39 research outputs found

    Clinical-Pharmacogenetic Predictive Models for Time to Occurrence of Levodopa Related Motor Complications in Parkinson’s Disease

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    The response to dopaminergic treatment in Parkinson’s disease depends on many clinical and genetic factors. The very common motor fluctuations (MF) and dyskinesia affect approximately half of patients after 5 years of treatment with levodopa. We did an evaluation of a combined effect of 16 clinical parameters and 34 single nucleotide polymorphisms to build clinical and clinical-pharmacogenetic models for prediction of time to occurrence of motor complications and to compare their predictive abilities. In total, 220 Parkinson’s disease patients were included in the analysis. Their demographic, clinical, and genotype data were obtained. The combined effect of clinical and genetic factors was assessed using The Least Absolute Shrinkage and Selection Operator penalized regression in the Cox proportional hazards model. Clinical and clinical-pharmacogenetic models were constructed. The predictive capacity of the models was evaluated with the cross-validated area under time-dependent receiver operating characteristic curve. Clinical-pharmacogenetic model included age at diagnosis (HR = 0.99), time from diagnosis to initiation of levodopa treatment (HR = 1.24), COMT rs165815 (HR = 0.90), DRD3 rs6280 (HR = 1.03), and BIRC5 rs9904341 (HR = 0.95) as predictive factors for time to occurrence of MF. Furthermore, clinical-pharmacogenetic model for prediction of time to occurrence of dyskinesia included female sex (HR = 1.07), age at diagnosis (HR = 0.97), tremor-predominant Parkinson’s disease (HR = 0.88), beta-blockers (HR = 0.95), alcohol consumption (HR = 0.99), time from diagnosis to initiation of levodopa treatment (HR = 1.15), CAT rs1001179 (HR = 1.27), SOD2 rs4880 (HR = 0.95), NOS1 rs2293054 (HR = 0.99), COMT rs165815 (HR = 0.92), and SLC22A1 rs628031 (HR = 0.80). Areas under the curves for clinical and clinical-pharmacogenetic models for MF after 5 years of levodopa treatment were 0.68 and 0.70, respectively. Areas under the curves for clinical and clinical-pharmacogenetic models for dyskinesia after 5 years of levodopa treatment were 0.71 and 0.68, respectively. These results show that clinical-pharmacogenetic models do not have better ability to predict time to occurrence of motor complications in comparison to the clinical ones despite the significance of several polymorphisms. Models could be improved by a larger sample size and by additional polymorphisms, epigenetic predictors or serum biomarkers

    Different approaches in microRNA analysis

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    MicroRNA might serve as a predictive biomarker for treatment response in stem cell treatment in knee osteoarthritis. Different sample types are going to be collected to enlighten the true biological role. MicroRNA analysis necessitates diverse approaches based on the sample type. In this study, we examined microRNA profiles in plasma samples, synovial fluid, and adipose-derived fat tissue. We conducted a comparative analysis of different microRNA analysis methods to assess the data. The first approach involved a series of steps, including adapter trimming, quality filtering, size filtering, and mapping of all reads to the human reference genome (GRCh38.p12). Subsequently, genome-mapped reads were aligned to known miRNA sequences from miRBase. Reads that did not match miRNAs were subjected to further classification using additional databases, such as RNAcentral. The second pipeline also encompassed adapter trimming, quality filtering, and size filtering. Additionally, it involved collapsing individual reads into repeat sequences, followed by alignment to the mature index of miRBase. Unaligned reads were classified as isomiRs based on their alignment to the hairpin index of miRBase. We processed sequences from three plasma samples, three adipose fat tissue samples, and three synovial fluid samples. Although there were slight variations in microRNA read counts, the average ratio between counts was 0.92 (SD=0.29). Notably, the second pipeline yielded higher read counts compared to the first pipeline. The results obtained from both microRNA bioinformatic pipelines demonstrated similar outcomes, suggesting that the choice of pipeline is unlikely to have a significant impact on the derived biological insights.Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 202

    Developing bioinformatics pipeline for processing environmental DNA metabarcoding sequencing data

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    Environmental DNA (eDNA) is DNA present in an environmental sample, originating from any biological material released from organisms living in that environment. This DNA can be isolated, amplified, sequenced, and analyzed in order to examine the taxonomic richness and abundance of different organism groups in the targeted environment. Methods of eDNA metabarcoding thus offer a unique opportunity to systematically streamline and scale-up regular biological assessments across many different environments of interest. Recently, as a part of the project funded by European structural and investment funds, Labena d.o.o. company established a modern laboratory in Zagreb focused on the research and provision of services in the field of eDNA. In collaboration with the Institute Ruđer Bošković we have been working on developing tests for analysis of water quality based on the eDNA and, as part of the standardization and optimization of sample-to-results eDNA analysis process, we developed a custom bioinformatics pipeline to facilitate efficient and effective eDNA sequencing data analysis. The pipeline was was written in Bash and utilizes several different algorithms to filter, trim, merge, denoise and classify targeted eDNA sequences. Python-based scripts which allow automatically download, filter, and format the data available on various online platforms were included in the pipeline to facilitate the curation of custom reference databases needed for taxonomic classification of targeted organism groups. User-friendly and interactive pipeline report generation, comprised of both wet- and dry-lab step-bystep sample statistics and graphical representations or the main results, is supported using Rmarkdown and Plotly and DataTables libraries. The pipeline is containerized in Docker, allowing for easier environment building and pipeline deployment.Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 202

