Abstract
Potentially modifiable risk factors including obesity, diabetes, hypertension, and smoking are associated with Alzheimer disease (AD) and represent promising targets for intervention. However, the causality of these associations is unclear. We sought to assess the causal nature of these associations using Mendelian randomization (MR). We used SNPs associated with each risk factor as instrumental variables in MR analyses. We considered type 2 diabetes (T2D, NSNPs= 49), fasting glucose (NSNPs= 36), insulin resistance (NSNPs= 10), body mass index (BMI, NSNPs= 32), total cholesterol (NSNPs= 73), HDL-cholesterol (NSNPs= 71), LDL-cholesterol (NSNPs= 57), triglycerides (NSNPs= 39), systolic blood pressure (SBP, NSNPs= 24), smoking initiation (NSNPs= 1), smoking quantity (NSNPs= 3), university completion (NSNPs= 2), and years of education (NSNPs= 1). We calculated MR estimates of associations between each exposure and AD risk using an inverse-variance weighted approach, with summary statistics of SNP–AD associations from the International Genomics of Alzheimer’s Project, comprising a total of 17,008 individuals with AD and 37,154 cognitively normal elderly controls. We found that genetically predicted higher SBP was associated with lower AD risk (odds ratio [OR] per standard deviation [15.4 mm Hg] of SBP [95% CI]: 0.75 [0.62–0.91]; p = 3.4 × 10−3). Genetically predicted higher SBP was also associated with a higher probability of taking antihypertensive medication (p = 6.7 × 10−8). Genetically predicted smoking quantity was associated with lower AD risk (OR per ten cigarettes per day [95% CI]: 0.67 [0.51–0.89]; p = 6.5 × 10−3), although we were unable to stratify by smoking history; genetically predicted smoking initiation was not associated with AD risk (OR = 0.70 [0.37, 1.33]; p = 0.28). We saw no evidence of causal associations between glycemic traits, T2D, BMI, or educational attainment and risk of AD (all p > 0.1). Potential limitations of this study include the small proportion of intermediate trait variance explained by genetic variants and other implicit limitations of MR analyses. Inherited lifetime exposure to higher SBP is associated with lower AD risk. These findings suggest that higher blood pressure—or some environmental exposure associated with higher blood pressure, such as use of antihypertensive medications—may reduce AD risk.
Original language | English |
---|---|
Article number | e1001841 |
Journal | PLoS Medicine |
Volume | 12 |
Issue number | 6 |
DOIs | |
State | Published - Jun 1 2015 |
Bibliographical note
Publisher Copyright:© 2015 Østergaard et al.
ASJC Scopus subject areas
- General Medicine
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In: PLoS Medicine, Vol. 12, No. 6, e1001841, 01.06.2015.
Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Associations between Potentially Modifiable Risk Factors and Alzheimer Disease
T2 - A Mendelian Randomization Study
AU - Østergaard, Søren D.
AU - Mukherjee, Shubhabrata
AU - Sharp, Stephen J.
AU - Proitsi, Petroula
AU - Lotta, Luca A.
AU - Day, Felix
AU - Perry, John R.B.
AU - Boehme, Kevin L.
AU - Walter, Stefan
AU - Kauwe, John S.
AU - Gibbons, Laura E.
AU - Larson, Eric B.
AU - Powell, John F.
AU - Langenberg, Claudia
AU - Crane, Paul K.
AU - Wareham, Nicholas J.
AU - Scott, Robert A.
AU - Albert, Marilyn S.
AU - Albin, Roger L.
AU - Apostolova, Liana G.
AU - Arnold, Steven E.
AU - Asthana, Sanjay
AU - Atwood, Craig S.
AU - Baldwin, Clinton T.
AU - Barber, Robert C.
AU - Barmada, Michael M.
AU - Barnes, Lisa L.
AU - Beach, Thomas G.
AU - Becker, James T.
AU - Beecham, Gary W.
AU - Beekly, Duane
AU - Bigio, Eileen H.
AU - Bird, Thomas D.
AU - Blacker, Deborah
AU - Boeve, Bradley F.
AU - Bowen, James D.
AU - Boxer, Adam
AU - Burke, James R.
AU - Buxbaum, Joseph D.
AU - Cairns, Nigel J.
AU - Cantwell, Laura B.
AU - Cao, Chuanhai
AU - Carlson, Chris S.
AU - Carlsson, Cynthia M.
AU - Carney, Regina M.
AU - Carrasquillo, Minerva M.
AU - Carroll, Steven L.
AU - Chui, Helena C.
AU - Clark, David G.
AU - Corneveaux, Jason
AU - Cribbs, David H.
