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Although horizontal gene transfer is well documented in microbial genomes, no case has been reported in higher plants. We discovered horizontal transfer of the mitochondrial nad1 intron 2 and adjacent exons b and c from an asterid to Gnetum (Gnetales, gymnosperms). Gnetum has two copies of intron 2, a group II intron, that differ in their exons, nucleotide composition, domain lengths, and structural characteristics. One of the copies, limited to an Asian clade of Gnetum, is almost identical to the homologous locus in angiosperms, and partial sequences of its exons b and c show characteristic substitutions unique to angiosperms. Analyses of 70 seed plant nad1 exons b and c and intron 2 sequences, including representatives of all angiosperm clades, support that this copy originated from a euasterid and was horizontally transferred to Gnetum. Molecular clock dating, using calibrations provided by gnetalean macrofossils, suggests an age of 5 to 2 million years for the Asian clade that received the horizontal transfer.

Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease in industrialized countries and is increasing in prevalence. The pathomechanisms, however, are poorly understood. This study assessed the unexpected role of the Hedgehog pathway in adult liver lipid metabolism. Using transgenic mice with conditional hepatocyte-specific deletion of Smoothened in adult mice, we showed that hepatocellular inhibition of Hedgehog signaling leads to steatosis by altering the abundance of the transcription factors GLI1 and GLI3. This steatotic 'Gli-code' caused the modulation of a complex network of lipogenic transcription factors and enzymes, including SREBP1 and PNPLA3, as demonstrated by microarray analysis and siRNA experiments and could be confirmed in other steatotic mouse models as well as in steatotic human livers. Conversely, activation of the Hedgehog pathway reversed the \"Gli-code\" and mitigated hepatic steatosis. Collectively, our results reveal that dysfunctions in the Hedgehog pathway play an important role in hepatic steatosis and beyond. The liver is one of the main organs responsible for processing everything that mammals eat and drink. Nutrients absorbed by the gut like sugars and lipids (fats) are processed by the liver and are stored or distributed to provide energy to other organs. Sometimes these metabolic processes become unbalanced. This can lead to lipids accumulating in the liver – a process known as steatosis, which is a feature of human non-alcoholic fatty liver disease. In organs like the liver, cells are instructed how to behave via signaling pathways. A protein outside the cell signals to specific proteins inside, which switch on a set of target genes. One such pathway is the Hedgehog pathway, which primarily regulates tissue regeneration and the development of embryos. A component of this pathway is the Smoothened gene, which indirectly switches on proteins called GLI factors that regulate metabolic genes, including those involved in lipid metabolism. The Hedgehog pathway has been found to control the metabolism of lipids in fat tissue but it is not known whether it is important for lipid metabolism in the liver. Matz-Soja et al. investigated this possible role of the Hedgehog pathway in the liver using mice with a Smoothened gene that could be deleted specifically in that organ. This deletion disrupted Hedgehog signaling and led to lipids accumulating in the liver and eventually to steatosis. These changes were associated with an increase in the amounts and activityof several enzymes (and the proteins that regulate these enzymes) that help to synthesize lipids. Steatosis was also associated with low amounts of two of the three GLI factors; indeed, this seems to be key for triggering problems with lipid metabolism. Human livers with steatosis showed the same changes in levels of the GLI factors. Increasing the amount of GLI factors in liver cells taken from mice with steatosis reduced the accumulation of lipids and brought lipid metabolism back to its normal balance. A focus of future studies will be to understand how the Hedgehog signaling pathway interacts with other signaling pathways known to regulate liver lipid metabolism, such as insulin signaling. This knowledge will help clinicians to design new treatments for lipid-associated diseases like non-alcoholic fatty liver disease.

Background Although polygenic risk score (PRS) has emerged as a promising tool for predicting cancer risk from genome-wide association studies (GWAS), the individual-level accuracy of lung cancer PRS and the extent to which its impact on subsequent clinical applications remains largely unexplored. Methods Lung cancer PRSs and confidence/credible interval (CI) were constructed using two statistical approaches for each individual: (1) the weighted sum of 16 GWAS-derived significant SNP loci and the CI through the bootstrapping method (PRS-16-CV) and (2) LDpred2 and the CI through posteriors sampling (PRS-Bayes), among 17,166 lung cancer cases and 12,894 controls with European ancestry from the International Lung Cancer Consortium. Individuals were classified into different genetic risk subgroups based on the relationship between their own PRS mean/PRS CI and the population level threshold. Results Considerable variances in PRS point estimates at the individual level were observed for both methods, with an average standard deviation (s.d.) of 0.12 for PRS-16-CV and a much larger s.d. of 0.88 for PRS-Bayes. Using PRS-16-CV, only 25.0% of individuals with PRS point estimates in the lowest decile of PRS and 16.8% in the highest decile have their entire 95% CI fully contained in the lowest and highest decile, respectively, while PRS-Bayes was unable to find any eligible individuals. Only 19% of the individuals were concordantly identified as having high genetic risk (> 90th percentile) using the two PRS estimators. An increased relative risk of lung cancer comparing the highest PRS percentile to the lowest was observed when taking the CI into account (OR = 2.73, 95% CI: 2.12–3.50, P -value = 4.13 × 10 −15 ) compared to using PRS-16-CV mean (OR = 2.23, 95% CI: 1.99–2.49, P -value = 5.70 × 10 −46 ). Improved risk prediction performance with higher AUC was consistently observed in individuals identified by PRS-16-CV CI, and the best performance was achieved by incorporating age, gender, and detailed smoking pack-years (AUC: 0.73, 95% CI = 0.72–0.74). Conclusions Lung cancer PRS estimates using different methods have modest correlations at the individual level, highlighting the importance of considering individual-level uncertainty when evaluating the practical utility of PRS.

