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8 result(s) for "Kamali Zoha"
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Bivariate genome-wide association analyses of the broad depression phenotype combined with major depressive disorder, bipolar disorder or schizophrenia reveal eight novel genetic loci for depression
Although a genetic basis of depression has been well established in twin studies, identification of genome-wide significant loci has been difficult. We hypothesized that bivariate analyses of findings from a meta-analysis of genome-wide association studies (meta-GWASs) of the broad depression phenotype with those from meta-GWASs of self-reported and recurrent major depressive disorder (MDD), bipolar disorder and schizophrenia would enhance statistical power to identify novel genetic loci for depression. LD score regression analyses were first used to estimate the genetic correlations of broad depression with self-reported MDD, recurrent MDD, bipolar disorder and schizophrenia. Then, we performed four bivariate GWAS analyses. The genetic correlations (rg ± SE) of broad depression with self-reported MDD, recurrent MDD, bipolar disorder and schizophrenia were 0.79 ± 0.07, 0.24 ± 0.08, 0.53 ± 0.09 and 0.57 ± 0.05, respectively. From a total of 20 independent genome-wide significant loci, 13 loci replicated of which 8 were novel for depression. These were MUC21 for the broad depression phenotype with self-reported MDD and ZNF804A, MIR3143, PSORS1C2, STK19, SPATA31D1, RTN1 and TCF4 for the broad depression phenotype with schizophrenia. Post-GWAS functional analyses of these loci revealed their potential biological involvement in psychiatric disorders. Our results emphasize the genetic similarities among different psychiatric disorders and indicate that cross-disorder analyses may be the best way forward to accelerate gene finding for depression, or psychiatric disorders in general.
A genome-wide association meta-analysis implicates Hedgehog and Notch signaling in Dupuytren’s disease
Dupuytren’s disease (DD) is a highly heritable fibrotic disorder of the hand with incompletely understood etiology. A number of genetic loci, including Wnt signaling members, have been previously identified. Our overall aim was to identify novel genetic loci, to prioritize genes within the loci for functional studies, and to assess genetic correlation with associated disorders. We performed a meta-analysis of six DD genome-wide association studies from three European countries and extensive bioinformatic follow-up analyses. Leveraging 11,320 cases and 47,023 controls, we identified 85 genome-wide significant single nucleotide polymorphisms in 56 loci, of which 11 were novel, explaining 13.3–38.1% of disease variance. Gene prioritization implicated the Hedgehog and Notch signaling pathways. We also identified a significant genetic correlation with frozen shoulder. The pathways identified highlight the potential for new therapeutic targets and provide a basis for additional mechanistic studies for a common disorder that can severely impact hand function. In this meta-analysis of the fibrotic hand disorder Dupuytren’s disease, the authors identify genetic risk variants, study them for their functional consequences and implicate two signaling pathways involved in the disease mechanism of this debilitating disorder.
Transcriptomics- and Genomics-Guided Drug Repurposing for the Treatment of Vesicular Hand Eczema
Vesicular hand eczema (VHE), a clinical subtype of hand eczema (HE), showed limited responsiveness to alitretinoin, the only approved systemic treatment for severe chronic HE. This emphasizes the need for alternative treatment approaches. Therefore, our study aimed to identify drug repurposing opportunities for VHE using transcriptomics and genomics data. We constructed a gene network by combining 52 differentially expressed genes (DEGs) from a VHE transcriptomics study with 3 quantitative trait locus (QTL) genes associated with HE. Through network analysis, clustering, and functional enrichment analyses, we investigated the underlying biological mechanisms of this network. Next, we leveraged drug–gene interactions and retrieved pharmaco-transcriptomics data from the DrugBank database to identify drug repurposing opportunities for (V)HE. We developed a drug ranking system, primarily based on efficacy, safety, and practical and pricing factors, to select the most promising drug repurposing candidates. Our results revealed that the (V)HE network comprised 78 genes that yielded several biological pathways underlying the disease. The drug–gene interaction search together with pharmaco-transcriptomics lookups revealed 123 unique drug repurposing opportunities. Based on our drug ranking system, our study identified the most promising drug repurposing opportunities (e.g., vitamin D analogues, retinoids, and immunomodulating drugs) that might be effective in treating (V)HE.
