Wiesje Van der Flier, Netherlands
Amsterdam UMC Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAuthor Of 6 Presentations
CSF PROTEIN PANELS REFLECTING MULTIPLE PATHOPHYSIOLOGICAL MECHANISMS FOR EARLY AND SPECIFIC DIAGNOSIS OF ALZHEIMER’S DISEASE.
Abstract
Aims
Development of disease-modifying therapies against Alzheimer’s disease (AD) requires early and specific diagnostic biomarkers that depict the molecular complexity of AD, whose clinicopathological features overlap with other common forms of dementia. Here we aimed to identify panels of cerebrospinal fluid (CSF) proteins covering different molecular pathways for early and specific diagnosis of AD.
Methods
We analyzed 979 proteins in CSF samples from patients with mild cognitive impairment with amyloid pathology (MCI-Aβ+;n=50), AD (n=230), non-AD dementias (n=322) and non-demented controls (n=195) using proximity ligation-based multiplex immunoassays
Results
CSF proteins were strongly dysregulated in MCI-Aβ+ (110 proteins) or AD (281 proteins) compared to controls as well as between AD and non-AD dementias (455 proteins). Proteins dysregulated in early AD stages were primarily related to oxidative stress and energy metabolism, while those dysregulated in later stages were related to cell remodeling, vascular function and immune system. We identified practicable CSF protein panels (<10 proteins) with a strong power to discriminate between MCI-Aβ+ or AD and controls (AUC: 0.99 and 0.95 respectively) or between AD and non-AD dementias (AUC: 0.87). The CSF panel discriminating AD from non-demented controls was validated in an independent cohort (n=62, AUC: 0.94). The selected proteins were linked to multiple AD-related mechanisms including energy/glucose metabolism, lysosomal function, vascular and immune system.
Conclusions
In this unprecedent large CSF study we identified and validated protein panels reflecting the specific molecular fingerprint of AD with high accuracy, which can be translated into customized assays for widespread validation and potential use in routine diagnosis or clinical trials.
NOVEL CSF INFLAMMATORY MARKERS MIF AND TREM-1 ARE INCREASED IN ALZHEIMER’S DISEASE
Abstract
Aims
Our recent discovery cerebrospinal fluid (CSF) proteomics study, revealed potential AD-specific biomarkers related to inflammatory pathology, such as migration inhibitory factor (MIF) and triggering receptor expressed on myeloid cells 1 (TREM-1). Here, we aimed to validate these findings including also samples from patients with dementia with Lewy Body (DLB) using an accessible technology, with the purpose for clinical implementation.
Methods
MIF and TREM-1 were measured in CSF from patients with AD (n=38), DLB (MIF: n=50, TREM-1: n=40) and non-demented controls (cognitively unimpaired, n=37) using assays on the antibody-based SimplePlex technology, that were validated for CSF analysis. Differences in protein levels between diagnostic groups and their correlation to AD CSF biomarkers and mini-mental state examination (MMSE) scores were tested.
Results
CSF MIF levels were increased in AD (1.2-fold, p=0.002) and DLB (1.14-fold, p=0.036) compared to controls. MIF levels correlated with both total- and phosphorylated-Tau (t-Tau, r=0.652, p<0.001; p-Tau, r=0.682 p<0.001) but not with Amyloid-beta 42 (Aβ42, p>0.05) or MMSE (p>0.05). CSF TREM-1 levels were increased in AD compared to DLB (1.4-fold, p=0.016) and controls (1.5-fold, p=0.003) and correlated with CSF biomarkers (t-Tau: r=0.317, p=0.001; p-Tau: r=0.297, p=0.001; Aβ42: r=-0.221, p=0.018) but not with MMSE (p>0.05).
Conclusions
Inflammatory-related proteins MIF and TREM-1 are increased in AD, thereby, validating our previous proteomics study in an independent cohort using a technology that can be used to reach clinical implementation. These novel biomarkers reflect an underlying neuroinflammatory process in AD, and further studies are needed to establish their diagnostic potential for the discrimination of AD from other dementias.
TOPMED-IMPUTED GENOME-WIDE ASSOCIATION STUDY OF ALZHEIMER’S DISEASE IN THE EADB PROJECT
Abstract
Aims
Strong efforts are still needed to characterize the genetic architecture of Alzheimer’s disease (AD). We thus conducted a complementary genome-wide association study (GWAS) with increased sample size and improved imputation quality of low frequency variants by applying the new TOPMed imputation panel.
Methods
The GWAS was performed in the European Alzheimer Disease Biobank (EADB) dataset. It groups together the main European AD GWAS consortia and a new dataset of 20,464 AD cases and 22,244 controls of European ancestry. Imputation was performed with the TOPMed reference panel or with the Haplotype Reference Consortium panel. The EADB results were meta-analysed with a proxy-AD GWAS performed in the UK Biobank, leading to a total Stage 1 sample size of 39,106 clinically diagnosed AD cases, 46,828 proxy-AD cases and 401,577 controls. The best hits from Stage 1 were finally tested in a large set of independent samples from ADGC and CHARGE.
Results
We identified 65 loci with a genome-wide significant signal of association (P<5x10-8), including 31 new AD loci. The most significant gene sets identified by a pathway analysis relate to amyloid-beta and tau, while many of the other most significant sets relate to lipids and immunity.
Conclusions
The EADB project allowed us to identify several new associated loci for AD, including several candidate genes linked to amyloid precursor protein metabolism or that are likely to be involved in AD-related microglia dysfunctions, and loci already associated with the risk of developing other neurodegenerative diseases. Additional insights into the genetics of AD are expected from other ongoing analyses.
