Jörg Hanrieder

Research interest

The research in our lab comprises both the development of innovative spatial biology techniques including imaging mass spectrometry, functional light microscopy and spatial transcriptomics and proteomics. Our central aim is to elucidate molecular aspects of brain amyloidosis associated with neurodegenerative processes particularly in Alzheimer’s disease (AD). In detail, we focuses on delineating beta-amyloid (Aβ) peptide and Tau protein aggregation dynamics, as well as the associated spatial lipid-, gene- and protein signatures in AD and other dementias with the aim to understand the mechanism behind transforming proteins like beta-amyloid (Aβ) and tau from being a non-toxic monomer to a neurotoxic oligomeric species that ultimately leads to nerve cell death and cognitive decline.

Here, our group has over the last years been working on different molecular imaging modalities to probe chemical and structural aspects of amyloid pathology in AD (1,2). We have used a large-scale effort in implementing multimodal chemical imaging technologies for comprehensive analysis of distinct plaque morphotypes in brain tissue (3,4). We developed a novel imaging paradigm that combined structure specific luminescent amyloid dyes with fluorescent imaging in combination with mass spectrometry imaging (MSI). Using this strategy, we were able to delineate the chemical traits, peptides and lipids, associated with plaque polymorphism in genetic AD mouse models (4).

Group members

Moreover, we integrated these hyperspectral chemical imaging tools to identify chemical factors underlying Aβ plaque polymorphisms in postmortem human brain tissue. The rationale is that Aβ deposits with diffuse morphology occur e.g. also in individuals without dementia (cognitively unaffected, amyloid positive CU-AP), while plaques observed in AD show both cored and diffuse morphologies, which suggests that formation of mature, cored plaques is critically associated with developing AD. It is therefore of particular interest of our research to characterize the chemical phenotype (peptide truncation, associated lipids) of different plaque phenotypes in CU-AP in AD and to further elucidate how these plaque characteristics correlate with spread of AD pathology and cognitive decline. Using our chemical imaging tools, we identified the distinct Aβ species associated with amyloid polymorphism in brain tissue from individuals with sporadic AD (s-AD) and CU-AP (5). We found that maturation of diffuse into cored plaques correlated with increased Aβ1-40 deposition, where Aβ1-40 was found to aggregate at the core structure of mature plaques, whereas Aβ1-42 localizes to diffuse amyloid aggregates. Moreover, we observed that diffuse plaques have increased pyroglutamated Aβx-42 levels in s-AD but not CU-AP, suggesting an AD pathology–related, hydrophobic functionalization of diffuse plaques facilitating Aβ1-40 deposition. These results suggest that diffuse deposits are immature precursors of cored plaques and that pyroglutamation of N-terminal Aβx-42, and Aβ1-40 deposition, are potentially critical events in priming and maturation of pathogenic Aβ from diffuse into cored plaques. These processes could underlie development of neurotoxic plaque pathology in AD and could hence provide a mechanistic target for potential intervention. Most recently we used this approach combining MALDI MSI and LCO to map chemical signatures of heterogenous amyloid pathology across the AD continuum. We developed a deep learning model based on the hyperspectral (MSI+LCO) data to identify plaque subtypes across different patients and forms of AD. Specifically this allowed to characterize distinct senile plaque morphotypes known as coarse gran plaques that show significantly different Aβ signatures with prominent Aβx-40 deposition, more close to vascular plaques (CAA) (7,8).

The multimodal imaging experiments developed by our group allow to characterize chemical and structural features of AD pathology beyond what is discernible using established techniques commonly used in pathology and biomedical research. However, amyloidogenic protein aggregation and deposition, have to be considered as a highly dynamic process. This requires experimental setups that allow to monitor these processes as a function of time as the fibrillization dynamics of Aβ are of integral relevance in AD pathogenesis. The hypothesis is that diffuse plaques represent a premature state of senile plaques and are promoted to dense core plaques by Aβ truncations with a panel of physically associated lipids. To address this issue, my group is currently working on expanding imaging mass spectrometry towards stable isotope labelling to measure protein aggregation kinetics (iSILK), which we use to quantify amyloid peptide aggregation dynamics in genetic mouse models of AD. We have recently completed and published a first iSILK study where we follow plaque formation in APP KI mice. The study received appraisal in the AD research community.

These iSILK experiments allowed for the first time to visualize aggregation dynamics of different Aβ peptides within single plaques and across different brain regions in evolving plaque pathology from early deposition to later plaque growth. Specifically, we have demonstrated, using 6-week-old APPNL-G-F mice, that the method of feeding the stable isotopes works and leads to detectable levels of label within the plaques for meaningful analysis. To establish the early events of Aβ aggregation and heterogenous plaque formation, we performed a series of elaborate, complementary PULSE/CHASE setups. We found that Ab pathology in APPNL-G-F mice precipitates in the cortex by forming small dense-core deposits (5mm in size) consisting of Ab1-42. The results show that plaques in APPNL-G-F mice form via early deposition of Aβ1-42 into compact core which is followed by plaque growth by homogenous deposition throughout the plaque. Later events in early plaque pathology involve deposition in the hippocampus, and secretion and deposition of Ab1-38 (9).

