| 1. |
- van Rheenen, Wouter, et al.
(author)
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Genome-wide association analyses identify new risk variants and the genetic architecture of amyotrophic lateral sclerosis
- 2016
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 48:9, s. 1043-1048
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Journal article (peer-reviewed)abstract
- To elucidate the genetic architecture of amyotrophic lateral sclerosis (ALS) and find associated loci, we assembled a custom imputation reference panel from whole-genome-sequenced patients with ALS and matched controls (n = 1,861). Through imputation and mixed-model association analysis in 12,577 cases and 23,475 controls, combined with 2,579 cases and 2,767 controls in an independent replication cohort, we fine-mapped a new risk locus on chromosome 21 and identified C21orf2 as a gene associated with ALS risk. In addition, we identified MOBP and SCFD1 as new associated risk loci. We established evidence of ALS being a complex genetic trait with a polygenic architecture. Furthermore, we estimated the SNP-based heritability at 8.5%, with a distinct and important role for low-frequency variants (frequency 1-10%). This study motivates the interrogation of larger samples with full genome coverage to identify rare causal variants that underpin ALS risk.
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| 2. |
- Hendriksen, Rene S., et al.
(author)
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Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage
- 2019
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1
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Journal article (peer-reviewed)abstract
- © 2019, The Author(s). Antimicrobial resistance (AMR) is a serious threat to global public health, but obtaining representative data on AMR for healthy human populations is difficult. Here, we use metagenomic analysis of untreated sewage to characterize the bacterial resistome from 79 sites in 60 countries. We find systematic differences in abundance and diversity of AMR genes between Europe/North-America/Oceania and Africa/Asia/South-America. Antimicrobial use data and bacterial taxonomy only explains a minor part of the AMR variation that we observe. We find no evidence for cross-selection between antimicrobial classes, or for effect of air travel between sites. However, AMR gene abundance strongly correlates with socio-economic, health and environmental factors, which we use to predict AMR gene abundances in all countries in the world. Our findings suggest that global AMR gene diversity and abundance vary by region, and that improving sanitation and health could potentially limit the global burden of AMR. We propose metagenomic analysis of sewage as an ethically acceptable and economically feasible approach for continuous global surveillance and prediction of AMR.
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| 3. |
- Skaftason, A., et al.
(author)
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Transcriptome sequencing of archived lymphoma specimens is feasible and clinically relevant using exome capture technology
- 2022
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In: Genes Chromosomes & Cancer. - : Wiley. - 1045-2257 .- 1098-2264. ; 61:1, s. 27-36
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Journal article (peer-reviewed)abstract
- Formalin-fixed, paraffin-embedded (FFPE) specimens are an underutilized resource in medical research, particularly in the setting of transcriptome sequencing, as RNA from these samples is often degraded. We took advantage of an exome capture-based RNA-sequencing protocol to explore global gene expression in paired fresh-frozen (FF) and FFPE samples from 16 diffuse large B-cell lymphoma (DLBCL) patients. While FFPE samples generated fewer mapped reads compared to their FF counterparts, these reads captured the same library complexity and had a similar number of genes expressed on average. Furthermore, gene expression demonstrated a high correlation when comparing housekeeping genes only or across the entire transcriptome (r = 0.99 for both comparisons). Differences in gene expression were primarily seen in lowly expressed genes and genes with small or large coding sequences. Using cell-of-origin classifiers and clinically relevant gene expression signatures for DLBCL, FF, and FFPE samples from the same biopsy paired nearly perfectly in clustering analysis. This was further confirmed in a validation cohort of 50 FFPE DLBCL samples. In summary, we found the biological differences between tumors to be far greater than artifacts created as a result of degraded RNA. We conclude that exome capture transcriptome sequencing data from archival samples can confidently be used for cell-of-origin classification of DLBCL samples.
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