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  1. Article ; Online: Phylogeny-guided microbiome OTU-specific association test (POST)

    Caizhi Huang / Benjamin J. Callahan / Michael C. Wu / Shannon T. Holloway / Hayden Brochu / Wenbin Lu / Xinxia Peng / Jung-Ying Tzeng

    Microbiome, Vol 10, Iss 1, Pp 1-

    2022  Volume 15

    Abstract: Abstract Background The relationship between host conditions and microbiome profiles, typically characterized by operational taxonomic units (OTUs), contains important information about the microbial role in human health. Traditional association testing ... ...

    Abstract Abstract Background The relationship between host conditions and microbiome profiles, typically characterized by operational taxonomic units (OTUs), contains important information about the microbial role in human health. Traditional association testing frameworks are challenged by the high dimensionality and sparsity of typical microbiome profiles. Phylogenetic information is often incorporated to address these challenges with the assumption that evolutionarily similar taxa tend to behave similarly. However, this assumption may not always be valid due to the complex effects of microbes, and phylogenetic information should be incorporated in a data-supervised fashion. Results In this work, we propose a local collapsing test called phylogeny-guided microbiome OTU-specific association test (POST). In POST, whether or not to borrow information and how much information to borrow from the neighboring OTUs in the phylogenetic tree are supervised by phylogenetic distance and the outcome-OTU association. POST is constructed under the kernel machine framework to accommodate complex OTU effects and extends kernel machine microbiome tests from community level to OTU level. Using simulation studies, we show that when the phylogenetic tree is informative, POST has better performance than existing OTU-level association tests. When the phylogenetic tree is not informative, POST achieves similar performance as existing methods. Finally, in real data applications on bacterial vaginosis and on preterm birth, we find that POST can identify similar or more outcome-associated OTUs that are of biological relevance compared to existing methods. Conclusions Using POST, we show that adaptively leveraging the phylogenetic information can enhance the selection performance of associated microbiome features by improving the overall true-positive and false-positive detection. We developed a user friendly R package POSTm which is freely available on CRAN ( https://CRAN.R-project.org/package=POSTm ). Video Abstract.
    Keywords Association test ; Phylogenetic tree ; Kernel machine regression ; Microbial ecology ; QR100-130
    Language English
    Publishing date 2022-06-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Establishment of reference standards in biosimilar studies

    Aijing Zhang / Jung-Ying Tzeng / Shein-Chung Chow

    Generics and Biosimilars Initiative Journal, Vol 2, Iss 4, Pp 173-

    2013  Volume 177

    Abstract: When an innovative biological product goes off-patent, biopharmaceutical or biotechnological companies may file an application for regulatory approval of biosimilar products. In practice, however, important information on the innovative (reference) ... ...

    Abstract When an innovative biological product goes off-patent, biopharmaceutical or biotechnological companies may file an application for regulatory approval of biosimilar products. In practice, however, important information on the innovative (reference) product may not be available for assessment. Thus, it is important to first establish a reference standard while assessing biosimilarity between a biosimilar product and the reference product. In this paper, reference standard is established through the biosimilarity index approach based on a reference-replicated study (or R-R study), in which the reference product is compared with itself under various scenarios. The reference standard can then be used for assessing the degree of similarity between the test and reference drugs in biosimilar studies.
    Keywords biosimilarity ; biosimilarity index ; highly similar ; reference standards ; replicate reference study ; Pharmacy and materia medica ; RS1-441 ; Medicine ; R
    Language English
    Publishing date 2013-12-01T00:00:00Z
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Rare Variants Association Analysis in Large-Scale Sequencing Studies at the Single Locus Level.

    Xinge Jessie Jeng / Zhongyin John Daye / Wenbin Lu / Jung-Ying Tzeng

    PLoS Computational Biology, Vol 12, Iss 6, p e

    2016  Volume 1004993

    Abstract: Genetic association analyses of rare variants in next-generation sequencing (NGS) studies are fundamentally challenging due to the presence of a very large number of candidate variants at extremely low minor allele frequencies. Recent developments often ... ...

