| 1. |
- Gustafsson, Mika, et al.
(författare)
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Modules, networks and systems medicine for understanding disease and aiding diagnosis
- 2014
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Ingår i: Genome Medicine. - : BioMed Central. - 1756-994X. ; 6:82
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Forskningsöversikt (refereegranskat)abstract
- Many common diseases, such as asthma, diabetes or obesity, involve altered interactions between thousands of genes. High-throughput techniques (omics) allow identification of such genes and their products, but functional understanding is a formidable challenge. Network-based analyses of omics data have identified modules of disease-associated genes that have been used to obtain both a systems level and a molecular understanding of disease mechanisms. For example, in allergy a module was used to find a novel candidate gene that was validated by functional and clinical studies. Such analyses play important roles in systems medicine. This is an emerging discipline that aims to gain a translational understanding of the complex mechanisms underlying common diseases. In this review, we will explain and provide examples of how network-based analyses of omics data, in combination with functional and clinical studies, are aiding our understanding of disease, as well as helping to prioritize diagnostic markers or therapeutic candidate genes. Such analyses involve significant problems and limitations, which will be discussed. We also highlight the steps needed for clinical implementation.
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| 2. |
- Lee, Bruce Y., et al.
(författare)
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Research gaps and opportunities in precision nutrition : an NIH workshop report
- 2022
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Ingår i: The American journal of clinical nutrition. - : Elsevier BV. - 1938-3207 .- 0002-9165. ; 116:6, s. 1877-1900
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Tidskriftsartikel (refereegranskat)abstract
- Precision nutrition is an emerging concept that aims to develop nutrition recommendations tailored to different people's circumstances and biological characteristics. Responses to dietary change and the resulting health outcomes from consuming different diets may vary significantly between people based on interactions between their genetic backgrounds, physiology, microbiome, underlying health status, behaviors, social influences, and environmental exposures. On 11-12 January 2021, the National Institutes of Health convened a workshop entitled "Precision Nutrition: Research Gaps and Opportunities" to bring together experts to discuss the issues involved in better understanding and addressing precision nutrition. The workshop proceeded in 3 parts: part I covered many aspects of genetics and physiology that mediate the links between nutrient intake and health conditions such as cardiovascular disease, Alzheimer disease, and cancer; part II reviewed potential contributors to interindividual variability in dietary exposures and responses such as baseline nutritional status, circadian rhythm/sleep, environmental exposures, sensory properties of food, stress, inflammation, and the social determinants of health; part III presented the need for systems approaches, with new methods and technologies that can facilitate the study and implementation of precision nutrition, and workforce development needed to create a new generation of researchers. The workshop concluded that much research will be needed before more precise nutrition recommendations can be achieved. This includes better understanding and accounting for variables such as age, sex, ethnicity, medical history, genetics, and social and environmental factors. The advent of new methods and technologies and the availability of considerably more data bring tremendous opportunity. However, the field must proceed with appropriate levels of caution and make sure the factors listed above are all considered, and systems approaches and methods are incorporated. It will be important to develop and train an expanded workforce with the goal of reducing health disparities and improving precision nutritional advice for all Americans.
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| 3. |
- Nanni, Mirco, et al.
(författare)
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Give more data, awareness and control to individual citizens, and they will help COVID-19 containment
- 2020
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Ingår i: Transactions on Data Privacy. - : Institut d'Investigació en Intel·ligència Artificial. - 1888-5063 .- 2013-1631. ; 23, s. 1-6
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Tidskriftsartikel (refereegranskat)abstract
- The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the "phase 2" of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are being proposed for large scale adoption by many countries. A centralized approach, where data sensed by the app are all sent to a nation-wide server, raises concerns about citizens' privacy and needlessly strong digital surveillance, thus alerting us to the need to minimize personal data collection and avoiding location tracking. We advocate the conceptual advantage of a decentralized approach, where both contact and location data are collected exclusively in individual citizens' "personal data stores", to be shared separately and selectively (e.g., with a backend system, but possibly also with other citizens), voluntarily, only when the citizen has tested positive for COVID-19, and with a privacy preserving level of granularity. This approach better protects the personal sphere of citizens and affords multiple benefits: it allows for detailed information gathering for infected people in a privacy-preserving fashion; and, in turn this enables both contact tracing, and, the early detection of outbreak hotspots on more finely-granulated geographic scale. The decentralized approach is also scalable to large populations, in that only the data of positive patients need be handled at a central level. Our recommendation is two-fold. First to extend existing decentralized architectures with a light touch, in order to manage the collection of location data locally on the device, and allowthe user to share spatio-temporal aggregates - if and when they want and for specific aims - with health authorities, for instance. Second, we favour a longerterm pursuit of realizing a Personal Data Store vision, giving users the opportunity to contribute to collective good in the measure they want, enhancing self-awareness, and cultivating collective efforts for rebuilding society.