AU - Crocco, Elizabeth A.
AU - Cruchaga, Carlos
AU - De Jager, Philip L.
AU - DeCarli, Charles
AU - Demirci, F. Yesim
AU - Dick, Malcolm
AU - Dickson, Dennis W.
AU - Duara, Ranjan
AU - Ertekin-Taner, Nilufer
AU - Evans, Denis
AU - Faber, Kelley M.
AU - Fallon, Kenneth B.
AU - Farlow, Martin R.
AU - Farrer, Lindsay A.
AU - Ferris, Steven
AU - Foroud, Tatiana M.
AU - Frosch, Matthew P.
AU - Galasko, Douglas R.
AU - Gearing, Marla
AU - Geschwind, Daniel H.
AU - Ghetti, Bernardino
AU - Gilbert, John R.
AU - Glass, Jonathan D.
AU - Goate, Alison M.
AU - Graff-Radford, Neill R.
AU - Green, Robert C.
AU - Growdon, John H.
AU - Haines, Jonathan L.
AU - Hakonarson, Hakon
AU - Hamilton, Ronald L.
AU - Hamilton-Nelson, Kara L.
AU - Hardy, John
AU - Harrell, Lindy E.
AU - Head, Elizabeth
AU - Honig, Lawrence S.
AU - Huebinger, Ryan M.
AU - Huentelman, Matthew J.
AU - Hulette, Christine M.
AU - Hyman, Bradley T.
AU - Jarvik, Gail P.
AU - Jicha, Gregory A.
AU - Jin, Lee Way
AU - Jun, Gyungah
AU - Kamboh, M. Ilyas
AU - Karydas, Anna
AU - Kaye, Jeffrey A.
AU - Kim, Ronald
AU - Kowall, Neil W.
AU - Kramer, Joel H.
AU - Kukull, Walter A.
AU - Kunkle, Brian W.
AU - LaFerla, Frank M.
AU - Lah, James J.
AU - Leverenz, James B.
AU - Levey, Allan I.
AU - Li, Ge
AU - Lieberman, Andrew P.
AU - Lin, Chiao Feng
AU - Lopez, Oscar L.
AU - Lunetta, Kathryn L.
AU - Lyketsos, Constantine G.
AU - Mack, Wendy J.
AU - Marson, Daniel C.
AU - Martin, Eden R.
AU - Martiniuk, Frank
AU - Mash, Deborah C.
AU - Masliah, Eliezer
AU - Mayeux, Richard
AU - McCormick, Wayne C.
AU - McCurry, Susan M.
AU - McDavid, Andrew N.
AU - McKee, Ann C.
AU - Mesulam, Marsel
AU - Miller, Bruce L.
AU - Miller, Carol A.
AU - Miller, Joshua W.
AU - Montine, Thomas J.
AU - Morris, John C.
AU - Murrell, Jill R.
AU - Myers, Amanda J.
AU - Naj, Adam C.
AU - Olichney, John M.
AU - Pankratz, Vernon S.
AU - Parisi, Joseph E.
AU - Partch, Amanda
AU - Paulson, Henry L.
AU - Pericak-Vance, Margaret A.
AU - Perry, William
AU - Peskind, Elaine
AU - Petersen, Ronald C.
AU - Pierce, Aimee
AU - Poon, Wayne W.
AU - Potter, Huntington
AU - Quinn, Joseph F.
AU - Raj, Ashok
AU - Raskind, Murray
AU - Reiman, Eric M.
AU - Reisberg, Barry
AU - Reitz, Christiane
AU - Ringman, John M.
AU - Roberson, Erik D.
AU - Rogaeva, Ekaterina
AU - Rosen, Howard J.
AU - Rosenberg, Roger N.
AU - Sager, Mark A.
AU - Sano, Mary
AU - Schellenberg, Gerard D.
AU - Schneider, Julie A.
AU - Schneider, Lon S.
AU - Seeley, William W.
AU - Smith, Amanda G.
AU - Sonnen, Joshua A.
AU - Spina, Salvatore
AU - St George-Hyslop, Peter
AU - Stern, Robert A.
AU - Tanzi, Rudolph E.
AU - Thornton-Wells, Tricia A.
AU - Trojanowski, John Q.
AU - Troncoso, Juan C.
AU - Tsuang, Debby W.
AU - Valladares, Otto
AU - VanDeerlin, Vivianna M.
AU - Van Eldik, Linda J.
AU - Vardarajan, Badri N.
AU - Vinters, Harry V.
AU - Vonsattel, Jean Paul
AU - Wang, Li San
AU - Weintraub, Sandra
AU - Welsh-Bohmer, Kathleen A.
