Abstract
Alzheimer's disease (AD) is a neurodegenerative disease that commonly causes dementia. Identifying biomarkers for the early detection of AD is an emerging need, as brain dysfunction begins two decades before the onset of clinical symptoms. To this end, we reanalyzed untargeted metabolomic mass spectrometry data from 905 patients enrolled in the AD Neuroimaging Initiative (ADNI) cohort using MS-DIAL, with 1,304,633 spectra of 39,108 unique biomolecules. Metabolic profiles of 93 hydrophilic metabolites were determined. Additionally, we integrated targeted lipidomic data (4873 samples from 1524 patients) to explore candidate biomarkers for predicting progressive mild cognitive impairment (pMCI) in patients diagnosed with AD within two years using the baseline metabolome. Patients with lower ergothioneine levels had a 12% higher rate of AD progression with the significance of P = 0.012 (Wald test). Furthermore, an increase in ganglioside (GM3) and decrease in plasmalogen lipids, many of which are associated with apolipoprotein E polymorphism, were confirmed in AD patients, and the higher levels of lysophosphatidylcholine (18:1) and GM3 d18:1/20:0 showed 19% and 17% higher rates of AD progression, respectively (Wald test: P = 3.9 × 10–8 and 4.3 × 10–7). Palmitoleamide, oleamide, diacylglycerols, and ether lipids were also identified as significantly altered metabolites at baseline in patients with pMCI. The integrated analysis of metabolites and genomics data showed that combining information on metabolites and genotypes enhances the predictive performance of AD progression, suggesting that metabolomics is essential to complement genomic data. In conclusion, the reanalysis of multiomics data provides new insights to detect early development of AD pathology and to partially understand metabolic changes in age-related onset of AD.
Original language | English |
---|---|
Article number | 6797 |
Journal | Scientific reports |
Volume | 14 |
Issue number | 1 |
DOIs | |
State | Published - Dec 2024 |
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In: Scientific reports, Vol. 14, No. 1, 6797, 12.2024.
Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Multiomics analysis to explore blood metabolite biomarkers in an Alzheimer’s Disease Neuroimaging Initiative cohort
AU - Oka, Takaki
AU - Matsuzawa, Yuki
AU - Tsuneyoshi, Momoka
AU - Nakamura, Yoshitaka
AU - Aoshima, Ken
AU - Tsugawa, Hiroshi
AU - Weiner, Michael
AU - Aisen, Paul
AU - Petersen, Ronald
AU - Jack, Clifford R.
AU - Jagust, William
AU - Trojanowki, John Q.
AU - Toga, Arthur W.
AU - Beckett, Laurel
AU - Green, Robert C.
AU - Saykin, Andrew J.
AU - Morris, John
AU - Shaw, Leslie M.
AU - Liu, Enchi
AU - Montine, Tom
AU - Thomas, Ronald G.
AU - Donohue, Michael
AU - Walter, Sarah
AU - Gessert, Devon
AU - Sather, Tamie
AU - Jiminez, Gus
AU - Harvey, Danielle
AU - Donohue, Michael
AU - Bernstein, Matthew
AU - Fox, Nick
AU - Thompson, Paul
AU - Schuff, Norbert
AU - DeCArli, Charles
AU - Borowski, Bret
AU - Gunter, Jeff
AU - Senjem, Matt
AU - Vemuri, Prashanthi
AU - Jones, David
AU - Kantarci, Kejal
AU - Ward, Chad
AU - Koeppe, Robert A.
AU - Foster, Norm
AU - Reiman, Eric M.
AU - Chen, Kewei
AU - Mathis, Chet
AU - Landau, Susan
AU - Cairns, Nigel J.
AU - Householder, Erin
AU - Reinwald, Lisa Taylor
AU - Lee, Virginia
AU - Korecka, Magdalena
AU - Figurski, Michal
AU - Crawford, Karen
AU - Neu, Scott
AU - Foroud, Tatiana M.
