Abstract

Background

   Multiple pathophysiological processes have been described in
   Alzheimer’s disease (AD). Their inter-individual variations, complex
   interrelations, and relevance for clinical manifestation and disease
   progression remain poorly understood. We hypothesize that specific
   molecular patterns indicating both known and yet unidentified pathway
   alterations are associated with distinct aspects of AD pathology.

Methods

   We performed multi-level cerebrospinal fluid (CSF) omics in a
   well-characterized cohort of older adults with normal cognition, mild
   cognitive impairment, and mild dementia. Proteomics, metabolomics,
   lipidomics, one-carbon metabolism, and neuroinflammation related
   molecules were analyzed at single-omic level with correlation and
   regression approaches. Multi-omics factor analysis was used to
   integrate all biological levels. Identified analytes were used to
   construct best predictive models of the presence of AD pathology and of
   cognitive decline with multifactorial regression analysis. Pathway
   enrichment analysis identified pathway alterations in AD.

Results

   Multi-omics integration identified five major dimensions of
   heterogeneity explaining the variance within the cohort and
   differentially associated with AD. Further analysis exposed multiple
   interactions between single ‘omics modalities and distinct multi-omics
   molecular signatures differentially related to amyloid pathology,
   neuronal injury, and tau hyperphosphorylation. Enrichment pathway
   analysis revealed overrepresentation of the hemostasis, immune
   response, and extracellular matrix signaling pathways in association
   with AD. Finally, combinations of four molecules improved prediction of
   both AD (protein 14-3-3 zeta/delta, clusterin, interleukin-15, and
   transgelin-2) and cognitive decline (protein 14-3-3 zeta/delta,
   clusterin, cholesteryl ester 27:1 16:0 and monocyte chemoattractant
   protein-1).

Conclusions

   Applying an integrative multi-omics approach we report novel molecular
   and pathways alterations associated with AD pathology. These findings
   are relevant for the development of personalized diagnosis and
   treatment approaches in AD.

Supplementary Information

   The online version contains supplementary material available at
   10.1186/s13195-021-00814-7.

   Keywords: Alzheimer’s disease, CSF, MOFA, Multi-omics, Biomarkers

Background

   Along with amyloid pathology and tau-related neurodegeneration,
   multiple other molecular alterations and pathway dysregulations have
   been reported in Alzheimer’s disease (AD). Indeed, there is strong
   evidence that pathophysiological changes involving neuroinflammation
   [[33]1] lipid metabolism [[34]2], one-carbon metabolism [[35]3], amino
   acids [[36]4], and glucose metabolism [[37]5], among others, are
   present in AD. However, the contribution and relevance of these
   alterations to clinical manifestation and progression of the disease as
   well as their inter-individual variations, and complex interrelations,
   remain poorly understood. While these processes are generally not
   considered part of the “core” AD pathology, they may substantially
   contribute to the development of amyloid pathology and
   neurodegeneration and precipitate the manifestation of symptoms. As
   they may be occurring at early clinical and preclinical disease stages,
   a better understanding of these processes may be highly relevant for
   both early diagnosis and prognosis and the design of targeted
   interventions to interfere with developing AD pathology and clinical
   disease progression.

   ‘Omics approaches and technologies have made major progress over the
   past decade to resolve the complexity of the metabolome, lipidome and
   proteome [[38]6]. As powerful phenotyping technologies, ‘omics
   significantly accelerate the understanding of mechanisms of
   pathophysiological alterations that underlie complex diseases such as
   AD [[39]7, [40]8]. Beyond the potential of identifying altered biofluid
   molecule profiles that could be used as biomarkers, these technological
   advances also offer the opportunity to explore different types of
   molecules in parallel by combining multiple ‘omics methods. Recent
   statistical advances have made it possible to integrate the information
   from multiple data modalities for a thorough exploration of
   endophenotype networks and biological interactions related to disease
   [[41]9]. While multi-omics approaches have recently shown their
   potential in relation to different other pathological conditions
   [[42]10–[43]12], these methods still need to be more broadly adapted
   and applied in AD [[44]13].

   Here, we hypothesized that specific patterns of proteins, lipids,
   neuroinflammatory markers, and metabolites are associated with core
   features of the AD pathology and indicate disease-related,
   inter-connected biological pathway alterations. We investigated these
   alterations across multiple biochemical pathways by using a multi-layer
   dataset acquired by analysis of cerebrospinal fluid (CSF) from a cohort
   of elder subjects with normal cognition. In order to integrate data
   from different ‘omics platforms in an unbiased fashion while
   considering interactions between modalities, we combined different
   approaches including single ‘omics analysis and multi-omics factor
   analysis (MOFA) [[45]14–[46]16].