Most recently we expanded our research towards using iSILK MS imaging to guide spatial transcriptomics and proteomics.  Here, we established a GeoMx platform in our lab and used this approach to see how plaque maturation in ageing models of amyloid pathology (APP NLF/NLF) affects cellular gene expression in proximal and distal cells. Interestingly, in 18mo mice iSILK and correlative spatial whole transcriptome profiling revealed that synaptic genes are downregulated in older plaques than in younger. In detail, synaptic gene signatures correlated negatively with plaque age. This is interesting as amyloid has long been suspected to affect synaptic genes and proteins though these processes are convoluted in whole tissue transcriptomics. Moreover, we observed a initial pos. correlation of microglial genes and MG activation at early precipitating pathology (10mo), while at older age (18mo) plaque maturation correlated with astrocytic activation related gene signatures (D, Wood et al 2025).

• 1, Michno W, Kaya I, Nyström S, Guerard L, Nilsson KPR, Hammarström P, Blennow K, Zetterberg H, Hanrieder J.*“Multimodal Chemical Imaging of Amyloid Plaque Polymorphism Reveals Aβ Aggregation Dependent Anionic Lipid Accumulations and Metabolism” 2018 Anal Chem. 90(13):8130-8138. PMID: 29856605
• 2, Dreos A., Ge J., Najera F., Ergette Tebikachew B., Perez-Inestrosa E., Zetterberg H., Blennow, K., Moth-Poulsen, K., Hanrieder J.* ” Investigating New Applications of a Photoswitchable Fluorescent Norbornadiene as a Multifunctional Probe for Delineation of Amyloid Plaque Polymorphism” 2023 ACS Sensors 8(4):1500-1509 PMID: 36946692
• 3, Ge J., Koutarapu S., Jha D., Dulewicz M., Zetterberg H., Blennow K., Hanrieder J.* ”Tetramodal Chemical Imaging Delineates the Lipid-Amyloid Peptide Interplay at Single Plaques in Transgenic Alzheimer’s Disease Models” 2023 Anal. Chem. 95(10):4692-4702 PMID: 36856542
• 4, Wehrli P., Michno W, Guerard L, Fernandes-Rodriguez J, Zetterberg H, Bergh A, Blennow K, Hanrieder J.*“Spatial Chemometrics and Comprehensive Chemical Imaging based Molecular Histopathology Delineates Anatomical Heterogeneity at Single Pixel Resolution” 2023 J Amer Chem Soc Au 3(3):762-774
• 5, Michno W, Nyström S, Lashley T., Wehrli P., Brinkmalm G., Kaya I, Brinet, D., Guerard L, Syvänen S., Sehlin D., Nilsson KPR, Hammarström P, Blennow K, Zetterberg H, Hanrieder J.* “Pyroglutamation of Aβx-42 followed by Aβ1-40 deposition underlie priming and maturation of diffuse into cored plaque morphotypes in progressing Alzheimer’s disease pathology” 2019 J Biol Chem 294(17):6719-6732. PMC6497931
• 6, Pagnon de la Vega M., Giedraitis V., Michno W. Kilander L, Guener G, Zielinski M, Brundin RM, Danfors T, Söderberg L, Alafuzoff I, Nilsson LNG, Erlandsson A, Willbold D, Schröder GF, Müller SA, Hanrieder J,  Lichtenthaler SF, Lannfelt L, Sehlin D and Ingelsson M. “The Uppsala APP mutation causes early onset Alzheimer’s  by altering APP processing and increasing amyloid-β fibril formation” Science Transl Med 2021 13(606):eabc6184. PMID:34380771
• 7, Michno W., Kotarapu S., Ge J., Tommey C., Jha, D. Stringer K., Minta K., Zetterberg H., Blennow, K., Ryan N., Lashley T., Hanrieder J.* “Chemical traits of vascular amyloid pathology in rare familial dementias” 2022 J Neurochem. 163(3):233-246 (Cover)
• 8, Kouterapu, Ge J., Dulewicz M, Szadziewska A., Zetterberg H., Blennow, K., Ryan N., Lashley T., Schöll M., Savas JN, Hanrieder J.* “Chemical signatures delineate heterogeneous amyloid plaque populations across the Alzheimer’s disease spectrum” 2025 Nature Communications 16(1):3889
• 9, Michno, W., Stringer, K. S., Enzlein, T., Passarelli, M. K., Escrig S., Blennow, K., Zetterberg, H., Meibom, A., Hopf, C., Edwards, F. A., Hanrieder, J.* “Following spatial Aβ plaque aggregation dynamics in evolving Alzheimer’s pathology by imaging stable isotope labelling kinetics (iSILK)” Science Advances 2021 7(25):eabg4855. PMC8208724
• 10, Wood J, Wong E, Joghee R, Balbaa A, Vitanova KS, Vanshoiack A, Phelan S-LJ, Launchbury F, Desai S, Tripathi T, Hanrieder J, Cummings DM, Hardy J, Edwards FA “Upregulation of Trem2 expression occurs exclusively on microglial contact with plaques.” Cell Reports 2022 41(8):111686
• 11, Wood J, Dulewicz M, Ge J., Szadziewska A., Desai S, Kouterapu S.,  Blennow K, Zetterberg H, Cummings DM, Savas JN, Edwards FA, Hanrieder J*, “Deciphering Plaque Age Through Metabolic Labelling: Insights into Structural maturation, Gene Expression, and Toxicity” 2025 Nature Communications 16(1):8170