Background We investigated whether markers, genes or terms of the Human Phenotype Ontology associated with genetic or rare diseases (GARDs) that affect airway or lung function are associated with lung cancer. Methods Genes of interest were extracted from GARD (Genetic and Rare Diseases Information Center) , OMIM ( Online Mendelian Inheritance in Man®), ORPHANET and Monarch Initiative. Individual SNP, gene level and gene-set analyses were performed for 52,207 SNPs, 1677 genes or for 620 terms of the Human Phenotype Ontology . The analysis included 14,068 lung cancer cases and 12,390 cancer-free control subjects of European descent from the International Lung Cancer Consortium ILCCO. Results The marker rs56113850 (OR=0.893, 95%CI: 0.862-0.924) was associated with lung cancer ( p =1.2x10 -10 ). This marker is located in CYP2A6 as well as in an enhancer region of LTBP4 , which is associated with cutis laxa. A suggestive significant association was observed for two markers associated with the DMD gene, which is linked to Duchenne muscular dystrophy. The gene sets \"Abnormal circulating adrenocorticotropin concentration\" and \"Central nervous system neoplasm\" were found to be significantly enriched with GARD genes, and can therefore be considered to be associated with lung cancer. Conclusions Genes associated with genetic and rare lung diseases do not generally appear to carry risk factors for lung cancer. However, genes associated with the hypothalamic-pituitary-adrenal axis show some, but rather weak or complex, associations with lung cancer. Tests at the gene level provide extremely inhomogeneous results, even when applied to the same data.

Squamous cell carcinomas (SqCC) of the aerodigestive tract have similar etiological risk factors. Although genetic risk variants for individual cancers have been identified, an agnostic, genome-wide search for shared genetic susceptibility has not been performed. To identify novel and pleotropic SqCC risk variants, we performed a meta-analysis of GWAS data on lung SqCC (LuSqCC), oro/pharyngeal SqCC (OSqCC), laryngeal SqCC (LaSqCC) and esophageal SqCC (ESqCC) cancers, totaling 13,887 cases and 61,961 controls of European ancestry. We identified one novel genome-wide significant ( P meta <5x10 -8 ) aerodigestive SqCC susceptibility loci in the 2q33.1 region (rs56321285, TMEM273 ). Additionally, three previously unknown loci reached suggestive significance ( P meta <5x10 -7 ): 1q32.1 (rs12133735, near MDM4 ), 5q31.2 (rs13181561, TMEM173 ) and 19p13.11 (rs61494113, ABHD8) . Multiple previously identified loci for aerodigestive SqCC also showed evidence of pleiotropy in at least another SqCC site, these include: 4q23 ( ADH1B ), 6p21.33 ( STK19 ), 6p21.32 ( HLA-DQB1 ), 9p21.33 ( CDKN2B-AS1 ) and 13q13.1( BRCA2 ). Gene-based association and gene set enrichment identified a set of 48 SqCC-related genes rel to DNA damage and epigenetic regulation pathways. Our study highlights the importance of cross-cancer analyses to identify pleiotropic risk loci of histology-related cancers arising at distinct anatomical sites.

The basis for associations between lung cancer and major histocompatibility complex genes is not completely understood. Here the authors further consider genetic variation within the MHC region in lung cancer patients and identify independent associations within HLA genes that explain MHC lung cancer associations in Europeans and Asian populations. Lung cancer has several genetic associations identified within the major histocompatibility complex (MHC); although the basis for these associations remains elusive. Here, we analyze MHC genetic variation among 26,044 lung cancer patients and 20,836 controls densely genotyped across the MHC, using the Illumina Illumina OncoArray or Illumina 660W SNP microarray. We impute sequence variation in classical HLA genes, fine-map MHC associations for lung cancer risk with major histologies and compare results between ethnicities. Independent and novel associations within HLA genes are identified in Europeans including amino acids in the HLA-B*0801 peptide binding groove and an independent HLA-DQB1*06 loci group. In Asians, associations are driven by two independent HLA allele sets that both increase risk in HLA-DQB1*0401 and HLA-DRB1*0701 ; the latter better represented by the amino acid Ala-104. These results implicate several HLA–tumor peptide interactions as the major MHC factor modulating lung cancer susceptibility.

