Citations

Antisense oligonucleotides (ASOs) represent a promising therapeutic modality for RNA-based disease mechanisms, but identifying high-efficacy candidates from large sequence spaces remains a major bottleneck in drug development. Here, we present ASOFormer, a novel Transformer-based neural network that predicts the inhibition efficiency of RNase H-mediated ASOs from sequence, predicted secondary structure, and chemical modification features. ASOFormer was trained on a knockdown efficacy dataset spanning over 170,000 ASO-target pairs compiled largely from published patents. Ablation analysis confirmed that the addition of chemical modification features to the primary sequence drove the largest performance gains, with predicted secondary structure providing complementary benefit when combined with modification information. Further analysis highlighted the importance of the wings of gapmer ASOs and other features. As independent validation, ASOFormer was applied to ASOs targeting seven genes that were not in the training dataset gene list. For four out of the seven genes, the ground truth ASO inhibition efficiency was obtained from a public dataset, whereas the others were measured in-house via qPCR. Compared to two published state-of-the-art methods, ASOFormer achieved the best overall accuracy and prioritized the strongest inhibitors. Crucially, only ASOFormer consistently exceeded random expectation for top-candidate recovery across all seven test genes.

Endocrine therapy remains the cornerstone of treatment for estrogen receptor alpha (ERα)-positive breast cancer, yet the relationship between individual genetic background and molecular response to ERα-targeted therapy remains incompletely understood. Using a well-characterized panel of lymphoblastoid cell lines (LCLs), we performed genome-wide pharmacogenomic expression quantitative trait locus (PGx-eQTL) analysis to identify estradiol (E2)- and tamoxifen (TAM)-induced SNP-gene pairs. PGx-eQTL signals were integrated with previously published breast cancer genome-wide association study datasets to examine their association with clinically relevant breast cancer phenotypes. We identified two ER-mediated PGx-eQTL SNP-gene pairs associated with breast cancer prognosis post-treatment with E2 or TAM. Notable loci included E2-regulated MRPL15 and TAM-regulated SYCP3, which have effects in a genotype-dependent manner, with genotype-dependent survival outcomes, from worse to better relapse-free survival. Similar endocrine-therapy effects on patient survival and breast cancer risk were observed in SIK2, post TAM-treatment, and in LSM4 with E2-treatment. Moreover, qRT-PCR validation in an independent LCL panel confirmed the genotype-specificity of these signals. Overall, we identified ER-mediated PGx-eQTL SNP-gene pairs which represent potential pharmacogenomic tools for identifying patients likely to benefit from ERα-targeted endocrine therapy, offering a foundation for more genotype-informed individualized treatment decisions in breast cancer.

Abstract Identification of gene expression changes in post-mortem brain tissue of Alzheimer’s disease donors compared to controls have implicated numerous biological pathways for Alzheimer’s disease pathophysiology. Nonetheless, there is still limited understanding of how gene expression dysregulation underpins specific proteinopathies core to Alzheimer’s disease. Here we investigate brain transcriptomic changes in a well characterized cohort of Alzheimer’s disease donors to identify genes and networks that associate with Alzheimer’s disease endophenotypes including neuropathology measures (Braak stage, Thal phase and cerebral amyloid angiopathy score) and Alzheimer’s disease-related brain protein levels (Apolipoprotein E, Amyloid-β 40, Amyloid-β 42, tau, and phospho-Tau). Bulk transcriptome measures were collected from the temporal cortex tissue of 477 Alzheimer’s disease donors. Following quality control, transcriptome-wide association studies were performed for each endophenotype. We used weighted gene co-expression network analysis to build co-expression networks and integrated transcriptome with epigenetic and genetic data from the same donors. We detected a total of 5,740 Bonferroni significant temporal cortex gene associations with Alzheimer’s disease endophenotypes, most of which were with brain tau levels. We discovered tau-associated co-expression modules enriched in known and novel Alzheimer’s disease pathways. We found that a beneficial (or neutral) brain biochemical state of higher total tau and lower phospho-Tau are associated with increased levels of synaptic, DNA damage/repair, nucleic acid metabolism and myelin processes. In contrast, in a detrimental state of lower total and higher phospho-Tau, there is upregulation of vascular and immune, and downregulation of mitochondrial and myelin pathways. There are brain gene expression perturbations that are associated with Alzheimer’s disease endophenotypes. While some of these associations are common across multiple endophenotypes, many are distinct for different Alzheimer’s disease-related proteins. Based on these findings, we propose a hypothetical model of dynamic brain gene expression changes that track with progressive Alzheimer’s disease proteostasis. These expression changes hold potential to serve as dynamic, precision biomarkers of brain Alzheimer’s disease progression. This study demonstrates the potential of integrative multiomics and deep Alzheimer’s disease endophenotype analyses in well-characterized brain tissues to uncover with precision the complex biology of Alzheimer’s disease.

