the StopDia Digital Screening Tool, including questions from the Finnish Diabetes Risk Score (FINDRISC). About 3000 individuals at increased risk of T2D (FINDRISC ≥12 or a history of gestational diabetes, impaired fasting glucose, or impaired glucose tolerance) participate in the one-year randomized controlled trial. We monitor lifestyle factors using the StopDia Digital Questionnaire and metabolism using laboratory tests performed as part of routine actions in the health care system.

DISCUSSION

Sustainable and scalable models are needed to reach and identify individuals at increased risk of T2D and to deliver personalized and effective lifestyle interventions. With the StopDia study we aim to answer these challenges in a scientific project that is fully digitally integrated into the routine health care.

TRIAL REGISTRATION

ClinicalTials.gov . Identifier: NCT03156478 . Date of registration 17.5.2017.

A multiomic approach to characterize the temporal sequence in Alzheimer's disease-related pathology

No single-omic approach completely elucidates the multitude of alterations taking place in Alzheimer's disease (AD). Here, we coupled transcriptomic and phosphoproteomic approaches to determine the temporal sequence of changes in mRNA, protein, and phosphopeptide expression levels from human temporal cortical samples, with varying degree of AD-related pathology. This approach highlighted fluctuation in synaptic and mitochondrial function as the earliest pathological events in brain samples with AD-related pathology. Subsequently, increased expression of inflammation and extracellular matrix-associated gene products was observed. Interaction network assembly for the associated gene products, emphasized the complex interplay between these processes and the role of addressing post-translational modifications in the identification of key regulators. Additionally, we evaluate the use of decision trees and random forests in identifying potential biomarkers differentiating individuals with different degree of AD-related pathology. This multiomic and temporal sequence-based approach provides a better understanding of the sequence of events leading to AD.

Kuopio birth cohort - design of a Finnish joint research effort for identification of environmental and lifestyle risk factors for the wellbeing of the mother and the newborn child

BACKGROUND

A Finnish joint research effort Kuopio Birth Cohort (KuBiCo) seeks to evaluate the effects of genetics, epigenetics and different risk factors (medication, nutrition, lifestyle factors and environmental aspects) during pregnancy on the somatic and psychological health status of the mother and the child.

METHODS

KuBiCo will ultimately include information on 10,000 mother-child pairs who have given their informed consent to participate in this cohort. Identification of foetal health risk factors that can potentially later manifest as disease requires a repository of relevant biological samples and a flexible open up-to-date data handling system to register, store and analyse biological, clinical and questionnaire-based data. KuBiCo includes coded questionnaire-based maternal background data gathered before, during and after the pregnancy and bio-banking of maternal and foetal samples that will be stored in deep freezers. Data from the questionnaires and biological samples will be collected into one electronic database. KuBiCo consists of several work packages which are complementary to each other: Maternal, foetal and placental metabolism and omics; Paediatrics; Mental wellbeing; Prenatal period and delivery; Analgesics and anaesthetics during peripartum period; Environmental effects; Nutrition; and Research ethics.

DISCUSSION

This report describes the set-up of the KuBiCo and descriptive analysis from 3532 parturients on response frequencies and feedback to KuBiCo questionnaires gathered from June 2012 to April 2016. Additionally, we describe basic demographic data of the participants (n = 1172). Based on the comparison of demographic data between official national statistics and our descriptive analysis, KuBiCo represents a cross-section of Finnish pregnant women.

Associations of Genetic Susceptibility to Alzheimer's Disease with Adiposity and Cardiometabolic Risk Factors among Children in a 2-Year Follow-up Study

