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The mechanisms underlying the low efficiency of reprogramming somatic cells into induced pluripotent stem (iPS) cells are poorly understood. There is a clear need to study whether the reprogramming process itself compromises genomic integrity and, through this, the efficiency of iPS cell establishment. Using a high-resolution single nucleotide polymorphism array, we compared copy number variations (CNVs) of different passages of human iPS cells with their fibroblast cell origins and with human embryonic stem (ES) cells. Here we show that significantly more CNVs are present in early-passage human iPS cells than intermediate passage human iPS cells, fibroblasts or human ES cells. Most CNVs are formed de novo and generate genetic mosaicism in early-passage human iPS cells. Most of these novel CNVs rendered the affected cells at a selective disadvantage. Remarkably, expansion of human iPS cells in culture selects rapidly against mutated cells, driving the lines towards a genetic state resembling human ES cells. Genetic abnormalities in iPS cells Epigenomic reprogramming of somatic cells to produce iPS (induced pluripotent stem) cells has important therapeutic potential and is the basis of potentially important disease models. Recent reports that the reprogramming and in vitro culture of iPS cells can induce genetic and epigenetic abnormalities raise concerns over the implications of these abnormalities for clinical applications of iPS cells. Three papers in this issue present genomics studies of human iPS and embryonic stem (ES) cells, and taken together, the results confirm that chromosomal, subchromosomal and single-base level anomalies do accumulate in iPS cells. Hussein et al . compare copy number alterations of early and intermediate passage human iPS cells and report a higher level of copy number variations associated with reprogramming. During moderate length culture, however, iPS cells undergo a selection process leading to a decreased mutation load equivalent to that seen in ES cells. Gore et al . report protein-coding point mutations in 22 human iPS cell lines reprogrammed using five different methods; some mutations were pre-existing in the somatic cells, others were new mutations linked to reprogramming. Lister et al . used whole-genome DNA methylation profiling of human ES, iPS and somatic progenitor cell lines to reveal 'hotspots' in the genomes of iPS cells that are aberrantly reprogrammed. Reprogramming of somatic cells to induced pluripotent stem (iPS) cells that can be differentiated into many cell types has great potential for personalized therapy. By comparing copy number variations of early- and intermediate-passage human iPS cells to their respective parental fibroblast cells and human embryonic stem (ES) cells, this study finds that a high mutation rate is associated with the reprogramming process. However, during moderate length culture, human iPS cells undergo a selection process leading to decreased mutation load of cells equivalent to that observed in human ES cells.

A digital health check can be used to screen health behavior risks in the population, help health care professionals with standardized risk estimation for their patients, and motivate a patient to change unhealthy behaviors. Long-term unemployed individuals comprise a particular subgroup with an increased risk of lifestyle-related diseases. This study aims to investigate the clinical utility of a general digital health examination, the STAR Duodecim Health Check and Coaching Program (STAR), which was developed in Finland, in the targeted screening of long-term unemployed individuals. For this purpose, we compared health challenges identified by a digital health check with those identified by a nurse during a face-to-face health check for unemployed individuals. In this comparison study, 49 unemployed participants attending a health check were recruited from two Finnish primary health care centers. The participants used STAR and attended a nurse's health check. Data were collected by surveys with multiple-choice and open-ended questions from the participants, nurses, and a study assistant who observed the session. The nurses were asked to name the three most significant health challenges for each participant. These health challenges were categorized into health challenges corresponding to STAR and these were compared with each other. Percentages of agreement between STAR and nurses were calculated. Sensitivity and specificity, as well as Cohen κ with P values and CIs, were computed for agreement. STAR identified a total of 365 health challenges, an average of 7.4 (SD 2.5) health challenges per participant (n=49). The nurses named a total of 160 health challenges (n=47). In 53% (95% CI 38.1-67.9; n=25) of cases, STAR identified all categorized health challenges named by nurses. In 64% (95% CI 48.5-77.3; n=30) of cases, STAR identified at least 2/3 of the health challenges identified by nurses. Cohen κ was 0.877 (P<.001) for alcohol, indicating almost perfect agreement, and 0.440 (P<.001) for smoking and 0.457 (P=.001) for cholesterol, indicating moderate agreement. STAR left a total of 89 health challenges, an average of 1.8 (SD 1.1) per participant, uncategorized because STAR lacked an answer to the question or questions required for the classification of a certain health challenge. The participants did not always add information on their blood pressure (n=36, 74%), cholesterol (n=22, 45%), and waist circumference (n=15, 31%). In conclusion, STAR identified most of the health challenges identified by nurses but missed some essential ones. Participants did not have information on measurements, such as blood pressure and cholesterol values, which are pivotal to STAR in assessing cardiovascular risks. Using the tool for screening or as a part of a traditional health check with necessary measurements and dialog with health care professionals may improve the risk assessments and streamline the health checks of unemployed individuals. RR2-10.2196/27668.