    A multinational prospective observational real-world cohort study

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    Funding Information: The authors thank the ISPAD executive committee and ISPAD JENIOUS members for their support. An abstract with partial study data was presented in June 2021 at the Virtual Advanced Technologies and Treatment for Diabetes (ATTD) conference. There was no commercial sponsor for this study. This study was partially funded by the ISPAD JDRF Fellowship Grant. KD was supported by the Slovenian National Research Agency (grant nos. J3–6798, V3–1505, and P3–0343). Funding Information: ISPAD, Grant/Award Number: ISPAD JDRF Fellowship Grant; Slovenian National Research Agency, Grant/Award Numbers: J36798, V31505, P30343 Funding information Funding Information: KD received honoraria for participation on the speakerʼs bureau of Pfizer, Novo Nordisk, and Eli Lilly. JG received speakerʼs honoraria from Eli Lilly and Sanofi, and clinical trials investigatorʼs payment from Novo Nordisk. RM received advisory board honoraria from Abbott and Novo Nordisk. JP received speakerʼs honoraria from Medtronic. JS serves as a consultant to Cecelia Health, Lexicon, Lilly, Insulet, Medtronic, and Sanofi, is a member of the advisory board for Bigfoot Biomedical, Cecelia Health, Insulet, Medtronic, and the T1D Fund and Vertex, and has had research support from the NIH, JDRF, and the Helmsley Charitable Trust. Her institution has had research support from Medtronic and Insulet. AC received speakerʼs honoraria from Medtronic, Eli Lilly, and Novo Nordisk. TB received speakerʼs honoraria from DexCom, Medtronic, Novo Nordisk, Roche, Sanofi, and Ypsomed, and advisory board honoraria from Ascensia, AstraZeneca, DexCom, Medtronic, and Sanofi.publishersversionpublishe

    Cabbage and fermented vegetables : From death rate heterogeneity in countries to candidates for mitigation strategies of severe COVID-19

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    Large differences in COVID-19 death rates exist between countries and between regions of the same country. Some very low death rate countries such as Eastern Asia, Central Europe, or the Balkans have a common feature of eating large quantities of fermented foods. Although biases exist when examining ecological studies, fermented vegetables or cabbage have been associated with low death rates in European countries. SARS-CoV-2 binds to its receptor, the angiotensin-converting enzyme 2 (ACE2). As a result of SARS-CoV-2 binding, ACE2 downregulation enhances the angiotensin II receptor type 1 (AT(1)R) axis associated with oxidative stress. This leads to insulin resistance as well as lung and endothelial damage, two severe outcomes of COVID-19. The nuclear factor (erythroid-derived 2)-like 2 (Nrf2) is the most potent antioxidant in humans and can block in particular the AT(1)R axis. Cabbage contains precursors of sulforaphane, the most active natural activator of Nrf2. Fermented vegetables contain many lactobacilli, which are also potent Nrf2 activators. Three examples are: kimchi in Korea, westernized foods, and the slum paradox. It is proposed that fermented cabbage is a proof-of-concept of dietary manipulations that may enhance Nrf2-associated antioxidant effects, helpful in mitigating COVID-19 severity.Peer reviewe

    Familial hypercholesterolaemia in children and adolescents from 48 countries: a cross-sectional study

