Pathway Analysis Integrating Genome-Wide and Functional Data Identifies PLCG2 as a Candidate Gene for Age-Related Macular Degeneration

Int Age-Related Macular Degenerati

Research output: Contribution to journalArticle

Abstract

PURPOSE. Age-related macular degeneration (AMD) is the worldwide leading cause of blindness among the elderly. Although genome-wide association studies (GWAS) have identified AMD risk variants, their roles in disease etiology are not well-characterized, and they only explain a portion of AMD heritability.

METHODS. We performed pathway analyses using summary statistics from the International AMD Genomics Consortium's 2016 GWAS and multiple pathway databases to identify biological pathways wherein genetic association signals for AMD may be aggregating. We determined which genes contributed most to significant pathway signals across the databases. We characterized these genes by constructing protein-protein interaction networks and performing motif analysis.

RESULTS. We determined that eight genes (C2, C3, LIPC, MICA, NOTCH4, PLCG2, PPARA, and RAD51B) "drive'' the statistical signals observed across pathways curated in the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and Gene Ontology (GO) databases. We further refined our definition of statistical driver gene to identify PLCG2 as a candidate gene for AMD due to its significant gene-level signals (P

CONCLUSIONS. We performed pathway analyses on the largest available collection of advanced AMD cases and controls in the world. Eight genes strongly contributed to significant pathways from the three larger databases, and one gene (PLCG2) was central to significant pathways from all four databases. This is, to our knowledge, the first study to identify PLCG2 as a candidate gene for AMD based solely on genetic burden. Our findings reinforce the utility of integrating in silico genetic and biological pathway data to investigate the genetic architecture of AMD.

Original languageEnglish
Pages (from-to)4041-4051
Number of pages11
JournalInvestigative ophthalmology & visual science
Volume60
Issue number12
DOIs
Publication statusPublished - Sep 2019