AU - Williamson, Jennifer
AU - Wishnek, Sarah
AU - Woltjer, Randall L.
AU - Wright, Clinton B.
AU - Younkin, Steven G.
AU - Yu, Chang En
AU - Yu, Lei
AU - Harold, Denise
AU - Abraham, Richard
AU - Hollingworth, Paul
AU - Sims, Rebecca
AU - Gerrish, Amy
AU - Chapman, Jade
AU - Russo, Giancarlo
AU - Hamshere, Marian
AU - Singh Pahwa, Jaspreet
AU - Escott-Price, Valentina
AU - Badarinarayan, Nandini
AU - Dowzell, Kimberley
AU - Williams, Amy
AU - Jones, Nicola
AU - Thomas, Charlene
AU - Stretton, Alexandra
AU - Morgan, Angharad
AU - Taylor, Sarah
AU - Lovestone, Simon
AU - Lupton, Michelle K.
AU - Brayne, Carol
AU - Rubinsztein, David C.
AU - Gill, Michael
AU - Lawlor, Brian
AU - Lynch, Aoibhinn
AU - Morgan, Kevin
AU - Brown, Kristelle
AU - Passmore, Peter
AU - Craig, David
AU - McGuinness, Bernadette
AU - Todd, Stephen
AU - Johnston, Janet
AU - Holmes, Clive
AU - Mann, David
AU - David Smith, A.
AU - Love, Seth
AU - Kehoe, Patrick G.
AU - Mead, Simon
AU - Fox, Nick
AU - Rossor, Martin
AU - Collinge, John
AU - Maier, Wolfgang
AU - Jessen, Frank
AU - Heun, Reiner
AU - Schürmann, Britta
AU - Ramirez, Alfredo
AU - Becker, Tim
AU - Herold, Christine
AU - Lacour, André
AU - Drichel, Dmitriy
AU - van den Bussche, Hendrik
AU - Heuser, Isabella
AU - Kornhuber, Johannes
AU - Wiltfang, Jens
AU - Dichgans, Martin
AU - Frölich, Lutz
AU - Hampel, Harald
AU - Hüll, Michael
AU - Rujescu, Dan
AU - Goate, Alison
AU - Kauwe, John S.K.
AU - Nowotny, Petra
AU - Mayo, Kevin
AU - Livingston, Gill
AU - Bass, Nicholas J.
AU - Gurling, Hugh
AU - McQuillin, Andrew
AU - Gwilliam, Rhian
AU - Deloukas, Panagiotis
AU - Al-Chalabi, Ammar
AU - Shaw, Christopher E.
AU - Singleton, Andrew B.
AU - Guerreiro, Rita
AU - Mühleisen, Thomas W.
AU - Nöthen, Markus M.
AU - Moebus, Susanne
AU - Jöckel, Karl Heinz
AU - Klopp, Norman
AU - Wichmann, H. Erich
AU - Shane Pankratz, V.
AU - Holmans, Peter
AU - Donovan, Michael O.
AU - Owen, Michael J.
AU - Williams, Julie
AU - Forouhi, Nita G.
AU - Kerrison, Nicola D.
AU - Sims, Matt
AU - Lucarelli, Debora M.E.
AU - Barroso, Inês
AU - McCarthy, Mark I.
AU - Arriola, Larraitz
AU - Balkau, Beverley
AU - Barricarte, Aurelio
AU - Boeing, Heiner
AU - Franks, Paul W.
AU - Gonzalez, Carlos
AU - Grioni, Sara
AU - Kaaks, Rudolf
AU - Key, Timothy J.
AU - Navarro, Carmen
AU - Nilsson, Peter M.
AU - Overvad, Kim
AU - Palli, Domenico
AU - Panico, Salvatore
AU - Ramón Quirós, J.
AU - Rolandsson, Olov
AU - Sacerdote, Carlotta
AU - Sánchez, Maria José
AU - Slimani, Nadia
AU - Tjonneland, Anne
AU - Tumino, Rosario
AU - van der Daphne, A. L.
AU - van der Schouw, Yvonne T.
AU - Riboli, Elio
N1 - Publisher Copyright: © 2015 Østergaard et al.
