# Study of blood biomarkers detected in NULISA to stratify the prospective multicenter ALZAN cohort of memory clinic patients according to ATN status, presence of synucleinopathy and diagnosis

## TL;DR

This study evaluates blood biomarkers in a memory clinic cohort to identify Alzheimer's disease and related dementias based on brain amyloidopathy, neurodegeneration, and synucleinopathy.

## Contribution

The study identifies top-performing blood biomarkers for Alzheimer's disease and highlights new potential targets using a multiplex approach.

## Key findings

- pTau_231, pTau_217, and pTau_181 were top biomarkers for brain amyloidopathy and Alzheimer's disease.
- No blood biomarkers showed significant differences for synucleinopathy detection.
- The study emphasizes the value of combining multiple biomarkers and investigating confounding factors.

## Abstract

The objective of this study in the multicenter prospective ALZAN cohort is to assess the performance of blood biomarkers for detecting biological processes based on the ATN classification and synuclein seed amplification assay (SAA), as well as for diagnosing Alzheimer's disease (AD) and related dementias, including frontotemporal dementia and Lewy body dementia.

The ALZAN cohort (NCT05427448) consists of over 400 patients seen in memory clinics at the Montpellier and Nîmes university hospitals and Perpignan hospital. As part of standard care, cerebrospinal fluid (CSF) biomarkers (Aβ40/42, Tau, pTau181) are measured. Clinical and biological data, including ApoE4 status and Mini‐Mental State Examination (MMSE) scores, are collected. Blood biomarkers are measured in plasma using the ultrasensitive multiplex NULISA approach, allowing relative quantification of 120 biomarkers of interest (https://alamarbio.com/). Biomarker performance is assessed by comparing patient groups stratified by core CSF AD biomarkers, SAA, and clinical diagnosis.

Among the 120 biomarkers measured using NULISA, those that remained statistically significant after adjustment for age, sex, body mass index (BMI), and ApoE4 status, considering multiple comparisons, were ranked in order of performance as follows:

For brain amyloidopathy (57% of the population, based on CSF biomarkers): pTau_217>pTau_231>pTau_181>GFAP>MAPT>BACE1>SQSTM1>ANXA5>RUVBL2>TARDBP>NRGN.

For neurodegeneration (49% of the population, based on total Tau in CSF): pTau_231>pTau_217>pTau_181>GFAP>MAPT>RUVBL2>TARDBP>IL18>ANXA5>NRGN>pTDP43_409>HTT>pSNCA_129>IL1B>PGK1>CD40LG>SOD1>FGF2>IL7>Oligo_SNCA>ARSA>PRDX6>PSEN1>SNCA>SQSTM1>UCHL1.

For Alzheimer's disease (51% of the population, defined by clinico‐biological criteria): pTau_231>pTau_217>pTau_181>GFAP>MAPT>BACE1>TARDBP>ANXA5>NRGN>RUVBL2>pTDP43_409>pSNCA_129>IL18>SOD1>SNCA>NCA>SQSTM1>CRP>MDH1.

For synucleinopathy (14% of the population, based on CSF SAA): No blood biomarkers showed significant differences.

This study identifies among the 120 biomarkers many already known to be pathological in AD. However, it also highlights new potential targets, emphasizing the value of this multiplex approach. Further analysis combining multiple biomarkers (ratios) will be useful, along with investigations into the impact of confounding factors such as renal function and pre‐analytical treatment. Notably, none of these blood biomarkers were able to differentiate between SSA‐positive and negative cases.