We investigated the associations of genetic risk score (GRS) for Alzheimer's disease and apolipoprotein E (APOE) ɛ variant with cardiometabolic risk factors during 2-year follow-up in children and whether body fat percentage (BF%) modify these associations. A population-based sample of 469 children (246 boys, 223 girls) at baseline and 398 children (201 boys, 197 girls) at 2-year follow-up participated in the study. Genotyping was performed using the Illumina Custom Infinium CardioMetabo BeadChip and the Illumina Infinium HumanCoreExome BeadChip. The GRS was calculated using information on nine independent gene variants available in our genomic data. We assessed BF%, waist circumference, insulin, glucose, triglycerides, high-density lipoprotein (HDL) and low-density lipoprotein (LDL) cholesterol, and systolic and diastolic blood pressure. We computed a cardiometabolic risk score and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR). In boys, the GRS was not associated with cardiometabolic risk factors. In girls, GRS was directly associated with LDL cholesterol (β= 0.133, 95% CI = 0.002 to 0.262) at baseline and with a higher cardiometabolic risk score (β= 0.154, 95% CI = 0.015 to 0.294), glucose (β= 0.143, 95% CI = 0.003 to 0.284), and HOMA-IR (β= 0.141, 95% CI = 0.004 to 0.278) at 2-year follow-up. GRS was directly associated with a cardiometabolic risk score at baseline and 2-year follow-up among girls in the highest third of BF% at baseline, but not in other girls (p < 0.05 for interaction). Children with the APOEɛ3/3 genotype had higher LDL cholesterol at and 2-year follow-up than those with the APOEɛ2/3 genotype. In conclusion, GRS was associated with increased cardiometabolic risk in girls and especially those with higher BF%.

Alzheimer's Disease-Related Polymorphisms in Shunt-Responsive Idiopathic Normal Pressure Hydrocephalus

BACKGROUND

Idiopathic normal pressure hydrocephalus (iNPH) is a late onset, surgically treated progressive brain disease caused by impaired cerebrospinal fluid dynamics and subsequent ventriculomegaly. Comorbid Alzheimer's disease (AD) seems to be frequent in iNPH.

OBJECTIVE

We aim to evaluate the role of AD-related polymorphisms in iNPH.

METHODS

Overall 188 shunt-operated iNPH patients and 688 controls without diagnosed neurodegenerative disease were included into analysis. Twenty-three single-nucleotide polymorphisms (SNPs FRMD4A [rs7081208_A, rs2446581_A, rs17314229_T], CR1, BIN, CD2AP, CLU, MS4A6A, MS4A4E, PICALM, ABCA7, CD33, INPP5D, HLA_DRB5, EPHA1, PTK2B, CELF1, SORL1, FERMT2, SLC24A, DSG2, CASS4, and NME8) adjusted to APOE were analyzed between groups by using binary logistic regression analysis. Neuroradiological characteristics and AD-related changes in the right frontal cortical brain biopsies were available for further analysis.

RESULTS

Logistic regression analysis adjusted to age, gender, and other SNPs indicated allelic variation of NME8 between iNPH patients and non-demented controls (p = 0.014). The allelic variation of NME8 was not related to the neuropathological changes in the brain biopsies of iNPH patients. However, periventricular white matter changes (p = 0.017) were more frequent in the iNPH patients with the AA-genotype, an identified risk factor of AD.

CONCLUSIONS

Our findings increase the evidence that iNPH is characterized by genetic and pathophysiological mechanisms independent from AD. Considering that NME8 plays a role in the ciliary function and displays SNP-related diversity in white matter changes, the mechanisms of NME8 in iNPH and other neurodegenerative processes are worth further study.

Transcription factors Tp73, Cebpd, Pax6, and Spi1 rather than DNA methylation regulate chronic transcriptomics changes after experimental traumatic brain injury

Traumatic brain injury (TBI) induces a wide variety of cellular and molecular changes that can continue for days to weeks to months, leading to functional impairments. Currently, there are no pharmacotherapies in clinical use that favorably modify the post-TBI outcome, due in part to limited understanding of the mechanisms of TBI-induced pathologies. Our system biology analysis tested the hypothesis that chronic transcriptomics changes induced by TBI are controlled by altered DNA-methylation in gene promoter areas or by transcription factors. We performed genome-wide methyl binding domain (MBD)-sequencing (seq) and RNA-seq in perilesional, thalamic, and hippocampal tissue sampled at 3 months after TBI induced by lateral fluid percussion in adult male Sprague-Dawley rats. We investigated the regulated molecular networks and mechanisms underlying the chronic regulation, particularly DNA methylation and transcription factors. Finally, we identified compounds that modulate the transcriptomics changes and could be repurposed to improve recovery. Unexpectedly, DNA methylation was not a major regulator of chronic post-TBI transcriptomics changes. On the other hand, the transcription factors Cebpd, Pax6, Spi1, and Tp73 were upregulated at 3 months after TBI (False discovery rate < 0.05), which was validated using digital droplet polymerase chain reaction. Transcription regulatory network analysis revealed that these transcription factors regulate apoptosis, inflammation, and microglia, which are well-known contributors to secondary damage after TBI. Library of Integrated Network-based Cellular Signatures (LINCS) analysis identified 118 pharmacotherapies that regulate the expression of Cebpd, Pax6, Spi1, and Tp73. Of these, the antidepressant and/or antipsychotic compounds trimipramine, rolipramine, fluspirilene, and chlorpromazine, as well as the anti-cancer therapies pimasertib, tamoxifen, and vorinostat were strong regulators of the identified transcription factors, suggesting their potential to modulate the regulated transcriptomics networks to improve post-TBI recovery.

