Variation in gene expression is an important mechanism underlying susceptibility to complex disease. The simultaneous genome-wide assay of gene expression and genetic variation allows the mapping of ...the genetic factors that underpin individual differences in quantitative levels of expression (expression QTLs; eQTLs). The availability of systematically generated eQTL information could provide immediate insight into a biological basis for disease associations identified through genome-wide association (GWA) studies, and can help to identify networks of genes involved in disease pathogenesis. Although there are limitations to current eQTL maps, understanding of disease will be enhanced with novel technologies and international efforts that extend to a wide range of new samples and tissues.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Clinical and epidemiological data suggest that asthma and allergic diseases are associated and may share a common genetic etiology. We analyzed genome-wide SNP data for asthma and allergic diseases ...in 33,593 cases and 76,768 controls of European ancestry from UK Biobank. Two publicly available independent genome-wide association studies were used for replication. We have found a strong genome-wide genetic correlation between asthma and allergic diseases (r
= 0.75, P = 6.84 × 10
). Cross-trait analysis identified 38 genome-wide significant loci, including 7 novel shared loci. Computational analysis showed that shared genetic loci are enriched in immune/inflammatory systems and tissues with epithelium cells. Our work identifies common genetic architectures shared between asthma and allergy and will help to advance understanding of the molecular mechanisms underlying co-morbid asthma and allergic diseases.
The famous Chinese scientist Professor Zeyuan Liu passed away on February 8, 2020, aged 80. He was a productive and influential scientist, both in quantitative and in qualitative studies. To cherish ...the memory of Professor Liu and in praise of his scientific thoughts and scientific spirit, we explored his academic career rhythm based on our rhythm indicator of science. The rhythm indicator is created based on a publication-citation matrix, eliminating the impact of length of citation windows, making citations comparable for different years. In Liu’s rhythm study the publication indicator and citation indicator are combined. Data were retrieved from China National Knowledge Infrastructure and WoS. The most important finding is that Liu’s academic career rhythm is totally different from that of two famous western scientists T. Braun and R. Rousseau. Because of the delayed scientific research by China’s Cultural Revolution, it was only in 1979 that Liu published his first scientific paper and launched his academic career. In the first 20 years he published 41 papers, mostly single-authored. Their research topics were scattered and mainly used qualitative methods. In 1999 Liu changed his research paradigm from qualitative to quantitative studies, focusing on scientometrics, citation analysis and knowledge mapping. New topics, new methods and multi-authored collaboration greatly increased his productivity (293 articles) and influence. The above exploration is based on both whole counting of publications/citations and fractional counting. Three problems, including the normalization of the
p
–
c
matrix, are discussed. The rhythm indicator of science is a contribution to the evaluation methodology for scientist-level and journal-level scientific impact.
Clinical and epidemiologic studies have shown that obesity is associated with asthma and that these associations differ by asthma subtype. Little is known about the shared genetic components between ...obesity and asthma.
We sought to identify shared genetic associations between obesity-related traits and asthma subtypes in adults.
A cross-trait genome-wide association study (GWAS) was performed using 457,822 subjects of European ancestry from the UK Biobank. Experimental evidence to support the role of genes significantly associated with both obesity-related traits and asthma through a GWAS was sought by using results from obese versus lean mouse RNA sequencing and RT-PCR experiments.
We found a substantial positive genetic correlation between body mass index and later-onset asthma defined by asthma age of onset at 16 years or greater (Rg = 0.25, P = 9.56 × 10−22). Mendelian randomization analysis provided strong evidence in support of body mass index causally increasing asthma risk. Cross-trait meta-analysis identified 34 shared loci among 3 obesity-related traits and 2 asthma subtypes. GWAS functional analyses identified potential causal relationships between the shared loci and Genotype-Tissue Expression (GTEx) quantitative trait loci and shared immune- and cell differentiation–related pathways between obesity and asthma. Finally, RNA sequencing data from lungs of obese versus control mice found that 2 genes (acyl-coenzyme A oxidase-like ACOXL and myosin light chain 6 MYL6) from the cross-trait meta-analysis were differentially expressed, and these findings were validated by using RT-PCR in an independent set of mice.
Our work identified shared genetic components between obesity-related traits and specific asthma subtypes, reinforcing the hypothesis that obesity causally increases the risk of asthma and identifying molecular pathways that might underlie both obesity and asthma.
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We introduce cross-trait penalized regression (CTPR), a powerful and practical approach for multi-trait polygenic risk prediction in large cohorts. Specifically, we propose a novel cross-trait ...penalty function with the Lasso and the minimax concave penalty (MCP) to incorporate the shared genetic effects across multiple traits for large-sample GWAS data. Our approach extracts information from the secondary traits that is beneficial for predicting the primary trait based on individual-level genotypes and/or summary statistics. Our novel implementation of a parallel computing algorithm makes it feasible to apply our method to biobank-scale GWAS data. We illustrate our method using large-scale GWAS data (~1M SNPs) from the UK Biobank (N = 456,837). We show that our multi-trait method outperforms the recently proposed multi-trait analysis of GWAS (MTAG) for predictive performance. The prediction accuracy for height by the aid of BMI improves from R
= 35.8% (MTAG) to 42.5% (MCP + CTPR) or 42.8% (Lasso + CTPR) with UK Biobank data.