    Abstract Genetic association analyses of rare variants in next-generation sequencing (NGS) studies are fundamentally challenging due to the presence of a very large number of candidate variants at extremely low minor allele frequencies. Recent developments often focus on pooling multiple variants to provide association analysis at the gene instead of the locus level. Nonetheless, pinpointing individual variants is a critical goal for genomic researches as such information can facilitate the precise delineation of molecular mechanisms and functions of genetic factors on diseases. Due to the extreme rarity of mutations and high-dimensionality, significances of causal variants cannot easily stand out from those of noncausal ones. Consequently, standard false-positive control procedures, such as the Bonferroni and false discovery rate (FDR), are often impractical to apply, as a majority of the causal variants can only be identified along with a few but unknown number of noncausal variants. To provide informative analysis of individual variants in large-scale sequencing studies, we propose the Adaptive False-Negative Control (AFNC) procedure that can include a large proportion of causal variants with high confidence by introducing a novel statistical inquiry to determine those variants that can be confidently dispatched as noncausal. The AFNC provides a general framework that can accommodate for a variety of models and significance tests. The procedure is computationally efficient and can adapt to the underlying proportion of causal variants and quality of significance rankings. Extensive simulation studies across a plethora of scenarios demonstrate that the AFNC is advantageous for identifying individual rare variants, whereas the Bonferroni and FDR are exceedingly over-conservative for rare variants association studies. In the analyses of the CoLaus dataset, AFNC has identified individual variants most responsible for gene-level significances. Moreover, single-variant results using the AFNC have been successfully applied to ...
    Keywords Biology (General) ; QH301-705.5
    Subject code 519
    Language English
    Publishing date 2016-06-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Identifying individual risk rare variants using protein structure guided local tests (POINT).

    Rachel Marceau West / Wenbin Lu / Daniel M Rotroff / Melaine A Kuenemann / Sheng-Mao Chang / Michael C Wu / Michael J Wagner / John B Buse / Alison A Motsinger-Reif / Denis Fourches / Jung-Ying Tzeng

    PLoS Computational Biology, Vol 15, Iss 2, p e

    2019  Volume 1006722

    Abstract: Rare variants are of increasing interest to genetic association studies because of their etiological contributions to human complex diseases. Due to the rarity of the mutant events, rare variants are routinely analyzed on an aggregate level. While ... ...

    Abstract Rare variants are of increasing interest to genetic association studies because of their etiological contributions to human complex diseases. Due to the rarity of the mutant events, rare variants are routinely analyzed on an aggregate level. While aggregation analyses improve the detection of global-level signal, they are not able to pinpoint causal variants within a variant set. To perform inference on a localized level, additional information, e.g., biological annotation, is often needed to boost the information content of a rare variant. Following the observation that important variants are likely to cluster together on functional domains, we propose a protein structure guided local test (POINT) to provide variant-specific association information using structure-guided aggregation of signal. Constructed under a kernel machine framework, POINT performs local association testing by borrowing information from neighboring variants in the 3-dimensional protein space in a data-adaptive fashion. Besides merely providing a list of promising variants, POINT assigns each variant a p-value to permit variant ranking and prioritization. We assess the selection performance of POINT using simulations and illustrate how it can be used to prioritize individual rare variants in PCSK9, ANGPTL4 and CETP in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) clinical trial data.
    Keywords Biology (General) ; QH301-705.5
    Subject code 500
    Language English
    Publishing date 2019-02-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Association test using Copy Number Profile Curves (CONCUR) enhances power in rare copy number variant analysis.

