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- Bryois, J., et al.
(författare)
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Genetic identification of cell types underlying brain complex traits yields insights into the etiology of Parkinson’s disease
- 2020
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 52:5, s. 482-493
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies have discovered hundreds of loci associated with complex brain disorders, but it remains unclear in which cell types these loci are active. Here we integrate genome-wide association study results with single-cell transcriptomic data from the entire mouse nervous system to systematically identify cell types underlying brain complex traits. We show that psychiatric disorders are predominantly associated with projecting excitatory and inhibitory neurons. Neurological diseases were associated with different cell types, which is consistent with other lines of evidence. Notably, Parkinson’s disease was genetically associated not only with cholinergic and monoaminergic neurons (which include dopaminergic neurons) but also with enteric neurons and oligodendrocytes. Using post-mortem brain transcriptomic data, we confirmed alterations in these cells, even at the earliest stages of disease progression. Our study provides an important framework for understanding the cellular basis of complex brain maladies, and reveals an unexpected role of oligodendrocytes in Parkinson’s disease. © 2020, The Author(s), under exclusive licence to Springer Nature America, Inc.
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- Kattge, Jens, et al.
(författare)
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TRY plant trait database - enhanced coverage and open access
- 2020
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Ingår i: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
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Tidskriftsartikel (refereegranskat)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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- Johnson, J. S., et al.
(författare)
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Mapping anorexia nervosa genes to clinical phenotypes
- 2023
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Ingår i: Psychological Medicine. - : Cambridge University Press (CUP). - 0033-2917 .- 1469-8978. ; 53:6, s. 2619-2633
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Tidskriftsartikel (refereegranskat)abstract
- Background Anorexia nervosa (AN) is a psychiatric disorder with complex etiology, with a significant portion of disease risk imparted by genetics. Traditional genome-wide association studies (GWAS) produce principal evidence for the association of genetic variants with disease. Transcriptomic imputation (TI) allows for the translation of those variants into regulatory mechanisms, which can then be used to assess the functional outcome of genetically regulated gene expression (GReX) in a broader setting through the use of phenome-wide association studies (pheWASs) in large and diverse clinical biobank populations with electronic health record phenotypes. Methods Here, we applied TI using S-PrediXcan to translate the most recent PGC-ED AN GWAS findings into AN-GReX. For significant genes, we imputed AN-GReX in the Mount Sinai BioMe (TM) Biobank and performed pheWASs on over 2000 outcomes to test the clinical consequences of aberrant expression of these genes. We performed a secondary analysis to assess the impact of body mass index (BMI) and sex on AN-GReX clinical associations. Results Our S-PrediXcan analysis identified 53 genes associated with AN, including what is, to our knowledge, the first-genetic association of AN with the major histocompatibility complex. AN-GReX was associated with autoimmune, metabolic, and gastrointestinal diagnoses in our biobank cohort, as well as measures of cholesterol, medications, substance use, and pain. Additionally, our analyses showed moderation of AN-GReX associations with measures of cholesterol and substance use by BMI, and moderation of AN-GReX associations with celiac disease by sex. Conclusions Our BMI-stratified results provide potential avenues of functional mechanism for AN-genes to investigate further.
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| 8. |
- Xu, J., et al.
