| 1. |
- Kattge, Jens, et al.
(author)
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TRY plant trait database - enhanced coverage and open access
- 2020
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In: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
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Journal article (peer-reviewed)abstract
- Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
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| 2. |
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| 3. |
- Lagou, Vasiliki, et al.
(author)
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Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability
- 2021
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In: Nature Communications. - : Nature Publishing Group. - 2041-1723. ; 12:1
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Journal article (peer-reviewed)abstract
- Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.
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| 5. |
- Nicoletti, Paola, et al.
(author)
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Genetic Risk Factors in Drug-Induced Liver Injury Due to Isoniazid-Containing Antituberculosis Drug Regimens
- 2021
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In: Clinical Pharmacology and Therapeutics. - : John Wiley & Sons. - 0009-9236 .- 1532-6535. ; 109:4, s. 1125-1135
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Journal article (peer-reviewed)abstract
- Drug-induced liver injury (DILI) is a complication of treatment with antituberculosis (TB) drugs, especially in isoniazid (INH)-containing regimens. To investigate genetic risk factors, we performed a genomewide association study (GWAS) involving anti-TB DILI cases (55 Indian and 70 European) and controls (1,199 Indian and 10,397 European). Most cases were treated with a standard anti-TB drug regimen; all received INH. We imputed single nucleotide polymorphism and HLA genotypes and performed trans-ethnic meta-analysis on GWAS and candidate gene genotypes. GWAS found one significant association (rs117491755) in Europeans only. For HLA, HLA-B*52:01 was significant (meta-analysis odds ratio (OR) 2.67, 95% confidence interval (CI) 1.63-4.37, P = 9.4 × 10-5 ). For N-acetyltransferase 2 (NAT2), NAT2*5 frequency was lower in cases (OR 0.69, 95% CI 0.57-0.83, P = 0.01). NAT2*6 and NAT2*7 were more common, with homozygotes for NAT2*6 and/or NAT2*7 enriched among cases (OR 1.89, 95% CI 0.84-4.22, P = 0.004). We conclude HLA genotype makes a small contribution to TB drug-related DILI and that the NAT2 contribution is complex, but consistent with previous reports when differences in the metabolic effect of NAT2*5 compared with those of NAT2*6 and NAT2*7 are considered.
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| 6. |
- Turro, Ernest, et al.
(author)
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Whole-genome sequencing of patients with rare diseases in a national health system.
- 2020
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In: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 583:7814, s. 96-102
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Journal article (peer-reviewed)abstract
- Most patients with rare diseases do not receive a molecular diagnosis and the aetiological variants and causative genes for more than half such disorders remain to be discovered1. Here we used whole-genome sequencing (WGS) in a national health system to streamline diagnosis and to discover unknown aetiological variants in the coding and non-coding regions of the genome. We generated WGS data for 13,037 participants, of whom 9,802 had a rare disease, and provided a genetic diagnosis to 1,138 of the 7,065extensively phenotypedparticipants. We identified 95 Mendelian associations between genes and rare diseases, of which 11 have been discovered since 2015 and at least 79 are confirmed to be aetiological. By generating WGS data ofUK Biobankparticipants2, we found that rare alleles can explain the presence of some individuals in the tails of a quantitative trait for red blood cells. Finally, we identified four novel non-coding variants that cause disease through the disruption of transcription of ARPC1B, GATA1, LRBA and MPL. Our study demonstrates a synergy by using WGS for diagnosis and aetiological discovery in routine healthcare.
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