| 1. |
- Badam, Tejaswi, et al.
(author)
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CD4(+) T-cell DNA methylation changes during pregnancy significantly correlate with disease-associated methylation changes in autoimmune diseases
- 2022
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In: Epigenetics. - : Taylor & Francis Group. - 1559-2294 .- 1559-2308. ; 17:9, s. 1040-1055
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Journal article (peer-reviewed)abstract
- Epigenetics may play a central, yet unexplored, role in the profound changes that the maternal immune system undergoes during pregnancy and could be involved in the pregnancy-induced modulation of several autoimmune diseases. We investigated changes in the methylome in isolated circulating CD4(+) T-cells in non-pregnant and pregnant women, during the 1(st) and 2(nd) trimester, using the Illumina Infinium Human Methylation 450K array, and explored how these changes were related to autoimmune diseases that are known to be affected during pregnancy. Pregnancy was associated with several hundreds of methylation differences, particularly during the 2(nd) trimester. A network-based modular approach identified several genes, e.g., CD28, FYN, VAV1 and pathways related to T-cell signalling and activation, highlighting T-cell regulation as a central component of the observed methylation alterations. The identified pregnancy module was significantly enriched for disease-associated methylation changes related to multiple sclerosis, rheumatoid arthritis and systemic lupus erythematosus. A negative correlation between pregnancy-associated methylation changes and disease-associated changes was found for multiple sclerosis and rheumatoid arthritis, diseases that are known to improve during pregnancy whereas a positive correlation was found for systemic lupus erythematosus, a disease that instead worsens during pregnancy. Thus, the directionality of the observed changes is in line with the previously observed effect of pregnancy on disease activity. Our systems medicine approach supports the importance of the methylome in immune regulation of T-cells during pregnancy. Our findings highlight the relevance of using pregnancy as a model for understanding and identifying disease-related mechanisms involved in the modulation of autoimmune diseases.
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| 2. |
- Badam, Tejaswi V. S., et al.
(author)
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A validated generally applicable approach using the systematic assessment of disease modules by GWAS reveals a multi-omic module strongly associated with risk factors in multiple sclerosis
- 2021
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In: BMC Genomics. - : BioMed Central. - 1471-2164. ; 22:1
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Journal article (peer-reviewed)abstract
- Background: There exist few, if any, practical guidelines for predictive and falsifiable multi-omic data integration that systematically integrate existing knowledge. Disease modules are popular concepts for interpreting genome-wide studies in medicine but have so far not been systematically evaluated and may lead to corroborating multi-omic modules. Result: We assessed eight module identification methods in 57 previously published expression and methylation studies of 19 diseases using GWAS enrichment analysis. Next, we applied the same strategy for multi-omic integration of 20 datasets of multiple sclerosis (MS), and further validated the resulting module using both GWAS and risk-factor-associated genes from several independent cohorts. Our benchmark of modules showed that in immune-associated diseases modules inferred from clique-based methods were the most enriched for GWAS genes. The multi-omic case study using MS data revealed the robust identification of a module of 220 genes. Strikingly, most genes of the module were differentially methylated upon the action of one or several environmental risk factors in MS (n = 217, P = 10− 47) and were also independently validated for association with five different risk factors of MS, which further stressed the high genetic and epigenetic relevance of the module for MS. Conclusions: We believe our analysis provides a workflow for selecting modules and our benchmark study may help further improvement of disease module methods. Moreover, we also stress that our methodology is generally applicable for combining and assessing the performance of multi-omic approaches for complex diseases.
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| 3. |
- Björn, Niclas, 1990-, et al.