(författare)
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Exploring the clinical and genetic associations of adult weight trajectories using electronic health records in a racially diverse biobank: a phenome-wide and polygenic risk study
- 2022
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Ingår i: The Lancet Digital Health. - 2589-7500. ; 4:8
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Tidskriftsartikel (refereegranskat)abstract
- Background: Weight trajectories might reflect individual health status. In this study, we aimed to examine the clinical and genetic associations of adult weight trajectories using electronic health records (EHRs) in the BioMe Biobank. Methods: We constructed four weight trajectories based on a-priori definitions of weight changes (5% or 10%) using annual weight in EHRs (stable weight, weight gain, weight loss, and weight cycle); the final weight dataset included 21 487 participants with 162 783 annual weight measures. To confirm accurate assignment of weight trajectories, we manually reviewed weight trajectory plots for 100 random individuals. We then did a hypothesis-free phenome-wide association study (PheWAS) to identify diseases associated with each weight trajectory. Next, we estimated the single-nucleotide polymorphism-based heritability (hSNP2) of weight trajectories using GCTA-GREML, and we did a hypothesis-driven analysis of anorexia nervosa and depression polygenic risk scores (PRS) on these weight trajectories, given both diseases are associated with weight changes. We extended our analyses to the UK Biobank to replicate findings from a patient population to a generally healthy population. Findings: We found high concordance between manually assigned weight trajectories and those assigned by the algorithm (accuracy ≥98%). Stable weight was consistently associated with lower disease risks among those passing Bonferroni-corrected p value in our PheWAS (p≤4·4 × 10–5). Additionally, we identified an association between depression and weight cycle (odds ratio [OR] 1·42, 95% CI 1·31–1·55, p≤7·7 × 10–16). The adult weight trajectories were heritable (using 5% weight change as the cutoff: hSNP2 of 2·1%, 95% CI 0·9–3·3, for stable weight; 4·1%, 1·4–6·8, for weight gain; 5·5%, 2·8–8·2, for weight loss; and 4·7%, 2·3–7·1%, for weight cycle). Anorexia nervosa PRS was positively associated with weight loss trajectory among individuals without eating disorder diagnoses (OR1SD 1·16, 95% CI 1·07–1·26, per 1 SD higher PRS, p=0·011), and the association was not attenuated by obesity PRS. No association was found between depression PRS and weight trajectories after permutation tests. All main findings were replicated in the UK Biobank (p<0·05). Interpretation: Our findings suggest the importance of considering weight from a longitudinal aspect for its association with health and highlight a crucial role of weight management during disease development and progression. Funding: Klarman Family Foundation, US National Institute of Mental Health (NIMH). © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license
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- Bower, G. C., et al.
(författare)
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THE ALLEN TELESCOPE ARRAY Pi GHz SKY SURVEY. I. SURVEY DESCRIPTION AND STATIC CATALOG RESULTS FOR THE BOOTES FIELD
- 2010
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Ingår i: Astrophysical Journal. - : American Astronomical Society. - 1538-4357 .- 0004-637X. ; 725:2, s. 1792-1804
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Tidskriftsartikel (refereegranskat)abstract
- The Pi GHz Sky Survey (PiGSS) is a key project of the Allen Telescope Array. PiGSS is a 3.1 GHz survey of radio continuum emission in the extragalactic sky with an emphasis on synoptic observations that measure the static and time-variable properties of the sky. During the 2.5 year campaign, PiGSS will twice observe similar to 250,000 radio sources in the 10,000 deg(2) region of the sky with b > 30 degrees to an rms sensitivity of similar to 1 mJy. Additionally, sub-regions of the sky will be observed multiple times to characterize variability on timescales of days to years. We present here observations of a 10 deg(2) region in the Bootes constellation overlapping the NOAO Deep Wide Field Survey field. The PiGSS image was constructed from 75 daily observations distributed over a 4 month period and has an rms flux density between 200 and 250 mu Jy. This represents a deeper image by a factor of 4-8 than we will achieve over the entire 10,000 deg(2). We provide flux densities, source sizes, and spectral indices for the 425 sources detected in the image. We identify similar to 100 new flat-spectrum radio sources; we project that when completed PiGSS will identify 10(4) flat-spectrum sources. We identify one source that is a possible transient radio source. This survey provides new limits on faint radio transients and variables with characteristic durations of months.
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- Bulik, CM, et al.
(författare)
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The Eating Disorders Genetics Initiative (EDGI): study protocol
- 2021
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Ingår i: BMC psychiatry. - : Springer Science and Business Media LLC. - 1471-244X. ; 21:1, s. 234-
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundThe Eating Disorders Genetics Initiative (EDGI) is an international investigation exploring the role of genes and environment in anorexia nervosa, bulimia nervosa, and binge-eating disorder.MethodsA total of 14,500 individuals with eating disorders and 1500 controls will be included from the United States (US), Australia (AU), New Zealand (NZ), and Denmark (DK). In the US, AU, and NZ, participants will complete comprehensive online phenotyping and will submit a saliva sample for genotyping. In DK, individuals with eating disorders will be identified by the National Patient Register, and genotyping will occur using bloodspots archived from birth. A genome-wide association study will be conducted within EDGI and via meta-analysis with other data from the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED).DiscussionEDGI represents the largest genetic study of eating disorders ever to be conducted and is designed to rapidly advance the study of the genetics of the three major eating disorders (anorexia nervosa, bulimia nervosa, and binge-eating disorder). We will explicate the genetic architecture of eating disorders relative to each other and to other psychiatric and metabolic disorders and traits. Our goal is for EDGI to deliver “actionable” findings that can be transformed into clinically meaningful insights.Trial registrationEDGI is a registered clinical trial: clinicaltrials.govNCT04378101.
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