Literature DB >> 35445209

Sex Differences in the Metabolome of Alzheimer's Disease Progression.

Tomás González Zarzar1,2, Brian Lee3, Rory Coughlin1, Dokyoon Kim3, Li Shen3, Molly A Hall1,2,4.   

Abstract

Alzheimer's disease (AD) is the leading cause of dementia; however, men and women face differential AD prevalence, presentation, and progression risks. Characterizing metabolomic profiles during AD progression is fundamental to understand the metabolic disruptions and the biological pathways involved. However, outstanding questions remain of whether peripheral metabolic changes occur equally in men and women with AD. Here, we evaluated differential effects of metabolomic and brain volume associations between sexes. We used three cohorts from the Alzheimer's Disease Neuroimaging Initiative (ADNI), evaluated 1,368 participants, two metabolomic platforms with 380 metabolites in total, and six brain segment volumes. Using dimension reduction techniques, we took advantage of the correlation structure of the brain volume phenotypes and the metabolite concentration values to reduce the number of tests while aggregating relevant biological structures. Using WGCNA, we aggregated modules of highly co-expressed metabolites. On the other hand, we used partial least squares regression-discriminant analysis (PLS-DA) to extract components of brain volumes that maximally co-vary with AD diagnosis as phenotypes. We tested for differences in effect sizes between sexes in the association between single metabolite and metabolite modules with the brain volume components. We found five metabolite modules and 125 single metabolites with significant differences between sexes. These results highlight a differential lipid disruption in AD progression between sexes. Men showed a greater negative association of phosphatidylcholines and sphingomyelins and a positive association of VLDL and large LDL with AD progression. In contrast, women showed a positive association of triglycerides in VLDL and small and medium LDL with AD progression. Explicitly identifying sex differences in metabolomics during AD progression can highlight particular metabolic disruptions in each sex. Our research study and strategy can lead to better-tailored studies and better-suited treatments that take sex differences into account.

Entities:  

Keywords:  Alzheimer’s disease; metabolomics; phosphatidylcholine; sex differences; very low-density lipoprotein (VLDL)

Year:  2022        PMID: 35445209      PMCID: PMC9014653          DOI: 10.3389/fradi.2022.782864

Source DB:  PubMed          Journal:  Front Radiol        ISSN: 2673-8740


  64 in total

Review 1.  Partial least squares-discriminant analysis (PLS-DA) for classification of high-dimensional (HD) data: a review of contemporary practice strategies and knowledge gaps.

Authors:  Loong Chuen Lee; Choong-Yeun Liong; Abdul Aziz Jemain
Journal:  Analyst       Date:  2018-07-23       Impact factor: 4.616

Review 2.  Immune attack: the role of inflammation in Alzheimer disease.

Authors:  Frank L Heppner; Richard M Ransohoff; Burkhard Becher
Journal:  Nat Rev Neurosci       Date:  2015-06       Impact factor: 34.870

3.  Plasma phospholipids identify antecedent memory impairment in older adults.

Authors:  Mark Mapstone; Amrita K Cheema; Massimo S Fiandaca; Xiaogang Zhong; Timothy R Mhyre; Linda H MacArthur; William J Hall; Susan G Fisher; Derick R Peterson; James M Haley; Michael D Nazar; Steven A Rich; Dan J Berlau; Carrie B Peltz; Ming T Tan; Claudia H Kawas; Howard J Federoff
Journal:  Nat Med       Date:  2014-03-09       Impact factor: 53.440

4.  Cardiovascular Risk Factors Associated With Blood Metabolite Concentrations and Their Alterations During a 4-Year Period in a Population-Based Cohort.

Authors:  Maria Elena Lacruz; Alexander Kluttig; Daniel Tiller; Daniel Medenwald; Ina Giegling; Dan Rujescu; Cornelia Prehn; Jerzy Adamski; Stefan Frantz; Karin Halina Greiser; Rebecca Thwing Emeny; Gabi Kastenmüller; Johannes Haerting
Journal:  Circ Cardiovasc Genet       Date:  2016-10-26

5.  Heterogeneous patterns of brain atrophy in Alzheimer's disease.

Authors:  Konstantinos Poulakis; Joana B Pereira; Patrizia Mecocci; Bruno Vellas; Magda Tsolaki; Iwona Kłoszewska; Hilkka Soininen; Simon Lovestone; Andrew Simmons; Lars-Olof Wahlund; Eric Westman
Journal:  Neurobiol Aging       Date:  2018-01-31       Impact factor: 4.673

6.  Sex modifies the APOE-related risk of developing Alzheimer disease.

Authors:  Andre Altmann; Lu Tian; Victor W Henderson; Michael D Greicius
Journal:  Ann Neurol       Date:  2014-04-14       Impact factor: 10.422

7.  Approaches to detect genetic effects that differ between two strata in genome-wide meta-analyses: Recommendations based on a systematic evaluation.

Authors:  Thomas W Winkler; Anne E Justice; L Adrienne Cupples; Florian Kronenberg; Zoltán Kutalik; Iris M Heid
Journal:  PLoS One       Date:  2017-07-27       Impact factor: 3.240

8.  CLARITE Facilitates the Quality Control and Analysis Process for EWAS of Metabolic-Related Traits.

Authors:  Anastasia M Lucas; Nicole E Palmiero; John McGuigan; Kristin Passero; Jiayan Zhou; Deven Orie; Marylyn D Ritchie; Molly A Hall
Journal:  Front Genet       Date:  2019-12-18       Impact factor: 4.599

9.  WGCNA: an R package for weighted correlation network analysis.

Authors:  Peter Langfelder; Steve Horvath
Journal:  BMC Bioinformatics       Date:  2008-12-29       Impact factor: 3.169

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