(author)
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Whole-genome sequencing and gene network modules predict gemcitabine/carboplatin-induced myelosuppression in non-small cell lung cancer patients
- 2020
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In: npj Systems Biology and Applications. - : Nature Publishing Group. - 2056-7189. ; 6:1
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Journal article (peer-reviewed)abstract
- Gemcitabine/carboplatin chemotherapy commonly induces myelosuppression, including neutropenia, leukopenia, and thrombocytopenia. Predicting patients at risk of these adverse drug reactions (ADRs) and adjusting treatments accordingly is a long-term goal of personalized medicine. This study used whole-genome sequencing (WGS) of blood samples from 96 gemcitabine/carboplatin-treated non-small cell lung cancer (NSCLC) patients and gene network modules for predicting myelosuppression. Association of genetic variants in PLINK found 4594, 5019, and 5066 autosomal SNVs/INDELs with p ≤ 1 × 10−3 for neutropenia, leukopenia, and thrombocytopenia, respectively. Based on the SNVs/INDELs we identified the toxicity module, consisting of 215 unique overlapping genes inferred from MCODE-generated gene network modules of 350, 345, and 313 genes, respectively. These module genes showed enrichment for differentially expressed genes in rat bone marrow, human bone marrow, and human cell lines exposed to carboplatin and gemcitabine (p < 0.05). Then using 80% of the patients as training data, random LASSO reduced the number of SNVs/INDELs in the toxicity module into a feasible prediction model consisting of 62 SNVs/INDELs that accurately predict both the training and the test (remaining 20%) data with high (CTCAE 3–4) and low (CTCAE 0–1) maximal myelosuppressive toxicity completely, with the receiver-operating characteristic (ROC) area under the curve (AUC) of 100%. The present study shows how WGS, gene network modules, and random LASSO can be used to develop a feasible and tested model for predicting myelosuppressive toxicity. Although the proposed model predicts myelosuppression in this study, further evaluation in other studies is required to determine its reproducibility, usability, and clinical effect.
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| 4. |
- Carlström, Karl E., et al.
(author)
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Therapeutic efficacy of dimethyl fumarate in relapsing-remitting multiple sclerosis associates with ROS pathway in monocytes
- 2019
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In: Nature Communications. - : Nature Publishing Group. - 2041-1723. ; 10:1, s. 1-13
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Journal article (peer-reviewed)abstract
- Dimethyl fumarate (DMF) is a first-line-treatment for relapsing-remitting multiple sclerosis (RRMS). The redox master regulator Nrf2, essential for redox balance, is a target of DMF, but its precise therapeutic mechanisms of action remain elusive. Here we show impact of DMF on circulating monocytes and T cells in a prospective longitudinal RRMS patient cohort. DMF increases the level of oxidized isoprostanes in peripheral blood. Other observed changes, including methylome and transcriptome profiles, occur in monocytes prior to T cells. Importantly, monocyte counts and monocytic ROS increase following DMF and distinguish patients with beneficial treatment-response from non-responders. A single nucleotide polymorphism in the ROS-generating NOX3 gene is associated with beneficial DMF treatment-response. Our data implicate monocyte-derived oxidative processes in autoimmune diseases and their treatment, and identify NOX3 genetic variant, monocyte counts and redox state as parameters potentially useful to inform clinical decisions on DMF therapy of RRMS.
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| 5. |
- Dybjer, Elin, et al.
(author)
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Type 1 diabetes, cognitive ability and incidence of cardiovascular disease and death over 60 years of follow-up time in men
- 2022
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In: Diabetic Medicine. - : Wiley. - 0742-3071 .- 1464-5491. ; 39:8
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Journal article (peer-reviewed)abstract
- Aims There are few cohorts of type 1 diabetes that follow individuals over more than half a century in terms of health outcomes. The aim of this study was to examine associations between type 1 diabetes, diagnosed before age 18, and long-term morbidity and mortality, and to investigate whether cognitive ability plays a role in long-term morbidity and mortality risk. Methods In a Swedish cohort, 120 men with type 1 diabetes and 469 without type 1 diabetes were followed between 18 and 77 years of age as regards morbidity and mortality outcomes, and impact of cognitive ability at military conscription for the outcomes. In Cox regression analyses and Kaplan-Meier analyses with log-rank tests, associations between diabetes and cognitive ability respectively, and outcomes (mortality, cardiovascular morbidity and diabetes complications) were investigated. Results Men with type 1 diabetes suffered from dramatically higher mortality (HR 4.62, 95% CI: 3.56-5.60), cardiovascular mortality (HR 5.60, 95% CI: 3.27-9.57), and cardiovascular events (HR 3.97, 95% CI: 2.79-5.64) compared to men without diabetes. Higher cognitive ability at military conscription was associated with lower mortality in men without diabetes, but was not associated with any outcome in men with diabetes. Conclusions In this historical cohort study with 60 years of follow-up time and a less effective treatment of diabetes than today, mortality rates and cardiovascular outcomes were high for men with type 1 diabetes. Morbidity or mortality did not differ between those that had low to normal or high cognitive ability among men with type 1 diabetes.
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| 6. |
- Hallgren, Jenny, 1978-, et al.
