Genome-wide association study of Alzheimer's disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset

Shengjun Hong; Dmitry Prokopenko; Valerija Dobricic; Fabian Kilpert; Isabelle Bos; Stephanie J. B. Vos; Betty M. Tijms; Ulf Andreasson; Kaj Blennow; Rik Vandenberghe; Isabelle Cleynen; Silvy Gabel; Jolien Schaeverbeke; Philip Scheltens; Charlotte E. Teunissen; Ellis Niemantsverdriet; Sebastiaan Engelborghs; Giovanni Frisoni; Olivier Blin; Jill C. Richardson; Regis Bordet; Jose Luis Molinuevo; Lorena Rami; Petronella Kettunen; Anders Wallin; Alberto Lleo; Isabel Sala; Julius Popp; Gwendoline Peyratout; Pablo Martinez-Lage; Mikel Tainta; Richard J. B. Dobson; Cristina Legido-Quigley; Kristel Sleegers; Christine Van Broeckhoven; Mara ten Kate; Frederik Barkhof; Henrik Zetterberg; Simon Lovestone; Johannes Streffer; Michael Wittig; Andre Franke; Rudolph E. Tanzi; Pieter Jelle Visser; Lars Bertram; Alzheimer's Disease Neuroimaging Initiative

doi:10.1038/s41398-020-01074-z

Genome-wide association study of Alzheimer's disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset

Shengjun Hong, Dmitry Prokopenko, Valerija Dobricic, Fabian Kilpert, Isabelle Bos, Stephanie J. B. Vos, Betty M. Tijms, Ulf Andreasson, Kaj Blennow, Rik Vandenberghe, Isabelle Cleynen, Silvy Gabel, Jolien Schaeverbeke, Philip Scheltens, Charlotte E. Teunissen, Ellis Niemantsverdriet, Sebastiaan Engelborghs, Giovanni Frisoni, Olivier Blin, Jill C. RichardsonRegis Bordet, Jose Luis Molinuevo, Lorena Rami, Petronella Kettunen, Anders Wallin, Alberto Lleo, Isabel Sala, Julius Popp, Gwendoline Peyratout, Pablo Martinez-Lage, Mikel Tainta, Richard J. B. Dobson, Cristina Legido-Quigley, Kristel Sleegers, Christine Van Broeckhoven, Mara ten Kate, Frederik Barkhof, Henrik Zetterberg, Simon Lovestone, Johannes Streffer, Michael Wittig, Andre Franke, Rudolph E. Tanzi, Pieter Jelle Visser, Lars Bertram^*, Alzheimer's Disease Neuroimaging Initiative

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Susceptibility to AD is considerably determined by genetic factors which hitherto were primarily identified using case-control designs. Elucidating the genetic architecture of additional AD-related phenotypic traits, ideally those linked to the underlying disease process, holds great promise in gaining deeper insights into the genetic basis of AD and in developing better clinical prediction models. To this end, we generated genome-wide single-nucleotide polymorphism (SNP) genotyping data in 931 participants of the European Medical Information Framework Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) sample to search for novel genetic determinants of AD biomarker variability. Specifically, we performed genome-wide association study (GWAS) analyses on 16 traits, including 14 measures derived from quantifications of five separate amyloid-beta (A beta) and tau-protein species in the cerebrospinal fluid (CSF). In addition to confirming the well-established effects of apolipoprotein E (APOE) on diagnostic outcome and phenotypes related to A beta 42, we detected novel potential signals in the zinc finger homeobox 3 (ZFHX3) for CSF-A beta 38 and CSF-A beta 40 levels, and confirmed the previously described sex-specific association between SNPs in geminin coiled-coil domain containing (GMNC) and CSF-tau. Utilizing the results from independent case-control AD GWAS to construct polygenic risk scores (PRS) revealed that AD risk variants only explain a small fraction of CSF biomarker variability. In conclusion, our study represents a detailed first account of GWAS analyses on CSF-A beta and -tau-related traits in the EMIF-AD MBD dataset. In subsequent work, we will utilize the genomics data generated here in GWAS of other AD-relevant clinical outcomes ascertained in this unique dataset.