Fetal Microsatellite in the Heme Oxygenase 1 Promoter Is Associated With Severe and Early-Onset Preeclampsia

Preeclampsia is a vascular pregnancy disorder that often involves impaired placental development. HO-1 (heme oxygenase 1, encoded by HMOX1 ) is a stress response enzyme crucial for endothelial and placental function. Long version of the guanine–thymine (GT n ) microsatellite in the HMOX1 promoter decreases HO-1 expression, and the long maternal repeat is associated with late-onset preeclampsia. Our aim was to study whether the length of fetal repeat is associated with mother’s preeclampsia, whether the length of fetal and maternal repeats affect HO-1 levels in placenta and maternal serum, and whether HO-1 levels are altered in preeclampsia. We genotyped the repeat in the cord blood of 609 preeclamptic and 745 nonpreeclamptic neonates. HO-1 levels were measured in 36 placental samples, and in the first (222 cases/243 controls) and third (176 cases/53 controls) pregnancy trimester serum samples using enzyme-linked immunosorbent assay. The long fetal GT n repeat was associated with preeclampsia and its severe and early-onset subtypes. Interaction analysis suggested the maternal and fetal effects to be independent. Placental or serum HO-1 levels were not altered in preeclamptics, possibly reflecting heterogeneity of preeclampsia. Carriers of the long fetal and maternal repeats had lower placental and serum HO-1 levels, respectively, providing functional evidence for the association. We conclude that the long fetal GT n repeat may increase mother’s risk for especially severe and early-onset preeclampsia. The fetal and maternal risk alleles likely predispose to different disease subtypes.

A Genome-Wide Association Study of IVGTT-Based Measures of First-Phase Insulin Secretion Refines the Underlying Physiology of Type 2 Diabetes Variants

Understanding the physiological mechanisms by which common variants predispose to type 2 diabetes requires large studies with detailed measures of insulin secretion and sensitivity. Here we performed the largest genome-wide association study of first-phase insulin secretion, as measured by intravenous glucose tolerance tests, using up to 5,567 individuals without diabetes from 10 studies. We aimed to refine the mechanisms of 178 known associations between common variants and glycemic traits and identify new loci. Thirty type 2 diabetes or fasting glucose-raising alleles were associated with a measure of first-phase insulin secretion at P < 0.05 and provided new evidence, or the strongest evidence yet, that insulin secretion, intrinsic to the islet cells, is a key mechanism underlying the associations at the HNF1A, IGF2BP2, KCNQ1, HNF1B, VPS13C/C2CD4A, FAF1, PTPRD, AP3S2, KCNK16, MAEA, LPP, WFS1, and TMPRSS6 loci. The fasting glucose-raising allele near PDX1, a known key insulin transcription factor, was strongly associated with lower first-phase insulin secretion but has no evidence for an effect on type 2 diabetes risk. The diabetes risk allele at TCF7L2 was associated with a stronger effect on peak insulin response than on C-peptide-based insulin secretion rate, suggesting a possible additional role in hepatic insulin clearance or insulin processing. In summary, our study provides further insight into the mechanisms by which common genetic variation influences type 2 diabetes risk and glycemic traits.

Screening approach for identifying candidate drugs and drug-drug interactions related to hip fracture risk in persons with Alzheimer disease

PURPOSE

To assess whether a "drugome-wide" screen with case-crossover design is a feasible approach for identifying candidate drugs and drug-drug interactions.

METHODS

All community-dwelling residents of Finland who received a clinically verified Alzheimer disease diagnosis in 2005 to 2011 and experienced incident hip fracture (HF) afterwards (N = 4851). Three scenarios were used to test the sensitivity of this approach (1) hazard period 0 to 30 and control period 31 to 61 days before HF, (2) hazard period 0 to 30 and control period 336 to 366 days before HF, and (3) hazard period 0 to 14 and control period 16 to 30 days before HF.

