The trnH-psbA intergenic spacer region has been used in many DNA barcoding studies. However, a comprehensive evaluation with rigorous sequence preprocessing and statistical testing on the utility of ...trnH-psbA and its combinations as DNA barcodes is lacking.
Sequences were searched from GenBank for a meta-analysis on the usefulness of trnH-psbA and its combinations as DNA barcodes. After preprocessing, we constructed full and matching data sets that contained 17 983 trnH-psbA sequences and 2190 sets of trnH-psbA, matK, rbcL, and ITS2 sequences from the same sample, repectively. These datasets were used to analyze the ability of trnH-psbA and its combinations to discriminate species by the BLAST and BLAST+P methods. The Fisher's exact test was used to evaluate the significance of performance differences. For the full data set, the identification success rates of trnH-psbA exceeded 70% in 18 families and 12 genera, respectively. For the matching data set, the identification rates of trnH-psbA were significantly higher than those of the other loci in two families and four genera. Similarly, the identification rates of trnH-psbA+ITS2 were significantly higher than those of matK+rbcL in 18 families and 21 genera. CONCLUSION/SIGNIFICANE: This study provides valuable information on the higher utility of trnH-psbA and its combinations. We found that trnH-psbA+ITS2 combination performs better or equally well compared with other combinations in most taxonomic groups investigated. This information will guide the optimal usage of trnH-psbA and its combinations for species identification.
Current genome-wide association studies (GWAS) use commercial genotyping microarrays that can assay over a million single nucleotide polymorphisms (SNPs). The number of SNPs is further boosted by ...advanced statistical genotype-imputation algorithms and large SNP databases for reference human populations. The testing of a huge number of SNPs needs to be taken into account in the interpretation of statistical significance in such genome-wide studies, but this is complicated by the non-independence of SNPs because of linkage disequilibrium (LD). Several previous groups have proposed the use of the effective number of independent markers (
M
e
) for the adjustment of multiple testing, but current methods of calculation for
M
e
are limited in accuracy or computational speed. Here, we report a more robust and fast method to calculate
M
e
. Applying this efficient method implemented in a free software tool named Genetic type 1 error calculator (GEC), we systematically examined the
M
e
, and the corresponding
p
-value thresholds required to control the genome-wide type 1 error rate at 0.05, for 13 Illumina or Affymetrix genotyping arrays, as well as for HapMap Project and 1000 Genomes Project datasets which are widely used in genotype imputation as reference panels. Our results suggested the use of a
p
-value threshold of ~10
−7
as the criterion for genome-wide significance for early commercial genotyping arrays, but slightly more stringent
p
-value thresholds ~5 × 10
−8
for current or merged commercial genotyping arrays, ~10
−8
for all common SNPs in the 1000 Genomes Project dataset and ~5 × 10
−8
for the common SNPs only within genes.
Abstract Objective Changes in the prevalence, treatment, and management of diabetes in the United States from 1999 to 2006 were studied using data from the National Health and Nutrition Examination ...Survey. Methods Data on 17,306 participants aged 20 years or more were analyzed. Glycemic, blood pressure, and cholesterol targets were glycosylated hemoglobin less than 7.0%, blood pressure less than 130/80 mm Hg, and low-density lipoprotein (LDL) cholesterol less than 100 mg/dL, respectively. Results The prevalence of diagnosed diabetes was 6.5% from 1999 to 2002 and 7.8% from 2003 to 2006 ( P < .05) and increased significantly in women, non-Hispanic whites, and obese people. Although there were no significant changes in the pattern of antidiabetic treatment, the age-adjusted percentage of people with diagnosed diabetes achieving glycemic and LDL targets increased from 43.1% to 57.1% ( P < .05) and from 36.1% to 46.5% ( P < .05), respectively. Glycosylated hemoglobin decreased from 7.62% to 7.15% during this period ( P < .05). The age-adjusted percentage achieving all 3 targets increased insignificantly from 7.0% to 12.2%. Conclusions The prevalence of diagnosed diabetes increased significantly from 1999 to 2006. The proportion of people with diagnosed diabetes achieving glycemic and LDL targets also increased. However, there is a need to achieve glycemic, blood pressure, and LDL targets simultaneously.
