Cíle: Poslední významné pokroky v lidské genomice a postgenomických „omics“ nyní přinášejí nové možnosti zdravotní péče, kterou nazýváme „medicína založená na omics vědách“. V tomto článku jsme zkoumali vývoj a budoucí možnosti medicíny založené na omics vědách. Metody: Rozdělili jsme vývoj medicíny založené na omics vědách do tří generací za účelem ujasnění hlavních klinických cílů a charakterizace informačních metod každé generace spolu s jejich budoucími možnostmi. Výsledky: První generace medicíny založené na omics vědách, začala s „genomickou medicínou“, založenou na vrozených individuálních rozdílech v genomu. Toto otevřelo studování genetických polymorfismů nemocí a napomohlo vývoji personalizovaných léků založených na farmakogenetických/ farmakogenomických rozdílech v reakci na lék. Ve druhé generaci omicsové medicíny, díky pokroku v technologii vysokorychlostního sekvencování, byl otevřen přístup k obrovskému množství různých omicsových dat postgenomických nemocí, obsahujících vyčerpávající molekulární informace o nemocech somatických buněk. Zobrazení průběžného stavu nemoci je tak mnohem věrnější a umožňuje tak prediktivní medicíně předpovězení prognózy nemoci uplatněním datové analýzy. A také, díky rychle se rozvíjejícím znalostem o buňkové molekulární síti, je nyní umožněno porozumět nemoci na systémové úrovni pomocí nového oboru, zvaného systémová patologie. Může plně využít významné znalosti omicsu nemoci a povede ke komplexnímu porozumění postupu nemoci použitím datové analýzy.

Objectives: Recent important advances in the human genomics and post-genomic “omics” are now bringing about a new medical care which we call “omics-based medicine”. In this article, we investigated the development and future possibilities of omics-based medicine. Methods: We divided the development of omics-based medicine into three generations in order to clarify the main clinical goals and characteristics of informatics method of each generation, together with its future possibilities. Results: The first generation of omics-based medicine started with “genomic medicine” based on the inborn individual differences of genome. It has opened the study of genetic polymorphism of the diseases and promoted the personalized medication based on the pharmacogenetic/pharmacogenomic difference of the drug response. In the second generation of omics-based medicine, owing to the advances in the high-throughput technology, vast amount of the various post-genomic disease omics data containing comprehensive molecular information of diseased somatic cells has become available. It reflects the ongoing state of diseases more closely and enables the predictive medicine such as prognosis prediction of disease by applying the data-driven analysis. Finally, due to the rapidly growing knowledge about the cellular molecular network, system-level understanding of the disease, called systems pathology, becomes possible. It can fully exploit the substantial contents of disease omics and will lead to a comprehensive understanding of disease process by using model-driven analysis. Conclusion: Omics-based medicine and systems pathology will realize a new personalized and predictive medicine.

• Klíčová slova
• omics vědy, farmakogenomika,
• MeSH
• farmakogenetika trendy   MeSH
• financování organizované MeSH
• genomika trendy   MeSH
• lidé MeSH
• nemoc genetika   MeSH
• terapie metody   trendy   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• práce podpořená grantem MeSH

Biological mechanisms related to cancer development can leave distinct molecular fingerprints in tumours. By leveraging multi-omics and epidemiological information, we can unveil relationships between carcinogenesis processes that would otherwise remain hidden. Our integrative analysis of DNA methylome, transcriptome, and somatic mutation profiles of kidney tumours linked ageing, epithelial-mesenchymal transition (EMT), and xenobiotic metabolism to kidney carcinogenesis. Ageing process was represented by associations with cellular mitotic clocks such as epiTOC2, SBS1, telomere length, and PBRM1 and SETD2 mutations, which ticked faster as tumours progressed. We identified a relationship between BAP1 driver mutations and the epigenetic upregulation of EMT genes (IL20RB and WT1), correlating with increased tumour immune infiltration, advanced stage, and poorer patient survival. We also observed an interaction between epigenetic silencing of the xenobiotic metabolism gene GSTP1 and tobacco use, suggesting a link to genotoxic effects and impaired xenobiotic metabolism. Our pan-cancer analysis showed these relationships in other tumour types. Our study enhances the understanding of kidney carcinogenesis and its relation to risk factors and progression, with implications for other tumour types.

