Ingham A

References (3)

Title : An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility - Wang_2021_Genome.Med_13_83
Author(s) : Wang L , Balmat TJ , Antonia AL , Constantine FJ , Henao R , Burke TW , Ingham A , McClain MT , Tsalik EL , Ko ER , Ginsburg GS , DeLong MR , Shen X , Woods CW , Hauser ER , Ko DC
Ref : Genome Med , 13 :83 , 2021
Abstract : BACKGROUND: While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility. RESULTS: Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb)) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs associated with both severe COVID-19 and other human traits demonstrated colocalization of the GWAS signal at the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN). This finding points to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity. CONCLUSIONS: Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches. The iCPAGdb web portal is accessible at http://cpag.oit.duke.edu and the software code at https://github.com/tbalmat/iCPAGdb .
ESTHER : Wang_2021_Genome.Med_13_83
PubMedSearch : Wang_2021_Genome.Med_13_83
PubMedID: 34001247

Title : An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility - Wang_2020_Medrxiv__
Author(s) : Wang L , Balmat TJ , Antonia AL , Constantine FJ , Henao R , Burke TW , Ingham A , McClain MT , Tsalik EL , Ko ER , Ginsburg GS , DeLong MR , Shen X , Woods CW , Hauser ER , Ko DC
Ref : Medrxiv , : , 2020
Abstract : While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility. Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb); http://cpag.oit.duke.edu ) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs with severe COVID-19 demonstrated colocalization of the GWAS signal of the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN), pointing to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity. Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches.
ESTHER : Wang_2020_Medrxiv__
PubMedSearch : Wang_2020_Medrxiv__
PubMedID: 33398303