The association between rheumatoid arthritis (RA) and blood lipid levels has often been described as paradoxical, despite the strong association between RA and cardiovascular disease (CVD) risk. We ...aimed to clarify the genetic architecture that would explain the relationship between RA and blood-lipid levels, while considering inflammation as measured by C-reactive protein (CRP).
Genome-wide association study (GWAS) summary statistics were collected from the CHARGE Consortium and Global Lipids Genetics Consortium. Blood-lipid levels includes HDL-C, LDL-C, triglycerides (TG), and total cholesterol (TC). Causality was examined by assessing Mendelian Randomization (MR) analysis. Pleiotropy, the identification of shared causal variants between traits, was assessed by conducting colocalization analyses.
Using the MR Egger method, RA did not appear to causally predict alterations in lipid factors, rather the MR Egger intercept revealed that the genetic relationship between RA and HDL-C, LDL-C and TC may be explained by horizontal pleiotropy (p=0.003, 0.006, and 0.018, respectively). MR was suggestive of a horizontally pleiotropic relationship between CRP and lipid factors, while a causal relationship could not be ruled out. Recurring genes arising from shared causal genetic variants between RA and varying lipid factors included NAT2/PSD3, FADS2/FADS1, SH2B3, and YDJC.
Horizontal pleiotropy appears to explain the genetic relationship between RA and blood-lipid levels. In addition, blood-lipid levels appear to suggest a horizontally pleiotropic relationship to CRP, if not mediated through RA as well. Consideration of the pleiotropic genes between RA and blood lipid levels may aid in enhancing diagnostic means to predict CVD.
Display omitted
•Lipid factors in rheumatoid arthritis patients are characterized as paradoxical.•CVD is a major comorbidity of RA, and lipid factors may predict CVD.•Several pleiotropic genes appeared between RA and the examined lipid factors.•Pleiotropic genes include NAT2/PSD3, FADS2/FADS1, SH2B3, and YDJC.•These genes may aid in predicting CVD prognosis and atherosclerosis in RA.
Efforts to find disease genes using high-density single-nucleotide polymorphism (SNP) maps will produce data sets that exceed the limitations of current computational tools. Here we describe a new, ...efficient method for the analysis of dense genetic maps in pedigree data that provides extremely fast solutions to common problems such as allele-sharing analyses and haplotyping. We show that sparse binary trees represent patterns of gene flow in general pedigrees in a parsimonious manner, and derive a family of related algorithms for pedigree traversal. With these trees, exact likelihood calculations can be carried out efficiently for single markers or for multiple linked markers. Using an approximate multipoint calculation that ignores the unlikely possibility of a large number of recombinants further improves speed and provides accurate solutions in dense maps with thousands of markers. Our multipoint engine for rapid likelihood inference (Merlin) is a computer program that uses sparse inheritance trees for pedigree analysis; it performs rapid haplotyping, genotype error detection and affected pair linkage analyses and can handle more markers than other pedigree analysis packages.
Metabolic syndrome (MetS) is a complex disease involving multiple physiological, biochemical, and metabolic abnormalities. The search for reliable biomarkers may help to better elucidate its ...pathogenesis and develop new preventive and therapeutic strategies. In the present population-based study, we looked for biomarkers of MetS among obesity- and inflammation-related circulating factors and body composition parameters in 1079 individuals (with age range between 18 and 80) belonging to an ethnically homogeneous population. Plasma levels of soluble markers were measured by using ELISA. Body composition parameters were assessed using bioimpedance analysis (BIA). Statistical analysis, including mixed-effects regression, with MetS as a dependent variable, revealed that the most significant independent variables were mainly adipose tissue-related phenotypes, including fat mass/weight (FM/WT) OR (95% CI), 2.77 (2.01-3.81); leptin/adiponectin ratio (L/A ratio), 1.50 (1.23-1.83); growth and differentiation factor 15 (GDF-15) levels, 1.32 (1.08-1.62); inflammatory markers, specifically monocyte to high-density lipoprotein cholesterol ratio (MHR), 2.53 (2.00-3.15), and a few others. Additive Bayesian network modeling suggests that age, sex, MHR, and FM/WT are directly associated with MetS and probably affect its manifestation. Additionally, MetS may be causing the GDF-15 and L/A ratio. Our novel findings suggest the existence of complex, age-related, and possibly hierarchical relationships between MetS and factors associated with obesity.