(author)
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Factors associated with increased hospitalisation risk among nursing home residents in Sweden : a prospective study with a three-year follow-up
- 2016
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In: International Journal of Older People Nursing. - : John Wiley & Sons. - 1748-3735 .- 1748-3743. ; 11:2, s. 130-139
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Journal article (peer-reviewed)abstract
- BackgroundHospitalisation of nursing home residents might lead to deteriorating health.AimTo evaluate physical and psychological factors associated with hospitalisation risk among nursing home residents.DesignProspective study with three years of follow-up.MethodsFour hundred and twenty-nine Swedish nursing home residents, ages 65–101 years, from 11 nursing homes in three municipalities were followed during three years. The participants' physical and psychological status was assessed at baseline. A Cox proportional hazards model was used to evaluate factors associated with hospitalisation risk using STATA.ResultsOf the 429 participants, 196 (45.7%) were hospitalised at least once during the three-year follow-up period, and 109 (25.4%) during the first six months of the study. The most common causes of hospitalisation were cardiovascular diseases or complications due to falls. A Cox regression model showed that residents who have had previous falls (P < 0.001), are malnourished (P < 0.001), use a greater number of drugs (P < 0.001) and have more diseases (P < 0.001), are at an increased risk of hospitalisation.ConclusionNursing home residents are frequently hospitalised, often due to falls or cardiovascular diseases. Study results underscore the relationships between malnutrition, previous falls, greater numbers of drugs and diseases and higher risk of hospitalisation.Implications for practicePreventive interventions aimed at malnutrition and falls at the nursing home could potentially reduce the number of hospitalisations. With improved education and support to nurses concerning risk assessment at the nursing homes, it may be possible to reduce the numbers of avoidable hospitalisation among nursing home residents and in the long run improve quality of life and reduce suffering.
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| 7. |
- Jacobsson, Jenny, et al.
(author)
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Injury patterns in Swedish elite athletics – part 1 : annual incidence and injury types
- 2013
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In: British Journal of Sports Medicine. - : BMJ PUBLISHING GROUP. - 0306-3674 .- 1473-0480. ; 47:15
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Journal article (peer-reviewed)abstract
- Objective To estimate the incidence, type and severity of musculoskeletal injuries in youth and adult elite athletics athletes and to explore risk factors for sustaining injuries. Design Prospective cohort study conducted during a 52-week period. Setting Male and female youth and adult athletics athletes ranked in the top 10 in Sweden (n=292). Results 199 (68%) athletes reported an injury during the study season. Ninety-six per cent of the reported injuries were non-traumatic (associated with overuse). Most injuries (51%) were severe, causing a period of absence from normal training exceeding 3 weeks. Log-rank tests revealed risk differences with regard to athlete category (p=0.046), recent previous injury (>3 weeks time-loss; p=0.039) and training load rank index (TLRI; p=0.019). Cox proportional hazards regression analyses showed that athletes in the third (HR 1.79; 95% CI 1.54 to 2.78) and fourth TLRI quartiles (HR 1.79; 95% CI 1.16 to 2.74) had almost a twofold increased risk of injury compared with their peers in the first quartile and interaction effects between athlete category and previous injury; youth male athletes with a previous serious injury had more than a fourfold increased risk of injury (HR=4.39; 95% CI 2.20 to 8.77) compared with youth females with no previous injury. Conclusions The injury incidence among both youth and adult elite athletics athletes is high. A training load index combing hours and intensity and a history of severe injury the previous year were predictors for injury. Further studies on measures to quantify training content and protocols for safe return to athletics are warranted.
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| 8. |
- Larsson, Per-Göran, et al.