• MeSH
• DNA vazebné proteiny genetika   metabolismus   MeSH
• epigeneze genetická MeSH
• epitelo-mezenchymální tranzice * genetika   MeSH
• glutathion-S-transferasa fí genetika   metabolismus   MeSH
• histonlysin-N-methyltransferasa genetika   metabolismus   MeSH
• karcinogeneze * genetika   MeSH
• lidé MeSH
• metylace DNA * MeSH
• multiomika MeSH
• mutace * MeSH
• nádorové supresorové proteiny genetika   metabolismus   MeSH
• nádory ledvin * genetika   patologie   MeSH
• regulace genové exprese u nádorů MeSH
• stárnutí genetika   MeSH
• thiolesterasa ubikvitinu MeSH
• transkripční faktory genetika   metabolismus   MeSH
• transkriptom MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

• MeSH
• biologie * MeSH
• biotechnologie MeSH
• genomika MeSH
• molekulární biologie MeSH
• Publikační typ
• periodika MeSH

• Konspekt
• Biologické vědy
• NLK Obory
• biologie
• biomedicínské inženýrství
• biologie

Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.

• MeSH
• bipolární porucha * farmakoterapie   genetika   MeSH
• celogenomová asociační studie MeSH
• fokální adheze MeSH
• fosfatidylinositol-3-kinasy genetika   MeSH
• lidé MeSH
• lithium * farmakologie   terapeutické užití   MeSH
• multiomika MeSH
• protoonkogenní proteiny c-akt genetika   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

Lithium (Li) is one of the most effective drugs for treating bipolar disorder (BD), however, there is presently no way to predict response to guide treatment. The aim of this study is to identify functional genes and pathways that distinguish BD Li responders (LR) from BD Li non-responders (NR). An initial Pharmacogenomics of Bipolar Disorder study (PGBD) GWAS of lithium response did not provide any significant results. As a result, we then employed network-based integrative analysis of transcriptomic and genomic data. In transcriptomic study of iPSC-derived neurons, 41 significantly differentially expressed (DE) genes were identified in LR vs NR regardless of lithium exposure. In the PGBD, post-GWAS gene prioritization using the GWA-boosting (GWAB) approach identified 1119 candidate genes. Following DE-derived network propagation, there was a highly significant overlap of genes between the top 500- and top 2000-proximal gene networks and the GWAB gene list (Phypergeometric = 1.28E-09 and 4.10E-18, respectively). Functional enrichment analyses of the top 500 proximal network genes identified focal adhesion and the extracellular matrix (ECM) as the most significant functions. Our findings suggest that the difference between LR and NR was a much greater effect than that of lithium. The direct impact of dysregulation of focal adhesion on axon guidance and neuronal circuits could underpin mechanisms of response to lithium, as well as underlying BD. It also highlights the power of integrative multi-omics analysis of transcriptomic and genomic profiling to gain molecular insights into lithium response in BD.

• MeSH
• antimanika farmakologie   terapeutické užití   MeSH
• bipolární porucha * farmakoterapie   genetika   MeSH
• celogenomová asociační studie * metody   MeSH
• farmakogenetika metody   MeSH
• fokální adheze * účinky léků   genetika   MeSH
• genomika metody   MeSH
• genové regulační sítě * účinky léků   genetika   MeSH
• indukované pluripotentní kmenové buňky účinky léků   metabolismus   MeSH
• lidé MeSH
• lithium * farmakologie   terapeutické užití   MeSH
• multiomika MeSH
• neurony metabolismus   účinky léků   MeSH
• sloučeniny lithia farmakologie   terapeutické užití   MeSH
• stanovení celkové genové exprese metody   MeSH
• transkriptom * genetika   účinky léků   MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Research Support, N.I.H., Extramural MeSH

