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  1. Article ; Online: Comprehensive Analysis of Constraint on the Spatial Distribution of Missense Variants in Human Protein Structures.

    Sivley, R Michael / Dou, Xiaoyi / Meiler, Jens / Bush, William S / Capra, John A

    American journal of human genetics

    2018  Volume 102, Issue 3, Page(s) 415–426

    Abstract: The spatial distribution of genetic variation within proteins is shaped by evolutionary constraint and provides insight into the functional importance of protein regions and the potential pathogenicity of protein alterations. Here, we comprehensively ... ...

    Abstract The spatial distribution of genetic variation within proteins is shaped by evolutionary constraint and provides insight into the functional importance of protein regions and the potential pathogenicity of protein alterations. Here, we comprehensively evaluate the 3D spatial patterns of human germline and somatic variation in 6,604 experimentally derived protein structures and 33,144 computationally derived homology models covering 77% of all human proteins. Using a systematic approach, we quantify differences in the spatial distributions of neutral germline variants, disease-causing germline variants, and recurrent somatic variants. Neutral missense variants exhibit a general trend toward spatial dispersion, which is driven by constraint on core residues. In contrast, germline disease-causing variants are generally clustered in protein structures and form clusters more frequently than recurrent somatic variants identified from tumor sequencing. In total, we identify 215 proteins with significant spatial constraints on the distribution of disease-causing missense variants in experimentally derived protein structures, only 65 (30%) of which have been previously reported. This analysis identifies many clusters not detectable from sequence information alone; only 12% of proteins with significant clustering in 3D were identified from similar analyses of linear protein sequence. Furthermore, spatial analyses of mutations in homology-based structural models are highly correlated with those from experimentally derived structures, supporting the use of computationally derived models. Our approach highlights significant differences in the spatial constraints on different classes of mutations in protein structure and identifies regions of potential function within individual proteins.
    MeSH term(s) Amino Acid Sequence ; Cluster Analysis ; Humans ; Models, Molecular ; Mutation, Missense/genetics ; Proteins/chemistry ; Proteins/genetics
    Chemical Substances Proteins
    Language English
    Publishing date 2018-02-15
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 219384-x
    ISSN 1537-6605 ; 0002-9297
    ISSN (online) 1537-6605
    ISSN 0002-9297
    DOI 10.1016/j.ajhg.2018.01.017
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Knowledge-constrained K-medoids Clustering of Regulatory Rare Alleles for Burden Tests.

    Sivley, R Michael / Fish, Alexandra E / Bush, William S

    Evolutionary computation, machine learning and data mining in bioinformatics. EvoBIO (Conference)

    2014  Volume 7833, Page(s) 35–42

    Abstract: Rarely occurring genetic variants are hypothesized to influence human diseases, but statistically associating these rare variants to disease is challenging due to a lack of statistical power in most feasibly sized datasets. Several statistical tests have ...

    Abstract Rarely occurring genetic variants are hypothesized to influence human diseases, but statistically associating these rare variants to disease is challenging due to a lack of statistical power in most feasibly sized datasets. Several statistical tests have been developed to either collapse multiple rare variants from a genomic region into a single variable (presence/absence) or to tally the number of rare alleles within a region, relating the burden of rare alleles to disease risk. Both these approaches, however, rely on user-specification of a genomic region to generate these collapsed or burden variables, usually an entire gene. Recent studies indicate that most risk variants for common diseases are found within regulatory regions, not genes. To capture the effect of rare alleles within non-genic regulatory regions for burden tests, we contrast a simple sliding window approach with a knowledge-guided k-medoids clustering method to group rare variants into statistically powerful, biologically meaningful windows. We apply these methods to detect genomic regions that alter expression of nearby genes.
    Language English
    Publishing date 2014-08-25
    Publishing country Germany
    Document type Journal Article
    DOI 10.1007/978-3-642-37189-9_4
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Rapid storage and retrieval of genomic intervals from a relational database system using nested containment lists.

    Wiley, Laura K / Sivley, R Michael / Bush, William S

    Database : the journal of biological databases and curation

    2013  Volume 2013, Page(s) bat056

    Abstract: Efficient storage and retrieval of genomic annotations based on range intervals is necessary, given the amount of data produced by next-generation sequencing studies. The indexing strategies of relational database systems (such as MySQL) greatly inhibit ... ...