Genetic Determinants of Serum Calcification Propensity and Cardiovascular Outcomes in the General Population
Serum calciprotein particle maturation time (T ), a measure of vascular calcification propensity, is associated with cardiovascular morbidity and mortality. We aimed to identify genetic loci associated with serum T and study their association with cardiovascular disease and mortality. We performed a genome-wide association study of serum T in 2,739 individuals of European descent participating in the Prevention of REnal and Vascular ENd-stage Disease (PREVEND) study, followed by a two-sample Mendelian randomization (MR) study to examine causal effects of T on cardiovascular outcomes. Finally, we examined associations between T loci and cardiovascular outcomes in 8,566 community-dwelling participants in the Rotterdam study. We identified three independent genome-wide significant single nucleotide polymorphism (SNPs) in the gene encoding fetuin-A: rs4917 ( = 1.72 × 10 ), rs2077119 ( = 3.34 × 10 ), and rs9870756 ( = 3.10 × 10 ), together explaining 18.3% of variation in serum T . MR did not demonstrate a causal effect of T on cardiovascular outcomes in the general population. Patient-level analyses revealed that the minor allele of rs9870756, which explained 9.1% of variation in T , was associated with a primary composite endpoint of all-cause mortality or cardiovascular disease [odds ratio (95% CI) 1.14 (1.01-1.28)] and all-cause mortality alone [1.14 (1.00-1.31)]. The other variants were not associated with clinical outcomes. In patients with type 2 diabetes or chronic kidney disease, the association between rs9870756 and the primary composite endpoint was stronger [OR 1.40 (1.06-1.84), relative excess risk due to interaction 0.54 (0.01-1.08)]. We identified three SNPs in the gene that explained 18.3% of variability in serum T levels. Only one SNP was associated with cardiovascular outcomes, particularly in individuals with type 2 diabetes or chronic kidney disease.
DNA methylation: a potential mediator between air pollution and metabolic syndrome
Given the global increase in air pollution and its crucial role in human health, as well as the steep rise in prevalence of metabolic syndrome (MetS), a better understanding of the underlying mechanisms by which environmental pollution may influence MetS is imperative. Exposure to air pollution is known to impact DNA methylation, which in turn may affect human health. This paper comprehensively reviews the evidence for the hypothesis that the effect of air pollution on the MetS is mediated by DNA methylation in blood. First, we present a summary of the impact of air pollution on metabolic dysregulation, including the components of MetS, i.e., disorders in blood glucose, lipid profile, blood pressure, and obesity. Then, we provide evidence on the relation between air pollution and endothelial dysfunction as one possible mechanism underlying the relation between air pollution and MetS. Subsequently, we review the evidence that air pollution (PM, ozone, NO 2 and PAHs) influences DNA methylation. Finally, we summarize association studies between DNA methylation and MetS. Integration of current evidence supports our hypothesis that methylation may partly mediate the effect of air pollution on MetS.
