| 1. |
- Björnsson, Bergthor, et al.
(författare)
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Digital twins to personalize medicine
- 2020
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Ingår i: Genome Medicine. - : Springer Science and Business Media LLC. - 1756-994X. ; 12:1
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Forskningsöversikt (refereegranskat)abstract
- Personalized medicine requires the integration and processing of vast amounts of data. Here, we propose a solution to this challenge that is based on constructing Digital Twins. These are high-resolution models of individual patients that are computationally treated with thousands of drugs to find the drug that is optimal for the patient.
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| 2. |
- Gawel, Danuta, et al.
(författare)
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Clinical translation of genomic medicine : Stor potential när genomikdata kan implementeras i klinisk rutin.
- 2021
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Ingår i: Läkartidningen. - 1652-7518. ; 118
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Tidskriftsartikel (refereegranskat)abstract
- Recent technical developments and early clinical examples support that precision medicine has potential to provide novel diagnostic and therapeutic solutions for patients with complex diseases, who are not responding to existing therapies. Those solutions will require integration of genomic data with routine clinical, imaging, sensor, biobank and registry data. Moreover, user-friendly tools for informed decision support for both patients and clinicians will be needed. While this will entail huge technical, ethical, societal and regulatory challenges, it may contribute to transforming and improving health care towards becoming predictive, preventive, personalised and participatory (4P-medicine).
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| 3. |
- Gawel, Danuta, 1988-, et al.
(författare)
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Stor potential när genomikdatakan implementeras i klinisk rutin : [Clinical translation of genomic medicine]
- 2021
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Ingår i: Läkartidningen. - : Sveriges Läkarförbund. - 0023-7205 .- 1652-7518. ; 118
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Forskningsöversikt (refereegranskat)abstract
- Recent technical developments and early clinical examples support that precision medicine has potential to provide novel diagnostic and therapeutic solutions for patients with complex diseases, who are not responding to existing therapies. Those solutions will require integration of genomic data with routine clinical, imaging, sensor, biobank and registry data. Moreover, user-friendly tools for informed decision support for both patients and clinicians will be needed. While this will entail huge technical, ethical, societal and regulatory challenges, it may contribute to transforming and improving health care towards becoming predictive, preventive, personalised and participatory (4P-medicine).
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| 4. |
- Jung Lee, Eun Jung, et al.
(författare)
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Analysis of expression profiling data suggests explanation for difficulties in finding biomarkers for nasal polyps
- 2020
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Ingår i: Rhinology. - : INT RHINOLOGIC SOC. - 0300-0729 .- 1996-8604. ; 58:4, s. 360-367
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Tidskriftsartikel (refereegranskat)abstract
- Background: Identification of clinically useful biomarkers for Nasal Polyposis in chronic rhinosinusitis (CRSwNP) has proven difficult. We analyzed gene expression profiling data to find explanations for this. Methods:We analyzed mRNA expression profiling data, GSE36830, of six uncinate tissues from healthy controls and six NP from CRSwNP patients. We performed Ingenuity Pathway Analysis (IPA) of differentially expressed genes to identify pathways and predicted upstream regulators. Results: We identified 1,608 differentially expressed genes and 177 significant pathways, of which Th1 and Th2 activation pathway and leukocyte extravasation signaling were most significant. We identified 75 upstream regulators whose activity was predicted to be upregulated.These included regulators of known pathogenic and therapeutic relevance, like IL-4. However, only seven of the 75 regulators were actually differentially expressed in NP, namely CSF1, TYROBP, CCL2, CCL11, SELP, ADORA3, ICAM1. Interestingly, these did not include IL-4, and four of the seven were receptors. This suggested a potential explanation for the discrepancy between the predicted and observed expression levels of the regulators, namely that the receptors, and not their ligands, were upregulated. Indeed, we found that 10 receptors of key predicted upstream regulators were upregulated, including IL4R. Conclusion: Our findings indicate that the difficulties in finding specific biomarkers for CRSwNP depend on the complex underlying mechanisms, which include multiple pathways and regulators, each of which may be subdivided into multiple components such as ligands, soluble and membrane-bound receptors. This suggests that combinations of biomarkers may be needed for CRSwNP diagnostics.
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| 5. |
- Källestål, Carina, 1954-, et al.
