79 research outputs found

    Insulin-like growth factor 1 (IGF1), IGF binding protein 3 (IGFBP3), and breast cancer risk: Pooled individual data analysis of 17 prospective studies

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    Background: Insulin-like growth factor 1 (IGF1) stimulates mitosis and inhibits apoptosis. Some published results have shown an association between circulating IGF1 and breast-cancer risk, but it has been unclear whether this relationship is consistent or whether it is modified by IGF binding protein 3 (IGFBP3), menopausal status, oestrogen receptor status or other factors. The relationship of IGF1 (and IGFBP3) with breast-cancer risk factors is also unclear. The Endogenous Hormones and Breast Cancer Collaborative Group was established to analyse pooled individual data from prospective studies to increase the precision of the estimated associations of endogenous hormones with breast-cancer risk. Methods: Individual data on prediagnostic IGF1 and IGFBP3 concentrations were obtained from 17 prospective studies in 12 countries. The associations of IGF1 with risk factors for breast cancer in controls were examined by calculating geometric mean concentrations in categories of these factors. The odds ratios (ORs) with 95% CIs of breast cancer associated with increasing IGF1 concentrations were estimated by conditional logistic regression in 4790 cases and 9428 matched controls, with stratification by study, age at baseline, and date of baseline. All statistical tests were two-sided, and a p value of less than 0\ub705 was considered significant. Findings: IGF1 concentrations, adjusted for age, were positively associated with height and age at first pregnancy, inversely associated with age at menarche and years since menopause, and were higher in moderately overweight women and moderate alcohol consumers than in other women. The OR for breast cancer for women in the highest versus the lowest fifth of IGF1 concentration was 1\ub728 (95% CI 1\ub714-1\ub744; p<0\ub70001). This association was not altered by adjusting for IGFBP3, and did not vary significantly by menopausal status at blood collection. The ORs for a difference in IGF1 concentration between the highest and lowest fifth were 1\ub738 (95% CI 1\ub714-1\ub768) for oestrogen-receptor-positive tumours and 0\ub780 (0\ub757-1\ub713) for oestrogen-receptor-negative tumours (p for heterogeneity=0\ub7007). Interpretation: Circulating IGF1 is positively associated with breast-cancer risk. The association is not substantially modified by IGFBP3, and does not differ markedly by menopausal status, but seems to be confined to oestrogen-receptor-positive tumours

    Whole-genome sequencing reveals host factors underlying critical COVID-19

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    Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

    Tree-ring analysis of timbers from Chiddingly Place, Chiddingly, East Sussex

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    Includes bibliographical referencesAvailable from British Library Document Supply Centre- DSC:3106. 4635(14/2003) / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo

    Tree-ring analysis of timbers from Manor House, High Street/Kings Street, Fordwich, Kent

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    Includes bibliographical referencesAvailable from British Library Document Supply Centre- DSC:3106. 4635(7/2003) / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo

    Tree-ring analysis of timbers from Finchale Priory Farmhouse, Finchale, Co Durham

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    Includes bibliographical referencesAvailable from British Library Document Supply Centre- DSC:3106. 4635(92/2002) / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo

    Tree-ring analysis of oak timbers from Combermere Abbey, Whitchurch, Cheshire

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    Includes bibliographical referencesSIGLEAvailable from British Library Document Supply Centre- DSC:3106. 4635(83/2003) / BLDSC - British Library Document Supply CentreGBUnited Kingdo

    Tree-ring analysis of timbers from Clifton Hall Tower, Clifton, near Penrith, Cumbria

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    Includes bibliographical referencesAvailable from British Library Document Supply Centre- DSC:3106. 4635(23/2003) / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo
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