Original language	English
Article number	403
Number of pages	12
Journal	Translational Psychiatry
Volume	10
Issue number	1
DOIs	https://doi.org/10.1038/s41398-020-01074-z
Publication status	Published - 22 Dec 2020

Keywords

RISK VARIANTS
SUSCEPTIBILITY LOCI
TAU

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10.1038/s41398-020-01074-zLicence: CC BY

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Hong, S., Prokopenko, D., Dobricic, V., Kilpert, F., Bos, I., Vos, S. J. B., Tijms, B. M., Andreasson, U., Blennow, K., Vandenberghe, R., Cleynen, I., Gabel, S., Schaeverbeke, J., Scheltens, P., Teunissen, C. E., Niemantsverdriet, E., Engelborghs, S., Frisoni, G., Blin, O., ... Alzheimer's Disease Neuroimaging Initiative (2020). Genome-wide association study of Alzheimer's disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset. Translational Psychiatry, 10(1), Article 403. https://doi.org/10.1038/s41398-020-01074-z

@article{7d77ae6c430141b4be947beab0f2b11f,

title = "Genome-wide association study of Alzheimer's disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset",

abstract = "Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Susceptibility to AD is considerably determined by genetic factors which hitherto were primarily identified using case-control designs. Elucidating the genetic architecture of additional AD-related phenotypic traits, ideally those linked to the underlying disease process, holds great promise in gaining deeper insights into the genetic basis of AD and in developing better clinical prediction models. To this end, we generated genome-wide single-nucleotide polymorphism (SNP) genotyping data in 931 participants of the European Medical Information Framework Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) sample to search for novel genetic determinants of AD biomarker variability. Specifically, we performed genome-wide association study (GWAS) analyses on 16 traits, including 14 measures derived from quantifications of five separate amyloid-beta (A beta) and tau-protein species in the cerebrospinal fluid (CSF). In addition to confirming the well-established effects of apolipoprotein E (APOE) on diagnostic outcome and phenotypes related to A beta 42, we detected novel potential signals in the zinc finger homeobox 3 (ZFHX3) for CSF-A beta 38 and CSF-A beta 40 levels, and confirmed the previously described sex-specific association between SNPs in geminin coiled-coil domain containing (GMNC) and CSF-tau. Utilizing the results from independent case-control AD GWAS to construct polygenic risk scores (PRS) revealed that AD risk variants only explain a small fraction of CSF biomarker variability. In conclusion, our study represents a detailed first account of GWAS analyses on CSF-A beta and -tau-related traits in the EMIF-AD MBD dataset. In subsequent work, we will utilize the genomics data generated here in GWAS of other AD-relevant clinical outcomes ascertained in this unique dataset.",

keywords = "RISK VARIANTS, SUSCEPTIBILITY LOCI, TAU",

author = "Shengjun Hong and Dmitry Prokopenko and Valerija Dobricic and Fabian Kilpert and Isabelle Bos and Vos, {Stephanie J. B.} and Tijms, {Betty M.} and Ulf Andreasson and Kaj Blennow and Rik Vandenberghe and Isabelle Cleynen and Silvy Gabel and Jolien Schaeverbeke and Philip Scheltens and Teunissen, {Charlotte E.} and Ellis Niemantsverdriet and Sebastiaan Engelborghs and Giovanni Frisoni and Olivier Blin and Richardson, {Jill C.} and Regis Bordet and Molinuevo, {Jose Luis} and Lorena Rami and Petronella Kettunen and Anders Wallin and Alberto Lleo and Isabel Sala and Julius Popp and Gwendoline Peyratout and Pablo Martinez-Lage and Mikel Tainta and Dobson, {Richard J. B.} and Cristina Legido-Quigley and Kristel Sleegers and {Van Broeckhoven}, Christine and {ten Kate}, Mara and Frederik Barkhof and Henrik Zetterberg and Simon Lovestone and Johannes Streffer and Michael Wittig and Andre Franke and Tanzi, {Rudolph E.} and Visser, {Pieter Jelle} and Lars Bertram and {Alzheimer's Disease Neuroimaging Initiative}",

note = "Funding Information: The present study was conducted as part of the EMIF-AD MBD project, which has received support from the Innovative Medicines Initiative Joint Undertaking under EMIF grant agreement n° 115372, the resources of which are composed of financial contribution from the European Union{\textquoteright}s Seventh Framework Program (FP7/2007–2013) and EFPIA companies{\textquoteright} in kind contribution. Parts of this study were made possible through support from the German Research Foundation (DFG grant FOR2488: Main support by subproject “INF-GDAC” BE2287/7-1 to LB). R.V. acknowledges the support by the Stichting Alzheimer Onderzoek (#13007, #11020, #2017-032) and the Flemish Government (VIND IWT 135043). H.Z. is a Wallenberg Academy Fellow supported by grants from the Swedish Research Council (#2018-02532), the European Research Council (#681712) and Swedish State Support for Clinical Research (#ALFGBG-720931). S. J.B.V. received funding from the Innovative Medicines Initiative 2 Joint Undertaking under ROADMAP grant agreement No. 116020 and from ZonMw during the conduct of this study. No conflict of interest exists. Research at VIB-UAntwerp was in part supported by the University of Antwerp Research Fund. The research was supported by ALF clinical grants from Region V{\"a}stra G{\"o}taland to A.W. and to P.K. We acknowledge the assistance of Ellen De Roeck, Naomi De Roeck, and Hanne Struyfs (UAntwerp) with data collection. The Lausanne study was funded by a grant from the Swiss National Research Foundation (SNF 320030_141179) to J.P. We thank Mrs. Tanja Wesse and Mrs. Sanaz Sedghpour Sabet at the Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany for technical assistance with the GSA genotyping. The LIGA team acknowledges computational support from the OMICS compute cluster at the University of L{\"u}beck. The computations in the ADNI cohort were run on the Odyssey cluster supported by the FAS Division of Science, Research Computing Group at Harvard University. For ADNI: Data was used for this project of which collection and sharing was funded by the Alzheimer{\textquoteright}s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer{\textquoteright}s Association; Alzheimer{\textquoteright}s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer{\textquoteright}s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for NeuroImaging at the University of Southern California. Publisher Copyright: {\textcopyright} 2020, The Author(s).",