AU - Potkin, Steven
AU - Shen, Li
AU - Kelley, Faber
AU - Kim, Sungeun
AU - Nho, Kwangsik
AU - Kachaturian, Zaven
AU - Frank, Richard
AU - Snyder, Peter J.
AU - Molchan, Susan
AU - Kaye, Jeffrey
AU - Quinn, Joseph
AU - Lind, Betty
AU - Carter, Raina
AU - Dolen, Sara
AU - Schneider, Lon S.
AU - Pawluczyk, Sonia
AU - Beccera, Mauricio
AU - Teodoro, Liberty
AU - Spann, Bryan M.
AU - Brewer, James
AU - Vanderswag, Helen
AU - Fleisher, Adam
AU - Heidebrink, Judith L.
AU - Lord, Joanne L.
AU - Petersen, Ronald
AU - Mason, Sara S.
AU - Albers, Colleen S.
AU - Knopman, David
AU - Johnson, Kris
AU - Doody, Rachelle S.
AU - Meyer, Javier Villanueva
AU - Chowdhury, Munir
AU - Rountree, Susan
AU - Dang, Mimi
AU - Stern, Yaakov
AU - Honig, Lawrence S.
AU - Bell, Karen L.
AU - Ances, Beau
AU - Morris, John C.
AU - Carroll, Maria
AU - Leon, Sue
AU - Householder, Erin
AU - Mintun, Mark A.
AU - Schneider, Stacy
AU - Oliver, Angela
AU - Marson, Daniel
AU - Griffith, Randall
AU - Clark, David
AU - Geldmacher, David
AU - Brockington, John
AU - Roberson, Erik
AU - Grossman, Hillel
AU - Mitsis, Effie
AU - de Toledo-Morrell, Leyla
AU - Shah, Raj C.
AU - Duara, Ranjan
AU - Varon, Daniel
AU - Greig, Maria T.
AU - Roberts, Peggy
AU - Albert, Marilyn
AU - Onyike, Chiadi
AU - D’Agostino, Daniel
AU - Kielb, Stephanie
AU - Galvin, James E.
AU - Pogorelec, Dana M.
AU - Cerbone, Brittany
AU - Michel, Christina A.
AU - Rusinek, Henry
AU - de Leon, Mony J.
AU - Glodzik, Lidia
AU - De Santi, Susan
AU - Doraiswamy, P. Murali
AU - Petrella, Jeffrey R.
AU - Wong, Terence Z.
AU - Arnold, Steven E.
AU - Karlawish, Jason H.
AU - Wolk, David
AU - Smith, Charles D.
AU - Jicha, Greg
AU - Hardy, Peter
AU - Sinha, Partha
AU - Oates, Elizabeth
AU - Conrad, Gary
AU - Lopez, Oscar L.
AU - Oakley, Mary Ann
AU - Simpson, Donna M.
AU - Porsteinsson, Anton P.
AU - Goldstein, Bonnie S.
AU - Martin, Kim
AU - Makino, Kelly M.
AU - Ismail, M. Saleem
AU - Brand, Connie
AU - Mulnard, Ruth A.
AU - Thai, Gaby
AU - Mc Adams Ortiz, Catherine
AU - Womack, Kyle
AU - Mathews, Dana
AU - Quiceno, Mary
AU - Arrastia, Ramon Diaz
AU - King, Richard
AU - Weiner, Myron
AU - Cook, Kristen Martin
AU - DeVous, Michael
AU - Levey, Allan I.
AU - Lah, James J.
AU - Cellar, Janet S.
AU - Burns, Jeffrey M.
AU - Anderson, Heather S.
AU - Swerdlow, Russell H.
AU - Apostolova, Liana
AU - Tingus, Kathleen
AU - Woo, Ellen
AU - Silverman, Daniel H.S.
AU - Lu, Po H.
AU - Bartzokis, George
AU - Graff Radford, Neill R.
AU - Parfitt, Francine
AU - Kendall, Tracy
AU - Johnson, Heather
AU - Farlow, Martin R.
AU - Hake, Ann Marie
AU - Matthews, Brandy R.