    Amanda Brucker / Wenbin Lu / Rachel Marceau West / Qi-You Yu / Chuhsing Kate Hsiao / Tzu-Hung Hsiao / Ching-Heng Lin / Patrik K E Magnusson / Patrick F Sullivan / Jin P Szatkiewicz / Tzu-Pin Lu / Jung-Ying Tzeng

    PLoS Computational Biology, Vol 16, Iss 5, p e

    2020  Volume 1007797

    Abstract: Copy number variants (CNVs) are the gain or loss of DNA segments in the genome that can vary in dosage and length. CNVs comprise a large proportion of variation in human genomes and impact health conditions. To detect rare CNV associations, kernel-based ... ...

    Abstract Copy number variants (CNVs) are the gain or loss of DNA segments in the genome that can vary in dosage and length. CNVs comprise a large proportion of variation in human genomes and impact health conditions. To detect rare CNV associations, kernel-based methods have been shown to be a powerful tool due to their flexibility in modeling the aggregate CNV effects, their ability to capture effects from different CNV features, and their accommodation of effect heterogeneity. To perform a kernel association test, a CNV locus needs to be defined so that locus-specific effects can be retained during aggregation. However, CNV loci are arbitrarily defined and different locus definitions can lead to different performance depending on the underlying effect patterns. In this work, we develop a new kernel-based test called CONCUR (i.e., copy number profile curve-based association test) that is free from a definition of locus and evaluates CNV-phenotype associations by comparing individuals' copy number profiles across the genomic regions. CONCUR is built on the proposed concepts of "copy number profile curves" to describe the CNV profile of an individual, and the "common area under the curve (cAUC) kernel" to model the multi-feature CNV effects. The proposed method captures the effects of CNV dosage and length, accounts for the numerical nature of copy numbers, and accommodates between- and within-locus etiological heterogeneity without the need to define artificial CNV loci as required in current kernel methods. In a variety of simulation settings, CONCUR shows comparable or improved power over existing approaches. Real data analyses suggest that CONCUR is well powered to detect CNV effects in the Swedish Schizophrenia Study and the Taiwan Biobank.
    Keywords Biology (General) ; QH301-705.5
    Language English
    Publishing date 2020-05-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Module-based association analysis for omics data with network structure.

    Zhi Wang / Arnab Maity / Chuhsing Kate Hsiao / Deepak Voora / Rima Kaddurah-Daouk / Jung-Ying Tzeng

    PLoS ONE, Vol 10, Iss 3, p e

    2015  Volume 0122309

    Abstract: Module-based analysis (MBA) aims to evaluate the effect of a group of biological elements sharing common features, such as SNPs in the same gene or metabolites in the same pathways, and has become an attractive alternative to traditional single bio- ... ...

    Abstract Module-based analysis (MBA) aims to evaluate the effect of a group of biological elements sharing common features, such as SNPs in the same gene or metabolites in the same pathways, and has become an attractive alternative to traditional single bio-element approaches. Because bio-elements regulate and interact with each other as part of network, incorporating network structure information can more precisely model the biological effects, enhance the ability to detect true associations, and facilitate our understanding of the underlying biological mechanisms. However, most MBA methods ignore the network structure information, which depicts the interaction and regulation relationship among basic functional units in biology system. We construct the connectivity kernel and the topology kernel to capture the relationship among bio-elements in a module, and use a kernel machine framework to evaluate the joint effect of bio-elements. Our proposed kernel machine approach directly incorporates network structure so to enhance the study efficiency; it can assess interactions among modules, account covariates, and is computational efficient. Through simulation studies and real data application, we demonstrate that the proposed network-based methods can have markedly better power than the approaches ignoring network information under a range of scenarios.
    Keywords Medicine ; R ; Science ; Q
    Subject code 006
    Language English
    Publishing date 2015-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Maternal blood cadmium, lead and arsenic levels, nutrient combinations, and offspring birthweight

    Yiwen Luo / Lauren E. McCullough / Jung-Ying Tzeng / Thomas Darrah / Avner Vengosh / Rachel L. Maguire / Arnab Maity / Carmen Samuel-Hodge / Susan K. Murphy / Michelle A. Mendez / Cathrine Hoyo

    BMC Public Health, Vol 17, Iss 1, Pp 1-

    2017  Volume 11

    Abstract: Abstract Background Cadmium (Cd), lead (Pb) and arsenic (As) are common environmental contaminants that have been associated with lower birthweight. Although some essential metals may mitigate exposure, data are inconsistent. This study sought to ... ...