Cite this

@article{eb3f876848bc4fc69865a7186deea4d3,
title = "Pathway Analysis Integrating Genome-Wide and Functional Data Identifies PLCG2 as a Candidate Gene for Age-Related Macular Degeneration",
abstract = "PURPOSE. Age-related macular degeneration (AMD) is the worldwide leading cause of blindness among the elderly. Although genome-wide association studies (GWAS) have identified AMD risk variants, their roles in disease etiology are not well-characterized, and they only explain a portion of AMD heritability.METHODS. We performed pathway analyses using summary statistics from the International AMD Genomics Consortium's 2016 GWAS and multiple pathway databases to identify biological pathways wherein genetic association signals for AMD may be aggregating. We determined which genes contributed most to significant pathway signals across the databases. We characterized these genes by constructing protein-protein interaction networks and performing motif analysis.RESULTS. We determined that eight genes (C2, C3, LIPC, MICA, NOTCH4, PLCG2, PPARA, and RAD51B) {"}drive'' the statistical signals observed across pathways curated in the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and Gene Ontology (GO) databases. We further refined our definition of statistical driver gene to identify PLCG2 as a candidate gene for AMD due to its significant gene-level signals (P CONCLUSIONS. We performed pathway analyses on the largest available collection of advanced AMD cases and controls in the world. Eight genes strongly contributed to significant pathways from the three larger databases, and one gene (PLCG2) was central to significant pathways from all four databases. This is, to our knowledge, the first study to identify PLCG2 as a candidate gene for AMD based solely on genetic burden. Our findings reinforce the utility of integrating in silico genetic and biological pathway data to investigate the genetic architecture of AMD.",
keywords = "age-related macular degeneration, pathway analysis, genome-wide association study, database, phospholipase C gamma 2, GROWTH-FACTOR RECEPTOR, PHOSPHATIDYLINOSITOL 3-KINASE, CELL-SURVIVAL, ACTIVATION, ASSOCIATION, VARIANTS, NETWORKS, THERAPY, RARE",
author = "{Int Age-Related Macular Degenerati} and Waksmunski, {Andrea R.} and Michelle Grunin and Kinzy, {Tyler G.} and Igo, {Robert P.} and Haines, {Jonathan L.} and Bailey, {Jessica N. Cooke} and Fritsche, {Lars G.} and Wilmar Igl and Felix Grassmann and Sebanti Sengupta and Bragg-Gresham, {Jennifer L.} and Burdon, {Kathryn P.} and Hebbring, {Scott J.} and Cindy Wen and Mathias Gorski and Kim, {Ivana K.} and David Cho and Donald Zack and Eric Souied and Scholl, {Hendrik P. N.} and Elisa Bala and Lee, {Kristine E.} and Hunter, {David J.} and Sardell, {Rebecca J.} and Paul Mitchell and Merriam, {Joanna E.} and Valentina Cipriani and Hoffman, {Joshua D.} and Tina Schick and Lechanteur, {Yara T. E.} and Guymer, {Robyn H.} and Johnson, {Matthew P.} and Yingda Jiang and Stanton, {Chloe M.} and Buitendijk, {Gabrielle H. S.} and Xiaowei Zhan and Kwong, {Alan M.} and Alexis Boleda and Matthew Brooks and Linn Gieser and Rinki Ratnapriya and Branham, {Kari E.} and Foerster, {Johanna R.} and Heckenlively, {John R.} and Mohammad Othman and Vote, {Brendan J.} and Liang, {Helena Hai} and Emmanuelle Souzeau and McAllister, {Ian L.} and Timothy Isaacs and Janette Hall and Stewart Lake and Mackey, {David A.} and Constable, {Ian J.} and Craig, {Jamie E.} and Kitchner, {Terrie E.} and Zhenglin Yang and Zhiguang Su and Hongrong Luo and Daniel Chen and Hong Ouyang and Ken Flagg and Danni Lin and Guanping Mao and Henry Ferreyra and Klaus Stark and {von Strachwitz}, {Claudia N.} and Armin Wolf and Caroline Brandl and Guenther Rudolph and Matthias Olden and Morrison, {Margaux A.} and Morgan, {Denise J.} and Matthew Schu and Jeeyun Ahn and Giuliana Silvestri and Tsironi, {Evangelia E.} and Park, {Kyu Hyung} and Farrer, {Lindsay A.} and Anton Orlin and Alexander Brucker and Mingyao Li and Curcio, {Christine A.} and Saddek Mohand-Said and Jose-Alain Sahel and Isabelle Audo and Mustapha Benchaboune and Cree, {Angela J.} and Rennie, {Christina A.} and Srinivas Goverdhan and Shira Hagbi-Levi and Peter Campochiaro and Nicholas Katsanis and Holz, {Frank G.} and Frederic Blond and Helene Blanche and Jean-Francois Deleuze and Barbara Truitt and Peachey, {Neal S.} and Meuer, {Stacy M.} and Myers, {Chelsea E.} and Moore, {Emily L.} and Ronald Klein and Hauser, {Michael A.} and Postel, {Eric A.} and Courtenay, {Monique D.} and Schwartz, {Stephen G.} and Kovach, {Jaclyn L.} and Scott, {William K.} and Gerald Liew and Tan, {Ava G.} and Bamini Gopinath and Merriam, {John C.} and Smith, {R. Theodore} and Khan, {Jane C.} and Humma Shahid and Moore, {Anthony T.} and McGrath, {J. Allie} and Renee Laux and Brantley, {Milam A.} and Anita Agarwal and Lebriz Ersoy and Albert Caramoy and Thomas Langmann and Saksens, {Nicole T. M.} and {de Jong}, {Eiko K.} and Hoyng, {Carel B.} and Cain, {Melinda S.} and Richardson, {Andrea J.} and Martin, {Tammy M.} and John Blangero and Weeks, {Daniel E.} and Bal Dhillon and {van Duijn}, {Cornelia M.} and Doheny, {Kimberly F.} and Jane Romm and Klaver, {Caroline C. W.} and Caroline Hayward and Gorin, {Michael B.} and Klein, {Michael L.} and Baird, {Paul N.} and {den Hollander}, Anneke and Sascha Fauser and Yates, {John R. W.} and Rando Allikmets and Wang, {Jie Jin} and Schaumberg, {Debra A.} and Klein, {Barbara E. K.} and Hagstrom, {Stephanie A.} and Itay Chowers and Lotery, {Andrew J.} and Thierry Leveillard and Kang Zhang and Brilliant, {Murray H.} and Hewitt, {Alex W.} and Anand Swaroop and Chew, {Emily Y.} and Pericak-Vance, {Margaret A.} and Margaret DeAngelis and Dwight Stambolian and Iyengar, {Sudha K.} and Weber, {Bernhard H. F.} and Abecasis, {Goncalo R.} and Heid, {Iris M.}",
year = "2019",
month = "9",
doi = "10.1167/iovs.19-27827",
language = "English",
volume = "60",
pages = "4041--4051",
journal = "Investigative Ophthalmology & Visual Science (IOVS)",
issn = "0146-0404",
publisher = "Association for Research in Vision and Ophthalmology (ARVO)",
number = "12",

}

Pathway Analysis Integrating Genome-Wide and Functional Data Identifies PLCG2 as a Candidate Gene for Age-Related Macular Degeneration. / Int Age-Related Macular Degenerati.

In: Investigative ophthalmology & visual science, Vol. 60, No. 12, 09.2019, p. 4041-4051.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Pathway Analysis Integrating Genome-Wide and Functional Data Identifies PLCG2 as a Candidate Gene for Age-Related Macular Degeneration

AU - Int Age-Related Macular Degenerati

AU - Waksmunski, Andrea R.

