Concordant peripheral lipidome signatures in two large clinical studies of Alzheimer's disease

Kevin Huynh^{1

2}, Wei Ling Florence Lim^{3

4}, Corey Giles¹, Kaushala S Jayawardana¹, Agus Salim^{1

5

6

7}, Natalie A Mellett¹, Adam Alexander T Smith¹, Gavriel Olshansky¹, Brian G Drew^{1

2}, Pratishtha Chatterjee^{3

8

9}, Ian Martins^{3

4}, Simon M Laws^{3

10

11}, Ashley I Bush¹², Christopher C Rowe^{12

13}, Victor L Villemagne^{13

14}, David Ames¹⁵, Colin L Masters¹², Matthias Arnold^{16

17}, Kwangsik Nho^{18

19

20}, Andrew J Saykin^{18

20

21}, Rebecca Baillie²², Xianlin Han²³, Rima Kaddurah-Daouk^{24

25

26}, Ralph N Martins^{27

28

29

30

31

32}, Peter J Meikle^{33

34}

Affiliations

¹ Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.
² Monash University, Melbourne, VIC, 3800, Australia.
³ School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia.
⁴ Cooperative research Centre (CRC) for Mental Health, Sydney, NSW, Australia.
⁵ Department of Mathematics and Statistics, La Trobe University, Melbourne, VIC, Australia.
⁶ Melbourne School of Global and Population Health, The University of Melbourne, Melbourne, VIC, 3010, Australia.
⁷ School of Mathematics and Statistics, The University of Melbourne, Melbourne, VIC, 3010, Australia.
⁸ Department of Biomedical Sciences, Macquarie University, Sydney, NSW, Australia.
⁹ KaRa Institute of Neurological Disease, Sydney, NSW, Australia.
¹⁰ Collaborative Genomics Group, School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia.
¹¹ Curtin Health Innovation Research Institute, Curtin University, Perth, WA, Australia.
¹² The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, Australia.
¹³ Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, VIC, Australia.
¹⁴ Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, VIC, Australia.
¹⁵ National Ageing Research Institute, Parkville, VIC, 3050, Australia.
¹⁶ Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA.
¹⁷ Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
¹⁸ Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
¹⁹ Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.
²⁰ Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA.
²¹ Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA.
²² Rosa & Co LLC, San Carlos, CA, USA.
²³ Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
²⁴ Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA. rima.kaddurahdaouk@duke.edu.
²⁵ Duke Institute of Brain Sciences, Duke University, Durham, NC, USA. rima.kaddurahdaouk@duke.edu.
²⁶ Department of Medicine, Duke University, Durham, NC, USA. rima.kaddurahdaouk@duke.edu.
²⁷ School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia. r.martins@ecu.edu.au.
²⁸ Cooperative research Centre (CRC) for Mental Health, Sydney, NSW, Australia. r.martins@ecu.edu.au.
²⁹ Department of Biomedical Sciences, Macquarie University, Sydney, NSW, Australia. r.martins@ecu.edu.au.
³⁰ KaRa Institute of Neurological Disease, Sydney, NSW, Australia. r.martins@ecu.edu.au.
³¹ School of Psychiatry and Clinical Neurosciences, The University of Western Australia, Perth, WA, Australia. r.martins@ecu.edu.au.
³² Australian Alzheimer's Research Foundation, Nedlands, WA, Australia. r.martins@ecu.edu.au.
³³ Baker Heart and Diabetes Institute, Melbourne, VIC, Australia. peter.meikle@baker.edu.au.
³⁴ Monash University, Melbourne, VIC, 3800, Australia. peter.meikle@baker.edu.au.

PMID: 33173055
PMCID: PMC7655942
DOI: 10.1038/s41467-020-19473-7

Concordant peripheral lipidome signatures in two large clinical studies of Alzheimer's disease

Kevin Huynh et al. Nat Commun. 2020.

. 2020 Nov 10;11(1):5698.

doi: 10.1038/s41467-020-19473-7.

Authors

Affiliations

¹ Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.
² Monash University, Melbourne, VIC, 3800, Australia.
³ School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia.
⁴ Cooperative research Centre (CRC) for Mental Health, Sydney, NSW, Australia.
⁵ Department of Mathematics and Statistics, La Trobe University, Melbourne, VIC, Australia.
⁶ Melbourne School of Global and Population Health, The University of Melbourne, Melbourne, VIC, 3010, Australia.
⁷ School of Mathematics and Statistics, The University of Melbourne, Melbourne, VIC, 3010, Australia.
⁸ Department of Biomedical Sciences, Macquarie University, Sydney, NSW, Australia.
⁹ KaRa Institute of Neurological Disease, Sydney, NSW, Australia.
¹⁰ Collaborative Genomics Group, School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia.
¹¹ Curtin Health Innovation Research Institute, Curtin University, Perth, WA, Australia.
¹² The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, Australia.
¹³ Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, VIC, Australia.
¹⁴ Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, VIC, Australia.
¹⁵ National Ageing Research Institute, Parkville, VIC, 3050, Australia.
¹⁶ Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA.
¹⁷ Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
¹⁸ Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
¹⁹ Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.
²⁰ Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA.
²¹ Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA.
²² Rosa & Co LLC, San Carlos, CA, USA.
²³ Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
²⁴ Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA. rima.kaddurahdaouk@duke.edu.
²⁵ Duke Institute of Brain Sciences, Duke University, Durham, NC, USA. rima.kaddurahdaouk@duke.edu.
²⁶ Department of Medicine, Duke University, Durham, NC, USA. rima.kaddurahdaouk@duke.edu.
²⁷ School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia. r.martins@ecu.edu.au.
²⁸ Cooperative research Centre (CRC) for Mental Health, Sydney, NSW, Australia. r.martins@ecu.edu.au.
²⁹ Department of Biomedical Sciences, Macquarie University, Sydney, NSW, Australia. r.martins@ecu.edu.au.
³⁰ KaRa Institute of Neurological Disease, Sydney, NSW, Australia. r.martins@ecu.edu.au.
³¹ School of Psychiatry and Clinical Neurosciences, The University of Western Australia, Perth, WA, Australia. r.martins@ecu.edu.au.
³² Australian Alzheimer's Research Foundation, Nedlands, WA, Australia. r.martins@ecu.edu.au.
³³ Baker Heart and Diabetes Institute, Melbourne, VIC, Australia. peter.meikle@baker.edu.au.
³⁴ Monash University, Melbourne, VIC, 3800, Australia. peter.meikle@baker.edu.au.