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    Background: Approximately 450 000 children are born with familial hypercholesterolaemia worldwide every year, yet only 2·1% of adults with familial hypercholesterolaemia were diagnosed before age 18 years via current diagnostic approaches, which are derived from observations in adults. We aimed to characterise children and adolescents with heterozygous familial hypercholesterolaemia (HeFH) and understand current approaches to the identification and management of familial hypercholesterolaemia to inform future public health strategies. Methods: For this cross-sectional study, we assessed children and adolescents younger than 18 years with a clinical or genetic diagnosis of HeFH at the time of entry into the Familial Hypercholesterolaemia Studies Collaboration (FHSC) registry between Oct 1, 2015, and Jan 31, 2021. Data in the registry were collected from 55 regional or national registries in 48 countries. Diagnoses relying on self-reported history of familial hypercholesterolaemia and suspected secondary hypercholesterolaemia were excluded from the registry; people with untreated LDL cholesterol (LDL-C) of at least 13·0 mmol/L were excluded from this study. Data were assessed overall and by WHO region, World Bank country income status, age, diagnostic criteria, and index-case status. The main outcome of this study was to assess current identification and management of children and adolescents with familial hypercholesterolaemia. Findings: Of 63 093 individuals in the FHSC registry, 11 848 (18·8%) were children or adolescents younger than 18 years with HeFH and were included in this study; 5756 (50·2%) of 11 476 included individuals were female and 5720 (49·8%) were male. Sex data were missing for 372 (3·1%) of 11 848 individuals. Median age at registry entry was 9·6 years (IQR 5·8-13·2). 10 099 (89·9%) of 11 235 included individuals had a final genetically confirmed diagnosis of familial hypercholesterolaemia and 1136 (10·1%) had a clinical diagnosis. Genetically confirmed diagnosis data or clinical diagnosis data were missing for 613 (5·2%) of 11 848 individuals. Genetic diagnosis was more common in children and adolescents from high-income countries (9427 [92·4%] of 10 202) than in children and adolescents from non-high-income countries (199 [48·0%] of 415). 3414 (31·6%) of 10 804 children or adolescents were index cases. Familial-hypercholesterolaemia-related physical signs, cardiovascular risk factors, and cardiovascular disease were uncommon, but were more common in non-high-income countries. 7557 (72·4%) of 10 428 included children or adolescents were not taking lipid-lowering medication (LLM) and had a median LDL-C of 5·00 mmol/L (IQR 4·05-6·08). Compared with genetic diagnosis, the use of unadapted clinical criteria intended for use in adults and reliant on more extreme phenotypes could result in 50-75% of children and adolescents with familial hypercholesterolaemia not being identified. Interpretation: Clinical characteristics observed in adults with familial hypercholesterolaemia are uncommon in children and adolescents with familial hypercholesterolaemia, hence detection in this age group relies on measurement of LDL-C and genetic confirmation. Where genetic testing is unavailable, increased availability and use of LDL-C measurements in the first few years of life could help reduce the current gap between prevalence and detection, enabling increased use of combination LLM to reach recommended LDL-C targets early in life

    Nrf2-interacting nutrients and COVID-19 : time for research to develop adaptation strategies

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    There are large between- and within-country variations in COVID-19 death rates. Some very low death rate settings such as Eastern Asia, Central Europe, the Balkans and Africa have a common feature of eating large quantities of fermented foods whose intake is associated with the activation of the Nrf2 (Nuclear factor (erythroid-derived 2)-like 2) anti-oxidant transcription factor. There are many Nrf2-interacting nutrients (berberine, curcumin, epigallocatechin gallate, genistein, quercetin, resveratrol, sulforaphane) that all act similarly to reduce insulin resistance, endothelial damage, lung injury and cytokine storm. They also act on the same mechanisms (mTOR: Mammalian target of rapamycin, PPAR gamma:Peroxisome proliferator-activated receptor, NF kappa B: Nuclear factor kappa B, ERK: Extracellular signal-regulated kinases and eIF2 alpha:Elongation initiation factor 2 alpha). They may as a result be important in mitigating the severity of COVID-19, acting through the endoplasmic reticulum stress or ACE-Angiotensin-II-AT(1)R axis (AT(1)R) pathway. Many Nrf2-interacting nutrients are also interacting with TRPA1 and/or TRPV1. Interestingly, geographical areas with very low COVID-19 mortality are those with the lowest prevalence of obesity (Sub-Saharan Africa and Asia). It is tempting to propose that Nrf2-interacting foods and nutrients can re-balance insulin resistance and have a significant effect on COVID-19 severity. It is therefore possible that the intake of these foods may restore an optimal natural balance for the Nrf2 pathway and may be of interest in the mitigation of COVID-19 severity

    Is diet partly responsible for differences in COVID-19 death rates between and within countries?

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    Correction: Volume: 10 Issue: 1 Article Number: 44 DOI: 10.1186/s13601-020-00351-w Published: OCT 26 2020Reported COVID-19 deaths in Germany are relatively low as compared to many European countries. Among the several explanations proposed, an early and large testing of the population was put forward. Most current debates on COVID-19 focus on the differences among countries, but little attention has been given to regional differences and diet. The low-death rate European countries (e.g. Austria, Baltic States, Czech Republic, Finland, Norway, Poland, Slovakia) have used different quarantine and/or confinement times and methods and none have performed as many early tests as Germany. Among other factors that may be significant are the dietary habits. It seems that some foods largely used in these countries may reduce angiotensin-converting enzyme activity or are anti-oxidants. Among the many possible areas of research, it might be important to understand diet and angiotensin-converting enzyme-2 (ACE2) levels in populations with different COVID-19 death rates since dietary interventions may be of great benefit.Peer reviewe
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