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Tan, Jianna

Mayo Clinic

Mayo Clinic in Florida

Citations 3

From novel targets to potential therapies: development of antisense oligonucleotides for progressive supranuclear palsy
Min, Yuhao , Bergman, Jeremiah, Tan, Jianna, Wang, Xue, Sotelo, Katie D., Reddy, Joseph S. , Quicksall, Zachary , Nguyen, Thuy T., Mitchell, Adriana O., Kawatani, Keiji , Selecky, Grace A., Reeves, Cristian A Lasagna, Crary, John F. , Kanekiyo, Takahisa , Allen, Mariet , Ertekin‐Taner, Nilüfer, Wang, Xue, Sotelo, Katie D., Nguyen, Thuy T. , Dickson, Dennis W. , Whitney, Kristen R. , Martínez, Pablo , Ertekin‐Taner, Nilüfer

Alzheimer's & Dementia | December 25, 2025 | Volume: 21 | Issue: S5 | Pages: No page available

10.1002/alz70859_100315 Get It

Abstract Background Progressive supranuclear palsy (PSP) is a devastating neurodegenerative disorder with rapid progression to death. Multiple efforts to develop a disease‐modifying therapy for PSP have yet to succeed. We previously reported the discovery of three potential therapeutic targets for PSP. These three genes, DDR2, KANK2, and STOM, are consistently upregulated in the brains of PSP patients and mouse models of tauopathy. Reducing their expression in a drosophila model significantly rescued the tau‐induced eye degeneration and tau seeding activity. To translate these targets into the clinic, we are developing antisense oligonucleotides (ASO) as potential therapies. Method We screened candidate ASOs in neuroglioma cell line H4. ASO hits were validated for their potency and safety. We also used iPSC‐derived neurons from PSP patients to test the potency and potential toxicity of our ASOs. To investigate target engagement, therapeutic efficacy and preliminary pharmacodynamic properties, we treated iPSC‐derived midbrain organoids with the ASO leads. Lastly, we will assess the off‐target effects of the ASOs by investigating the levels of mRNA transcripts that share similar sequences as our targets using RNAseq. Result Our in vitro screening identified ASO leads that significantly reduce the target gene expressions at mRNA and protein levels in a dose‐dependent manner. The ASO hits also exhibit low cellular toxicity in the H4 cell line. Upon treating iPSC neurons with ASO hits, we were able to validate the dose‐dependent reduction of target mRNAs. Cell viability analysis indicated low toxicity, suggesting that these ASOs are potent and safe. In midbrain organoid model, DDR2‐targeting ASO showed time‐dependent target engagement and were prioritized for further development. Conclusion We developed candidate therapeutics for PSP using ASOs that silence novel therapeutic targets discovered in our systems based cross‐species screening. We showed that our ASOs have low toxicity and confirmed target engagement at both mRNA and protein levels in vitro. The results suggest a favorable preclinical profile of our ASO leads that warrants additional investigations. Importantly, PSP shares congruent pathophysiological changes with other tauopathies, such as Alzheimer’s disease. These common perturbed pathways indicate that our ASOs can be potentially repurposed for multiple neurodegenerative tauopathies.
Microglia‐dependent protective and risk signatures driven by Alzheimer's disease genetic factors
İş, Özkan , Tan, Jianna, Bergman, Jeremiah, Wang, Xue, Tutor‐New, Frederick Q, Min, Yuhao , Quicksall, Zachary , Atik, Merve, Reddy, Joseph S. , Gao, Junli, Tsai, Wei, Sotelo, Katie D., Nguyen, Thuy T. , Kanekiyo, Takahisa , Allen, Mariet , Ertekin‐Taner, Nilüfer, Tutor‐New, Frederick Q, Atık, Merve, Sotelo, Katie D., Dickson, Dennis W. , Ertekin‐Taner, Nilüfer

Alzheimer's & Dementia | December 23, 2025 | Volume: 21 | Issue: S1 | Pages: No page available