year = "2020",

month = dec,

day = "22",

doi = "10.1038/s41398-020-01074-z",

language = "English",

volume = "10",

journal = "Translational Psychiatry",

issn = "2158-3188",

publisher = "Nature Publishing Group",

number = "1",

}

Hong, S, Prokopenko, D, Dobricic, V, Kilpert, F, Bos, I, Vos, SJB, Tijms, BM, Andreasson, U, Blennow, K, Vandenberghe, R, Cleynen, I, Gabel, S, Schaeverbeke, J, Scheltens, P, Teunissen, CE, Niemantsverdriet, E, Engelborghs, S, Frisoni, G, Blin, O, Richardson, JC, Bordet, R, Molinuevo, JL, Rami, L, Kettunen, P, Wallin, A, Lleo, A, Sala, I, Popp, J, Peyratout, G, Martinez-Lage, P, Tainta, M, Dobson, RJB, Legido-Quigley, C, Sleegers, K, Van Broeckhoven, C, ten Kate, M, Barkhof, F, Zetterberg, H, Lovestone, S, Streffer, J, Wittig, M, Franke, A, Tanzi, RE, Visser, PJ, Bertram, L & Alzheimer's Disease Neuroimaging Initiative 2020, 'Genome-wide association study of Alzheimer's disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset', Translational Psychiatry, vol. 10, no. 1, 403. https://doi.org/10.1038/s41398-020-01074-z

TY - JOUR

T1 - Genome-wide association study of Alzheimer's disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset

AU - Hong, Shengjun

AU - Prokopenko, Dmitry

AU - Dobricic, Valerija

AU - Kilpert, Fabian

AU - Bos, Isabelle

AU - Vos, Stephanie J. B.

AU - Tijms, Betty M.

AU - Andreasson, Ulf

AU - Blennow, Kaj

AU - Vandenberghe, Rik

AU - Cleynen, Isabelle

AU - Gabel, Silvy

AU - Schaeverbeke, Jolien

AU - Scheltens, Philip

AU - Teunissen, Charlotte E.

AU - Niemantsverdriet, Ellis

AU - Engelborghs, Sebastiaan

AU - Frisoni, Giovanni

AU - Blin, Olivier

AU - Richardson, Jill C.

AU - Bordet, Regis

AU - Molinuevo, Jose Luis

AU - Rami, Lorena

AU - Kettunen, Petronella

AU - Wallin, Anders

AU - Lleo, Alberto

AU - Sala, Isabel

AU - Popp, Julius

AU - Peyratout, Gwendoline

AU - Martinez-Lage, Pablo

AU - Tainta, Mikel

AU - Dobson, Richard J. B.

AU - Legido-Quigley, Cristina

AU - Sleegers, Kristel

AU - Van Broeckhoven, Christine

AU - ten Kate, Mara

AU - Barkhof, Frederik

AU - Zetterberg, Henrik

AU - Lovestone, Simon

AU - Streffer, Johannes

AU - Wittig, Michael

AU - Franke, Andre

AU - Tanzi, Rudolph E.