AU - Herring, Scott
AU - Hunt, Cynthia
AU - van Dyck, Christopher H.
AU - Carson, Richard E.
AU - MacAvoy, Martha G.
AU - Chertkow, Howard
AU - Bergman, Howard
AU - Hosein, Chris
AU - Black, Sandra
AU - Stefanovic, Bojana
AU - Caldwell, Curtis
AU - Hsiung, Ging Yuek Robin
AU - Feldman, Howard
AU - Mudge, Benita
AU - Assaly, Michele
AU - Kertesz, Andrew
AU - Rogers, John
AU - Trost, Dick
AU - Bernick, Charles
AU - Munic, Donna
AU - Kerwin, Diana
AU - Mesulam, Marek Marsel
AU - Lipowski, Kristine
AU - Wu, Chuang Kuo
AU - Johnson, Nancy
AU - Sadowsky, Carl
AU - Martinez, Walter
AU - Villena, Teresa
AU - Turner, Raymond Scott
AU - Johnson, Kathleen
AU - Reynolds, Brigid
AU - Sperling, Reisa A.
AU - Johnson, Keith A.
AU - Marshall, Gad
AU - Frey, Meghan
AU - Yesavage, Jerome
AU - Taylor, Joy L.
AU - Lane, Barton
AU - Rosen, Allyson
AU - Tinklenberg, Jared
AU - Sabbagh, Marwan N.
AU - Belden, Christine M.
AU - Jacobson, Sandra A.
AU - Sirrel, Sherye A.
AU - Kowall, Neil
AU - Killiany, Ronald
AU - Budson, Andrew E.
AU - Norbash, Alexander
AU - Johnson, Patricia Lynn
AU - Obisesan, Thomas O.
AU - Wolday, Saba
AU - Allard, Joanne
AU - Lerner, Alan
AU - Ogrocki, Paula
AU - Hudson, Leon
AU - Fletcher, Evan
AU - Carmichael, Owen
AU - Olichney, John
AU - DeCarli, Charles
AU - Kittur, Smita
AU - Borrie, Michael
AU - Lee, T. Y.
AU - Bartha, Rob
AU - Johnson, Sterling
AU - Asthana, Sanjay
AU - Carlsson, Cynthia M.
AU - Potkin, Steven G.
AU - Preda, Adrian
AU - Nguyen, Dana
AU - Tariot, Pierre
AU - Fleisher, Adam
AU - Reeder, Stephanie
AU - Bates, Vernice
AU - Capote, Horacio
AU - Rainka, Michelle
AU - Scharre, Douglas W.
AU - Kataki, Maria
AU - Adeli, Anahita
AU - Zimmerman, Earl A.
AU - Celmins, Dzintra
AU - Brown, Alice D.
AU - Pearlson, Godfrey D.
AU - Blank, Karen
AU - Anderson, Karen
AU - Santulli, Robert B.
AU - Kitzmiller, Tamar J.
AU - Schwartz, Eben S.
AU - Sink, Kaycee M.
AU - Williamson, Jeff D.
AU - Garg, Pradeep
AU - Watkins, Franklin
AU - Ott, Brian R.
AU - Querfurth, Henry
AU - Tremont, Geoffrey
AU - Salloway, Stephen
AU - Malloy, Paul
AU - Correia, Stephen
AU - Rosen, Howard J.
AU - Miller, Bruce L.
AU - Mintzer, Jacobo
AU - Spicer, Kenneth
AU - Bachman, David
AU - Finger, Elizabether
AU - Pasternak, Stephen
AU - Rachinsky, Irina
AU - Rogers, John
AU - Kertesz, Andrew
AU - Drost, Dick
AU - Pomara, Nunzio
AU - Hernando, Raymundo
AU - Sarrael, Antero
AU - Schultz, Susan K.
AU - Ponto, Laura L.Boles
AU - Shim, Hyungsub
AU - Smith, Karen Elizabeth
AU - Relkin, Norman
AU - Chaing, Gloria
AU - Raudin, Lisa
AU - Smith, Amanda
AU - Fargher, Kristin
AU - Raj, Balebail Ashok
N1 - Publisher Copyright: © The Author(s) 2024.