RESULTS

Nine, 44, and 5 drugs were associated with increased HF risk and 8, 23, and 4 with decreased risk in scenarios 1, 2, and 3, respectively. Six drugs were identified with scenario 1 only and 54 and 1 with scenarios 2 and 3, respectively. Only six drugs (metoprolol, simvastatin, trimethoprim, codeine combinations, fentanyl, and paracetamol) were associated with HF in all scenarios, four with 1 and 2 (cefalexin, buprenorphine, olanzapine, and memantine), and one with 1 and 3 (enalapril) or 2 and 3 (ciprofloxacin). The direction of associations was the same in all/both scenarios. The interaction results were equally versatile, with hydroxocobalamin*oxazepam being the only interaction observed in all scenarios.

CONCLUSIONS

Case-crossover analysis is a potential approach for identifying candidate drugs and drug-drug interactions associated with adverse events as it implicitly controls for fixed confounders. The results are highly dependent on applied hazard and control periods, but the choice of periods can help in targeting the analyses to different phases of drug use.

Analysis of Post-Traumatic Brain Injury Gene Expression Signature Reveals Tubulins, Nfe2l2, Nfkb, Cd44, and S100a4 as Treatment Targets

We aimed to define the chronically altered gene expression signature of traumatic brain injury (TBI-sig) to discover novel treatments to reverse pathologic gene expression or reinforce the expression of recovery-related genes. Genome-wide RNA-sequencing was performed at 3 months post-TBI induced by lateral fluid-percussion injury in rats. We found 4964 regulated genes in the perilesional cortex and 1966 in the thalamus (FDR < 0.05). TBI-sig was used for a LINCS analysis which identified 11 compounds that showed a strong connectivity with the TBI-sig in neuronal cell lines. Of these, celecoxib and sirolimus were recently reported to have a disease-modifying effect in in vivo animal models of epilepsy. Other compounds revealed by the analysis were BRD-K91844626, BRD-A11009626, NO-ASA, BRD-K55260239, SDZ-NKT-343, STK-661558, BRD-K75971499, ionomycin, and desmethylclomipramine. Network analysis of overlapping genes revealed the effects on tubulins (Tubb2a, Tubb3, Tubb4b), Nfe2l2, S100a4, Cd44, and Nfkb2, all of which are linked to TBI-relevant outcomes, including epileptogenesis and tissue repair. Desmethylclomipramine modulated most of the gene targets considered favorable for TBI outcome. Our data demonstrate long-lasting transcriptomics changes after TBI. LINCS analysis predicted that these changes could be modulated by various compounds, some of which are already in clinical use but never tested in TBI.

The effects of a 2-year individualized and family-based lifestyle intervention on physical activity, sedentary behavior and diet in children

OBJECTIVE

To investigate the effects of a long-term, individualized and family-based lifestyle intervention on physical activity, sedentary behavior and diet quality in children.

METHODS

We carried out a 2-year intervention study in a population sample of 506 children aged 6-8years in Finland in 2007-2012. We allocated the participants at baseline in the intervention and control group. We assessed physical activity and sedentary behavior by questionnaires and diet by food records.

RESULTS

Total physical activity (+9min/d in intervention group vs. -5min/d in control group, p=0.001 for time*group interaction), unsupervised physical activity (+7min/d vs. -9min/d, p<0.001) and organized sports (+8min/d vs. +3min/d, p=0.001) increased in the intervention group but not in the control group. Using computer and playing video games increased less in the intervention group than in the control group (+9min/d vs. +19min/d, p=0.003). Consumption of vegetables (+12g/d vs. -12g/d, p=0.001), high-fat vegetable-oil based margarine (+10g/d vs. +3g/d, p<0.001) and low-fat milk (+69g/d vs. +11g/d, p=0.042) and intake of dietary fiber (+1.3g/d vs. +0.2g/d, p=0.023), vitamin C (+4.5mg/d vs. -7.2mg/d, p=0.042) and vitamin E (+1.4mg/d vs. +0.5mg/d, p=0.002) increased in the intervention group but not in the control group. Consumption of butter-based spreads increased in the control group but not in the intervention group (+2g/d vs. -1g/d, p=0.002).

CONCLUSIONS

Individualized and family-based lifestyle intervention increased physical activity, attenuated increase in sedentary behavior and enhanced diet quality in children.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT01803776.

Associations of TM6SF2 167K allele with liver enzymes and lipid profile in children: the PANIC Study

BACKGROUND

The 167K allele in the TM6SF2 gene has been suggested to protect against cardiovascular disease at the cost of developing nonalcoholic fatty liver disease in adults.

