| 1. |
|
|
| 2. |
- Niemi, MEK, et al.
(author)
-
- 2021
-
swepub:Mat__t
|
|
| 3. |
- Kanai, M, et al.
(author)
-
- 2023
-
swepub:Mat__t
|
|
| 4. |
|
|
| 5. |
- Bravo, L, et al.
(author)
-
- 2021
-
swepub:Mat__t
|
|
| 6. |
- Tabiri, S, et al.
(author)
-
- 2021
-
swepub:Mat__t
|
|
| 7. |
|
|
| 8. |
- Thomas, HS, et al.
(author)
-
- 2019
-
swepub:Mat__t
|
|
| 9. |
|
|
| 10. |
|
|
| 11. |
|
|
| 12. |
|
|
| 13. |
- Kousathanas, A, et al.
(author)
-
Whole-genome sequencing reveals host factors underlying critical COVID-19
- 2022
-
In: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 607:7917, s. 97-
-
Journal article (peer-reviewed)abstract
- Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 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.
|
|
| 14. |
- Law, PJ, et al.
(author)
-
Genome-wide association analysis implicates dysregulation of immunity genes in chronic lymphocytic leukaemia
- 2017
-
In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 8, s. 14175-
-
Journal article (peer-reviewed)abstract
- Several chronic lymphocytic leukaemia (CLL) susceptibility loci have been reported; however, much of the heritable risk remains unidentified. Here we perform a meta-analysis of six genome-wide association studies, imputed using a merged reference panel of 1,000 Genomes and UK10K data, totalling 6,200 cases and 17,598 controls after replication. We identify nine risk loci at 1p36.11 (rs34676223, P=5.04 × 10−13), 1q42.13 (rs41271473, P=1.06 × 10−10), 4q24 (rs71597109, P=1.37 × 10−10), 4q35.1 (rs57214277, P=3.69 × 10−8), 6p21.31 (rs3800461, P=1.97 × 10−8), 11q23.2 (rs61904987, P=2.64 × 10−11), 18q21.1 (rs1036935, P=3.27 × 10−8), 19p13.3 (rs7254272, P=4.67 × 10−8) and 22q13.33 (rs140522, P=2.70 × 10−9). These new and established risk loci map to areas of active chromatin and show an over-representation of transcription factor binding for the key determinants of B-cell development and immune response.
|
|
| 15. |
|
|
| 16. |
|
|
| 17. |
|
|
| 18. |
- Pendall, E, et al.
(author)
-
Below-ground process responses to elevated CO2 and temperature: a discussion of observations, measurement methods, and models
- 2004
-
In: New Phytologist. - : Wiley. - 1469-8137 .- 0028-646X. ; 162:2, s. 311-322
-
Research review (peer-reviewed)abstract
- Rising atmospheric CO2 and temperatures are probably altering ecosystem carbon cycling, causing both positive and negative feedbacks to climate. Below-ground processes play a key role in the global carbon (C) cycle because they regulate storage of large quantities of C, and are potentially very sensitive to direct and indirect effects of elevated CO2 and temperature. Soil organic matter pools, roots and associated rhizosphere organisms all have distinct responses to environmental change drivers, although availability of C substrates will regulate all the responses. Elevated CO2 increases C supply below-ground, whereas warming is likely to increase respiration and decomposition rates, leading to speculation that these effects will moderate one another. However, indirect effects on soil moisture availability and nutrient supply may alter processes in unexpected directions. Detailed, mechanistic understanding and modelling of below-ground flux components, pool sizes and turnover rates is needed to adequately predict long-term, net C storage in ecosystems. In this synthesis, we discuss the current status of below-ground responses to elevated CO2 and temperature and potential feedback effects, methodological challenges, and approaches to integrating models and measurements.
|
|
| 19. |
|
|
| 20. |
|
|
| 21. |
|
|
| 22. |
- Thomas, M, et al.
(author)
-
Combining Asian-European Genome-Wide Association Studies of Colorectal Cancer Improves Risk Prediction Across Race and Ethnicity
- 2023
-
In: medRxiv : the preprint server for health sciences. - : Cold Spring Harbor Laboratory.
-
Journal article (other academic/artistic)abstract
- Polygenic risk scores (PRS) have great potential to guide precision colorectal cancer (CRC) prevention by identifying those at higher risk to undertake targeted screening. However, current PRS using European ancestry data have sub-optimal performance in non-European ancestry populations, limiting their utility among these populations. Towards addressing this deficiency, we expanded PRS development for CRC by incorporating Asian ancestry data (21,731 cases; 47,444 controls) into European ancestry training datasets (78,473 cases; 107,143 controls). The AUC estimates (95% CI) of PRS were 0.63(0.62-0.64), 0.59(0.57-0.61), 0.62(0.60-0.63), and 0.65(0.63-0.66) in independent datasets including 1,681-3,651 cases and 8,696-115,105 controls of Asian, Black/African American, Latinx/Hispanic, and non-Hispanic White, respectively. They were significantly better than the European-centric PRS in all four major US racial and ethnic groups (p-values<0.05). Further inclusion of non-European ancestry populations, especially Black/African American and Latinx/Hispanic, is needed to improve the risk prediction and enhance equity in applying PRS in clinical practice.
|
|
| 23. |
|
|
| 24. |
|
|
| 25. |
|
|
