From Neurological Biomarker Discovery to Clinical Impact

The Accelerated Discovery of DDC – A Novel Biomarker for Early PD and LBD

Diagnosis of Parkinsonian disorders at early stages is challenging, as current clinical parameters detect disease only after significant neurodegeneration has already occurred. A recent study used high-throughput proteomics with Olink’s Explore 3072 platform to identify early, disease-specific biomarkers for PD and Lewy Body dementia (LBD) in cerebrospinal fluid (CSF) and plasma (1). 

Among 14 significantly dysregulated proteins in LBD compared to controls in a prospective cohort, dopa decarboxylase (DDC), stood out in the degree of observed effect, corroborating findings from earlier work by Del Campo et al (2).

In the present study, DDC in CSF had an AUC of 0.89 to discriminate LBD from controls and was associated with worse cognitive performance. It also identified preclinical stages of LBD in cognitively unimpaired individuals (AUC=0.81) and predicted future disease progression.  In the replication cohort, plasma DDC showed an even higher diagnostic performance to identify LBD and atypical Parkinsonian disorders than CFS-derived DDC in the discovery cohort (AUC=0.92), suggesting its potential utility as a minimally invasive early diagnostic tool.

While further evaluation in other cohorts is warranted, the authors conclude that “this biomarker could be important for early and even preclinical detection of Parkinsonian disorders and predict future conversion to clinical LBD.”

Within just 18 months, seven publications from four independent research groups—leveraging Olink protein analysis of patient-derived biofluids and cells — have consistently supported DDC as a novel, early biomarker of Parkinsonian disorders. This underscores the power of broad proteomic screening to accelerate biomarker discovery and translation into clinically relevant tools.

Plasma Proteomics Predicting Dementia in a Southeast Asian Cohort 

In an effort to improve early dementia detection across diverse populations, researchers used Olink Explore 1536 to profile plasma proteins in a Southeast Asian cohort (3). Twelve proteins were significantly associated with future cognitive decline, with NfL and PPY demonstrating the strongest predictive power. A machine learning model incorporating 26 proteins markedly outperformed clinical models alone (AUC 0.85 vs. 0.62). Notably, several markers, including AREG, predicted progression from mild cognitive impairment to dementia. Key findings—particularly for NfL, PPY, GFAP, and AREG—were validated using orthogonal immunoassays and were consistent with CSF-based data in Caucasian populations. Furthermore, the authors state that most of these key findings are consistent with findings published from UKB-PPP data. These results highlight the power of high-throughput proteomics in uncovering scalable, blood-based biomarkers for cognitive decline across diverse populations.

Age-Dependent Proteomic Signatures in MS Reveal Overlapping Pathology and New Potential Therapeutic Targets

Using the Olink Explore platform, researchers profiled CSF and serum from patients with relapsing and progressive forms of MS to identify biomarkers linked to disease stage and age (4). While CSF proteomes of relapsing and progressive MS showed minimal differences, 47 proteins were significantly altered in MS vs. controls—primarily markers of lymphocyte activation and humoral immunity. In an independent cohort, 43 of the 47 markers were validated. Several of these differentially expressed CSF proteins represent entirely novel potential biomarkers for MS, notably LY9 and JCHAIN. Others were suggested as potential new therapeutic avenues, as SLAMF7, BCMA, and IL5RA are already targets for drugs currently approved for other indications.

Importantly, age-stratified analysis revealed a shift in the MS proteome after age 50, with a marked decline in inflammatory markers and a rise in proteins linked to aging (e.g., GDF15, MFGE8). These findings suggest that aging alters the immune response, potentially explaining reduced immunotherapy efficacy in older MS patients and underscoring the need for age-adapted treatment strategies. This study illustrates the power of proteomics to uncover actionable insights into disease heterogeneity and progression.

Proteomics identifies causal protein biomarkers of ALS  

ALS is a complex neurodegenerative disease with limited treatment options, largely due to its poorly understood pathophysiology. Proteomics has emerged as a powerful approach to uncover systemic inflammatory mechanisms that may contribute to disease progression. In this study, researchers integrated proteogenomic data from a SCALLOP consortium (Systematic and Combined AnaLysis of Olink Proteins) project utilizing Olink’s Target 96 Inflammation panel with ALS GWAS data (5). By performing the across a range of p values to ensure they did not miss any information, the authors identified several protein quantitative trait loci (pQTLs) with causal links to ALS risk, including ADA, IL-17C, OSM, LIFR, and OPG. Reverse Mendelian randomization further suggested that ALS itself may influence levels of proteins such as CCL20, TNFSF12, and IL-5—pointing to a bidirectional relationship between neurodegeneration and inflammation. These findings emphasize the role of inflammation in ALS pathology and demonstrate the value of proteomics in revealing novel, causal biomarkers that could guide future therapeutic development for ALS 

What’s next?

These recent studies highlight the translational potential of proteomics in neurology research—from biomarker discovery to real-world application. As research moves toward early detection and personalized interventions, scalable proteomic technologies will be essential for uncovering actionable insights across diverse populations, disease stages, and biological pathways. 

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References

1. Pereira, J.B., Kumar, A., Hall, S. et al. DOPA decarboxylase is an emerging biomarker for Parkinsonian disorders including preclinical Lewy body disease. (2023) Nat Aging.
   https://doi.org/10.1038/s43587-023-00478-y
2. del Campo, M., Vermunt, L., Peeters, et al. CSF proteome profiling reveals biomarkers to discriminate dementia with Lewy bodies from Alzheimer´s disease. (2023) Nat Commun.
   https://doi.org/10.1038/s41467-023-41122-y
3. Sim MA, Doecke JD, Liew OW, et al. Plasma proteomics for cognitive decline and dementia—A Southeast Asian cohort study. (2025) Alzheimer’s Dement.
   https://doi.org/10.1002/alz.14577
4. Held F, Makarov C, Gasperi C, et al. Proteomics Reveals Age as Major Modifier of Inflammatory CSF Signatures in Multiple Sclerosis. (2025) Neurol Neuroimmunol Neuroinflamm.
   doi: 10.1212/NXI.0000000000200322. 
5. Jian H, Dipender G, Verena Z, et. al. Circulatory proteins relate cardiovascular disease to cognitive performance: A mendelian randomisation study (2023) Frontiers in Genetics.
   doi: 10.3389/fgene.2023.1124431