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- Magi, CAO, et al.
(author)
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Allergic disease and risk of stress in pregnant women: a PreventADALL study
- 2020
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In: ERJ open research. - : European Respiratory Society (ERS). - 2312-0541. ; 6:4
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Journal article (peer-reviewed)abstract
- Maternal stress during pregnancy may negatively affect the health of mother and child. We therefore aimed to identify the proportion of women reporting high maternal stress in mid and late pregnancy and explore whether symptoms of maternal allergic disease are associated with perceived maternal stress in late pregnancy.MethodThe population-based Preventing Atopic Dermatitis and Allergy in Children (PreventADALL) study enrolled 2697 pregnant women at their 18-week routine ultrasound examination in Norway and Sweden. Information about sociodemographic factors, symptoms and doctor-diagnosed asthma, allergic rhinitis, atopic dermatitis, food allergy, and anaphylaxis and stress using the 14-item perceived stress scale (PSS) was collected at 18 weeks (mid) and 34 weeks (late) pregnancy. High stress was defined as a PSS score ≥29. Scores were analysed using multivariate logistic and linear regression.ResultsAmong the 2164 women with complete PSS data, 17% reported asthma, 20% atopic dermatitis, 23% allergic rhinitis, 12% food allergy and 2% anaphylaxis. The proportion of women reporting high stress decreased from 15% at mid to 13% at late pregnancy (p<0.01). The adjusted odds ratio for high stress in late pregnancy was 2.25 (95% CI 1.41–3.58) for self-reported symptoms of asthma, 1.46 (95% CI 1.02–2.10) for allergic rhinitis and 2.25 (95% CI 1.32–3.82) for food allergy. A multivariate linear regression model confirmed that symptoms of asthma (β coefficient 2.11; 0.71–3.51), atopic dermatitis (β coefficient 1.76; 0.62–2.89) and food allergy (β coefficient 2.24; 0.63–3.84) were independently associated with increased PSS score.ConclusionAllergic disease symptoms in pregnancy were associated with increased stress, highlighting the importance of optimal disease control in pregnancy.
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| 2. |
- Campbell, PJ, et al.
(author)
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Pan-cancer analysis of whole genomes
- 2020
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In: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 578:7793, s. 82-
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Journal article (peer-reviewed)abstract
- Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1–3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10–18.
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