Loyalty card data automatically collected by retailers provide an excellent source for evaluating health-related purchase behavior of customers. The data comprise information on every grocery purchase, including expenditures on product groups and the time of purchase for each customer. Such data where customers have an expenditure value for every product group for each time can be formulated as 3D tensorial data. This study aimed to use the modern tensorial principal component analysis (PCA) method to uncover the characteristics of health-related purchase patterns from loyalty card data. Another aim was to identify card holders with distinct purchase patterns. We also considered the interpretation, advantages, and challenges of tensorial PCA compared with standard PCA. Loyalty card program members from the largest retailer in Finland were invited to participate in this study. Our LoCard data consist of the purchases of 7251 card holders who consented to the use of their data from the year 2016. The purchases were reclassified into 55 product groups and aggregated across 52 weeks. The data were then analyzed using tensorial PCA, allowing us to effectively reduce the time and product group-wise dimensions simultaneously. The augmentation method was used for selecting the suitable number of principal components for the analysis. Using tensorial PCA, we were able to systematically search for typical food purchasing patterns across time and product groups as well as detect different purchasing behaviors across groups of card holders. For example, we identified customers who purchased large amounts of meat products and separated them further into groups based on time profiles, that is, customers whose purchases of meat remained stable, increased, or decreased throughout the year or varied between seasons of the year. Using tensorial PCA, we can effectively examine customers' purchasing behavior in more detail than with traditional methods because it can handle time and product group dimensions simultaneously. When interpreting the results, both time and product dimensions must be considered. In further analyses, these time and product groups can be directly associated with additional consumer characteristics such as socioeconomic and demographic predictors of dietary patterns. In addition, they can be linked to external factors that impact grocery purchases such as inflation and unexpected pandemics. This enables us to identify what types of people have specific purchasing patterns, which can help in the development of ways in which consumers can be steered toward making healthier food choices.

Fatty liver is a major cause of obesity-related morbidity and mortality. The aim of this study was to identify early metabolic alterations associated with liver fat accumulation in 50- to 55-year-old men (n = 49) and women (n = 52) with and without NAFLD. Hepatic fat content was measured using proton magnetic resonance spectroscopy (1H MRS). Serum samples were analyzed using a nuclear magnetic resonance (NMR) metabolomics platform. Global gene expression profiles of adipose tissues and skeletal muscle were analyzed using Affymetrix microarrays and quantitative PCR. Muscle protein expression was analyzed by Western blot. Increased branched-chain amino acid (BCAA), aromatic amino acid (AAA) and orosomucoid were associated with liver fat accumulation already in its early stage, independent of sex, obesity or insulin resistance (p<0.05 for all). Significant down-regulation of BCAA catabolism and fatty acid and energy metabolism was observed in the adipose tissue of the NAFLD group (p<0.001for all), whereas no aberrant gene expression in the skeletal muscle was found. Reduced BCAA catabolic activity was inversely associated with serum BCAA and liver fat content (p<0.05 for all). Liver fat accumulation, already in its early stage, is associated with increased serum branched-chain and aromatic amino acids. The observed associations of decreased BCAA catabolism activity, mitochondrial energy metabolism and serum BCAA concentration with liver fat content suggest that adipose tissue dysfunction may have a key role in the systemic nature of NAFLD pathogenesis.