FUNCTIONAL INTERPRETATION OF GENETIC RISK LOCI FOR DEMENTIA USING A PROTEIN QUANTITATIVE TRAIT LOCI (PQTLS) APPROACH IN CEREBROSPINAL FLUID
Abstract
Aims
Exact biological mechanisms through which genetic risk factors contribute to dementia remains unclear. To reveal intermediate molecular pathways connecting genetic variance to development of dementia, we aimed to identify protein quantitative trait loci (pQTLs) in cerebrospinal fluid (CSF) in Alzheimer’s disease (AD), dementia with Lewy bodies (DLB) and frontotemporal dementia (FTD).
Methods
We included 503 subjects for discovery (146 controls, 214 AD, 50 DLB, 93 FTD) and 99 for validation from the Amsterdam Dementia Cohort, from which genetics (Illumina Genome Screening Array) and CSF proteomics (n=665, ligand-proximity immunoarrays) was available. Association signals between risk loci and CSF proteins were tested using linear regression with Bonferroni correction, adjusted for principal components, age and sex and stratified by diagnosis.
Results
Three AD and one DLB risk loci were associated with levels of seven CSF proteins (Figure 1). CR1 locus associated with higher CR2 (Pdiscovery=5.47e-7, Preplication=1.66e-3), ZCWPW1 with lower PILRB (Pdiscovery=2.73e-32, Preplication=7.82e-8) and HESX1 with higher RETN CSF levels (Pdiscovery=6.00e-8, Preplication=0.01); proteins related to the immune system and glucose metabolism. DLB locus GBA associated with higher CSF protein levels of ANG, CD79B, CXCL13 and TNFRSF13B (all Pdiscovery<1.00x10-8); proteins associated to angiogenesis and immune response. FTD risk loci did not significantly associate with CSF proteins.
Conclusions
The four pQTLs identified suggest that specific risk loci for AD and DLB may contribute to the pathogenesis of these dementias by exerting effects on the immune system, glucose metabolism and angiogenesis. Dissecting the contribution of risk loci to neurobiological processes aids in understanding disease mechanisms underlying different types of dementia.
LIVE DISCUSSION
- Takeshi Iwatsubo, Japan
- Philip Scheltens, Netherlands
- Eliezer Masliah, United States of America
- Hitoshi Okazawa, Japan
- Ronald C. Petersen, United States of America
- Peter J. Snyder, United States of America
- John C. Morris, United States of America
- Shannon L. Risacher, United States of America
- Wiesje Van der Flier, Netherlands
THE ATN FRAMEWORK FOR AD RESEARCH SET TO WORK: REAL WORLD EVIDENCE
Abstract
Abstract Body
The ATN framework clearly paves the way for a diagnosis before the stage of AD-dementia. In clinical practice, a diagnosis in predementia stages in fact entails a prognosis, as patients want to know what they can expect. Using ATN biomarkers, individualized risk profiling for MCI patients becomes feasible. A clinical encounter study evaluating doctor-patient communication in memory clinics revealed however that clinicians are quite reluctant to share specific prognostic information with MCI patients. In the context of predementia diagnosis, Subjective Cognitive Decline (SCD) is even more challenging. A recent point of view paper provides a clinical characterization of SCD, and attempts to provide directions for clinicians. Although on a group level, ATN biomarkers clearly predict incident dementia in SCD, individualized risk modeling remains challenging, as current models have suboptimal generalizability, due to the lack of truly longitudinal data.Yet, the number of people wanting to know the status of their brain health with the ambition to maintain or improve their own brain health rapidly increases. In a Delphi study to identify topics most relevant to discuss in the diagnostic process, patients and caregivers indicated they value precise and specific information, even when that does not provide complete certainty.Tools to support both clinicians and patients/families in decision making and communicating about AD diagnosis are therefore urgently needed. ADappt (www.adappt.health) is a first attempt at providing such a tool.
Presenter of 2 Presentations
LIVE DISCUSSION
- Takeshi Iwatsubo, Japan
- Philip Scheltens, Netherlands
- Eliezer Masliah, United States of America
- Hitoshi Okazawa, Japan
- Ronald C. Petersen, United States of America
- Peter J. Snyder, United States of America
- John C. Morris, United States of America
- Shannon L. Risacher, United States of America
- Wiesje Van der Flier, Netherlands
THE ATN FRAMEWORK FOR AD RESEARCH SET TO WORK: REAL WORLD EVIDENCE
Abstract
Abstract Body
The ATN framework clearly paves the way for a diagnosis before the stage of AD-dementia. In clinical practice, a diagnosis in predementia stages in fact entails a prognosis, as patients want to know what they can expect. Using ATN biomarkers, individualized risk profiling for MCI patients becomes feasible. A clinical encounter study evaluating doctor-patient communication in memory clinics revealed however that clinicians are quite reluctant to share specific prognostic information with MCI patients. In the context of predementia diagnosis, Subjective Cognitive Decline (SCD) is even more challenging. A recent point of view paper provides a clinical characterization of SCD, and attempts to provide directions for clinicians. Although on a group level, ATN biomarkers clearly predict incident dementia in SCD, individualized risk modeling remains challenging, as current models have suboptimal generalizability, due to the lack of truly longitudinal data.Yet, the number of people wanting to know the status of their brain health with the ambition to maintain or improve their own brain health rapidly increases. In a Delphi study to identify topics most relevant to discuss in the diagnostic process, patients and caregivers indicated they value precise and specific information, even when that does not provide complete certainty.Tools to support both clinicians and patients/families in decision making and communicating about AD diagnosis are therefore urgently needed. ADappt (www.adappt.health) is a first attempt at providing such a tool.