Title : The genome sequence of taurine cattle: a window to ruminant biology and evolution - Elsik_2009_Science_324_522
Author(s) : Elsik CG , Tellam RL , Worley KC , Gibbs RA , Muzny DM , Weinstock GM , Adelson DL , Eichler EE , Elnitski L , Guigo R , Hamernik DL , Kappes SM , Lewin HA , Lynn DJ , Nicholas FW , Reymond A , Rijnkels M , Skow LC , Zdobnov EM , Schook L , Womack J , Alioto T , Antonarakis SE , Astashyn A , Chapple CE , Chen HC , Chrast J , Camara F , Ermolaeva O , Henrichsen CN , Hlavina W , Kapustin Y , Kiryutin B , Kitts P , Kokocinski F , Landrum M , Maglott D , Pruitt K , Sapojnikov V , Searle SM , Solovyev V , Souvorov A , Ucla C , Wyss C , Anzola JM , Gerlach D , Elhaik E , Graur D , Reese JT , Edgar RC , McEwan JC , Payne GM , Raison JM , Junier T , Kriventseva EV , Eyras E , Plass M , Donthu R , Larkin DM , Reecy J , Yang MQ , Chen L , Cheng Z , Chitko-McKown CG , Liu GE , Matukumalli LK , Song J , Zhu B , Bradley DG , Brinkman FS , Lau LP , Whiteside MD , Walker A , Wheeler TT , Casey T , German JB , Lemay DG , Maqbool NJ , Molenaar AJ , Seo S , Stothard P , Baldwin CL , Baxter R , Brinkmeyer-Langford CL , Brown WC , Childers CP , Connelley T , Ellis SA , Fritz K , Glass EJ , Herzig CT , Iivanainen A , Lahmers KK , Bennett AK , Dickens CM , Gilbert JG , Hagen DE , Salih H , Aerts J , Caetano AR , Dalrymple B , Garcia JF , Gill CA , Hiendleder SG , Memili E , Spurlock D , Williams JL , Alexander L , Brownstein MJ , Guan L , Holt RA , Jones SJ , Marra MA , Moore R , Moore SS , Roberts A , Taniguchi M , Waterman RC , Chacko J , Chandrabose MM , Cree A , Dao MD , Dinh HH , Gabisi RA , Hines S , Hume J , Jhangiani SN , Joshi V , Kovar CL , Lewis LR , Liu YS , Lopez J , Morgan MB , Nguyen NB , Okwuonu GO , Ruiz SJ , Santibanez J , Wright RA , Buhay C , Ding Y , Dugan-Rocha S , Herdandez J , Holder M , Sabo A , Egan A , Goodell J , Wilczek-Boney K , Fowler GR , Hitchens ME , Lozado RJ , Moen C , Steffen D , Warren JT , Zhang J , Chiu R , Schein JE , Durbin KJ , Havlak P , Jiang H , Liu Y , Qin X , Ren Y , Shen Y , Song H , Bell SN , Davis C , Johnson AJ , Lee S , Nazareth LV , Patel BM , Pu LL , Vattathil S , Williams RL, Jr. , Curry S , Hamilton C , Sodergren E , Wheeler DA , Barris W , Bennett GL , Eggen A , Green RD , Harhay GP , Hobbs M , Jann O , Keele JW , Kent MP , Lien S , McKay SD , McWilliam S , Ratnakumar A , Schnabel RD , Smith T , Snelling WM , Sonstegard TS , Stone RT , Sugimoto Y , Takasuga A , Taylor JF , Van Tassell CP , Macneil MD , Abatepaulo AR , Abbey CA , Ahola V , Almeida IG , Amadio AF , Anatriello E , Bahadue SM , Biase FH , Boldt CR , Carroll JA , Carvalho WA , Cervelatti EP , Chacko E , Chapin JE , Cheng Y , Choi J , Colley AJ , de Campos TA , De Donato M , Santos IK , de Oliveira CJ , Deobald H , Devinoy E , Donohue KE , Dovc P , Eberlein A , Fitzsimmons CJ , Franzin AM , Garcia GR , Genini S , Gladney CJ , Grant JR , Greaser ML , Green JA , Hadsell DL , Hakimov HA , Halgren R , Harrow JL , Hart EA , Hastings N , Hernandez M , Hu ZL , Ingham A , Iso-Touru T , Jamis C , Jensen K , Kapetis D , Kerr T , Khalil SS , Khatib H , Kolbehdari D , Kumar CG , Kumar D , Leach R , Lee JC , Li C , Logan KM , Malinverni R , Marques E , Martin WF , Martins NF , Maruyama SR , Mazza R , McLean KL , Medrano JF , Moreno BT , More DD , Muntean CT , Nandakumar HP , Nogueira MF , Olsaker I , Pant SD , Panzitta F , Pastor RC , Poli MA , Poslusny N , Rachagani S , Ranganathan S , Razpet A , Riggs PK , Rincon G , Rodriguez-Osorio N , Rodriguez-Zas SL , Romero NE , Rosenwald A , Sando L , Schmutz SM , Shen L , Sherman L , Southey BR , Lutzow YS , Sweedler JV , Tammen I , Telugu BP , Urbanski JM , Utsunomiya YT , Verschoor CP , Waardenberg AJ , Wang Z , Ward R , Weikard R , Welsh TH, Jr. , White SN , Wilming LG , Wunderlich KR , Yang J , Zhao FQ
Ref : Science , 324 :522 , 2009
Abstract : To understand the biology and evolution of ruminants, the cattle genome was sequenced to about sevenfold coverage. The cattle genome contains a minimum of 22,000 genes, with a core set of 14,345 orthologs shared among seven mammalian species of which 1217 are absent or undetected in noneutherian (marsupial or monotreme) genomes. Cattle-specific evolutionary breakpoint regions in chromosomes have a higher density of segmental duplications, enrichment of repetitive elements, and species-specific variations in genes associated with lactation and immune responsiveness. Genes involved in metabolism are generally highly conserved, although five metabolic genes are deleted or extensively diverged from their human orthologs. The cattle genome sequence thus provides a resource for understanding mammalian evolution and accelerating livestock genetic improvement for milk and meat production.
ESTHER : Elsik_2009_Science_324_522
PubMedSearch : Elsik_2009_Science_324_522
PubMedID: 19390049
Gene_locus related to this paper: bovin-2neur , bovin-a0jnh8 , bovin-a5d7b7 , bovin-ACHE , bovin-balip , bovin-dpp4 , bovin-dpp6 , bovin-e1bi31 , bovin-e1bn79 , bovin-est8 , bovin-f1mbd6 , bovin-f1mi11 , bovin-f1mr65 , bovin-f1n1l4 , bovin-g3mxp5 , bovin-q0vcc8 , bovin-q2kj30 , bovin-q3t0r6 , bovin-thyro