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. 2024 Oct;20(10):7090-7103.
doi: 10.1002/alz.14194. Epub 2024 Aug 27.

Alzheimer's disease CSF biomarkers correlate with early pathology and alterations in neuronal and glial gene expression

Ali S Ropri  1   2 , Tiffany G Lam  1   2 , Vrinda Kalia  3 , Heather M Buchanan  1   2 , Anne Marie W Bartosch  1   2 , Elliot H H Youth  1   2 , Harrison Xiao  1   2 , Sophie K Ross  1   2 , Anu Jain  4 , Jayanta K Chakrabarty  4 , Min Suk Kang  2   5 , Deborah Boyett  6 , Eleonora F Spinazzi  6 , Gail Iodice  7 , Robert A McGovern  8 , Lawrence S Honig  2   5 , Lewis M Brown  4 , Gary W Miller  3 , Guy M McKhann  6 , Andrew F Teich  1   2   5
Affiliations

Alzheimer's disease CSF biomarkers correlate with early pathology and alterations in neuronal and glial gene expression

Ali S Ropri et al. Alzheimers Dement. 2024 Oct.

Abstract

Introduction: Normal pressure hydrocephalus (NPH) patients undergoing cortical shunting frequently show early Alzheimer's disease (AD) pathology on cortical biopsy, which is predictive of progression to clinical AD. The objective of this study was to use samples from this cohort to identify cerebrospinal fluid (CSF) biomarkers for AD-related central nervous system (CNS) pathophysiologic changes using tissue and fluids with early pathology, free of post mortem artifact.

Methods: We analyzed Simoa, proteomic, and metabolomic CSF data from 81 patients with previously documented pathologic and transcriptomic changes.

Results: AD pathology on biopsy correlates with CSF β-amyloid-42/40, neurofilament light chain (NfL), and phospho-tau-181(p-tau181)/β-amyloid-42, while several gene expression modules correlate with NfL. Proteomic analysis highlights seven core proteins that correlate with pathology and gene expression changes on biopsy, and metabolomic analysis of CSF identifies disease-relevant groups that correlate with biopsy data.

Discussion: As additional biomarkers are added to AD diagnostic panels, our work provides insight into the CNS pathophysiology these markers are tracking.

Highlights: AD CSF biomarkers correlate with CNS pathology and transcriptomic changes. Seven proteins correlate with CNS pathology and gene expression changes. Inflammatory and neuronal gene expression changes correlate with YKL-40 and NPTXR, respectively. CSF metabolomic analysis identifies pathways that correlate with biopsy data. Fatty acid metabolic pathways correlate with β-amyloid pathology.

Keywords: Alzheimer's disease; CSF; biomarkers; metabolomics; proteomics.

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Conflict of interest statement

L.S.H. reports grants from NIH, New York State Dept of Health, Lewy Body Disease Association, CurePSP, Abbvie, Acumen, Alector, Biogen, Bristol‐Myer Squibb, Cognition, EIP, Eisai, Genentech/Roche, Janssen/Johnson and Johnson, Transposon Therapeutics, UCB, and Vaccinex, as well as consulting fees from Biogen, Corium, Eisai, Genentech/Roche, and New Amsterdam, Payment or honoraria from Eisai Pharmaceuticals, Medscape, and Biogen, Payment for expert testimony from Monsanto and legal firms, support for attending meetings and/or travel from Eisai Pharmaceuticals, participation on a data safety monitoring or advisory board from Prevail Therapeutics/Lilly, Cortexyme, and Eisai, and a leadership role in the Alzheimer's Association. G.W.M. reports grant funding from NIH, CancerUK, Department of Defense (USAMRAA), Alley Corp, and SPARK‐NS. A.F.T. reports grant funding from NIH and Regeneron, stock ownership in Biogen and Ionis, paid committee work for DOD and NIH, and unpaid committee work for the Alzheimer's Association. R.A.M. reports grants from NIH, Minnesota Partnership for Biotechnology and Genomics, Minnesota Robotics Institute, and MnDRIVE Data Science Initiative. G.M.M. reports grants from NIH, consulting with Koh Young Inc and NeuroOne Technologies, participation on the Medronic SLATE trial Publication Committee, and leadership/committee roles in the Neurosurgical Society of America, AANS, and ASSFN. L.M.B. reports support from NIH. The other authors have nothing to report. Author disclosures are available in the supporting information.