AU - Grunin, Michelle

AU - Kinzy, Tyler G.

AU - Igo, Robert P.

AU - Haines, Jonathan L.

AU - Bailey, Jessica N. Cooke

AU - Fritsche, Lars G.

AU - Igl, Wilmar

AU - Grassmann, Felix

AU - Sengupta, Sebanti

AU - Bragg-Gresham, Jennifer L.

AU - Burdon, Kathryn P.

AU - Hebbring, Scott J.

AU - Wen, Cindy

AU - Gorski, Mathias

AU - Kim, Ivana K.

AU - Cho, David

AU - Zack, Donald

AU - Souied, Eric

AU - Scholl, Hendrik P. N.

AU - Bala, Elisa

AU - Lee, Kristine E.

AU - Hunter, David J.

AU - Sardell, Rebecca J.

AU - Mitchell, Paul

AU - Merriam, Joanna E.

AU - Cipriani, Valentina

AU - Hoffman, Joshua D.

AU - Schick, Tina

AU - Lechanteur, Yara T. E.

AU - Guymer, Robyn H.

AU - Johnson, Matthew P.

AU - Jiang, Yingda

AU - Stanton, Chloe M.

AU - Buitendijk, Gabrielle H. S.

AU - Zhan, Xiaowei

AU - Kwong, Alan M.

AU - Boleda, Alexis

AU - Brooks, Matthew

AU - Gieser, Linn

AU - Ratnapriya, Rinki

AU - Branham, Kari E.

AU - Foerster, Johanna R.

AU - Heckenlively, John R.

AU - Othman, Mohammad

AU - Vote, Brendan J.

AU - Liang, Helena Hai

AU - Souzeau, Emmanuelle

AU - McAllister, Ian L.

AU - Isaacs, Timothy

AU - Hall, Janette

AU - Lake, Stewart

AU - Mackey, David A.

AU - Constable, Ian J.

AU - Craig, Jamie E.

AU - Kitchner, Terrie E.

AU - Yang, Zhenglin

AU - Su, Zhiguang

AU - Luo, Hongrong

AU - Chen, Daniel

AU - Ouyang, Hong

AU - Flagg, Ken

AU - Lin, Danni

AU - Mao, Guanping

AU - Ferreyra, Henry

AU - Stark, Klaus

AU - von Strachwitz, Claudia N.

AU - Wolf, Armin

AU - Brandl, Caroline

AU - Rudolph, Guenther

AU - Olden, Matthias

AU - Morrison, Margaux A.

AU - Morgan, Denise J.

AU - Schu, Matthew

AU - Ahn, Jeeyun

AU - Silvestri, Giuliana

AU - Tsironi, Evangelia E.

AU - Park, Kyu Hyung

AU - Farrer, Lindsay A.

AU - Orlin, Anton

AU - Brucker, Alexander

AU - Li, Mingyao

AU - Curcio, Christine A.

AU - Mohand-Said, Saddek

AU - Sahel, Jose-Alain

AU - Audo, Isabelle

AU - Benchaboune, Mustapha

AU - Cree, Angela J.

AU - Rennie, Christina A.

AU - Goverdhan, Srinivas

AU - Hagbi-Levi, Shira

AU - Campochiaro, Peter

AU - Katsanis, Nicholas

AU - Holz, Frank G.

AU - Blond, Frederic

AU - Blanche, Helene

AU - Deleuze, Jean-Francois

AU - Truitt, Barbara

AU - Peachey, Neal S.

AU - Meuer, Stacy M.

AU - Myers, Chelsea E.

AU - Moore, Emily L.

AU - Klein, Ronald

AU - Hauser, Michael A.

AU - Postel, Eric A.

AU - Courtenay, Monique D.

AU - Schwartz, Stephen G.

AU - Kovach, Jaclyn L.

AU - Scott, William K.

AU - Liew, Gerald

AU - Tan, Ava G.

AU - Gopinath, Bamini

AU - Merriam, John C.

AU - Smith, R. Theodore

AU - Khan, Jane C.

AU - Shahid, Humma

AU - Moore, Anthony T.

AU - McGrath, J. Allie

AU - Laux, Renee

AU - Brantley, Milam A.

AU - Agarwal, Anita

AU - Ersoy, Lebriz

AU - Caramoy, Albert

AU - Langmann, Thomas

AU - Saksens, Nicole T. M.

AU - de Jong, Eiko K.

AU - Hoyng, Carel B.

AU - Cain, Melinda S.

AU - Richardson, Andrea J.

AU - Martin, Tammy M.

AU - Blangero, John

AU - Weeks, Daniel E.

AU - Dhillon, Bal

AU - van Duijn, Cornelia M.