PMID: 33173055
PMCID: PMC7655942
DOI: 10.1038/s41467-020-19473-7

Abstract

Changes to lipid metabolism are tightly associated with the onset and pathology of Alzheimer's disease (AD). Lipids are complex molecules comprising many isomeric and isobaric species, necessitating detailed analysis to enable interpretation of biological significance. Our expanded targeted lipidomics platform (569 species across 32 classes) allows for detailed lipid separation and characterisation. In this study we examined peripheral samples of two cohorts (AIBL, n = 1112 and ADNI, n = 800). We are able to identify concordant peripheral signatures associated with prevalent AD arising from lipid pathways including; ether lipids, sphingolipids (notably GM₃ gangliosides) and lipid classes previously associated with cardiometabolic disease (phosphatidylethanolamine and triglycerides). We subsequently identified similar lipid signatures in both cohorts with future disease. Lastly, we developed multivariate lipid models that improved classification and prediction. Our results provide a holistic view between the lipidome and AD using a comprehensive approach, providing targets for further mechanistic investigation.

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Conflict of interest statement

P.J.M., R.N.M., K.H. and W.L.F.L filed a provisional patent using the AIBL data. Application number: App Number 2018901220; DEMENTIA RISK ANALYSIS; Baker Heart and Diabetes Institute, Edith Cowan University. All other authors declare no competing interests.

Figures

**Fig. 1. Characterisation of lipid isomeric species and the relationship of lipid classes and subclasses within the AIBL and ADNI cohorts.**
a Characterisation of sphingomyelin isomers. Black trace corresponds to the chromatogram seen under normal conditions. Additional experimental results in the green and blue traces used for identification, corresponding to SM(d18:1/24:1) and SM(d18:2/24:0) respectively. b Characterisation of glycerophospholipid isomers. Black trace corresponds to the chromatogram seen under normal conditions. Red trace is the same scan after sample acid hydrolysis. c Spearman correlation of total lipid classes, subclasses and commonly reported clinical measures (bolded) for the AIBL baseline and ADNI studies.

**Fig. 2. Associations of lipid class totals with prevalent and incident Alzheimer’s disease.**
Forest plots of lipid class associations for a prevalent Alzheimer’s disease (logistic regression, AIBL = 268 cases, 696 control, ADNI = 178 cases, 210 controls) and b incident Alzheimer’s disease (Cox regression, AIBL = 68 cases, 714 controls, ADNI = 166 cases, 397 controls). Lipid classes are generated by the sum of each individual species measured in each class. Regressions are adjusted for age, sex, BMI, total cholesterol, HDL-C, triglycerides, number of APOE4 alleles, statin use and omega-3 supplementation. AIBL was further adjusted for time points (only in logistic regression analysis) and site of blood collection. ADNI was further adjusted for fasting status.

**Fig. 3. Associations of individual lipid species with prevalent Alzheimer’s disease.**
Forest plot outlining the logistic regression results of individual species, between controls and prevalent AD in both the AIBL (blue n = 268 cases, 696 controls) and ADNI (red, n = 178 cases, 210 controls) cohorts with the combined meta-analysis in the middle (green). P value was corrected for multiple comparison using approach by Benjamini and Hochberg. Covariates include age, sex, BMI, total cholesterol, HDL-C, triglycerides, number of APOE4 alleles, statin use and omega-3 supplementation. Additional covariates for AIBL include site of blood collection and time point while ADNI includes fasting status. Open circles, not significant; closed dark circles, significant after FDR correction; coloured circles, top 20 associations ranked by p value.

**Fig. 4. Associations of individual lipid species with future onset Alzheimer’s disease.**
Forest plot outlining the Cox regression results of individual species, between non-converters and future converters in both the AIBL (cyan n = 68 cases, 714 controls) and ADNI (orange, n = 166 cases, 397 controls) cohorts with the combined meta-analysis in the middle (purple). P value was corrected for multiple comparison using approach by Benjamini and Hochberg. Covariates include age (set as timescale), sex, BMI, total cholesterol, HDL-C, triglycerides, number of APOE4 alleles, statin use and omega-3 supplementation. Open circles, not significant; closed dark circles, uncorrected p value; coloured squares, top 10/20 associations ranked by p value.

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Concordant peripheral lipidome signatures in two large clinical studies of Alzheimer's disease

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Concordant peripheral lipidome signatures in two large clinical studies of Alzheimer's disease

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Conflict of interest statement

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