    Abstract Abstract Background Cadmium (Cd), lead (Pb) and arsenic (As) are common environmental contaminants that have been associated with lower birthweight. Although some essential metals may mitigate exposure, data are inconsistent. This study sought to evaluate the relationship between toxic metals, nutrient combinations and birthweight among 275 mother-child pairs. Methods Non-essential metals, Cd, Pb, As, and essential metals, iron (Fe), zinc (Zn), selenium (Se), copper (Cu), calcium (Ca), magnesium (Mg), and manganese (Mn) were measured in maternal whole blood obtained during the first trimester using inductively coupled plasma mass spectrometry. Folate concentrations were measured by microbial assay. Birthweight was obtained from medical records. We used quantile regression to evaluate the association between toxic metals and nutrients due to their underlying wedge-shaped relationship. Ordinary linear regression was used to evaluate associations between birth weight and toxic metals. Results After multivariate adjustment, the negative association between Pb or Cd and a combination of Fe, Se, Ca and folate was robust, persistent and dose-dependent (p < 0.05). However, a combination of Zn, Cu, Mn and Mg was positively associated with Pb and Cd levels. While prenatal blood Cd and Pb were also associated with lower birthweight. Fe, Se, Ca and folate did not modify these associations. Conclusion Small sample size and cross-sectional design notwithstanding, the robust and persistent negative associations between some, but not all, nutrient combinations with these ubiquitous environmental contaminants suggest that only some recommended nutrient combinations may mitigate toxic metal exposure in chronically exposed populations. Larger longitudinal studies are required to confirm these findings.
    Keywords Toxic metals ; Dietary nutrients ; Birthweight ; Epidemiology ; Public aspects of medicine ; RA1-1270
    Subject code 333
    Language English
    Publishing date 2017-04-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: A mega-analysis of genome-wide association studies for major depressive disorder.

    Ripke, Stephan / Wray, Naomi R / Lewis, Cathryn M / Hamilton, Steven P / Weissman, Myrna M / Breen, Gerome / Byrne, Enda M / Blackwood, Douglas H R / Boomsma, Dorret I / Cichon, Sven / Heath, Andrew C / Holsboer, Florian / Lucae, Susanne / Madden, Pamela A F / Martin, Nicholas G / McGuffin, Peter / Muglia, Pierandrea / Noethen, Markus M / Penninx, Brenda P /
    Pergadia, Michele L / Potash, James B / Rietschel, Marcella / Lin, Danyu / Müller-Myhsok, Bertram / Shi, Jianxin / Steinberg, Stacy / Grabe, Hans J / Lichtenstein, Paul / Magnusson, Patrik / Perlis, Roy H / Preisig, Martin / Smoller, Jordan W / Stefansson, Kari / Uher, Rudolf / Kutalik, Zoltan / Tansey, Katherine E / Teumer, Alexander / Viktorin, Alexander / Barnes, Michael R / Bettecken, Thomas / Binder, Elisabeth B / Breuer, René / Castro, Victor M / Churchill, Susanne E / Coryell, William H / Craddock, Nick / Craig, Ian W / Czamara, Darina / De Geus, Eco J / Degenhardt, Franziska / Farmer, Anne E / Fava, Maurizio / Frank, Josef / Gainer, Vivian S / Gallagher, Patience J / Gordon, Scott D / Goryachev, Sergey / Gross, Magdalena / Guipponi, Michel / Henders, Anjali K / Herms, Stefan / Hickie, Ian B / Hoefels, Susanne / Hoogendijk, Witte / Hottenga, Jouke Jan / Iosifescu, Dan V / Ising, Marcus / Jones, Ian / Jones, Lisa / Jung-Ying, Tzeng / Knowles, James A / Kohane, Isaac S / Kohli, Martin A / Korszun, Ania / Landen, Mikael / Lawson, William B / Lewis, Glyn / Macintyre, Donald / Maier, Wolfgang / Mattheisen, Manuel / McGrath, Patrick J / McIntosh, Andrew / McLean, Alan / Middeldorp, Christel M / Middleton, Lefkos / Montgomery, Grant M / Murphy, Shawn N / Nauck, Matthias / Nolen, Willem A / Nyholt, Dale R / O'Donovan, Michael / Oskarsson, Högni / Pedersen, Nancy / Scheftner, William A / Schulz, Andrea / Schulze, Thomas G / Shyn, Stanley I / Sigurdsson, Engilbert / Slager, Susan L / Smit, Johannes H / Stefansson, Hreinn / Steffens, Michael / Thorgeirsson, Thorgeir / Tozzi, Federica / Treutlein, Jens / Uhr, Manfred / van den Oord, Edwin J C G / Van Grootheest, Gerard / Völzke, Henry / Weilburg, Jeffrey B / Willemsen, Gonneke / Zitman, Frans G / Neale, Benjamin / Daly, Mark / Levinson, Douglas F / Sullivan, Patrick F