Background Research in high-income countries has identified low socioeconomic status as a risk factor for disability pension (DP) due to common mental disorders (CMDs). Psychotherapy is an evidence-based treatment for the majority of CMDs along with medication and it is often targeted to prevent work disability. This study examines socioeconomic differences in the use of rehabilitative psychotherapy in Finland, where citizens have universal health coverage, but psychotherapy is partly dependent on personal finance. Methods The study subjects ( N =  22,501) were all the Finnish citizens granted a DP due to CMD between 2010 and 2015 and a comparison group ( N =  57,732) matched based on age, gender, and hospital district. Socioeconomic differences in psychotherapy use were studied using logistic regression models. Socioeconomic status was defined by education, income, and occupation. Age, gender, and family status were also examined. Results A lower level of education, lower occupational status (blue-collar worker), male gender, and older age, were associated with less frequent psychotherapy use, in both groups. Education was the strongest component of socioeconomic status associated with psychotherapy use, but the role of income was not straightforward. Unemployment when approaching DP, but not otherwise, was a risk factor for not receiving rehabilitative psychotherapy. Socioeconomic disparities were not any smaller among CMD patients approaching DP than in the comparison group. Conclusion This study demonstrates the disparity in the provision of psychotherapy for CMD patients, even on the verge of DP with an acute need for services. This disparity is partly related to a complex interplay of socioeconomic factors and the service system characteristics. Factors predisposing to unequal access to mental health services are presumably diverse and should be studied further.

The effects of bone morphogenetic protein‐2 (BMP‐2) on SMAD1/5 signaling, proliferation, and differentiation in human adipose stem cells (hASCs) were analyzed. BMP‐2 induced dose‐dependent activation of SMAD signaling and decreased proliferation in all the cell lines studied. Furthermore, depending on the hASC donor line, BMP‐2 also induced osteogenic and adipogenic differentiation in hASCs. Bone morphogenetic protein‐2 (BMP‐2) is a growth factor used to stimulate bone regeneration in clinical applications. However, there are contradicting reports on the functionality of BMP‐2 in human adipose stem cells (hASCs), which are frequently used in tissue engineering. In this study, we analyzed the effects of BMP‐2 on SMAD1/5 signaling, proliferation, and differentiation in hASCs. Our results indicated that BMP‐2 induced dose‐dependent (25–100 ng/ml) activation of SMAD signaling. Furthermore, the cell proliferation analysis revealed that BMP‐2 (100 ng/ml) consistently decreased the proliferation in all the cell lines studied. However, the analysis of the differentiation potential revealed that BMP‐2 (100 ng/ml) exhibited a donor‐dependent dual role, inducing both osteogenic and adipogenic differentiation in hASCs. The quantitative alkaline phosphatase (qALP) activity and mineralization levels were clearly enhanced in particular donor cell lines by BMP‐2 stimulus. On the contrary, in other cell lines, qALP and mineralization levels were diminished and the lipid formation was enhanced. The current study also suggests that hASCs have accelerated biochemical responsiveness to BMP‐2 stimulus in human serum‐supplemented culture medium compared with fetal bovine serum. The production origin of the BMP‐2 growth factor is also important for its response: BMP‐2 produced in mammalian cells enhanced signaling and differentiation responses compared with BMP‐2 produced in Escherichia coli. These results explain the existing contradiction in the reported BMP‐2 studies and indicate the variability in the functional end mechanism of BMP‐2‐stimulated hASCs. Significance This study examined how bone morphogenetic protein‐2 (BMP‐2) modulates the SMAD signaling mechanism and the proliferation and differentiation outcome of human adipose stem cells (hASCs) derived from several donors. The results indicate that BMP‐2 triggers molecular SMAD signaling mechanisms in hASCs and regulates differentiation processes in human serum‐culture conditions. Importantly, BMP‐2 has dual activity, inducing osteogenic and adipogenic differentiation, subject to hASC donor line studied. These findings explain contradictory previous results and highlight the importance of further studies to understand how signaling pathways guide mesenchymal stem cell functions at the molecular level.