(author)
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Extended antimicrobial treatment of bacterial vaginosis combined with human lactobacilli to find the best treatment and minimize the risk of relapses
- 2011
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In: BMC Infectious Diseases. - : BioMed Central. - 1471-2334. ; 11:223
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Journal article (peer-reviewed)abstract
- Background: The primary objective of this study was to investigate if extended antibiotic treatment against bacterial vaginosis (BV) together with adjuvant lactobacilli treatment could cure BV and, furthermore, to investigate factors that could cause relapse. less thanbrgreater than less thanbrgreater thanMethods: In all, 63 consecutive women with bacterial vaginosis diagnosed by Amsel criteria were offered a much more aggressive treatment of BV than used in normal clinical practice with repeated antibiotic treatment with clindamycin and metronidazole together with vaginal gelatine capsules containing different strains of lactobacilli both newly characterised and a commercial one (10(9) freeze-dried bacteria per capsule). Oral clindamycin treatment was also given to the patients sexual partner. less thanbrgreater than less thanbrgreater thanResults: The cure rate was 74.6% after 6 months. The patients were then followed as long as possible or until a relapse. The cure rate was 65.1% at 12 months and 55.6% after 24 months. There was no significant difference in cure rate depending on which Lactobacillus strains were given to the women or if the women were colonised by lactobacilli. The most striking factor was a new sex partner during the follow up period where the Odds Ratio of having a relapse was 9.3 (2.8-31.2) if the patients had a new sex partner during the observation period. less thanbrgreater than less thanbrgreater thanConclusions: The study shows that aggressive treatment of the patient with antibiotics combined with specific Lactobacillus strain administration and partner treatment can provide long lasting cure. A striking result of our study is that change of partner is strongly associated with relapse of BV.
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| 9. |
- Magnusson, Rasmus, 1992-, et al.
(author)
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Deep neural network prediction of genome-wide transcriptome signatures – beyond the Black-box
- 2022
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In: npj Systems Biology and Applications. - : Springer Nature. - 2056-7189. ; 8:1
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Journal article (peer-reviewed)abstract
- Prediction algorithms for protein or gene structures, including transcription factor binding from sequence information, have been transformative in understanding gene regulation. Here we ask whether human transcriptomic profiles can be predicted solely from the expression of transcription factors (TFs). We find that the expression of 1600 TFs can explain >95% of the variance in 25,000 genes. Using the light-up technique to inspect the trained NN, we find an over-representation of known TF-gene regulations. Furthermore, the learned prediction network has a hierarchical organization. A smaller set of around 125 core TFs could explain close to 80% of the variance. Interestingly, reducing the number of TFs below 500 induces a rapid decline in prediction performance. Next, we evaluated the prediction model using transcriptional data from 22 human diseases. The TFs were sufficient to predict the dysregulation of the target genes (rho = 0.61, P < 10−216). By inspecting the model, key causative TFs could be extracted for subsequent validation using disease-associated genetic variants. We demonstrate a methodology for constructing an interpretable neural network predictor, where analyses of the predictors identified key TFs that were inducing transcriptional changes during disease.
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| 10. |
- Nilsson, Emma, et al.
(author)
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Transcriptional and Epigenetic Changes Influencing Skeletal Muscle Metabolism in Women With Polycystic Ovary Syndrome
- 2018
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In: Journal of Clinical Endocrinology & Metabolism. - : The Endocrine Society. - 0021-972X .- 1945-7197. ; 103:12, s. 4465-4477
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Journal article (peer-reviewed)abstract
- Context: Insulin resistance in skeletal muscle is a major risk factor for the development of type 2 diabetes in women with polycystic ovary syndrome (PCOS). Despite this, the mechanisms underlying insulin resistance in PCOS are largely unknown. Objective: To investigate the genome-wide DNA methylation and gene expression patterns in skeletal muscle from women with PCOS and controls and relate them to phenotypic variations. Design/Participants: In a case-control study, skeletal muscle biopsies from women with PCOS (n = 17) and age-, weight-, and body mass index. matched controls (n = 14) were analyzed by array-based DNA methylation and mRNA expression profiling. Results: Eighty-five unique transcripts were differentially expressed in muscle from women with PCOS vs controls, including DYRK1A, SYNPO2, SCP2, and NAMPT. Furthermore, women with PCOS had reduced expression of genes involved in immune system pathways. Two CpG sites showed differential DNA methylation after correction for multiple testing. However, an mRNA expression of similar to 30% of the differentially expressed genes correlated with DNA methylation levels of CpG sites in or near the gene. Functional follow-up studies demonstrated that KLF10 is under transcriptional control of insulin, where insulin promotes glycogen accumulation in myotubes of human muscle cells. Testosterone downregulates the expression levels of COL1A1 and MAP2K6. Conclusion: PCOS is associated with aberrant skeletal muscle gene expression with dysregulated pathways. Furthermore, we identified specific changes in muscle DNA methylation that may affect gene expression. This study showed that women with PCOS have epigenetic and transcriptional changes in skeletal muscle that, in part, can explain the metabolic abnormalities seen in these women.
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