Reach- and catchment-scale determinants of the distribution of freshwater mussels (Bivalvia: Unionidae) in south-eastern Michigan, U.S.A.

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73643/1/j.1365-2426.2003.01165.x.pd

Large autosomal copy-number differences within unselected monozygotic twin pairs are rare

Monozygotic (MZ) twins form an important system for the study of biological plasticity in humans. While MZ twins are generally considered to be genetically identical, a number of studies have emerged that have demonstrated copy-number differences within a twin pair, particularly in those discordant for disease. The rate of autosomal copy-number variation (CNV) discordance within MZ twin pairs was investigated using a population sample of 376 twin pairs genotyped on Illumina Human610-Quad arrays. After CNV calling using both QuantiSNP and PennCNV followed by manual annotation, only a single CNV difference was observed within the MZ twin pairs, being a 130 KB duplication of chromosome 5. Five other potential discordant CNV were called by the software, but excluded based on manual annotation of the regions. It is concluded that large CNV discordance is rare within MZ twin pairs, indicating that any CNV difference found within phenotypically discordant MZ twin pairs has a high probability of containing the causal gene(s) involved

Inadequate reporting of research ethics review and informed consent in cluster randomized trials : review of random sample of published trials

Peer reviewedPublisher PD

Examining the Impact of Imputation Errors on Fine-Mapping Using DNA Methylation QTL as a Model Trait

Genetic variants disrupting DNA methylation at CpG dinucleotides (CpG-SNP) provide a set of known causal variants to serve as models for testing fine-mapping methodology. We use 1716 CpG-SNPs to test three fine-mapping approaches (BIMBAM, BSLMM, and the J-test), assessing the impact of imputation errors and the choice of reference panel by using both whole-genome sequence (WGS), and genotype array data on the same individuals (n=1166). The choice of imputation reference panel had a strong effect on imputation accuracy, with the 1000 Genomes Phase 3 (1000G) reference panel (n=2504 from 26 populations) giving a mean non-reference discordance rate between imputed and sequenced genotypes of 3.2% compared to 1.6% when using the Haplotype Reference Consortium (HRC) reference panel (n=32470 Europeans). These imputation errors impacted on whether the CpG-SNP was included in the 95% credible set, with a difference of ∼ 23% and ∼ 7% between the WGS and the 1000G and HRC imputed datasets respectively. All of the fine-mapping methods failed to reach the expected 95% coverage of the CpG-SNP. This is attributed to secondary cis genetic effects that are unable to be statistically separated from the CpG-SNP, and through a masking mechanism where the effect of the methylation disrupting allele at the CpG-SNP is hidden by the effect of a nearby SNP that has strong LD with the CpG-SNP. The reduced accuracy in fine-mapping a known causal variant in a low level biological trait with imputed genetic data has implications for the study of higher order complex traits and disease

Cyclic diarylboron derivatives as NLRP3 inflammasome inhibitors

Inhibitor compounds are disclosed. The compounds are effective in the treatment of diseases or conditions in which interleukin 1 .beta. activity is implicated. Methods of synthesis of the compounds, as well as pharmaceutical compositions comprising the compounds are also disclosed

The epigenetic clock is correlated with physical and cognitive fitness in the Lothian Birth Cohort 1936

Background: The DNA methylation-based 'epigenetic clock' correlates strongly with chronological age, but it is currently unclear what drives individual differences. We examine cross-sectional and longitudinal associations between the epigenetic clock and four mortality-linked markers of physical and mental fitness: lung function, walking speed, grip strength and cognitive ability. Methods: DNA methylation-based age acceleration (residuals of the epigenetic clock estimate regressed on chronological age) were estimated in the Lothian Birth Cohort 1936 at ages 70 (n=920), 73 (n=299) and 76 (n=273) years. General cognitive ability, walking speed, lung function and grip strength were measured concurrently. Cross-sectional correlations between age acceleration and the fitness variables were calculated. Longitudinal change in the epigenetic clock estimates and the fitness variables were assessed via linear mixed models and latent growth curves. Epigenetic age acceleration at age 70 was used as a predictor of longitudinal change in fitness. Epigenome-wide association studies (EWASs) were conducted on the four fitness measures. Results: Cross-sectional correlations were significant between greater age acceleration and poorer performance on the lung function, cognition and grip strength measures (r range: -0.07 to -0.05, P range: 9.7 x 10 to 0.024). All of the fitness variables declined over time but age acceleration did not correlate with subsequent change over 6 years. There were no EWAS hits for the fitness traits. Conclusions: Markers of physical and mental fitness are associated with the epigenetic clock (lower abilities associated with age acceleration). However, age acceleration does not associate with decline in these measures, at least over a relatively short follow-up