    Abstract Efficient storage and retrieval of genomic annotations based on range intervals is necessary, given the amount of data produced by next-generation sequencing studies. The indexing strategies of relational database systems (such as MySQL) greatly inhibit their use in genomic annotation tasks. This has led to the development of stand-alone applications that are dependent on flat-file libraries. In this work, we introduce MyNCList, an implementation of the NCList data structure within a MySQL database. MyNCList enables the storage, update and rapid retrieval of genomic annotations from the convenience of a relational database system. Range-based annotations of 1 million variants are retrieved in under a minute, making this approach feasible for whole-genome annotation tasks. Database URL: https://github.com/bushlab/mynclist.
    MeSH term(s) Algorithms ; Database Management Systems ; Databases, Genetic ; Genomics ; Information Storage and Retrieval ; Search Engine
    Language English
    Publishing date 2013-07-26
    Publishing country England
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 2496706-3
    ISSN 1758-0463 ; 1758-0463
    ISSN (online) 1758-0463
    ISSN 1758-0463
    DOI 10.1093/database/bat056
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Integrated Polygenic Tool Substantially Enhances Coronary Artery Disease Prediction.

    Riveros-Mckay, Fernando / Weale, Michael E / Moore, Rachel / Selzam, Saskia / Krapohl, Eva / Sivley, R Michael / Tarran, William A / Sørensen, Peter / Lachapelle, Alexander S / Griffiths, Jonathan A / Saffari, Ayden / Deanfield, John / Spencer, Chris C A / Hippisley-Cox, Julia / Hunter, David J / O'Sullivan, Jack W / Ashley, Euan A / Plagnol, Vincent / Donnelly, Peter

    Circulation. Genomic and precision medicine

    2021  Volume 14, Issue 2, Page(s) e003304

    Abstract: Background: There is considerable interest in whether genetic data can be used to improve standard cardiovascular disease risk calculators, as the latter are routinely used in clinical practice to manage preventative treatment.: Methods: Using the UK ...

    Abstract Background: There is considerable interest in whether genetic data can be used to improve standard cardiovascular disease risk calculators, as the latter are routinely used in clinical practice to manage preventative treatment.
    Methods: Using the UK Biobank resource, we developed our own polygenic risk score for coronary artery disease (CAD). We used an additional 60 000 UK Biobank individuals to develop an integrated risk tool (IRT) that combined our polygenic risk score with established risk tools (either the American Heart Association/American College of Cardiology pooled cohort equations [PCE] or UK QRISK3), and we tested our IRT in an additional, independent set of 186 451 UK Biobank individuals.
    Results: The novel CAD polygenic risk score shows superior predictive power for CAD events, compared with other published polygenic risk scores, and is largely uncorrelated with PCE and QRISK3. When combined with PCE into an IRT, it has superior predictive accuracy. Overall, 10.4% of incident CAD cases were misclassified as low risk by PCE and correctly classified as high risk by the IRT, compared with 4.4% misclassified by the IRT and correctly classified by PCE. The overall net reclassification improvement for the IRT was 5.9% (95% CI, 4.7-7.0). When individuals were stratified into age-by-sex subgroups, the improvement was larger for all subgroups (range, 8.3%-15.4%), with the best performance in 40- to 54-year-old men (15.4% [95% CI, 11.6-19.3]). Comparable results were found using a different risk tool (QRISK3) and also a broader definition of cardiovascular disease. Use of the IRT is estimated to avoid up to 12 000 deaths in the United States over a 5-year period.
    Conclusions: An IRT that includes polygenic risk outperforms current risk stratification tools and offers greater opportunity for early interventions. Given the plummeting costs of genetic tests, future iterations of CAD risk tools would be enhanced with the addition of a person's polygenic risk.
    MeSH term(s) Adult ; Aged ; Coronary Artery Disease/diagnosis ; Coronary Artery Disease/epidemiology ; Coronary Artery Disease/genetics ; Databases, Genetic ; Female ; Genetic Predisposition to Disease ; Humans ; Incidence ; Male ; Middle Aged ; Proportional Hazards Models ; Risk Factors
    Language English
    Publishing date 2021-03-02
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 2574-8300
    ISSN (online) 2574-8300
    DOI 10.1161/CIRCGEN.120.003304
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Validation of an Integrated Risk Tool, Including Polygenic Risk Score, for Atherosclerotic Cardiovascular Disease in Multiple Ethnicities and Ancestries.