    Molecular psychiatry

    2012  Volume 18, Issue 4, Page(s) 497–511

    Abstract: Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we ... ...

    Abstract Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we analyzed more than 1.2 million autosomal and X chromosome single-nucleotide polymorphisms (SNPs) in 18 759 independent and unrelated subjects of recent European ancestry (9240 MDD cases and 9519 controls). In the MDD replication phase, we evaluated 554 SNPs in independent samples (6783 MDD cases and 50 695 controls). We also conducted a cross-disorder meta-analysis using 819 autosomal SNPs with P<0.0001 for either MDD or the Psychiatric GWAS Consortium bipolar disorder (BIP) mega-analysis (9238 MDD cases/8039 controls and 6998 BIP cases/7775 controls). No SNPs achieved genome-wide significance in the MDD discovery phase, the MDD replication phase or in pre-planned secondary analyses (by sex, recurrent MDD, recurrent early-onset MDD, age of onset, pre-pubertal onset MDD or typical-like MDD from a latent class analyses of the MDD criteria). In the MDD-bipolar cross-disorder analysis, 15 SNPs exceeded genome-wide significance (P<5 × 10(-8)), and all were in a 248 kb interval of high LD on 3p21.1 (chr3:52 425 083-53 822 102, minimum P=5.9 × 10(-9) at rs2535629). Although this is the largest genome-wide analysis of MDD yet conducted, its high prevalence means that the sample is still underpowered to detect genetic effects typical for complex traits. Therefore, we were unable to identify robust and replicable findings. We discuss what this means for genetic research for MDD. The 3p21.1 MDD-BIP finding should be interpreted with caution as the most significant SNP did not replicate in MDD samples, and genotyping in independent samples will be needed to resolve its status.
    MeSH term(s) Bipolar Disorder/genetics ; Case-Control Studies ; Depressive Disorder, Major/genetics ; Female ; Genetic Predisposition to Disease/genetics ; Genome-Wide Association Study/statistics & numerical data ; Humans ; Male ; Polymorphism, Single Nucleotide/genetics ; Whites/genetics
    Language English
    Publishing date 2012-04-03
    Publishing country England
    Document type Journal Article ; Meta-Analysis ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 1330655-8
    ISSN 1476-5578 ; 1359-4184
    ISSN (online) 1476-5578
    ISSN 1359-4184
    DOI 10.1038/mp.2012.21
    Database MEDical Literature Analysis and Retrieval System OnLINE

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