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. 2022;86(4):1875-1895.
doi: 10.3233/JAD-215448.

Targeted Metabolomic Analysis in Alzheimer's Disease Plasma and Brain Tissue in Non-Hispanic Whites

Karel Kalecký  1   2 , Dwight C German  3 , Albert A Montillo  4 , Teodoro Bottiglieri  1   2
Affiliations

Targeted Metabolomic Analysis in Alzheimer's Disease Plasma and Brain Tissue in Non-Hispanic Whites

Karel Kalecký et al. J Alzheimers Dis. 2022.

Abstract

Background: Metabolites are biological compounds reflecting the functional activity of organs and tissues. Understanding metabolic changes in Alzheimer's disease (AD) can provide insight into potential risk factors in this multifactorial disease and suggest new intervention strategies or improve non-invasive diagnosis.

Objective: In this study, we searched for changes in AD metabolism in plasma and frontal brain cortex tissue samples and evaluated the performance of plasma measurements as biomarkers.

Methods: This is a case-control study with two tissue cohorts: 158 plasma samples (94 AD, 64 controls; Texas Alzheimer's Research and Care Consortium - TARCC) and 71 postmortem cortex samples (35 AD, 36 controls; Banner Sun Health Research Institute brain bank). We performed targeted mass spectrometry analysis of 630 compounds (106 small molecules: UHPLC-MS/MS, 524 lipids: FIA-MS/MS) and 232 calculated metabolic indicators with a metabolomic kit (Biocrates MxP® Quant 500).

Results: We discovered disturbances (FDR≤0.05) in multiple metabolic pathways in AD in both cohorts including microbiome-related metabolites with pro-toxic changes, methylhistidine metabolism, polyamines, corticosteroids, omega-3 fatty acids, acylcarnitines, ceramides, and diglycerides. In AD, plasma reveals elevated triglycerides, and cortex shows altered amino acid metabolism. A cross-validated diagnostic prediction model from plasma achieves AUC = 82% (CI95 = 75-88%); for females specifically, AUC = 88% (CI95 = 80-95%). A reduced model using 20 features achieves AUC = 79% (CI95 = 71-85%); for females AUC = 84% (CI95 = 74-92%).

Conclusion: Our findings support the involvement of gut environment in AD and encourage targeting multiple metabolic areas in the design of intervention strategies, including microbiome composition, hormonal balance, nutrients, and muscle homeostasis.

Keywords: Alzheimer’s disease; antioxidants; bacterial toxins; biomarkers; human microbiome; hyperlipidemia; lipidomics; metabolic pathways; metabolomics; polyamines.

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Conflict of interest statement

Authors’ disclosures available online (https://www.j-alz.com/manuscript-disclosures/21-5448r1).

Figures

Fig. 1
Fig. 1
Volcano Plots for Plasma Metabolites. Volcano plots of AD regression coefficients for small molecules (A) and lipids (B) in plasma. The red referrence line denotes FDR significance of 0.05. The most outlying values for small molecules are labeled. Notice the large skew towards positive significant values in lipids, indicating hyperlipidemia. 5-AVA, 5-aminovaleric acid; beta-Ala, β-alanine; DHA, docosahexaenoic acid; EPA, eicosapentaenoic; Ind-SO4, indoxyl sulfate; 3-IAA, 3-indoleacetic acid; 3-IPA, 3-indolepropionic acid; t4-OH-Pro, trans-4-hydroxyproline.
Fig. 2
Fig. 2
Predictive Performance and Most Important Features For Plasma Samples. A) AUC of a diagnostic prediction model for AD versus controls in the plasma cohort in dependence on the number of selected features (analytes+basic sociodemographic profile: sex, age, education, BMI, APOE ɛ4). Dashed gold line shows AUC of a reference model using only basic sociodemographic profile. Dashed black line shows AUC of a reference random model. Shaded areas illustrate 95% confidence intervals. The p-value was obtained with DeLong’s test between the full model and basic model. B) Average importance (magnitude of feature contribution to the model decision) of the model features plotted against the feature rank (as ranked by consecutive feature elimination, 0 = best). The green line denotes a threshold of top 30 features, which are deatiled in (C). The color scale corresponds to the importance weight. Positive value: increased in AD; negative: decreased in AD. This figure presents results averaged over 20 randomizations to reduce random noise. Metabolic indicators: Asymmetrical arginine methylation, asymmetrically dimethylated arginine (ADMA)/arginine; Carnosine synthesis, carnosine/histidine; MCAD deficiency screen, C8/C2; 1-Methylhistidine synthesis, 1-methylhistidine/(carnosine + anserine); Proline hydroxylation, hydroxyproline/proline; SBCAD deficiency screen, C5/C0. ACs, acylcarnitines; AUC, area under receiver operating characteristic curve; 5-AVA, 5-aminovaleric acid; CE, cholesteryl ester; Cer, ceramide; Cn, acylcarnitine Cn:0; DHA, docosahexaenoic acid; DHEAS, dehydroepiandrosterone sulfate; 2MBG, 2-methylbutyrylglycinuria; MCAD, medium-chain acyl-CoA dehydrogenase; OH, hydroxylated; PC, phosphatidylcholine; PUFA, polyunsaturated fatty acid; SBCAD, short/branched-chain acyl-CoA dehydrogenase; TG, triglyceride; VLCFA, very long-chain fatty acid.
Fig. 3
Fig. 3
Predictive Performance and Most Important Features For Cortex Samples. A) AUC (area under receiver operating characteristic curve) of a diagnostic prediction model for AD versus controls in the cortex cohort in dependence on the number of selected features (analytes + basic sociodemographic profile: sex, age, education, BMI, APOE ɛ4). Dashed gold line shows AUC of a reference model using only basic sociodemographic profile. Dashed black line shows AUC of a reference random model. Shaded areas illustrate 95% confidence intervals. The p-value was obtained with DeLong’s test between the full model and basic model. B) Average importance (magnitude of feature contribution to the model decision) of the model features plotted against the feature rank (as ranked by consecutive feature elimination, 0 = best). The green line denotes a threshold of top 30 features, which are deatiled in (C). The color scale corresponds to the importance weight. Positive value: increased in AD; negative: decreased in AD. This figure presents results averaged over 20 randomizations to reduce random noise. Metabolic indicators: Anserine synthesis, anserine/carnosine; MC deficiency screen, C16/C3; Serotonin synthesis, serotonin/tryptophan; Spermidine synthesis, spermidine/putrescine. ACs, acylcarnitines; ae, acyl-alkyl; alpha-AAA, α-aminoadipic acid; AUC, area under receiver operating characteristic curve; 5-AVA, 5-aminovaleric acid; CE, cholesteryl ester; Cer, ceramide; Cn, acylcarnitine Cn:0; OH, hydroxylated; PC, phosphatidylcholine; MC, multiple carboxylase; MUFA, monounsaturated fatty acid; t4-OH-pro, trans-4-hydroxyproline; TG, triglyceride.
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