TINITALY/01: a new Triangular Irregular Network of Italy

A new Digital Elevation Model (DEM) of the natural landforms of Italy is presented. A methodology is discussed to build a DEM over wide areas where elevation data from non-homogeneous (in density and accuracy) input sources are available. The input elevation data include contour lines and spot heights derived from the Italian Regional topographic maps, satellite-based global positioning system points, ground based and radar altimetry data. Owing to the great heterogeneity of the input data density, the DEM format that better preserves the original accuracy is a Triangular Irregular Network (TIN). A Delaunay-based TIN structure is improved by using the DEST algorithm that enhances input data by evaluating inferred break-lines. Accordingly to this approach, biased distributions in slopes and elevations are absent. To prevent discontinuities at the boundary between regions characterized by data with different resolution a cubic Hermite blending weight S-shaped function is adopted. The TIN of Italy consists of 1.39×109 triangles. The average triangle area ranges from 12 to about 13000 m2 accordingly to different morphologies and different sources. About 50% of the model has a local average triangle area <500 m2. The vertical accuracy of the obtained DEM is evaluated by more than 200000 sparse control points. The overall Root Mean Square Error (RMSE) is less than 3.5 m. The obtained national-scale DEM constitutes an useful support to carry out accurate geomorphological and geological investigations over large areas. The problem of choosing the best step size in deriving a grid from a TIN is then discussed and a method to quantify the loss of vertical information is presented as a function of the grid step. Some examples of DEM application are outlined. Under request, an high resolution stereo image database of the whole Italian territory (derived from the presented DEM) is available to browse via internet

Inflammation-driven bone formation in a mouse model of ankylosing spondylitis: sequential not parallel processes

Background\ud \ud Ankylosing spondylitis (AS) is an immune-mediated arthritis particularly targeting the spine and pelvis and is characterised by inflammation, osteoproliferation and frequently ankylosis. Current treatments that predominately target inflammatory pathways have disappointing efficacy in slowing disease progression. Thus, a better understanding of the causal association and pathological progression from inflammation to bone formation, particularly whether inflammation directly initiates osteoproliferation, is required.\ud \ud Methods\ud \ud The proteoglycan-induced spondylitis (PGISp) mouse model of AS was used to histopathologically map the progressive axial disease events, assess molecular changes during disease progression and define disease progression using unbiased clustering of semi-quantitative histology. PGISp mice were followed over a 24-week time course. Spinal disease was assessed using a novel semi-quantitative histological scoring system that independently evaluated the breadth of pathological features associated with PGISp axial disease, including inflammation, joint destruction and excessive tissue formation (osteoproliferation). Matrix components were identified using immunohistochemistry.\ud \ud Results\ud \ud Disease initiated with inflammation at the periphery of the intervertebral disc (IVD) adjacent to the longitudinal ligament, reminiscent of enthesitis, and was associated with upregulated tumor necrosis factor and metalloproteinases. After a lag phase, established inflammation was temporospatially associated with destruction of IVDs, cartilage and bone. At later time points, advanced disease was characterised by substantially reduced inflammation, excessive tissue formation and ectopic chondrocyte expansion. These distinct features differentiated affected mice into early, intermediate and advanced disease stages. Excessive tissue formation was observed in vertebral joints only if the IVD was destroyed as a consequence of the early inflammation. Ectopic excessive tissue was predominantly chondroidal with chondrocyte-like cells embedded within collagen type II- and X-rich matrix. This corresponded with upregulation of mRNA for cartilage markers Col2a1, sox9 and Comp. Osteophytes, though infrequent, were more prevalent in later disease.\ud \ud Conclusions\ud \ud The inflammation-driven IVD destruction was shown to be a prerequisite for axial disease progression to osteoproliferation in the PGISp mouse. Osteoproliferation led to vertebral body deformity and fusion but was never seen concurrent with persistent inflammation, suggesting a sequential process. The findings support that early intervention with anti-inflammatory therapies will be needed to limit destructive processes and consequently prevent progression of AS

Identification of influential probe types in epigenetic predictions of human traits: implications for microarray design

BACKGROUND: CpG methylation levels can help to explain inter-individual differences in phenotypic traits. Few studies have explored whether identifying probe subsets based on their biological and statistical properties can maximise predictions whilst minimising array content. Variance component analyses and penalised regression (epigenetic predictors) were used to test the influence of (i) the number of probes considered, (ii) mean probe variability and (iii) methylation QTL status on the variance captured in eighteen traits by blood DNA methylation. Training and test samples comprised ≤ 4450 and ≤ 2578 unrelated individuals from Generation Scotland, respectively. RESULTS: As the number of probes under consideration decreased, so too did the estimates from variance components and prediction analyses. Methylation QTL status and mean probe variability did not influence variance components. However, relative effect sizes were 15% larger for epigenetic predictors based on probes with known or reported methylation QTLs compared to probes without reported methylation QTLs. Relative effect sizes were 45% larger for predictors based on probes with mean Beta-values between 10 and 90% compared to those based on hypo- or hypermethylated probes (Beta-value ≤ 10% or ≥ 90%). CONCLUSIONS: Arrays with fewer probes could reduce costs, leading to increased sample sizes for analyses. Our results show that reducing array content can restrict prediction metrics and careful attention must be given to the biological and distribution properties of CpG probes in array content selection. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13148-022-01320-9