PY - 2024/12
Y1 - 2024/12
N2 - Alzheimer's disease (AD) is a neurodegenerative disease that commonly causes dementia. Identifying biomarkers for the early detection of AD is an emerging need, as brain dysfunction begins two decades before the onset of clinical symptoms. To this end, we reanalyzed untargeted metabolomic mass spectrometry data from 905 patients enrolled in the AD Neuroimaging Initiative (ADNI) cohort using MS-DIAL, with 1,304,633 spectra of 39,108 unique biomolecules. Metabolic profiles of 93 hydrophilic metabolites were determined. Additionally, we integrated targeted lipidomic data (4873 samples from 1524 patients) to explore candidate biomarkers for predicting progressive mild cognitive impairment (pMCI) in patients diagnosed with AD within two years using the baseline metabolome. Patients with lower ergothioneine levels had a 12% higher rate of AD progression with the significance of P = 0.012 (Wald test). Furthermore, an increase in ganglioside (GM3) and decrease in plasmalogen lipids, many of which are associated with apolipoprotein E polymorphism, were confirmed in AD patients, and the higher levels of lysophosphatidylcholine (18:1) and GM3 d18:1/20:0 showed 19% and 17% higher rates of AD progression, respectively (Wald test: P = 3.9 × 10–8 and 4.3 × 10–7). Palmitoleamide, oleamide, diacylglycerols, and ether lipids were also identified as significantly altered metabolites at baseline in patients with pMCI. The integrated analysis of metabolites and genomics data showed that combining information on metabolites and genotypes enhances the predictive performance of AD progression, suggesting that metabolomics is essential to complement genomic data. In conclusion, the reanalysis of multiomics data provides new insights to detect early development of AD pathology and to partially understand metabolic changes in age-related onset of AD.
AB - Alzheimer's disease (AD) is a neurodegenerative disease that commonly causes dementia. Identifying biomarkers for the early detection of AD is an emerging need, as brain dysfunction begins two decades before the onset of clinical symptoms. To this end, we reanalyzed untargeted metabolomic mass spectrometry data from 905 patients enrolled in the AD Neuroimaging Initiative (ADNI) cohort using MS-DIAL, with 1,304,633 spectra of 39,108 unique biomolecules. Metabolic profiles of 93 hydrophilic metabolites were determined. Additionally, we integrated targeted lipidomic data (4873 samples from 1524 patients) to explore candidate biomarkers for predicting progressive mild cognitive impairment (pMCI) in patients diagnosed with AD within two years using the baseline metabolome. Patients with lower ergothioneine levels had a 12% higher rate of AD progression with the significance of P = 0.012 (Wald test). Furthermore, an increase in ganglioside (GM3) and decrease in plasmalogen lipids, many of which are associated with apolipoprotein E polymorphism, were confirmed in AD patients, and the higher levels of lysophosphatidylcholine (18:1) and GM3 d18:1/20:0 showed 19% and 17% higher rates of AD progression, respectively (Wald test: P = 3.9 × 10–8 and 4.3 × 10–7). Palmitoleamide, oleamide, diacylglycerols, and ether lipids were also identified as significantly altered metabolites at baseline in patients with pMCI. The integrated analysis of metabolites and genomics data showed that combining information on metabolites and genotypes enhances the predictive performance of AD progression, suggesting that metabolomics is essential to complement genomic data. In conclusion, the reanalysis of multiomics data provides new insights to detect early development of AD pathology and to partially understand metabolic changes in age-related onset of AD.
UR - http://www.scopus.com/inward/record.url?scp=85189156050&partnerID=8YFLogxK
U2 - 10.1038/s41598-024-56837-1
DO - 10.1038/s41598-024-56837-1
M3 - Article
C2 - 38565541
AN - SCOPUS:85189156050
SN - 2045-2322
VL - 14
JO - Scientific reports
JF - Scientific reports
IS - 1
M1 - 6797
ER -