Bordetella pertussis je lidský patogen, který je původcem černého kašle, vysoce nakažlivé respirační choroby, jejíž výskyt je v současné době na vzestupu a to i v ekonomicky vyspělých zemích s vysokou proočkovaností jako je Česká republika. Tento vzestup je přičítán zejména přechodu z celobuněčných vakcín na vakcíny acelulární. Acelulární vakcíny jsou sice ve srovnání s celobuněčnými méně reaktogenní, nicméně poskytují sníženou a kratší ochranu před nákazou. Navíc došlo u cirkulujících kmenů B. pertussis v reakci na antigeny obsažené ve vakcínách ke genotypovým změnám. Naším cílem je analyzovat celogenomové sekvence a produkci faktorů virulence v klinických izolátech získaných na území České republiky v letech 2008 – 2015. Pro srovnávací analýzu budou využity i původní vakcinační kmeny používané k výrobě celobuněčné vakcíny. Dále pomocí proteomiky a imunoprecipitace použijeme séra pacientů nakažených černým kašlem k identifikaci nových imunogenních antigenů produkovaných současnými kmeny B. pertussis.; Bordetella pertussis is the causative agent of human whooping cough (pertussis), a highly contagious respiratory disease that remains to be the least controlled vaccine-preventable infectious disease. Despite generalized vaccination, pertussis is again on the rise in highly vaccinated populations including Czech Republic. The increase in pertussis cases has been mostly attributed to short-lived immunity induced by the acellular vaccine and escape from immunity due to pathogen adaptation and antigen variation. Therefore, using comparative genomics we will analyze Czech clinical isolates of B. pertussis collected during the recent period 2008 - 2015. Importantly, genomic sequences, expression and production of virulence factors will be compared with those of B. pertussis vaccine strains. In addition, using proteomics and immunoprecipitation we will apply recent human sera of infected patients for identification of novel immunogenic antigens of B. pertussis.

• MeSH
• Bordetella pertussis genetika   patogenita   MeSH
• faktory virulence rodu Bordetella analýza   MeSH
• lidé MeSH
• pertuse genetika   prevence a kontrola   MeSH
• sekvenování celého genomu metody   MeSH
• virulence MeSH
• Check Tag
• lidé MeSH

• Konspekt
• Patologie. Klinická medicína
• NLK Obory
• genetika, lékařská genetika
• pneumologie a ftizeologie
• NLK Publikační typ
• závěrečné zprávy o řešení grantu AZV MZ ČR

AIM: The metabolic performance of the gut microbiota contributes to the onset of type 2 diabetes. However, targeted dietary interventions are limited by the highly variable inter-individual response. We hypothesized (1) that the composition of the complex gut microbiome and metabolome (MIME) differ across metabolic spectra (lean-obese-diabetes); (2) that specific MIME patterns could explain the differential responses to dietary inulin; and (3) that the response can be predicted based on baseline MIME signature and clinical characteristics. METHOD: Forty-nine patients with newly diagnosed pre/diabetes (DM), 66 metabolically healthy overweight/obese (OB), and 32 healthy lean (LH) volunteers were compared in a cross-sectional case-control study integrating clinical variables, dietary intake, gut microbiome, and fecal/serum metabolomes (16 S rRNA sequencing, metabolomics profiling). Subsequently, 27 DM were recruited for a predictive study: 3 months of dietary inulin (10 g/day) intervention. RESULTS: MIME composition was different between groups. While the DM and LH groups represented opposite poles of the abundance spectrum, OB was closer to DM. Inulin supplementation was associated with an overall improvement in glycemic indices, though the response was very variable, with a shift in microbiome composition toward a more favorable profile and increased serum butyric and propionic acid concentrations. The improved glycemic outcomes of inulin treatment were dependent on better baseline glycemic status and variables related to the gut microbiota, including the abundance of certain bacterial taxa (i.e., Blautia, Eubacterium halii group, Lachnoclostridium, Ruminiclostridium, Dialister, or Phascolarctobacterium), serum concentrations of branched-chain amino acid derivatives and asparagine, and fecal concentrations of indole and several other volatile organic compounds. CONCLUSION: We demonstrated that obesity is a stronger determinant of different MIME patterns than impaired glucose metabolism. The large inter-individual variability in the metabolic effects of dietary inulin was explained by differences in baseline glycemic status and MIME signatures. These could be further validated to personalize nutritional interventions in patients with newly diagnosed diabetes.