Carbon-based nanomaterials including carbon nanotubes (CNTs) have been shown to trigger inflammation. However, how these materials are ‘sensed’ by immune cells is not known. Here we compared the effects of two carbon-based nanomaterials, single-walled CNTs (SWCNTs) and graphene oxide (GO), on primary human monocyte-derived macrophages. Genome-wide transcriptomics assessment was performed at sub-cytotoxic doses. Pathway analysis of the microarray data revealed pronounced effects on chemokine-encoding genes in macrophages exposed to SWCNTs, but not in response to GO, and these results were validated by multiplex array-based cytokine and chemokine profiling. Conditioned medium from SWCNT-exposed cells acted as a chemoattractant for dendritic cells. Chemokine secretion was reduced upon inhibition of NF-κB, as predicted by upstream regulator analysis of the transcriptomics data, and Toll-like receptors (TLRs) and their adaptor molecule, MyD88 were shown to be important for CCL5 secretion. Moreover, a specific role for TLR2/4 was confirmed by using reporter cell lines. Computational studies to elucidate how SWCNTs may interact with TLR4 in the absence of a protein corona suggested that binding is guided mainly by hydrophobic interactions. Taken together, these results imply that CNTs may be ‘sensed’ as pathogens by immune cells.

Background Autism spectrum disorder (ASD) is a partially heritable neurodevelopmental trait, and people with ASD may also have other co-occurring trait such as ADHD, anxiety disorders, depression, mental health issues, learning difficulty, physical health traits and communication challenges. The concomitant development of ASD and other neurological traits is assumed to result from a complex interplay between genetics and the environment. However, only a limited number of studies have performed multivariate genome-wide association studies (GWAS) for ASD. Methods We conducted to-date the largest multivariate GWAS on ASD and 8 ASD co-occurring traits (ADHD, ADHD childhood, anxiety stress (ASDR), bipolar (BIP), disruptive behaviour (DBD), educational attainment (EA), major depression, and schizophrenia (SCZ)) using summary statistics from leading studies. Multivariate associations and central traits were further identified. Subsequently, colocalization and Mendelian randomization (MR) analysis were performed on the associations identified with the central traits containing ASD. To further validate our findings, pathway and quantified trait loci (QTL) resources as well as independent datasets consisting of 112 (45 probands) whole genome sequence data from the GEMMA project were utilized. Results Multivariate GWAS resulted in 637 significant associations ( p  < 5e-8), among which 322 are reported for the first time for any trait. 37 SNPs were identified to contain ASD and one or more traits in their central trait set, including variants mapped to known SFARI ASD genes MAPT , CADPS and NEGR1 as well as novel ASD genes KANSL1 , NSF and NTM , associated with immune response, synaptic transmission, and neurite growth respectively. Mendelian randomization analyses found that genetic liability for ADHD childhood, ASRD and DBT has causal effects on the risk of ASD while genetic liability for ASD has causal effects on the risk of ADHD, ADHD childhood, BIP, WA, MDD and SCZ. Frequency differences of SNPs found in NTM and CADPS genes, respectively associated with neurite growth and neural/endocrine calcium regulation, were found between GEMMA ASD probands and controls. Pathway, QTL and cell type enrichment implicated microbiome, enteric inflammation, and central nervous system enrichments. Conclusions Our study, combining multivariate GWAS with systematic decomposition, identified novel genetic associations related to ASD and ASD co-occurring driver traits. Statistical tests were applied to discern evidence for shared and interpretable liability between ASD and co-occurring traits. These findings expand upon the current understanding of the complex genetics regulating ASD and reveal insights of neuronal brain disruptions potentially driving development and manifestation. Highlights Multivariate GWAS resulted in 637 significant ASD associations ( p  < 5e-8), among which 322 are reported for the first time. The novel associations mapped to known SFARI ASD genes CADPS , MAPT and NEGR1 and novel ASD genes KANSL1 , NSF and NTM , associated with immune response, synaptic transmission, and neurite growth, potentially driving the gut brain-barrier hypothesis underpinning ASD development. CuONPs induce co-occurrence of autophagy activation and autophagic flux blockade. Mendelian randomization analyses found that genetic liability for ASRD and DBT have causal effects on the risk of ASD while genetic liability for ASD have causal effects on the risk of ADHD, BIP, WA, MDD and SCZ. Bidirectional genetic liability causal effects were confirmed between ASD and ADHD childhood.