    Weale, Michael E / Riveros-Mckay, Fernando / Selzam, Saskia / Seth, Priyanka / Moore, Rachel / Tarran, William A / Gradovich, Eva / Giner-Delgado, Carla / Palmer, Duncan / Wells, Daniel / Saffari, Ayden / Sivley, R Michael / Lachapelle, Alexander S / Wand, Hannah / Clarke, Shoa L / Knowles, Joshua W / O'Sullivan, Jack W / Ashley, Euan A / McVean, Gil /
    Plagnol, Vincent / Donnelly, Peter

    The American journal of cardiology

    2021  Volume 148, Page(s) 157–164

    Abstract: The American College of Cardiology / American Heart Association pooled cohort equations tool (ASCVD-PCE) is currently recommended to assess 10-year risk for atherosclerotic cardiovascular disease (ASCVD). ASCVD-PCE does not currently include genetic risk ...

    Abstract The American College of Cardiology / American Heart Association pooled cohort equations tool (ASCVD-PCE) is currently recommended to assess 10-year risk for atherosclerotic cardiovascular disease (ASCVD). ASCVD-PCE does not currently include genetic risk factors. Polygenic risk scores (PRSs) have been shown to offer a powerful new approach to measuring genetic risk for common diseases, including ASCVD, and to enhance risk prediction when combined with ASCVD-PCE. Most work to date, including the assessment of tools, has focused on performance in individuals of European ancestries. Here we present evidence for the clinical validation of a new integrated risk tool (IRT), ASCVD-IRT, which combines ASCVD-PCE with PRS to predict 10-year risk of ASCVD across diverse ethnicity and ancestry groups. We demonstrate improved predictive performance of ASCVD-IRT over ASCVD-PCE, not only in individuals of self-reported White ethnicities (net reclassification improvement [NRI]; with 95% confidence interval = 2.7% [1.1 to 4.2]) but also Black / African American / Black Caribbean / Black African (NRI = 2.5% [0.6-4.3]) and South Asian (Indian, Bangladeshi or Pakistani) ethnicities (NRI = 8.7% [3.1 to 14.4]). NRI confidence intervals were wider and included zero for ethnicities with smaller sample sizes, including Hispanic (NRI = 7.5% [-1.4 to 16.5]), but PRS effect sizes in these ethnicities were significant and of comparable size to those seen in individuals of White ethnicities. Comparable results were obtained when individuals were analyzed by genetically inferred ancestry. Together, these results validate the performance of ASCVD-IRT in multiple ethnicities and ancestries, and favor their generalization to all ethnicities and ancestries.
    MeSH term(s) Adult ; African Continental Ancestry Group ; Aged ; Asia, Western ; Asian Continental Ancestry Group ; Atherosclerosis/epidemiology ; Atherosclerosis/ethnology ; Atherosclerosis/genetics ; Cohort Studies ; European Continental Ancestry Group ; Female ; Genetic Predisposition to Disease ; Heart Disease Risk Factors ; Humans ; Male ; Middle Aged ; Reproducibility of Results
    Language English
    Publishing date 2021-03-03
    Publishing country United States
    Document type Journal Article ; Validation Study
    ZDB-ID 80014-4
    ISSN 1879-1913 ; 0002-9149
    ISSN (online) 1879-1913
    ISSN 0002-9149
    DOI 10.1016/j.amjcard.2021.02.032
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  6. Article ; Online: Three-dimensional spatial analysis of missense variants in RTEL1 identifies pathogenic variants in patients with Familial Interstitial Pneumonia.

    Sivley, R Michael / Sheehan, Jonathan H / Kropski, Jonathan A / Cogan, Joy / Blackwell, Timothy S / Phillips, John A / Bush, William S / Meiler, Jens / Capra, John A

    BMC bioinformatics

    2018  Volume 19, Issue 1, Page(s) 18

    Abstract: Background: Next-generation sequencing of individuals with genetic diseases often detects candidate rare variants in numerous genes, but determining which are causal remains challenging. We hypothesized that the spatial distribution of missense variants ...