PY - 2015/6/1
Y1 - 2015/6/1
N2 - Potentially modifiable risk factors including obesity, diabetes, hypertension, and smoking are associated with Alzheimer disease (AD) and represent promising targets for intervention. However, the causality of these associations is unclear. We sought to assess the causal nature of these associations using Mendelian randomization (MR). We used SNPs associated with each risk factor as instrumental variables in MR analyses. We considered type 2 diabetes (T2D, NSNPs= 49), fasting glucose (NSNPs= 36), insulin resistance (NSNPs= 10), body mass index (BMI, NSNPs= 32), total cholesterol (NSNPs= 73), HDL-cholesterol (NSNPs= 71), LDL-cholesterol (NSNPs= 57), triglycerides (NSNPs= 39), systolic blood pressure (SBP, NSNPs= 24), smoking initiation (NSNPs= 1), smoking quantity (NSNPs= 3), university completion (NSNPs= 2), and years of education (NSNPs= 1). We calculated MR estimates of associations between each exposure and AD risk using an inverse-variance weighted approach, with summary statistics of SNP–AD associations from the International Genomics of Alzheimer’s Project, comprising a total of 17,008 individuals with AD and 37,154 cognitively normal elderly controls. We found that genetically predicted higher SBP was associated with lower AD risk (odds ratio [OR] per standard deviation [15.4 mm Hg] of SBP [95% CI]: 0.75 [0.62–0.91]; p = 3.4 × 10−3). Genetically predicted higher SBP was also associated with a higher probability of taking antihypertensive medication (p = 6.7 × 10−8). Genetically predicted smoking quantity was associated with lower AD risk (OR per ten cigarettes per day [95% CI]: 0.67 [0.51–0.89]; p = 6.5 × 10−3), although we were unable to stratify by smoking history; genetically predicted smoking initiation was not associated with AD risk (OR = 0.70 [0.37, 1.33]; p = 0.28). We saw no evidence of causal associations between glycemic traits, T2D, BMI, or educational attainment and risk of AD (all p > 0.1). Potential limitations of this study include the small proportion of intermediate trait variance explained by genetic variants and other implicit limitations of MR analyses. Inherited lifetime exposure to higher SBP is associated with lower AD risk. These findings suggest that higher blood pressure—or some environmental exposure associated with higher blood pressure, such as use of antihypertensive medications—may reduce AD risk.
AB - Potentially modifiable risk factors including obesity, diabetes, hypertension, and smoking are associated with Alzheimer disease (AD) and represent promising targets for intervention. However, the causality of these associations is unclear. We sought to assess the causal nature of these associations using Mendelian randomization (MR). We used SNPs associated with each risk factor as instrumental variables in MR analyses. We considered type 2 diabetes (T2D, NSNPs= 49), fasting glucose (NSNPs= 36), insulin resistance (NSNPs= 10), body mass index (BMI, NSNPs= 32), total cholesterol (NSNPs= 73), HDL-cholesterol (NSNPs= 71), LDL-cholesterol (NSNPs= 57), triglycerides (NSNPs= 39), systolic blood pressure (SBP, NSNPs= 24), smoking initiation (NSNPs= 1), smoking quantity (NSNPs= 3), university completion (NSNPs= 2), and years of education (NSNPs= 1). We calculated MR estimates of associations between each exposure and AD risk using an inverse-variance weighted approach, with summary statistics of SNP–AD associations from the International Genomics of Alzheimer’s Project, comprising a total of 17,008 individuals with AD and 37,154 cognitively normal elderly controls. We found that genetically predicted higher SBP was associated with lower AD risk (odds ratio [OR] per standard deviation [15.4 mm Hg] of SBP [95% CI]: 0.75 [0.62–0.91]; p = 3.4 × 10−3). Genetically predicted higher SBP was also associated with a higher probability of taking antihypertensive medication (p = 6.7 × 10−8). Genetically predicted smoking quantity was associated with lower AD risk (OR per ten cigarettes per day [95% CI]: 0.67 [0.51–0.89]; p = 6.5 × 10−3), although we were unable to stratify by smoking history; genetically predicted smoking initiation was not associated with AD risk (OR = 0.70 [0.37, 1.33]; p = 0.28). We saw no evidence of causal associations between glycemic traits, T2D, BMI, or educational attainment and risk of AD (all p > 0.1). Potential limitations of this study include the small proportion of intermediate trait variance explained by genetic variants and other implicit limitations of MR analyses. Inherited lifetime exposure to higher SBP is associated with lower AD risk. These findings suggest that higher blood pressure—or some environmental exposure associated with higher blood pressure, such as use of antihypertensive medications—may reduce AD risk.
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UR - http://www.scopus.com/inward/citedby.url?scp=84936961448&partnerID=8YFLogxK
U2 - 10.1371/journal.pmed.1001841
DO - 10.1371/journal.pmed.1001841
M3 - Article
C2 - 26079503
AN - SCOPUS:84936961448
SN - 1549-1277
VL - 12
JO - PLoS Medicine
JF - PLoS Medicine
IS - 6
M1 - e1001841
ER -