(författare)
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Assessing the Multiple Dimensions of Poverty : Data Mining Approaches to the 2004-14 Health and Demographic Surveillance System in Cuatro Santos, Nicaragua
- 2020
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Ingår i: Frontiers In Public Health. - : FRONTIERS MEDIA SA. - 2296-2565. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- We identified clusters of multiple dimensions of poverty according to the capability approach theory by applying data mining approaches to the Cuatro Santos Health and Demographic Surveillance database, Nicaragua. Four municipalities in northern Nicaragua constitute the Cuatro Santos area, with 25,893 inhabitants in 5,966 households (2014). A local process analyzing poverty-related problems, prioritizing suggested actions, was initiated in 1997 and generated a community action plan 2002-2015. Interventions were school breakfasts, environmental protection, water and sanitation, preventive healthcare, home gardening, microcredit, technical training, university education stipends, and use of the Internet. In 2004, a survey of basic health and demographic information was performed in the whole population, followed by surveillance updates in 2007, 2009, and 2014 linking households and individuals. Information included the house material (floor, walls) and services (water, sanitation, electricity) as well as demographic data (birth, deaths, migration). Data on participation in interventions, food security, household assets, and women's self-rated health were collected in 2014. A K-means algorithm was used to cluster the household data (56 variables) in six clusters. The poverty ranking of household clusters using the unsatisfied basic needs index variables changed when including variables describing basic capabilities. The households in the fairly rich cluster with assets such as motorbikes and computers were described as modern. Those in the fairly poor cluster, having different degrees of food insecurity, were labeled vulnerable. Poor and poorest clusters of households were traditional, e.g., in using horses for transport. Results displayed a society transforming from traditional to modern, where the forerunners were not the richest but educated, had more working members in household, had fewer children, and were food secure. Those lagging were the poor, traditional, and food insecure. The approach may be useful for an improved understanding of poverty and to direct local policy and interventions.
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| 6. |
- Li, Xinxiu, et al.
(författare)
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A dynamic single cell-based framework for digital twins to prioritize disease genes and drug targets
- 2022
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Ingår i: Genome Medicine. - : BMC. - 1756-994X. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Background Medical digital twins are computational disease models for drug discovery and treatment. Unresolved problems include how to organize and prioritize between disease-associated changes in digital twins, on cellulome- and genome-wide scales. We present a dynamic framework that can be used to model such changes and thereby prioritize upstream regulators (URs) for biomarker- and drug discovery. Methods We started with seasonal allergic rhinitis (SAR) as a disease model, by analyses of in vitro allergen-stimulated peripheral blood mononuclear cells (PBMC) from SAR patients. Time-series a single-cell RNA-sequencing (scRNA-seq) data of these cells were used to construct multicellular network models (MNMs) at each time point of molecular interactions between cell types. We hypothesized that predicted molecular interactions between cell types in the MNMs could be traced to find an UR gene, at an early time point. We performed bioinformatic and functional studies of the MNMs to develop a scalable framework to prioritize UR genes. This framework was tested on a single-cell and bulk-profiling data from SAR and other inflammatory diseases. Results Our scRNA-seq-based time-series MNMs of SAR showed thousands of differentially expressed genes (DEGs) across multiple cell types, which varied between time points. Instead of a single-UR gene in each MNM, we found multiple URs dispersed across the cell types. Thus, at each time point, the MNMs formed multi-directional networks. The absence of linear hierarchies and time-dependent variations in MNMs complicated the prioritization of URs. For example, the expression and functions of Th2 cytokines, which are approved drug targets in allergies, varied across cell types, and time points. Our analyses of bulk- and single-cell data from other inflammatory diseases also revealed multi-directional networks that showed stage-dependent variations. We therefore developed a quantitative approach to prioritize URs: we ranked the URs based on their predicted effects on downstream target cells. Experimental and bioinformatic analyses supported that this kind of ranking is a tractable approach for prioritizing URs. Conclusions We present a scalable framework for modeling dynamic changes in digital twins, on cellulome- and genome-wide scales, to prioritize UR genes for biomarker and drug discovery.
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| 7. |
- Lilja, Sandra, et al.
(författare)
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Multi-organ single-cell analysis reveals an on/off switch system with potential for personalized treatment of immunological diseases
- 2023
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Ingår i: Cell Reports Medicine. - : ELSEVIER. - 2666-3791. ; 4:3
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Tidskriftsartikel (refereegranskat)abstract
- Prioritization of disease mechanisms, biomarkers, and drug targets in immune-mediated inflammatory dis-eases (IMIDs) is complicated by altered interactions between thousands of genes. Our multi-organ single -cell RNA sequencing of a mouse IMID model, namely collagen-induced arthritis, shows highly complex and heterogeneous expression changes in all analyzed organs, even though only joints showed signs of inflammation. We organized those into a multi-organ multicellular disease model, which shows predicted mo-lecular interactions within and between organs. That model supports that inflammation is switched on or off by altered balance between pro-and anti-inflammatory upstream regulators (URs) and downstream path-ways. Meta-analyses of human IMIDs show a similar, but graded, on/off switch system. This system has the potential to prioritize, diagnose, and treat optimal combinations of URs on the levels of IMIDs, subgroups, and individual patients. That potential is supported by UR analyses in more than 600 sera from patients with systemic lupus erythematosus.
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| 8. |
- Pérez, Wilton, 1979-, et al.