Background Next generation sequencing (NGS) technology allows laboratories to investigate virome composition in clinical and environmental samples in a culture-independent way. There is a need for bioinformatic tools capable of parallel processing of virome sequencing data by exactly identical methods: this is especially important in studies of multifactorial diseases, or in parallel comparison of laboratory protocols. Results We have developed a web-based application allowing direct upload of sequences from multiple virome samples using custom parameters. The samples are then processed in parallel using an identical protocol, and can be easily reanalyzed. The pipeline performs de-novo assembly, taxonomic classification of viruses as well as sample analyses based on user-defined grouping categories. Tables of virus abundance are produced from cross-validation by remapping the sequencing reads to a union of all observed reference viruses. In addition, read sets and reports are created after processing unmapped reads against known human and bacterial ribosome references. Secured interactive results are dynamically plotted with population and diversity charts, clustered heatmaps and a sortable and searchable abundance table. Conclusions The Vipie web application is a unique tool for multi-sample metagenomic analysis of viral data, producing searchable hits tables, interactive population maps, alpha diversity measures and clustered heatmaps that are grouped in applicable custom sample categories. Known references such as human genome and bacterial ribosomal genes are optionally removed from unmapped (‘dark matter’) reads. Secured results are accessible and shareable on modern browsers. Vipie is a freely available web-based tool whose code is open source.

A comprehensive in vitro assessment of two commercial metal oxide nanoparticles, TiO2 and ZnO, was performed using human monocyte-derived macrophages (HMDM), monocyte-derived dendritic cells (MDDC), and Jurkat T cell leukemia-derived cell line. TiO2 nanoparticles were found to be non-toxic whereas ZnO nanoparticles caused dose-dependent cell death. Subsequently, global gene expression profiling was performed to identify transcriptional response underlying the cytotoxicity caused by ZnO nanoparticles. Analysis was done with doses 1 µg/ml and 10 µg/ml after 6 and 24 h of exposure. Interestingly, 2703 genes were significantly differentially expressed in HMDM upon exposure to 10 µg/ml ZnO nanoparticles, while in MDDCs only 12 genes were affected. In Jurkat cells, 980 genes were differentially expressed. It is noteworthy that only the gene expression of metallothioneins was upregulated in all the three cell types and a notable proportion of the genes were regulated in a cell type-specific manner. Gene ontology analysis revealed that the top biological processes disturbed in HMDM and Jurkat cells were regulating cell death and growth. In addition, genes controlling immune system development were affected. Using a panel of modified ZnO nanoparticles, we obtained an additional support that the cellular response to ZnO nanoparticles is largely dependent on particle dissolution and show that the ligand used to modify ZnO nanoparticles modulates Zn(2+) leaching. Overall, the study provides an extensive resource of transcriptional markers for mediating ZnO nanoparticle-induced toxicity for further mechanistic studies, and demonstrates the value of assessing nanoparticle responses through a combined transcriptomics and bioinformatics approach.