Background Imputation of untyped markers is a standard tool in genome-wide association studies to close the gap between directly genotyped and other known DNA variants. However, high accuracy with which genotypes are imputed is fundamental. Several accuracy measures have been proposed and some are implemented in imputation software, unfortunately diversely across platforms. In the present paper, we introduce Iam   hiQ , an independent pair of accuracy measures that can be applied to dosage files, the output of all imputation software. Iam ( imputation accuracy measure ) quantifies the average amount of individual-specific versus population-specific genotype information in a linear manner. hiQ (heterogeneity in quantities of dosages) addresses the inter-individual heterogeneity between dosages of a marker across the sample at hand. Results Applying both measures to a large case–control sample of the International Lung Cancer Consortium (ILCCO), comprising 27,065 individuals, we found meaningful thresholds for Iam and hiQ suitable to classify markers of poor accuracy. We demonstrate how Manhattan-like plots and moving averages of Iam and hiQ can be useful to identify regions enriched with less accurate imputed markers, whereas these regions would by missed when applying the accuracy measure info (implemented in IMPUTE2). Conclusion We recommend using Iam hiQ additional to other accuracy scores for variant filtering before stepping into the analysis of imputed GWAS data.

Abstract Background Imputation of untyped markers is a standard tool in genome-wide association studies to close the gap between directly genotyped and other known DNA variants. However, high accuracy with which genotypes are imputed is fundamental. Several accuracy measures have been proposed and some are implemented in imputation software, unfortunately diversely across platforms. In the present paper, we introduce Iam hiQ, an independent pair of accuracy measures that can be applied to dosage files, the output of all imputation software. Iam (imputation accuracy measure) quantifies the average amount of individual-specific versus population-specific genotype information in a linear manner. hiQ (heterogeneity in quantities of dosages) addresses the inter-individual heterogeneity between dosages of a marker across the sample at hand. Results Applying both measures to a large case–control sample of the International Lung Cancer Consortium (ILCCO), comprising 27,065 individuals, we found meaningful thresholds for Iam and hiQ suitable to classify markers of poor accuracy. We demonstrate how Manhattan-like plots and moving averages of Iam and hiQ can be useful to identify regions enriched with less accurate imputed markers, whereas these regions would by missed when applying the accuracy measure info (implemented in IMPUTE2). Conclusion We recommend using Iam hiQ additional to other accuracy scores for variant filtering before stepping into the analysis of imputed GWAS data.

Primary hepatocyte cell cultures are widely used for studying hepatic diseases with alterations in hepatic glucose and lipid metabolism, such as diabetes and non-alcoholic fatty liver disease. Therefore, small interfering RNAs (siRNAs) provide a potent and specific tool to elucidate the signaling pathways and gene functions involved in these pathologies. Although RNA interference (RNAi) in vitro is frequently used in these investigations, the metabolic alterations elucidated by different siRNA delivery strategies have hardly been investigated in transfected hepatocytes. To elucidate the influence of the most commonly used lipid-based transfection reagents on cultured primary hepatocytes, we studied the cytotoxic effects and transfection efficiencies of INTERFERin ® , Lipofectamine ® RNAiMAX, and HiPerFect ® . All of these transfection agents displayed low cytotoxicity (5.6–9.0 ± 1.3–3.4 %), normal cell viability, and high transfection efficiency (fold change 0.08–0.13 ± 0.03–0.05), and they also favored the satisfactory down-regulation of target gene expression. However, when effects on the metabolome and lipidome were studied, considerable differences were observed among the transfection reagents. Cellular triacylglycerides levels were either up- or down-regulated [maximum fold change: INTERFERin ® (48 h) 2.55 ± 0.34, HiPerFect ® (24 h) 0.79 ± 0.08, Lipofectamine ® RNAiMAX (48 h) 1.48 ± 0.21], and mRNA levels of genes associated with lipid metabolism were differentially affected. Likewise, metabolic functions such as amino acid utilization from were perturbed (alanine, arginine, glycine, ornithine, and pyruvate). In conclusion, these findings demonstrate that the choice of non-viral siRNA delivery agent is critical in hepatocytes. This should be remembered, especially if RNA silencing is used for studying hepatic lipid homeostasis and its regulation.