(författare)
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Trends and factors related to adolescent pregnancies : an incidence trend and conditional inference trees analysis of northern Nicaragua demographic surveillance data
- 2021
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Ingår i: BMC Pregnancy and Childbirth. - : BioMed Central. - 1471-2393 .- 1471-2393. ; 21:1
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: We aimed to identify the 2001-2013 incidence trend, and characteristics associated with adolescent pregnancies reported by 20-24-year-old women.METHODS: A retrospective analysis of the Cuatro Santos Northern Nicaragua Health and Demographic Surveillance 2004-2014 data on women aged 15-19 and 20-24. To calculate adolescent birth and pregnancy rates, we used the first live birth at ages 10-14 and 15-19 years reported by women aged 15-19 and 20-24 years, respectively, along with estimates of annual incidence rates reported by women aged 20-24 years. We conducted conditional inference tree analyses using 52 variables to identify characteristics associated with adolescent pregnancies.RESULTS: The number of first live births reported by women aged 20-24 years was 361 during the study period. Adolescent pregnancies and live births decreased from 2004 to 2009 and thereafter increased up to 2014. The adolescent pregnancy incidence (persons-years) trend dropped from 2001 (75.1 per 1000) to 2007 (27.2 per 1000), followed by a steep upward trend from 2007 to 2008 (19.1 per 1000) that increased in 2013 (26.5 per 1000). Associated factors with adolescent pregnancy were living in low-education households, where most adults in the household were working, and high proportion of adolescent pregnancies in the local community. Wealth was not linked to teenage pregnancies.CONCLUSIONS: Interventions to prevent adolescent pregnancy are imperative and must bear into account the context that influences the culture of early motherhood and lead to socioeconomic and health gains in resource-poor settings.
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| 9. |
- Schäfer, Samuel, et al.
(författare)
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scDrugPrio: a framework for the analysis of single-cell transcriptomics to address multiple problems in precision medicine in immune-mediated inflammatory diseases
- 2024
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Ingår i: Genome Medicine. - : BMC. - 1756-994X. ; 16:1
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Tidskriftsartikel (refereegranskat)abstract
- Background Ineffective drug treatment is a major problem for many patients with immune-mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic solutions for drug prioritisation and repurposing based on characterisation of the complex and heterogeneous cellular and molecular changes in IMIDs.Methods Here, we propose a computational framework, scDrugPrio, which constructs network models of inflammatory disease based on single-cell RNA sequencing (scRNA-seq) data. scDrugPrio constructs detailed network models of inflammatory diseases that integrate information on cell type-specific expression changes, altered cellular crosstalk and pharmacological properties for the selection and ranking of thousands of drugs.Results scDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive in vitro, in vivo, and in silico studies of drugs that were predicted, but not approved, for the studied diseases. Next, scDrugPrio was applied to multiple sclerosis, Crohn's disease, and psoriatic arthritis, further supporting scDrugPrio through prioritisation of relevant and approved drugs. However, in contrast to the mouse model of arthritis, great interindividual cellular and gene expression differences were found in patients with the same diagnosis. Such differences could explain why some patients did or did not respond to treatment. This explanation was supported by the application of scDrugPrio to scRNA-seq data from eleven individual Crohn's disease patients. The analysis showed great variations in drug predictions between patients, for example, assigning a high rank to anti-TNF treatment in a responder and a low rank in a nonresponder to that treatment.Conclusions We propose a computational framework, scDrugPrio, for drug prioritisation based on scRNA-seq of IMID disease. Application to individual patients indicates scDrugPrio's potential for personalised network-based drug screening on cellulome-, genome-, and drugome-wide scales. For this purpose, we made scDrugPrio into an easy-to-use R package (https://github.com/SDTC-CPMed/scDrugPrio).
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| 10. |
- Svahn, Caroline, et al.
(författare)
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CCVAE: A Variational Autoencoder for Handling Censored Covariates
- 2022
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Ingår i: 2022 21ST IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, ICMLA. - : IEEE COMPUTER SOC. - 9781665462839 - 9781665462846 ; , s. 709-714
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Konferensbidrag (refereegranskat)abstract
- For time or safety critical scenarios when faulty predictions or decisions can have crucial consequences, such as in certain telecommunications scenarios, reliable prediction models and accurate data are of the essence. When modeling and predicting data in such scenarios, data with censored covariates remain an issue as ignoring them or imputing them with lack of precision may cause inaccurate or uncertain predictions. In this paper, we provide a fast, reliable Variational Autoencoder framework which can handle covariate censoring in high dimensional data. Our numerical experiments demonstrate that our framework compares favorably to alternative methods in terms of prediction accuracy for both the response and the covariates, while enabling estimation of the prediction uncertainties. We moreover demonstrate that the method is at least 8 times faster than the benchmark models used in this paper, and more robust to initial imputations and noise than existing models. The method can also be used directly for predicting unseen data, which is a challenge for some state-of-the-art methods.
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