AU - Doheny, Kimberly F.

AU - Romm, Jane

AU - Klaver, Caroline C. W.

AU - Hayward, Caroline

AU - Gorin, Michael B.

AU - Klein, Michael L.

AU - Baird, Paul N.

AU - den Hollander, Anneke

AU - Fauser, Sascha

AU - Yates, John R. W.

AU - Allikmets, Rando

AU - Wang, Jie Jin

AU - Schaumberg, Debra A.

AU - Klein, Barbara E. K.

AU - Hagstrom, Stephanie A.

AU - Chowers, Itay

AU - Lotery, Andrew J.

AU - Leveillard, Thierry

AU - Zhang, Kang

AU - Brilliant, Murray H.

AU - Hewitt, Alex W.

AU - Swaroop, Anand

AU - Chew, Emily Y.

AU - Pericak-Vance, Margaret A.

AU - DeAngelis, Margaret

AU - Stambolian, Dwight

AU - Iyengar, Sudha K.

AU - Weber, Bernhard H. F.

AU - Abecasis, Goncalo R.

AU - Heid, Iris M.

PY - 2019/9

Y1 - 2019/9

N2 - PURPOSE. Age-related macular degeneration (AMD) is the worldwide leading cause of blindness among the elderly. Although genome-wide association studies (GWAS) have identified AMD risk variants, their roles in disease etiology are not well-characterized, and they only explain a portion of AMD heritability.METHODS. We performed pathway analyses using summary statistics from the International AMD Genomics Consortium's 2016 GWAS and multiple pathway databases to identify biological pathways wherein genetic association signals for AMD may be aggregating. We determined which genes contributed most to significant pathway signals across the databases. We characterized these genes by constructing protein-protein interaction networks and performing motif analysis.RESULTS. We determined that eight genes (C2, C3, LIPC, MICA, NOTCH4, PLCG2, PPARA, and RAD51B) "drive'' the statistical signals observed across pathways curated in the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and Gene Ontology (GO) databases. We further refined our definition of statistical driver gene to identify PLCG2 as a candidate gene for AMD due to its significant gene-level signals (P CONCLUSIONS. We performed pathway analyses on the largest available collection of advanced AMD cases and controls in the world. Eight genes strongly contributed to significant pathways from the three larger databases, and one gene (PLCG2) was central to significant pathways from all four databases. This is, to our knowledge, the first study to identify PLCG2 as a candidate gene for AMD based solely on genetic burden. Our findings reinforce the utility of integrating in silico genetic and biological pathway data to investigate the genetic architecture of AMD.

AB - PURPOSE. Age-related macular degeneration (AMD) is the worldwide leading cause of blindness among the elderly. Although genome-wide association studies (GWAS) have identified AMD risk variants, their roles in disease etiology are not well-characterized, and they only explain a portion of AMD heritability.METHODS. We performed pathway analyses using summary statistics from the International AMD Genomics Consortium's 2016 GWAS and multiple pathway databases to identify biological pathways wherein genetic association signals for AMD may be aggregating. We determined which genes contributed most to significant pathway signals across the databases. We characterized these genes by constructing protein-protein interaction networks and performing motif analysis.RESULTS. We determined that eight genes (C2, C3, LIPC, MICA, NOTCH4, PLCG2, PPARA, and RAD51B) "drive'' the statistical signals observed across pathways curated in the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and Gene Ontology (GO) databases. We further refined our definition of statistical driver gene to identify PLCG2 as a candidate gene for AMD due to its significant gene-level signals (P CONCLUSIONS. We performed pathway analyses on the largest available collection of advanced AMD cases and controls in the world. Eight genes strongly contributed to significant pathways from the three larger databases, and one gene (PLCG2) was central to significant pathways from all four databases. This is, to our knowledge, the first study to identify PLCG2 as a candidate gene for AMD based solely on genetic burden. Our findings reinforce the utility of integrating in silico genetic and biological pathway data to investigate the genetic architecture of AMD.

KW - age-related macular degeneration

KW - pathway analysis

KW - genome-wide association study

KW - database

KW - phospholipase C gamma 2

KW - GROWTH-FACTOR RECEPTOR

KW - PHOSPHATIDYLINOSITOL 3-KINASE

KW - CELL-SURVIVAL

KW - ACTIVATION

KW - ASSOCIATION

KW - VARIANTS

KW - NETWORKS

KW - THERAPY

KW - RARE

U2 - 10.1167/iovs.19-27827

DO - 10.1167/iovs.19-27827

M3 - Article

VL - 60

SP - 4041

EP - 4051

JO - Investigative Ophthalmology & Visual Science (IOVS)

JF - Investigative Ophthalmology & Visual Science (IOVS)

SN - 0146-0404

IS - 12

ER -