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| 4. |
- Persson, Emma, 1991-
(författare)
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Big data networks and orthology analysis
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Understanding biological systems in complex organisms is important in life science in order to comprehend the interplay of genes, proteins, and compounds causing complex diseases. As biological systems are intricate, bioinformatics tools, models, and algorithms are of the utmost importance to understand the bigger picture and decipher biological meaning from the vast amounts of information available from biological experiments and predictions. Bioinformatics programs and algorithms do not only depend on information from experiments, but also on information generated from other tools in order to draw accurate conclusions and make predictions. Prediction of orthologs, genes having a common ancestry, separated by a speciation event, are important building blocks for a wide variety of tools and analysis pipelines, as they can be used to transfer gene function between species. Orthologs can for example be used to map genes of model organisms to genes in humans in studies of drug targets. They are extensively used in functional association networks in order to transfer information between species. Functional association networks are models of associations between genes or proteins, where associations can be derived from experimental evidence of different types, from the species itself, or transferred from other species using orthologs. The networks can be used to explore the context and neighbors of a gene, but also for a variety of higher-level analyses, e.g. network-based pathway enrichment analysis. In pathway enrichment analysis the networks can be utilized to contextualize experimental gene sets and annotate them with biological functions. As these tools depend on each other, it is of great importance that the networks used in pathway enrichment analysis are comprehensive and accurate, and that the orthologs used in the networks are relevant and significant. In this thesis, the development and improvement of five bioinformatics tools within three areas of bioinformatics are presented. Despite the tools residing within slightly different areas, they all rely on each other, and can all on different levels improve our understanding of biological functions and biological meaning, from the level of orthology analysis to functional association networks to pathway enrichment analysis.
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| 5. |
- Sharma, Amitabh, et al.
(författare)
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Controllability in an islet specific regulatory network identifies the transcriptional factor NFATC4, which regulates Type 2 Diabetes associated genes
- 2018
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Ingår i: npj Systems Biology and Applications. - : Springer Science and Business Media LLC. - 2056-7189. ; 4:1
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Tidskriftsartikel (refereegranskat)abstract
- Probing the dynamic control features of biological networks represents a new frontier in capturing the dysregulated pathways in complex diseases. Here, using patient samples obtained from a pancreatic islet transplantation program, we constructed a tissue-specific gene regulatory network and used the control centrality (Cc) concept to identify the high control centrality (HiCc) pathways, which might serve as key pathobiological pathways for Type 2 Diabetes (T2D). We found that HiCc pathway genes were significantly enriched with modest GWAS p-values in the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) study. We identified variants regulating gene expression (expression quantitative loci, eQTL) of HiCc pathway genes in islet samples. These eQTL genes showed higher levels of differential expression compared to non-eQTL genes in low, medium, and high glucose concentrations in rat islets. Among genes with highly significant eQTL evidence, NFATC4 belonged to four HiCc pathways. We asked if the expressions of T2D-associated candidate genes from GWAS and literature are regulated by Nfatc4 in rat islets. Extensive in vitro silencing of Nfatc4 in rat islet cells displayed reduced expression of 16, and increased expression of four putative downstream T2D genes. Overall, our approach uncovers the mechanistic connection of NFATC4 with downstream targets including a previously unknown one, TCF7L2, and establishes the HiCc pathways’ relationship to T2D.
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