Figures

FIGURE 1
FIGURE 1
Study overview and review of cohort biopsy data. (A) Schematic for the NPH study in this paper (see text for details). (B) Our four modules correlate with quantified β‐amyloid and tau pathology on the 81 biopsies with CSF similarly to the correlations reported in ref. [10]. For this study, we also added quantified GFAP staining, and correlations with the four modules are shown (* = FDR adjusted p‐value < 0.05, see Table S5 for numbers used in this figure). (C) Schematic for our filtering of proteins for proteomic analysis. We selected proteins that passed an FDR of 0.05 in at least one previously published study and trended in the same direction (i.e., up or down in AD) with an unadjusted p‐value of 0.05 in at least one other study, and which also correlated with one of our pathology variables or gene expression modules with an unadjusted p‐value of 0.05. (See the Methods section for all details of our filtering steps, cohorts labeled using names assigned in ref. [24]). AD, Alzheimer's disease; NPH, normal pressure hydrocephalus.
FIGURE 2
FIGURE 2
Histologic measurements of AD pathology correlate with CSF biomarkers. (A) Correlations of histologic data with CSF Simoa measurements of AD biomarkers. All correlations shown in this figure are Spearman's rank correlation coefficient. The n for each Simoa analysis is variable due to some sample failure. In summary, 80 samples have CSF Aβ40 values, 78 samples have CSF Aβ42 values, 78 samples have CSF Aβ42/40 values, 80 have CSF ptau 181 values, 77 have CSF ptau 181/Aβ42 values, 80 have CSF tau values, and all 81 have CSF NfL values. GFAP staining was also only achieved on 80 samples. All other analyses here and in the rest of the study are completed on all 81 samples. (B) Spearman's correlations of the seven core proteins highlighted in this study with quantified β‐amyloid, tau, and GFAP on biopsy. (C) Biological pathways highlighted by mummichog analysis of metabolite correlations with histologic variables (see the Methods section); *FDR adjusted p‐value < 0.05 in panels A and C, *p‐value < 0.05 in panel B. See text for details, and Tables S2, S6, and S7 for numbers used in this figure. AD, Alzheimer's disease; CFS, Cerebrospinal fluid.
FIGURE 3
FIGURE 3
Biopsy gene expression modules correlate with CSF biomarkers. (A) Correlations of gene expression modules from Figure 1B with CSF Simoa measurements of AD biomarkers. All correlations shown in this figure are Spearman's rank correlation coefficient. (B) Spearman's correlations of the seven core proteins highlighted in this study with gene expression modules. (C) Spearman's correlation across 81 CSF samples of YKL‐40 ELISA values versus microglial (DAM) and astrocytic module eigengenes and NPTXR ELISA values versus neuronal and microglial homeostatic module eigengenes. r‐ and p‐values indicated. (D) Biological pathways highlighted by mummichog analysis of metabolite correlations with gene expression modules (see the Methods section); *FDR adjusted p‐value < 0.05 in panels A and D , *p‐value < 0.05 in panel B. See text for details, and Tables S2, S6, S7, and S9 for numbers used in this figure. AD, Alzheimer's disease; CFS, Cerebrospinal fluid; DAM, disease‐associated microglia.
FIGURE 4
FIGURE 4
CSF YKL‐40 correlates with microglial and astrocytic genes. Shown are the hub genes for the astrocytic and microglial (DAM) modules, with astrocytic genes highlighted for the astrocytic module and microglial genes highlighted for the microglial (DAM) module. Both modules correlate with CSF YKL‐40. The mean gene expression vector of the astrocytic genes from the astrocytic module and microglial genes from the microglial (DAM) module also correlate with YKL‐40, supporting a role for these genes in the relationship between brain pathophysiology and CSF YKL‐40. See, Table S10 for hub gene analysis. DAM, disease‐associated microglia.
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