​In 2022, we initiated a series of biomarker case studies aimed at enhancing the understanding, detection and diagnosis of neurodegenerative diseases such as Alzheimer's Disease (AD), Parkinson's Disease (PD), and Dementia with Lewy Bodies (DLB). These studies not only advance biomarker research but also serve to test and refine our data and sample sharing platform.

EPND's Sanofi partner Rajaraman "Ram" Krishnan, who is Senior Director for Research in the Rare and Neurologic Diseases Therapeutic Area (RNDTA), will be presenting case study results at the 2025 AD PD conference in Vienna. Ram also co-leads our case study workstream, together with Prof. Giovanni Frisoni and Dr. Sophie Mutel from the University of Geneva. To find out more, we spoke to Ram, who shared some of the key findings, as well as his views on how EPND can accelerate biomarker research.

Hi Ram! What is the background to the research you are presenting at AD PD, and what was the research question you were trying to answer?

The EPND case studies aim to advance biomarker research while road testing the EPND platform across multiple neurodegenerative diseases, including Alzheimer’s Disease (AD), Parkinson’s Disease (PD), and Dementia with Lewy Bodies (DLB). By analysing biomarkers across these diseases, we seek to identify commonalities and distinctions between different diseases at a molecular level.

The work I’m presenting at AD/PD focuses on case studies 1 and 2, which investigate cerebrospinal fluid (CSF) and plasma biomarkers associated with amyloid aggregation, neurodegeneration, and neuroinflammation. Specifically, we asked whether the levels of neurodegeneration- and neuroinflammation-associated biomarkers correlate with amyloid beta, tau, or alpha-synuclein aggregates, as well as disease type and progression.

What were the key findings?

To understand the molecular mechanisms underlying AD, PD and DLB, we used the Olink system to analyse over 3000 different proteins in each CSF sample. This revealed a few really interesting findings. First of all, we saw that around 10% of the proteins measured in CSF from AD patients were significantly different from controls. We saw similar numbers – but for different proteins – in PD. Only 3% of CSF proteins showed changes in DLB samples.

Secondly, we found that strong levels of complement activation correlated with levels of pTau181 in CSF samples. Participants with high levels of pTau181 in CSF were also likely to have high levels of complement biomarkers. This observation was consistent with previous findings from EPND. We do not yet know what the complete consequence of this finding, but it suggests that the buildup of tau aggregates is linked with neuroinflammation and faster neurodegeneration.

Together, these results reveal connections between different pathologies, which is advancing our understanding of disease biology. In the future, this information could inform our selection of therapeutic approaches for neurodegenerative diseases as well as the assessment of their efficacy.

What methods and cohorts were involved?

This study brought together biomarker technologies from several different companies. As well as the Olink platform, samples were analysed using the NeuroToolKit (Roche Diagnostics), with ELISA tests for complement (Merck and SVAR) and the SOMAscan proteomics system. In total, over a million data measurements were carried out.

EPND allows the scientific community to collaborate in a much more effective way. Thanks to the Hub, we can get information on studies, datasets and biosample collections - so we can find resources we are interested in, and contact investigators.

Rajaraman Krishnan, Senior Director for Research, Sanofi

This study would not have been possible without the collaboration of academic cohorts, study investigators, and, most importantly, the participants who provided biosamples and data. A total of 350 CSF samples were obtained from 10 European cohorts across six centres, including the Amsterdam Dementia Cohort (Amsterdam University Medical Center), the DANCER, DELCODE, DESCRIBE, and MiGAP cohorts (DZNE), COSCODE/gMAD cohort (University of Geneva), the Luxembourgish Parkinson’s Study (University of Luxembourg), NOR-DLB (Stavanger University Hospital), and DDI (Akershus University Hospital).

How can proteomics advance our understanding of neurodegenerative diseases, and how could your findings impact how we detect, diagnose or treat these conditions?

Neurodegenerative diseases such as AD, PD and DLB are highly heterogeneous, with multiple risk factors influencing their onset, progression, and severity. This makes them very complicated to diagnose, treat and prevent. Large-scale proteomic analyses are incredibly powerful, allowing thousands of proteins to be measured in a single sample, providing unparalleled insights into biological processes.

We anticipate that these proteomic measurements will enhance the accurate diagnosis of neurodegenerative diseases, including AD, PD, multiple system atrophy (MSA), DLB, and tauopathies. Additionally, they have the potential to improve disease progression assessment, offering a level of precision comparable to or exceeding Braak staging. Furthermore, this approach could be instrumental in evaluating target engagement and therapeutic efficacy, supporting the development of more effective treatments.

What is the value of cross-cohort research, and what makes EPND special for you?

The EPND Hub is a fantastic resource for the neurodegeneration community. It allows investigators to identify, request and access high quality biosamples across Europe, to advance their research. Currently there is demographic and clinical information for over 90 neurodegenerative disease cohorts, representing over 265,000 research participants. This allows researchers to choose large patient populations for research, minimising individual variability and allowing us to discover really fundamental aspects of disease biology.

EPND also allows the scientific community to collaborate in a much more effective way. For example, Sanofi over the years has used EPND as an umbrella to initiate collaborations with investigators at Amsterdam University Medical Center, Maastricht University, Oxford University, University College London, the Karolinska Institute, and Gothenburg University. Thanks to the EPND Hub, we can get information on studies, datasets and biosample collections, so we can find resources we are interested in, contact investigators, and initiate collaborations.

Download Ram's poster by clicking on the button below.