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Träfflista för sökning "WFRF:(Zeggini E) srt2:(2020-2021)"

Search: WFRF:(Zeggini E) > (2020-2021)

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1.
  • Munn-Chernoff, M. A., et al. (author)
  • Shared genetic risk between eating disorder- and substance-use-related phenotypes: Evidence from genome-wide association studies
  • 2021
  • In: Addiction Biology. - : Wiley. - 1355-6215 .- 1369-1600. ; 26:1
  • Journal article (peer-reviewed)abstract
    • Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [r(g)], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from similar to 2400 to similar to 537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (r(g) = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (r(g) = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (r(g) = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (r(gs) = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors.
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2.
  • Bryois, J., et al. (author)
  • Genetic identification of cell types underlying brain complex traits yields insights into the etiology of Parkinson’s disease
  • 2020
  • In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 52:5, s. 482-493
  • Journal article (peer-reviewed)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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5.
  • Surendran, Praveen, et al. (author)
  • Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals
  • 2020
  • In: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 52:12, s. 1314-1332
  • Journal article (peer-reviewed)abstract
    • Genetic studies of blood pressure (BP) to date have mainly analyzed common variants (minor allele frequency > 0.05). In a meta-analysis of up to similar to 1.3 million participants, we discovered 106 new BP-associated genomic regions and 87 rare (minor allele frequency <= 0.01) variant BP associations (P < 5 x 10(-8)), of which 32 were in new BP-associated loci and 55 were independent BP-associated single-nucleotide variants within known BP-associated regions. Average effects of rare variants (44% coding) were similar to 8 times larger than common variant effects and indicate potential candidate causal genes at new and known loci (for example, GATA5 and PLCB3). BP-associated variants (including rare and common) were enriched in regions of active chromatin in fetal tissues, potentially linking fetal development with BP regulation in later life. Multivariable Mendelian randomization suggested possible inverse effects of elevated systolic and diastolic BP on large artery stroke. Our study demonstrates the utility of rare-variant analyses for identifying candidate genes and the results highlight potential therapeutic targets.
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  • Erzurumluoglu, A. Mesut, et al. (author)
  • Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci
  • 2020
  • In: Molecular Psychiatry. - : Nature Publishing Group. - 1359-4184 .- 1476-5578. ; 25:10, s. 2392-2409
  • Journal article (peer-reviewed)abstract
    • Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations with P < 5 × 10-8 in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P < 5 × 10-8) in the discovery samples. Ten novel SNVs, including rs12616219 near TMEM182, were followed-up and five of them (rs462779 in REV3L, rs12780116 in CNNM2, rs1190736 in GPR101, rs11539157 in PJA1, and rs12616219 near TMEM182) replicated at a Bonferroni significance threshold (P < 4.5 × 10-3) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, in CCDC141 and two low-frequency SNVs in CEP350 and HDGFRP2. Functional follow-up implied that decreased expression of REV3L may lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.
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8.
  • Png, G, et al. (author)
  • Mapping the serum proteome to neurological diseases using whole genome sequencing
  • 2021
  • In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 12:1, s. 7042-
  • Journal article (peer-reviewed)abstract
    • Despite the increasing global burden of neurological disorders, there is a lack of effective diagnostic and therapeutic biomarkers. Proteins are often dysregulated in disease and have a strong genetic component. Here, we carry out a protein quantitative trait locus analysis of 184 neurologically-relevant proteins, using whole genome sequencing data from two isolated population-based cohorts (N = 2893). In doing so, we elucidate the genetic landscape of the circulating proteome and its connection to neurological disorders. We detect 214 independently-associated variants for 107 proteins, the majority of which (76%) are cis-acting, including 114 variants that have not been previously identified. Using two-sample Mendelian randomisation, we identify causal associations between serum CD33 and Alzheimer’s disease, GPNMB and Parkinson’s disease, and MSR1 and schizophrenia, describing their clinical potential and highlighting drug repurposing opportunities.
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10.
  • Vogelezang, Suzanne, et al. (author)
  • Novel loci for childhood body mass index and shared heritability with adult cardiometabolic traits.
  • 2020
  • In: PLoS genetics. - : Public Library of Science (PLoS). - 1553-7404. ; 16:10
  • Journal article (peer-reviewed)abstract
    • The genetic background of childhood body mass index (BMI), and the extent to which the well-known associations of childhood BMI with adult diseases are explained by shared genetic factors, are largely unknown. We performed a genome-wide association study meta-analysis of BMI in 61,111 children aged between 2 and 10 years. Twenty-five independent loci reached genome-wide significance in the combined discovery and replication analyses. Two of these, located near NEDD4L and SLC45A3, have not previously been reported in relation to either childhood or adult BMI. Positive genetic correlations of childhood BMI with birth weight and adult BMI, waist-to-hip ratio, diastolic blood pressure and type 2 diabetes were detected (Rg ranging from 0.11 to 0.76, P-values <0.002). A negative genetic correlation of childhood BMI with age at menarche was observed. Our results suggest that the biological processes underlying childhood BMI largely, but not completely, overlap with those underlying adult BMI. The well-known observational associations of BMI in childhood with cardio-metabolic diseases in adulthood may reflect partial genetic overlap, but in light of previous evidence, it is also likely that they are explained through phenotypic continuity of BMI from childhood into adulthood.
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