Animal studies suggest vital roles of sphingolipids, especially ceramides, in the pathogenesis of type 2 diabetes (T2D) via pathways involved in insulin resistance, β-cell dysfunction, and ...inflammation, but human studies are limited. We aimed to evaluate the associations of circulating sphingolipids with incident T2D and to explore underlying mechanisms.
The current study included 826 men and 1,148 women who were aged 50-70 years, from Beijing and Shanghai, and without T2D in 2005 and who were resurveyed in 2011. Cardiometabolic traits were measured at baseline and follow-up surveys. A total of 76 sphingolipids were quantified using high-coverage targeted lipidomics. Summary data for 2-sample Mendelian randomization were obtained from genome-wide association studies of circulating sphingolipids and the China Health and Nutrition Survey (n = 5,731). During the 6-year period, 529 participants developed T2D. Eleven novel and 3 reported sphingolipids, namely ceramides (d18:1/18:1, d18:1/20:0, d18:1/20:1, d18:1/22:1), saturated sphingomyelins (C34:0, C36:0, C38:0, C40:0), unsaturated sphingomyelins (C34:1, C36:1, C42:3), hydroxyl-sphingomyelins (C34:1, C38:3), and a hexosylceramide (d18:1/20:1), were positively associated with incident T2D (relative risks RRs: 1.14-1.21; all P < 0.001), after multivariate adjustment including lifestyle characteristics and BMI. Network analysis further identified 5 modules, and 2 modules containing saturated sphingomyelins showed the strongest associations with increased T2D risk (RRQ4 versus Q1 = 1.59 and 1.43; both Ptrend < 0.001). Mediation analysis suggested that the detrimental associations of 13 sphingolipids with T2D were largely mediated through β-cell dysfunction, as indicated by HOMA-B (mediation proportion: 11.19%-42.42%; all P < 0.001). Moreover, Mendelian randomization evidenced a positive association between a genetically instrumented ceramide (d18:1/20:1) and T2D (odds ratio: 1.15 95% CI 1.05-1.26; P = 0.002). Main limitations in the current study included potential undiagnosed cases and lack of an independent population for replication.
In this study, we observed that a panel of novel sphingolipids with unique structures were positively associated with incident T2D, largely mediated through β-cell dysfunction, in Chinese individuals.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Autogenous arteriovenous fistula (AVF) is the preferred dialysis access for receiving hemodialysis treatment in end-stage renal disease patients. After AVF is established, vascular remodeling occurs ...in order to adapt to hemodynamic changes. Uremia toxins, surgical injury, blood flow changes and other factors can induce inflammatory response, immune microenvironment changes, and play an important role in the maintenance of AVF vascular remodeling. This process involves the infiltration of pro-inflammatory and anti-inflammatory immune cells and the secretion of cytokines. Pro-inflammatory and anti-inflammatory immune cells include neutrophil (NEUT), dendritic cell (DC), T lymphocyte, macrophage (Mφ), etc. This article reviews the latest research progress and focuses on the role of immune microenvironment changes in vascular remodeling of AVF, in order to provide a new theoretical basis for the prevention and treatment of AVF failure.
Acylcarnitines were suggested as early biomarkers even prior to insulin resistance in animal studies, but their roles in predicting type 2 diabetes were unknown. Therefore, we aimed to determine ...whether acylcarnitines could independently predict type 2 diabetes by using a targeted metabolic profiling approach.
A population-based prospective study was conducted among 2,103 community-living Chinese individuals aged 50-70 years from Beijing and Shanghai with a mean follow-up duration of 6 years. Fasting glucose, glycohemoglobin, and insulin were determined at baseline and in a follow-up survey. Baseline plasma acylcarnitines were profiled by liquid chromatography-tandem mass spectrometry.
Over the 6-year period, 507 participants developed diabetes. A panel of acylcanitines, especially with long chain, was significantly associated with increased risk of type 2 diabetes. The relative risks of type 2 diabetes per SD increase of the predictive model score were 2.48 (95% CI 2.20-2.78) for the conventional and 9.41 (95% CI 7.62-11.62) for the full model including acylcarnitines, respectively. Moreover, adding selected acylcarnitines substantially improved predictive ability for incident diabetes, as area under the receiver operator characteristic curve improved to 0.89 in the full model compared with 0.73 in the conventional model. Similar associations were obtained when the predictive models were established separately among Beijing or Shanghai residents.
A panel of acylcarnitines, mainly involving mitochondrial lipid dysregulation, significantly improved predictive ability for type 2 diabetes beyond conventional risk factors. These findings need to be replicated in other populations, and the underlying mechanisms should be elucidated.
Identifying methylation quantitative trait loci (meQTLs) and integrating them with disease-associated variants from genome-wide association studies (GWAS) may illuminate functional mechanisms ...underlying genetic variant-disease associations. Here, we perform GWAS of >415 thousand CpG methylation sites in whole blood from 4170 individuals and map 4.7 million cis- and 630 thousand trans-meQTL variants targeting >120 thousand CpGs. Independent replication is performed in 1347 participants from two studies. By linking cis-meQTL variants with GWAS results for cardiovascular disease (CVD) traits, we identify 92 putatively causal CpGs for CVD traits by Mendelian randomization analysis. Further integrating gene expression data reveals evidence of cis CpG-transcript pairs causally linked to CVD. In addition, we identify 22 trans-meQTL hotspots each targeting more than 30 CpGs and find that trans-meQTL hotspots appear to act in cis on expression of nearby transcriptional regulatory genes. Our findings provide a powerful meQTL resource and shed light on DNA methylation involvement in human diseases.
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