A history of childhood adversity is associated with psychotic disorder, with an increase in risk according to number or severity of exposures. However, it is not known why only some exposed ...individuals go on to develop psychosis. One possibility is pre-existing genetic vulnerability. Research on gene-environment interaction in psychosis has primarily focused on candidate genes, although the genetic effects are now known to be polygenic. This pilot study investigated whether the effect of childhood adversity on psychosis is moderated by the polygenic risk score for schizophrenia (PRS). Data were utilised from the Genes and Psychosis (GAP) study set in South London, UK. The GAP sample comprises 285 first-presentation psychosis cases and 256 unaffected controls with information on childhood adversity. We studied only white subjects (80 cases and 110 controls) with PRS data, as the PRS has limited predictive ability in patients of African ancestry. The occurrence of childhood adversity was assessed with the Childhood Experience of Care and Abuse Questionnaire (CECA.Q) and the PRS was based on genome-wide meta-analysis results for schizophrenia from the Psychiatric Genomics Consortium. Higher schizophrenia PRS and childhood adversities each predicted psychosis status. Nevertheless, no evidence was found for interaction as departure from additivity, indicating that the effect of polygenic risk scores on psychosis was not increased in the presence of a history of childhood adversity. These findings are compatible with a multifactorial threshold model in which both genetic liability and exposure to environmental risk contribute independently to the etiology of psychosis.
Bone mineral density (BMD) and lipid levels are two of the most extensively studied risk factors for common diseases of aging, such as cardiovascular disease (CVD) and osteoporosis (OP). These two ...risk factors are also correlated with each other, but little is known about the molecular mechanisms behind this correlation. Recent studies revealed that circulating levels of several metabolites involved in the biosynthesis of androsterone correlate significantly with BMD and have the capacity to affect cholesterol and lipids levels. A main aim of the present study was to investigate the hypothesis that androsterone-related metabolites could provide a link between CVD and OP, as a common cause of lipid levels and BMD. The present study employed data from the NIHR BRC TwinsUK BioResource, comprising 1909 and 1994 monozygotic and dizygotic twin pairs, respectively, to address the causal relationships among BMD and lipids, and their associated metabolites, using reciprocal causation twin modelling, as well as Mendelian randomization (MR) using large publicly-available GWAS datasets on lipids and BMD, in conjunction with TwinsUK metabolite data. While results involving the twin modelling and MR analyses with metabolites were unable to establish a causal link between metabolite levels and either lipids or BMD, MR analyses of BMD and lipids suggest that lipid levels have a causal impact on BMD, which is consistent with findings from clinical trials of lipid-lowering drugs, which have also increased BMD.
The relationship between rheumatoid arthritis (RA) and early onset atherosclerosis is well depicted, each with an important inflammatory component. Glycoprotein acetyls (GlycA), a novel biomarker of ...inflammation, may play a role in the manifestation of these two inflammatory conditions. The present study examined a potential mediating role of GlycA within the RA–atherosclerosis relationship to determine whether it accounts for the excess risk of cardiovascular disease over that posed by lipid risk factors. The UK Biobank dataset was acquired to establish associations among RA, atherosclerosis, GlycA, and major lipid factors: total cholesterol (TC), high- and low-density lipoprotein (HDL, LDL) cholesterol, and triglycerides (TGs). Genome-wide association study summary statistics were collected from various resources to perform genetic analyses. Causality among variables was tested using Mendelian Randomization (MR) analysis. Genes of interest were identified using colocalization analysis and gene enrichment analysis. MR results appeared to indicate that the genetic relationship between GlycA and RA and also between RA and atherosclerosis was explained by horizontal pleiotropy (p-value = 0.001 and <0.001, respectively), while GlycA may causally predict atherosclerosis (p-value = 0.017). Colocalization analysis revealed several functionally relevant genes shared between GlycA and all the variables assessed. Two loci were apparent in all relationships tested and included the HLA region as well as SLC22A1. GlycA appears to mediate the RA–atherosclerosis relationship through several possible pathways. GlycA, although pleiotropically related to RA, appears to causally predict atherosclerosis. Thus, GlycA is suggested as a significant factor in the etiology of atherosclerosis development in RA.
PDF