    Abstract Background: Next-generation sequencing of individuals with genetic diseases often detects candidate rare variants in numerous genes, but determining which are causal remains challenging. We hypothesized that the spatial distribution of missense variants in protein structures contains information about function and pathogenicity that can help prioritize variants of unknown significance (VUS) and elucidate the structural mechanisms leading to disease.
    Results: To illustrate this approach in a clinical application, we analyzed 13 candidate missense variants in regulator of telomere elongation helicase 1 (RTEL1) identified in patients with Familial Interstitial Pneumonia (FIP). We curated pathogenic and neutral RTEL1 variants from the literature and public databases. We then used homology modeling to construct a 3D structural model of RTEL1 and mapped known variants into this structure. We next developed a pathogenicity prediction algorithm based on proximity to known disease causing and neutral variants and evaluated its performance with leave-one-out cross-validation. We further validated our predictions with segregation analyses, telomere lengths, and mutagenesis data from the homologous XPD protein. Our algorithm for classifying RTEL1 VUS based on spatial proximity to pathogenic and neutral variation accurately distinguished 7 known pathogenic from 29 neutral variants (ROC AUC = 0.85) in the N-terminal domains of RTEL1. Pathogenic proximity scores were also significantly correlated with effects on ATPase activity (Pearson r = -0.65, p = 0.0004) in XPD, a related helicase. Applying the algorithm to 13 VUS identified from sequencing of RTEL1 from patients predicted five out of six disease-segregating VUS to be pathogenic. We provide structural hypotheses regarding how these mutations may disrupt RTEL1 ATPase and helicase function.
    Conclusions: Spatial analysis of missense variation accurately classified candidate VUS in RTEL1 and suggests how such variants cause disease. Incorporating spatial proximity analyses into other pathogenicity prediction tools may improve accuracy for other genes and genetic diseases.
    MeSH term(s) Algorithms ; Area Under Curve ; DNA Helicases/chemistry ; DNA Helicases/genetics ; DNA Helicases/metabolism ; Humans ; Lung Diseases, Interstitial/genetics ; Lung Diseases, Interstitial/pathology ; Mutation, Missense ; Protein Structure, Tertiary ; ROC Curve ; Spatial Analysis
    Chemical Substances RTEL1 protein, human (EC 3.6.1.-) ; DNA Helicases (EC 3.6.4.-)
    Language English
    Publishing date 2018-01-23
    Publishing country England
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 2041484-5
    ISSN 1471-2105 ; 1471-2105
    ISSN (online) 1471-2105
    ISSN 1471-2105
    DOI 10.1186/s12859-018-2010-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: SIRT4 Is a Lysine Deacylase that Controls Leucine Metabolism and Insulin Secretion.

    Anderson, Kristin A / Huynh, Frank K / Fisher-Wellman, Kelsey / Stuart, J Darren / Peterson, Brett S / Douros, Jonathan D / Wagner, Gregory R / Thompson, J Will / Madsen, Andreas S / Green, Michelle F / Sivley, R Michael / Ilkayeva, Olga R / Stevens, Robert D / Backos, Donald S / Capra, John A / Olsen, Christian A / Campbell, Jonathan E / Muoio, Deborah M / Grimsrud, Paul A /
    Hirschey, Matthew D

    Cell metabolism

    2017  Volume 25, Issue 4, Page(s) 838–855.e15

    Abstract: Sirtuins are ... ...

    Abstract Sirtuins are NAD
    MeSH term(s) Amidohydrolases/metabolism ; Amino Acid Sequence ; Animals ; Carbon-Carbon Ligases/metabolism ; Glucose/metabolism ; HEK293 Cells ; Homeostasis ; Humans ; Insulin/metabolism ; Insulin Resistance ; Insulin Secretion ; Leucine/metabolism ; Lysine/metabolism ; Metabolic Flux Analysis ; Mice, Inbred C57BL ; Mice, Knockout ; Mitochondrial Proteins/chemistry ; Mitochondrial Proteins/metabolism ; Models, Molecular ; Phylogeny ; Sirtuins/chemistry ; Sirtuins/metabolism
    Chemical Substances Insulin ; Mitochondrial Proteins ; Amidohydrolases (EC 3.5.-) ; SIRT4 protein, mouse (EC 3.5.1.-) ; Sirtuins (EC 3.5.1.-) ; Carbon-Carbon Ligases (EC 6.4.-) ; methylcrotonoyl-CoA carboxylase (EC 6.4.1.4) ; Leucine (GMW67QNF9C) ; Glucose (IY9XDZ35W2) ; Lysine (K3Z4F929H6)
    Language English
    Publishing date 2017-04-06
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2176834-1
    ISSN 1932-7420 ; 1550-4131
    ISSN (online) 1932-7420
    ISSN 1550-4131
    DOI 10.1016/j.cmet.2017.03.003
    Database MEDical Literature Analysis and Retrieval System OnLINE

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