429 research outputs found

    Compressible laminar streaks with wall suction

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    SNP Prioritization Using a B ayesian Probability of Association

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    Prioritization is the process whereby a set of possible candidate genes or SNP s is ranked so that the most promising can be taken forward into further studies. In a genome‐wide association study, prioritization is usually based on the P ‐values alone, but researchers sometimes take account of external annotation information about the SNP s such as whether the SNP lies close to a good candidate gene. Using external information in this way is inherently subjective and is often not formalized, making the analysis difficult to reproduce. Building on previous work that has identified 14 important types of external information, we present an approximate B ayesian analysis that produces an estimate of the probability of association. The calculation combines four sources of information: the genome‐wide data, SNP information derived from bioinformatics databases, empirical SNP weights, and the researchers’ subjective prior opinions. The calculation is fast enough that it can be applied to millions of SNPS and although it does rely on subjective judgments, those judgments are made explicit so that the final SNP selection can be reproduced. We show that the resulting probability of association is intuitively more appealing than the P ‐value because it is easier to interpret and it makes allowance for the power of the study. We illustrate the use of the probability of association for SNP prioritization by applying it to a meta‐analysis of kidney function genome‐wide association studies and demonstrate that SNP selection performs better using the probability of association compared with P ‐values alone.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/96317/1/gepi21704.pd

    Importance of Different Types of Prior Knowledge in Selecting Genome‐Wide Findings for Follow‐Up

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    Biological plausibility and other prior information could help select genome‐wide association ( GWA ) findings for further follow‐up, but there is no consensus on which types of knowledge should be considered or how to weight them. We used experts’ opinions and empirical evidence to estimate the relative importance of 15 types of information at the single‐nucleotide polymorphism ( SNP ) and gene levels. Opinions were elicited from 10 experts using a two‐round Delphi survey. Empirical evidence was obtained by comparing the frequency of each type of characteristic in SNP s established as being associated with seven disease traits through GWA meta‐analysis and independent replication, with the corresponding frequency in a randomly selected set of SNP s. SNP and gene characteristics were retrieved using a specially developed bioinformatics tool. Both the expert and the empirical evidence rated previous association in a meta‐analysis or more than one study as conferring the highest relative probability of true association, whereas previous association in a single study ranked much lower. High relative probabilities were also observed for location in a functional protein domain, although location in a region evolutionarily conserved in vertebrates was ranked high by the data but not by the experts. Our empirical evidence did not support the importance attributed by the experts to whether the gene encodes a protein in a pathway or shows interactions relevant to the trait. Our findings provide insight into the selection and weighting of different types of knowledge in SNP or gene prioritization, and point to areas requiring further research.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/96262/1/gepi21705.pd

    New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

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    Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

    Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization.

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    The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 new QT interval-associated loci in 298 unrelated probands with LQTS identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies new candidate genes for ventricular arrhythmias, LQTS and SCD

    Hundreds of variants clustered in genomic loci and biological pathways affect human height

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    Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

    COVID-19 vaccine-induced antibody responses in immunosuppressed patients with inflammatory bowel disease (VIP): a multicentre, prospective, case-control study.

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    BACKGROUND: The effects that therapies for inflammatory bowel disease (IBD) have on immune responses to SARS-CoV-2 vaccination are not yet fully known. Therefore, we sought to determine whether COVID-19 vaccine-induced antibody responses were altered in patients with IBD on commonly used immunosuppressive drugs. METHODS: In this multicentre, prospective, case-control study (VIP), we recruited adults with IBD treated with one of six different immunosuppressive treatment regimens (thiopurines, infliximab, a thiopurine plus infliximab, ustekinumab, vedolizumab, or tofacitinib) and healthy control participants from nine centres in the UK. Eligible participants were aged 18 years or older and had received two doses of COVID-19 vaccines (either ChAdOx1 nCoV-19 [Oxford-AstraZeneca], BNT162b2 [Pfizer-BioNTech], or mRNA1273 [Moderna]) 6-12 weeks apart (according to scheduling adopted in the UK). We measured antibody responses 53-92 days after a second vaccine dose using the Roche Elecsys Anti-SARS-CoV-2 spike electrochemiluminescence immunoassay. The primary outcome was anti-SARS-CoV-2 spike protein antibody concentrations in participants without previous SARS-CoV-2 infection, adjusted by age and vaccine type, and was analysed by use of multivariable linear regression models. This study is registered in the ISRCTN Registry, ISRCTN13495664, and is ongoing. FINDINGS: Between May 31 and Nov 24, 2021, we recruited 483 participants, including patients with IBD being treated with thiopurines (n=78), infliximab (n=63), a thiopurine plus infliximab (n=72), ustekinumab (n=57), vedolizumab (n=62), or tofacitinib (n=30), and 121 healthy controls. We included 370 participants without evidence of previous infection in our primary analysis. Geometric mean anti-SARS-CoV-2 spike protein antibody concentrations were significantly lower in patients treated with infliximab (156·8 U/mL [geometric SD 5·7]; p<0·0001), infliximab plus thiopurine (111·1 U/mL [5·7]; p<0·0001), or tofacitinib (429·5 U/mL [3·1]; p=0·0012) compared with controls (1578·3 U/mL [3·7]). There were no significant differences in antibody concentrations between patients treated with thiopurine monotherapy (1019·8 U/mL [4·3]; p=0·74), ustekinumab (582·4 U/mL [4·6]; p=0·11), or vedolizumab (954·0 U/mL [4·1]; p=0·50) and healthy controls. In multivariable modelling, lower anti-SARS-CoV-2 spike protein antibody concentrations were independently associated with infliximab (geometric mean ratio 0·12, 95% CI 0·08-0·17; p<0·0001) and tofacitinib (0·43, 0·23-0·81; p=0·0095), but not with ustekinumab (0·69, 0·41-1·19; p=0·18), thiopurines (0·89, 0·64-1·24; p=0·50), or vedolizumab (1·16, 0·74-1·83; p=0·51). mRNA vaccines (3·68, 2·80-4·84; p<0·0001; vs adenovirus vector vaccines) were independently associated with higher antibody concentrations and older age per decade (0·79, 0·72-0·87; p<0·0001) with lower antibody concentrations. INTERPRETATION: For patients with IBD, the immunogenicity of COVID-19 vaccines varies according to immunosuppressive drug exposure, and is attenuated in recipients of infliximab, infliximab plus thiopurines, and tofacitinib. Scheduling of third primary, or booster, doses could be personalised on the basis of an individual's treatment, and patients taking anti-tumour necrosis factor and tofacitinib should be prioritised. FUNDING: Pfizer
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