Displaying all 3 publications

Abstract:
Sort:
  1. Differential Correlations Informed Metabolite Set Enrichment Analysis to Decipher Metabolic Heterogeneity of Disease
    Lin G, Dong L, Cheng KK, Xu X, Wang Y, Deng L, et al.
    Anal Chem, 2023 Aug 22;95(33):12505-12513.
    PMID: 37557184 DOI: 10.1021/acs.analchem.3c02246
    Metabolic pathways are regarded as functional and basic components of the biological system. In metabolomics, metabolite set enrichment analysis (MSEA) is often used to identify the altered metabolic pathways (metabolite sets) associated with phenotypes of interest (POI), e.g., disease. However, in most studies, MSEA suffers from the limitation of low metabolite coverage. Random walk (RW)-based algorithms can be used to propagate the perturbation of detected metabolites to the undetected metabolites through a metabolite network model prior to MSEA. Nevertheless, most of the existing RW-based algorithms run on a general metabolite network constructed based on public databases, such as KEGG, without taking into consideration the potential influence of POI on the metabolite network, which may reduce the phenotypic specificities of the MSEA results. To solve this problem, a novel pathway analysis strategy, namely, differential correlation-informed MSEA (dci-MSEA), is proposed in this paper. Statistically, differential correlations between metabolites are used to evaluate the influence of POI on the metabolite network, so that a phenotype-specific metabolite network is constructed for RW-based propagation. The experimental results show that dci-MSEA outperforms the conventional RW-based MSEA in identifying the altered metabolic pathways associated with colorectal cancer. In addition, by incorporating the individual-specific metabolite network, the dci-MSEA strategy is easily extended to disease heterogeneity analysis. Here, dci-MSEA was used to decipher the heterogeneity of colorectal cancer. The present results highlight the clustering of colorectal cancer samples with their cluster-specific selection of differential pathways and demonstrate the feasibility of dci-MSEA in heterogeneity analysis. Taken together, the proposed dci-MSEA may provide insights into disease mechanisms and determination of disease heterogeneity.
  2. A standard panel of microsatellites for Asian seabass (Lates calcarifer)
    Zhu ZY, Wang CM, Lo LC, Lin G, Feng F, Tan J, et al.
    Anim. Genet., 2010 Apr;41(2):208-12.
    PMID: 19793264 DOI: 10.1111/j.1365-2052.2009.01973.x
    Microsatellites are the most popular markers for parentage assignment and population genetic studies. To meet the demand for international comparability for genetic studies of Asian seabass, a standard panel of 28 microsatellites has been selected and characterized using the DNA of 24 individuals from Thailand, Malaysia, Indonesia and Australia. The average allele number of these markers was 10.82 +/- 0.71 (range: 6-19), and the expected heterozygosity averaged 0.76 +/- 0.02 (range: 0.63-1.00). All microsatellites showed Mendelian inheritance. In addition, eight standard size controls have been developed by cloning a set of microsatellite alleles into a pGEM-T vector to calibrate allele sizes determined by different laboratories, and are available upon request. Seven multiplex PCRs, each amplifying 3-5 markers, were optimized to accurately and rapidly genotype microsatellites. Parentage assignment using 10 microsatellites in two crosses (10 x 10 and 20 x 20) demonstrated a high power of these markers for revealing parent-sibling connections. This standard set of microsatellites will standardize genetic diversity studies of Asian seabass, and the multiplex PCR sets will facilitate parentage assignment.
  3. Performance of Echocardiographic Algorithms for Assessment of High Aortic Bioprosthetic Valve Gradients
    Roslan AB, Naser JA, Nkomo VT, Padang R, Lin G, Pislaru C, et al.
    J Am Soc Echocardiogr, 2022 Feb 11.
    PMID: 35158051 DOI: 10.1016/j.echo.2022.01.019
    BACKGROUND: Bioprosthetic aortic valve dysfunction (BAVD) is a challenging diagnosis. Commonly used algorithms to classify high-gradient BAVD are the 2009 American Society of Echocardiography (ASE), 2014 Blauwet-Miller, and 2016 European Association of Cardiovascular Imaging (EACVI). We sought 1) to evaluate the accuracy of existing algorithms against objectively proven BAVD and 2) to propose an improved algorithm.

    METHODS: Retrospective study of 266 patients with objectively proven BAVD (pathology of explanted valves, 4D-CT prior to transcatheter valve-in-valve, or therapeutically confirmed bioprosthetic thrombosis) who were treated. Of those, 191 had obstruction, 48 had regurgitation, 15 had mixed stenosis and regurgitation, and 12 had patient-prosthesis mismatch (PPM). Normal controls were matched 1:1 (age, prosthesis size and type), of which 43 had high gradients (PPM in 30, high flow in 9 and normal prosthesis in 9). Algorithm assignment was based on the echocardiogram leading to BAVD diagnosis and the pre-discharge "fingerprint" echocardiogram after surgical or transcatheter aortic valve replacement. A novel algorithm (Mayo Clinic algorithm) incorporating valve appearance in addition to Doppler parameters was developed to improve observed deficiencies.

    RESULTS: The accuracy of existing algorithms was suboptimal (2009 ASE: 62%; 2014 Blauwet-Miller: 62%; 2016 EACVI: 57%). The most common overdiagnosis was PPM (22-29% of patients and controls with high gradients). The novel Mayo Clinic algorithm correctly identified the mechanism in 256 of 307 patients and controls (83%). Recognition of regurgitation was substantially improved (42 of 47 patients, 89%) and the number of PPM misdiagnoses significantly reduced (5 patients).

    CONCLUSION: Currently recommended algorithms misclassify a significant number of BAVD patients. The accuracy was improved by a newly proposed algorithm.

Related Terms
    Try searching for something
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links