• MeSH
• diabetes mellitus 2. typu * MeSH
• inulin * metabolismus   farmakologie   MeSH
• lidé MeSH
• multiomika MeSH
• nadváha metabolismus   MeSH
• obezita metabolismus   MeSH
• průřezové studie MeSH
• studie případů a kontrol MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• pozorovací studie MeSH
• práce podpořená grantem MeSH

Sepsis is a multifactorial clinical syndrome with an extremely dynamic clinical course and with high diverse clinical phenotype. Early diagnosis is crucial for the final clinical outcome. Previous studies have not identified a biomarker for the diagnosis of sepsis which would have sufficient sensitivity and specificity. Identification of the infectious agents or the use of molecular biology, next gene sequencing, has not brought significant benefit for the patient in terms of early diagnosis. Therefore, we are currently searching for biomarkers, through "omics" technologies with sufficient diagnostic specificity and sensitivity, able to predict the clinical course of the disease and the patient response to therapy. Current progress in the use of systems biology technologies brings us hope that by using big data from clinical trials such biomarkers will be found.

• MeSH
• biologické markery analýza   MeSH
• genomika MeSH
• infekční nemoci diagnóza   terapie   MeSH
• kritický stav terapie   MeSH
• lidé MeSH
• proteomika MeSH
• sepse krev   diagnóza   terapie   MeSH
• systémová biologie MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

Omics-based methods are increasingly used in current ecotoxicology. Therefore, a large number of observations for various toxic substances and organisms are available and may be used for identifying modes of action, adverse outcome pathways, or novel biomarkers. For these purposes, good statistical analysis of toxicogenomic data is vital. In contrast to established ecotoxicological techniques, concentration-response modeling is rarely used for large datasets. Instead, statistical hypothesis testing is prevalent, which provides only a limited scope for inference. The present study therefore applied automated concentration-response modeling for 3 different ecotoxicotranscriptomic and ecotoxicometabolomic datasets. The modeling process was performed by simultaneously applying 9 different regression models, representing distinct mechanistic, toxicological, and statistical ideas that result in different curve shapes. The best-fitting models were selected by using Akaike's information criterion. The linear and exponential models represented the best data description for more than 50% of responses. Models generating U-shaped curves were frequently selected for transcriptomic signals (30%), and sigmoid models were identified as best fit for many metabolomic signals (21%). Thus, selecting the models from an array of different types seems appropriate, because concentration-response functions may vary because of the observed response type, and they also depend on the compound, the organism, and the investigated concentration and exposure duration range. The application of concentration-response models can help to further tap the potential of omics data and is a necessary step for quantitative mixture effect assessment at the molecular response level.

• MeSH
• dánio pruhované růst a vývoj   metabolismus   MeSH
• ekosystém * MeSH
• embryo nesavčí účinky léků   metabolismus   MeSH
• genomika * MeSH
• látky znečišťující životní prostředí toxicita   MeSH
• lineární modely MeSH
• metabolomika * MeSH
• rychlé screeningové testy MeSH
• sekvenční analýza hybridizací s uspořádaným souborem oligonukleotidů MeSH
• tetrachlorethylen toxicita   MeSH
• transkriptom účinky léků   MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

The exposome concept encourages holistic consideration of the non-genetic factors (environmental exposures including lifestyle) that influence an individual's health over their life course. However, disconnect between the concept and practical application has promoted divergent interpretations of the exposome across disciplines and reinforced separation of the environmental (emphasizing exposures) and biological (emphasizing responses) research communities. In particular, while knowledge of biological responses can help to distinguish actual (i.e. experienced) from potential exposures, the inclusion of endogenous processes has generated confusion about the position of the exposome in a multi-omics systems biology context. We propose a reattribution of "exposome" to exclusively represent the totality of contact with external factors that a biological entity experiences, and introduce the term "functional exposomics" to denote the systematic study of exposure-phenotype interaction. This reoriented definition of the exposome allows a more readily integrable dataset for multi-omics and systems biology research.

• Publikační typ
• časopisecké články MeSH
• přehledy MeSH