10.1002/alz70855_098044 Get It

Abstract Background Alzheimer's disease (AD) affects all brain cells and has complex genomic and immunological alterations. Previous research discovered missense AD risk or protective variants in microglial genes ABI3 and PLCG2, respectively. Expression levels of these genes are altered in AD and can influence microglial function. This study aims to uncover protective, and risk microglial molecular signatures associated with these variants to determine their role in microglial subtypes and states in AD by single cell expression and functional studies. Method We generated microglia‐enriched snRNAseq data from donors harboring either AD protective PLCG2 or AD risk ABI3 missense mutations, or neither mutation. After standard snRNAseq QC, we performed differential expressed gene (DEG) analysis of all microglial cells between variant carriers and non‐carriers using MAST. We defined protective signature as genes that are both down in ABI3 and up in PLCG2 mutation‐carriers. In contrast, risk signature genes are up in ABI3 and down in PLCG2 mutation‐carriers. We investigated the conservation of protective and risk signatures across multiple datasets, including scRNAseq data from iPSC‐derived microglia cells carrying PLCG2 protective variant, snRNAseq data from AD‐resilient donors, and data from AD and other diagnostic groups across multiple brain regions sourced from external datasets. Result We obtained snRNAseq profiles of 35,000 microglia from AD variant carriers. Our DEG analysis among all microglia cells provided 227 microglial protective and 293 risk signature genes defined by these variants. Using integrated analysis of multiple internal and external datasets, we further narrowed down these signatures. We determined that these high‐confidence protective signature genes are downregulated in early AD, upregulated in late AD brains and positively‐correlated with protective variant load in in vitro models. In contrast, risk signature genes are upregulated in early AD, downregulated in late AD and resilient donors. Risk signature expression is decreased with protective PLCG2 variant load, and altered with Aβ treatment in in vitro models. Conclusion Our study uncovers microglia specific protective and risk signatures associated with AD using sn/scRNAseq datasets from multiple sources and models. These findings nominate novel immune targets and pathways with implications for microglial function in health and disease, and ultimately therapeutic potential.
Microglia‐dependent protective and risk signatures driven by Alzheimer's disease genetic factors
İş, Özkan , Tan, Jianna, Bergman, Jeremiah, Wang, Xue, Tutor‐New, Frederick Q, Min, Yuhao , Quicksall, Zachary , Atik, Merve, Reddy, Joseph S. , Gao, Junli, Tsai, Wei, Sotelo, Katie D., Nguyen, Thuy T. , Kanekiyo, Takahisa , Allen, Mariet , Ertekin‐Taner, Nilüfer, Tutor‐New, Frederick Q, Atık, Merve, Sotelo, Katie D., Dickson, Dennis W. , Ertekin‐Taner, Nilüfer

Alzheimer's & Dementia | December 23, 2025 | Volume: 21 | Issue: S8 | Pages: No page available

10.1002/alz70862_110127 Get It

Abstract Background Alzheimer's disease (AD) affects all brain cells and has complex genomic and immunological alterations. Previous research discovered missense AD risk or protective variants in microglial genes ABI3 and PLCG2 , respectively. Expression levels of these genes are altered in AD and can influence microglial function. This study aims to uncover protective, and risk microglial molecular signatures associated with these variants to determine their role in microglial subtypes and states in AD by single cell expression and functional studies. Method We generated microglia‐enriched snRNAseq data from donors harboring either AD protective PLCG2 or AD risk ABI3 missense mutations, or neither mutation. After standard snRNAseq QC, we performed differential expressed gene (DEG) analysis of all microglial cells between variant carriers and non‐carriers using MAST. We defined protective signature as genes that are both down in ABI3 and up in PLCG2 mutation‐carriers. In contrast, risk signature genes are up in ABI3 and down in PLCG2 mutation‐carriers. We investigated the conservation of protective and risk signatures across multiple datasets, including scRNAseq data from iPSC‐derived microglia cells carrying PLCG2 protective variant, snRNAseq data from AD‐resilient donors, and data from AD and other diagnostic groups across multiple brain regions sourced from external datasets. Result We obtained snRNAseq profiles of 35,000 microglia from AD variant carriers. Our DEG analysis among all microglia cells provided 227 microglial protective and 293 risk signature genes defined by these variants. Using integrated analysis of multiple internal and external datasets, we further narrowed down these signatures. We determined that these high‐confidence protective signature genes are downregulated in early AD, upregulated in late AD brains and positively‐correlated with protective variant load in in vitro models. In contrast, risk signature genes are upregulated in early AD, downregulated in late AD and resilient donors. Risk signature expression is decreased with protective PLCG2 variant load, and altered with Aβ treatment in in vitro models. Conclusion Our study uncovers microglia specific protective and risk signatures associated with AD using sn/scRNAseq datasets from multiple sources and models. These findings nominate novel immune targets and pathways with implications for microglial function in health and disease, and ultimately therapeutic potential.