Building trust in blood biomarkers: Landmark proteomics study identifies reproducible signals in Alzheimer’s disease
A flagship study published in Nature Medicine recently, presents one of the most comprehensive proteomics datasets to date for neurodegenerative diseases. The paper is the first major publication from the Global Neurodegeneration Proteomics Consortium (GNPC), a public–private partnership by Gates Ventures and Janssen Research and Development, with support from international partners including SciLifeLab and the Wallenberg Data Driven Life Science Program (DDLS).
Among the co-authors is Jacob Vogel, DDLS Fellow at Lund University, who contributed to the consortium’s effort to harmonize proteomic data across more than 35,000 blood and cerebrospinal fluid samples. By aggregating data from 23 partner institutions and over 17 independent cohorts spanning North America, Europe, Asia, and Australia, the study demonstrates that blood-based biomarkers for diseases like Alzheimer’s can yield robust, reproducible signals across populations and platforms.
“You almost never see a study that finds a plasma signal and then replicates it across seven plus other cohorts,” says Vogel. “That’s what gives us confidence that we’re on the right track. We need results that aren’t just interesting in one lab, but that work in the real world.”
The study underscores the power of consortium-based science at a time when reproducibility is one of the biggest challenges in biomarker research. By aligning protocols, sharing data, and coordinating analyses across research teams worldwide, the GNPC model enables researchers to identify signals that hold up across populations, platforms, and disease types.
It’s precisely this kind of open, collaborative approach that also drew Jacob Vogel to Sweden.
“What attracted me to SciLifeLab and the DDLS program was the national commitment to open science, to big data, and to building the infrastructure that modern biology depends on,” he says. “For someone early in their career, it’s an incredible environment to step into. SciLifeLab is operating at the cutting edge, and there aren’t many places in the world this focused on pushing the frontier of science.”
Vogel, who grew up in the U.S., sees a fundamental difference in how Sweden approaches research investments. “In many places, funding is more reactive. You wait to see what pans out. But Sweden has taken a proactive stance. It recognizes that these emerging technologies will be transformative, even disruptive, and is choosing to invest heavily now, not later. That’s what makes this place so unique.”
That forward-thinking approach is not just about discovery, it’s also about impact. By generating large-scale, reproducible biomarker data, Vogel and his collaborators are laying the groundwork for clinical use.
“There are at least two key ways these blood-based biomarkers could be useful,” he explains. “In memory clinics, they could help pinpoint the underlying disease when symptoms are unclear, improving diagnosis, prognosis, and matching patients to the right clinical trials. Looking further ahead, reliable early indicators in the blood could allow us to monitor at-risk individuals, like we do with high blood pressure, and act early if levels stay high or symptoms begin to appear.”
To build the GNPC dataset, most of the samples were analyzed using the SomaScan platform, while a small proportion was analyzed with mass spectrometry. With this foundation, the next phase of the GNPC project is already underway, scaling to over 50,000 samples using NULISA, Olink Explore HT, and SomaScan.
“The platforms aren’t interchangeable,” says Vogel. “Sometimes they even show opposite trends. But that’s exactly why it’s so important to compare them. Each method brings a different lens.” Many of these technologies are also available in-house at SciLifeLab, “it’s the kind of technology that allows us to do the sci-fi things that we dream,” he says.
Importantly, the GNPC dataset is now openly available to the research community, with a dedicated website for data requests and further resources. The consortium strongly encourages scientists worldwide to explore the data, collaborate, and build upon these findings. A growing collection of papers already highlights the breadth of research possibilities.