AU - Visser, Pieter Jelle

AU - Bertram, Lars

AU - Alzheimer's Disease Neuroimaging Initiative

N1 - Funding Information: The present study was conducted as part of the EMIF-AD MBD project, which has received support from the Innovative Medicines Initiative Joint Undertaking under EMIF grant agreement n° 115372, the resources of which are composed of financial contribution from the European Union’s Seventh Framework Program (FP7/2007–2013) and EFPIA companies’ in kind contribution. Parts of this study were made possible through support from the German Research Foundation (DFG grant FOR2488: Main support by subproject “INF-GDAC” BE2287/7-1 to LB). R.V. acknowledges the support by the Stichting Alzheimer Onderzoek (#13007, #11020, #2017-032) and the Flemish Government (VIND IWT 135043). H.Z. is a Wallenberg Academy Fellow supported by grants from the Swedish Research Council (#2018-02532), the European Research Council (#681712) and Swedish State Support for Clinical Research (#ALFGBG-720931). S. J.B.V. received funding from the Innovative Medicines Initiative 2 Joint Undertaking under ROADMAP grant agreement No. 116020 and from ZonMw during the conduct of this study. No conflict of interest exists. Research at VIB-UAntwerp was in part supported by the University of Antwerp Research Fund. The research was supported by ALF clinical grants from Region Västra Götaland to A.W. and to P.K. We acknowledge the assistance of Ellen De Roeck, Naomi De Roeck, and Hanne Struyfs (UAntwerp) with data collection. The Lausanne study was funded by a grant from the Swiss National Research Foundation (SNF 320030_141179) to J.P. We thank Mrs. Tanja Wesse and Mrs. Sanaz Sedghpour Sabet at the Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany for technical assistance with the GSA genotyping. The LIGA team acknowledges computational support from the OMICS compute cluster at the University of Lübeck. The computations in the ADNI cohort were run on the Odyssey cluster supported by the FAS Division of Science, Research Computing Group at Harvard University. For ADNI: Data was used for this project of which collection and sharing was funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for NeuroImaging at the University of Southern California. Publisher Copyright: © 2020, The Author(s).

PY - 2020/12/22

Y1 - 2020/12/22

N2 - Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Susceptibility to AD is considerably determined by genetic factors which hitherto were primarily identified using case-control designs. Elucidating the genetic architecture of additional AD-related phenotypic traits, ideally those linked to the underlying disease process, holds great promise in gaining deeper insights into the genetic basis of AD and in developing better clinical prediction models. To this end, we generated genome-wide single-nucleotide polymorphism (SNP) genotyping data in 931 participants of the European Medical Information Framework Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) sample to search for novel genetic determinants of AD biomarker variability. Specifically, we performed genome-wide association study (GWAS) analyses on 16 traits, including 14 measures derived from quantifications of five separate amyloid-beta (A beta) and tau-protein species in the cerebrospinal fluid (CSF). In addition to confirming the well-established effects of apolipoprotein E (APOE) on diagnostic outcome and phenotypes related to A beta 42, we detected novel potential signals in the zinc finger homeobox 3 (ZFHX3) for CSF-A beta 38 and CSF-A beta 40 levels, and confirmed the previously described sex-specific association between SNPs in geminin coiled-coil domain containing (GMNC) and CSF-tau. Utilizing the results from independent case-control AD GWAS to construct polygenic risk scores (PRS) revealed that AD risk variants only explain a small fraction of CSF biomarker variability. In conclusion, our study represents a detailed first account of GWAS analyses on CSF-A beta and -tau-related traits in the EMIF-AD MBD dataset. In subsequent work, we will utilize the genomics data generated here in GWAS of other AD-relevant clinical outcomes ascertained in this unique dataset.

AB - Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Susceptibility to AD is considerably determined by genetic factors which hitherto were primarily identified using case-control designs. Elucidating the genetic architecture of additional AD-related phenotypic traits, ideally those linked to the underlying disease process, holds great promise in gaining deeper insights into the genetic basis of AD and in developing better clinical prediction models. To this end, we generated genome-wide single-nucleotide polymorphism (SNP) genotyping data in 931 participants of the European Medical Information Framework Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) sample to search for novel genetic determinants of AD biomarker variability. Specifically, we performed genome-wide association study (GWAS) analyses on 16 traits, including 14 measures derived from quantifications of five separate amyloid-beta (A beta) and tau-protein species in the cerebrospinal fluid (CSF). In addition to confirming the well-established effects of apolipoprotein E (APOE) on diagnostic outcome and phenotypes related to A beta 42, we detected novel potential signals in the zinc finger homeobox 3 (ZFHX3) for CSF-A beta 38 and CSF-A beta 40 levels, and confirmed the previously described sex-specific association between SNPs in geminin coiled-coil domain containing (GMNC) and CSF-tau. Utilizing the results from independent case-control AD GWAS to construct polygenic risk scores (PRS) revealed that AD risk variants only explain a small fraction of CSF biomarker variability. In conclusion, our study represents a detailed first account of GWAS analyses on CSF-A beta and -tau-related traits in the EMIF-AD MBD dataset. In subsequent work, we will utilize the genomics data generated here in GWAS of other AD-relevant clinical outcomes ascertained in this unique dataset.

KW - RISK VARIANTS

KW - SUSCEPTIBILITY LOCI

KW - TAU

U2 - 10.1038/s41398-020-01074-z

DO - 10.1038/s41398-020-01074-z

M3 - Article

C2 - 33223526

SN - 2158-3188

VL - 10

JO - Translational Psychiatry

JF - Translational Psychiatry

IS - 1

M1 - 403

ER -