METHODS

We performed a cross-sectional study in a population sample of 462 Caucasian children aged 6-9 y, genotyped the polymorphism using HumanCoreExome BeadChip, and assessed several cardiometabolic risk factors.

RESULTS

The 51 (11%) carriers of the 167K allele had higher plasma alanine aminotransferase (ALT) (20.8 vs. 18.4 U/l, P = 0.011) but lower plasma triglycerides (0.54 vs. 0.61 mmol/l, P = 0.024), total cholesterol (4.08 vs. 4.30 mmol/l, P = 0.016), and low-density lipoprotein (LDL) cholesterol (2.22 vs. 2.38 mmol/l, P = 0.012) than the 411 noncarriers. In factor analysis, the first factor was heavily loaded by plasma ALT (factor loading 0.63), triglycerides (-0.82), LDL cholesterol (-0.71), and waist circumference (0.61) in the carriers but not in the noncarriers.

CONCLUSIONS

The carriers of the 167K allele have higher plasma ALT but lower plasma triglycerides and total and LDL cholesterol than the noncarriers already in childhood.

SEPT8 modulates β-amyloidogenic processing of APP by affecting the sorting and accumulation of BACE1

Dysfunction and loss of synapses are early pathogenic events in Alzheimer's disease. A central step in the generation of toxic amyloid-β (Aβ) peptides is the cleavage of amyloid precursor protein (APP) by β-site APP-cleaving enzyme (BACE1). Here, we have elucidated whether downregulation of septin (SEPT) protein family members, which are implicated in synaptic plasticity and vesicular trafficking, affects APP processing and Aβ generation. SEPT8 was found to reduce soluble APPβ and Aβ levels in neuronal cells through a post-translational mechanism leading to decreased levels of BACE1 protein. In the human temporal cortex, we identified alterations in the expression of specific SEPT8 transcript variants in a manner that correlated with Alzheimer's-disease-related neurofibrillary pathology. These changes were associated with altered β-secretase activity. We also discovered that the overexpression of a specific Alzheimer's-disease-associated SEPT8 transcript variant increased the levels of BACE1 and Aβ peptides in neuronal cells. These changes were related to an increased half-life of BACE1 and the localization of BACE1 in recycling endosomes. These data suggest that SEPT8 modulates β-amyloidogenic processing of APP through a mechanism affecting the intracellular sorting and accumulation of BACE1.

Effects of a healthy Nordic diet on gene expression changes in peripheral blood mononuclear cells in response to an oral glucose tolerance test in subjects with metabolic syndrome: a SYSDIET sub-study

Background

Diet has a great impact on the risk of developing features of metabolic syndrome (MetS), type 2 diabetes mellitus (T2DM), and cardiovascular diseases (CVD). We evaluated whether a long-term healthy Nordic diet (ND) can modify the expression of inflammation and lipid metabolism-related genes in peripheral blood mononuclear cells (PBMCs) during a 2-h oral glucose tolerance test (OGTT) in individuals with MetS.

Methods

A Nordic multicenter randomized dietary study included subjects (n = 213) with MetS, randomized to a ND group or a control diet (CD) group applying an isocaloric study protocol. In this sub-study, we included subjects (n = 89) from three Nordic centers: Kuopio (n = 26), Lund (n = 30), and Oulu (n = 33) with a maximum weight change of ±4 kg, high-sensitivity C-reactive protein concentration ≤10 mg L⁻¹, and baseline body mass index <39 kg m⁻². PBMCs were isolated, and the mRNA gene expression analysis was measured by quantitative real-time polymerase chain reaction (qPCR). We analyzed the mRNA expression changes of 44 genes before and after a 2hOGTT at the beginning and the end of the intervention.

Results

The healthy ND significantly down-regulated the expression of toll-like receptor 4 (TLR4), interleukin 18 (IL18), and thrombospondin receptor (CD36) mRNA transcripts and significantly up-regulated the expression of peroxisome proliferator-activated receptor delta (PPARD) mRNA transcript after the 2hOGTT compared to the CD.

Conclusions

A healthy ND is able to modify the gene expression in PBMCs after a 2hOGTT. However, more studies are needed to clarify the biological and clinical relevance of these findings.

Electronic supplementary material

The online version of this article (doi:10.1186/s12263-016-0521-4) contains supplementary material, which is available to authorized users.