Methods

Study population

   One hundred and twenty community dwelling individuals, aged 55 or
   older, including subjects with normal cognition, mild cognitive
   impairment (MCI), or mild AD dementia (defined as previously described
   [[47]3]), were enrolled into a brain aging study conducted in the
   Department of Psychiatry and the Department of Clinical Neurosciences,
   University Hospital of Lausanne, Switzerland. They were recruited among
   memory clinic outpatients or through advertisement. An overall
   clinical, neurological, and comprehensive neuropsychological assessment
   was performed between 2013 and 2016, which included the Mini Mental
   State Examination (MMSE, [[48]17]) and Clinical Dementia Rating (CDR,
   [[49]18]). Candidates with unstable medical conditions or with
   neurological or psychiatric diseases that could interfere with
   cognitive performance were excluded as previously described [[50]19].
   Clinical and neuropsychological follow-up evaluations were performed at
   18 and 36 months using the same methods and tests.

Study procedures

Clinical assessment

   We determined Mini-Mental State Examination (MMSE), CDR, and CDR sum of
   boxes (CDR-SoB), for all participants. CDR-SoB and CDR were based on
   the information available from the participant and his/her relative,
   the clinical examination, and comprehensive neuropsychological test
   performance, as previously described [[51]19].

Biochemical sample collection and handling

   Ten to 12 ml of cerebrospinal fluid (CSF) obtained from lumbar
   punctures conducted after an overnight fast at participant inclusion
   were spun down at 4 °C, immediately aliquoted, and snap frozen at
   − 80 °C until assayed [[52]19], with no freeze-thaw cycles allowed.
   Samples were stored for a maximum of 3 years before analysis. Study
   personnel blinded to clinical data performed biochemical and genetic
   analyses.

Cerebrospinal fluid AD biomarkers

   CSF beta-amyloid 1-42 (Aβ[1-42]), total-tau (Tau), and tau
   phosphorylated at threonine 181 (P-Tau) concentrations were measured
   using commercially available ELISA kits (Fujirebio, Gent, Belgium) in
   all samples within the cohort.

Analyte measurements

   Multiple ‘omics data from different pathways and various biological
   levels were acquired from a vast majority of participants within the
   cohort (n = 114/120 for proteomics, 118 for metabolomics, 119 for
   neuroinflammation and one-carbon metabolism, and 120 for lipidomics).

   CSF samples were measured using an untargeted shotgun proteomic
   workflow based on liquid chromatography (LC) tandem MS (MS/MS) using an
   Ultimate 3000 RSLC nano system and a hybrid linear ion trap-Orbitrap
   (LTQ-OT) Elite (Thermo Scientific, San Jose, CA, USA) [[53]20, [54]21].
   Relative quantification of proteins between the samples was obtained
   using isobaric tagging with the tandem mass tag technology [[55]22].
   Full experimental details and parameters of the proteomic analysis have
   been published previously [[56]23, [57]24]. A targeted subset of
   thirty-seven CSF inflammatory proteins including IFNγ, IL-1β, IL-2,
   IL-4, IL-6, IL-8, IL-10, IL-13, TNFα, IL-1α, IL-5, IL-7, IL-12/23p40,
   IL-15, IL-16, IL-17A, TNFβ, VEGFA, Eotaxin, MIP-1β, Eotaxin-3, TARC,
   IP-10, MIP-1α, MCP-1, MDC, MCP-4, VEGF-C, VEGF-D, Tie-2, sFLT-1
   (VEGFR-1), PIGF-1R, bFGF, SAA1, CRP, sVCAM-1, and sICAM-1 were
   separately quantified using a sandwich immunoassay (Meso Scale
   Diagnostics (MSD), Rockville, MD, USA), according to the manufacturer’s
   instructions. This platform has been validated by the manufacturer
   ([58]https://www.mesoscale.com/~/media/files/product%20inserts/neuroinf
   lammation%20panel%201%20human%20insert.pdf) and has been previously
   used successfully [[59]25].

   CSF lipids were quantified using an MS-based shotgun approach [[60]26].
   This technology can cover 22 quantifiable different lipid classes
   encompassing more than 200 lipid species; it achieves absolute
   quantification, by inclusion of internal standards for every lipid
   class measured. Figure-of-merits are an average coefficient of
   variation of < 10% (intra-day), approximatively 10% (inter-day), and
   approximatively 15% (inter-site) for most lipid species.

   Metabolomic profiling was carried out by means of ^1H NMR spectroscopy,
   as reported previously [[61]27]. This approach covered major metabolic
   pathways, including amino acids, carboxylic acids, and central energy
   metabolism. Metabolites within the one-carbon pathway are a
   hypothesis-driven subset of metabolites [[62]3] and were separately
   analyzed using LC-MS/MS as previously described [[63]28] with an Accela
   UHPLC 1250 Pump coupled to a TSQ Quantum Vantage triple quadrupole mass
   spectrometer equipped with a heated electrospray ionization source
   (Thermo Scientific). Selected reaction monitoring transitions have been
   described previously [[64]28].

   The initial number of analytes measured in CSF, the final number of
   analytes selected per platform (a total of 891 analytes covered), and
   quantification method used for each platform are summarized in
   Table [65]1.

Table 1.

   Datasets used in this study
   Dataset Analytes initial/final Quantification technique References