Large-Scale Multi-Omics Studies Provide New Insights into Blood Pressure Regulation
Recent genome-wide association studies uncovered part of blood pressure’s heritability. However, there is still a vast gap between genetics and biology that needs to be bridged. Here, we followed up blood pressure genome-wide summary statistics of over 750,000 individuals, leveraging comprehensive epigenomic and transcriptomic data from blood with a follow-up in cardiovascular tissues to prioritise likely causal genes and underlying blood pressure mechanisms. We first prioritised genes based on coding consequences, multilayer molecular associations, blood pressure-associated expression levels, and coregulation evidence. Next, we followed up the prioritised genes in multilayer studies of genomics, epigenomics, and transcriptomics, functional enrichment, and their potential suitability as drug targets. Our analyses yielded 1880 likely causal genes for blood pressure, tens of which are targets of the available licensed drugs. We identified 34 novel genes for blood pressure, supported by more than one source of biological evidence. Twenty-eight (82%) of these new genes were successfully replicated by transcriptome-wide association analyses in a large independent cohort (n = ~220,000). We also found a substantial mediating role for epigenetic regulation of the prioritised genes. Our results provide new insights into genetic regulation of blood pressure in terms of likely causal genes and involved biological pathways offering opportunities for future translation into clinical practice.
Bioinformatic Prioritization and Functional Annotation of GWAS-Based Candidate Genes for Primary Open-Angle Glaucoma
Background: Primary open-angle glaucoma (POAG) is the most prevalent glaucoma subtype, but its exact etiology is still unknown. In this study, we aimed to prioritize the most likely ‘causal’ genes and identify functional characteristics and underlying biological pathways of POAG candidate genes. Methods: We used the results of a large POAG genome-wide association analysis study from GERA and UK Biobank cohorts. First, we performed systematic gene-prioritization analyses based on: (i) nearest genes; (ii) nonsynonymous single-nucleotide polymorphisms; (iii) co-regulation analysis; (iv) transcriptome-wide association studies; and (v) epigenomic data. Next, we performed functional enrichment analyses to find overrepresented functional pathways and tissues. Results: We identified 142 prioritized genes, of which 64 were novel for POAG. BICC1, AFAP1, and ABCA1 were the most highly prioritized genes based on four or more lines of evidence. The most significant pathways were related to extracellular matrix turnover, transforming growth factor-β, blood vessel development, and retinoic acid receptor signaling. Ocular tissues such as sclera and trabecular meshwork showed enrichment in prioritized gene expression (>1.5 fold). We found pleiotropy of POAG with intraocular pressure and optic-disc parameters, as well as genetic correlation with hypertension and diabetes-related eye disease. Conclusions: Our findings contribute to a better understanding of the molecular mechanisms underlying glaucoma pathogenesis and have prioritized many novel candidate genes for functional follow-up studies.
Pathway-Based Mendelian Randomization for Pre-Infection IL-6 Levels Highlights Its Role in Coronavirus Disease
Objectives: Interleukin 6 (IL-6) levels at hospital admission have been suggested for disease prognosis, and IL-6 antagonists have been suggested for the treatment of patients with severe COVID-19. However, less is known about the relationship between pre-COVID-19 IL-6 levels and the risk of severe COVID-19. To fill in this gap, here we extensively investigated the association of genetically instrumented IL-6 pathway components with the risk of severe COVID-19. Methods: We used a two-sample Mendelian randomization study design and retrieved genetic instruments for blood biomarkers of IL-6 activation, including IL-6, soluble IL-6 receptor, IL-6 signal transducer, and CRP, from respective large available GWASs. To establish associations of these instruments with COVID-19 outcomes, we used data from the Host Genetics Initiative and GenOMICC studies. Results: Our analyses revealed inverse associations of genetically instrumented levels of IL-6 and its soluble receptor with the risk of developing severe disease (OR = 0.60 and 0.94, respectively). They also demonstrated a positive association of severe disease with the soluble signal transducer level (OR = 1.13). Only IL-6 associations with severe COVID-19 outcomes reached the significance threshold corrected for multiple testing (p < 0.003; with COVID-19 hospitalization and critical illness). Conclusions: These potential causal relationships for pre-COVID-19 IL-6 levels with the risk of developing severe symptoms provide opportunities for further evaluation of these factors as prognostic/preventive markers of severe COVID-19. Further studies will need to clarify whether the higher risk for a severe disease course with lower baseline IL-6 levels may also extend to other infectious diseases.