Abstract Introduction Alzheimer’s disease (AD) is characterized by pathologies including amyloid, tau, neurodegeneration reflected in established blood biomarkers and track with clinical changes. However, the association between peripheral cell-specific signatures and AD-related phenotypes remain poorly characterized. Methods We analyzed bulk blood transcriptome data from the Mayo Clinic Study of Aging (MCSA) and Emory University Vascular study. We used BayesPrism, CIBERSORTx, and an in-house pipeline CNNreg to deconvolute these data and obtain peripheral cell proportions. Cell type specific transcripts were estimated with BayesPrism. We compared cell proportions between cases (AD/MCI) and controls. Association analysis was performed between cell type specific transcripts and AD-related phenotypes including diagnosis and cognition. Meta-analysis of transcripts associations and gene ontology analysis were conducted to assess the enriched pathways for significant genes. Results In MCSA, B and CD4+ T cells proportions are significantly lower while that of myeloid cells higher in cases. The Emory cohort had similar trends. We identified transcripts associated with AD-related phenotypes in CD4+ T and CD8+ T cells. In CD4+ T cells, transcripts downregulated in case are enriched in response to stimulus pathway, whereas those upregulated in negative regulation of immune response. Downregulation of CD4+ T genes enriched in extracellular matrix disassembly and epigenetic regulation and upregulation of those in protein localization associate with better cognition. In CD8+T cells, genes pertinent to vascular development were downregulated while those to metabolic processes were upregulated in cases. Downregulation of CD8+T genes involved in lipid transportation and upregulation of those in mitochondria associate with better cognition. Conclusion We identified peripheral cellular transcriptional changes associated with AD/MCI phenotypes and involved in important biological pathways, revealing potential disease mechanisms in AD. Funding Source RF1 AG051504 Topic Categories Neuroimmunology (NEUR)

Abstract Background African Americans (AA) are twice as likely to develop dementia than non‐Hispanic Whites but remain underrepresented in Alzheimer's Disease (AD) research. Recent studies have identified AA specific risk factors for AD. Therefore, targeted biomarkers and/or therapies may be needed to effectively treat AD in AA. In this study, we aimed to determine if genetic variants that show association with AD‐risk, plasma transcript or protein levels in AA, may serve as accurate and accessible AD biomarkers. Method In 189 clinically diagnosed AA AD cases and 183 AA cognitively unimpaired (CU) controls, we performed targeted DNA sequencing of 10 AD‐associated loci. Genetic variants at these loci were tested for association with corresponding plasma transcripts and total tau protein levels previously measured in this cohort using a custom nanoString panel and Simoa assays, respectively. Utilizing phased haplotypes (SHAPEIT4) from target sequencing, we inferred local ancestry (RFMix v2) using five superpopulations from the 1000 Genomes Project as anchors. Subsequently, we tested the association of each ancestry specific allelic dosages with endophenotypes using Tractor. In receiver operating characteristic (ROC) analyses, the most significant e/pQTLs were added sequentially to a base model that included age and sex to identify e/pQTLs that improved the accuracy to correctly classify AD cases and CU controls. Result Of the 5,112 variants that were tested, 70 were nominally associated with AD‐risk and with plasma transcript or protein levels. Seven of these 70 variants also showed nominally significant associations of AD‐risk and transcript levels with either African or East Asian local ancestry. ROC analysis of age, sex, 33 e/pQTLs in APOE , SORL1 , TLR4 , EPHA1 , ABCA7 , CLU , and CR1 , and plasma levels of APP, ABCA7, AKAP9, CD14, CLU, and APOE ‐ɛ4 dosage achieved 88.2% area under the curve to discriminate AD vs. CU, a 30.4% improvement over the base model that only included age and sex. Conclusion Plasma transcript levels and e/pQTLs are promising diagnostic biomarkers for AD that may improve accessibility and reduce costs for a more accurate diagnosis of AD.

Abstract Background Most existing biomarkers for Alzheimer's disease (AD) inform on core AD pathologies in the central nervous system, namely amyloid, tau and neurodegeneration (ATN). However, molecular disease mechanisms underlying AD are complex and heterogeneous, highlighting the need for cost‐effective blood‐based biomarkers that reflect brain molecular changes in AD beyond ATN. Method Using peripheral blood transcriptome data from the Mayo Clinic Study of Aging(MCSA) and the Alzheimer's Disease Neuroimaging Initiative, we identified genes associated with AD or mild cognitive impairment (MCI) diagnosis, cognitive, and harmonized neuroimaging measures in two cohorts, followed by meta‐analysis. We identified consensus gene co‐expression modules in MCSA and ADNI using WGCNA and assessed the association between module eigengenes and aforementioned measures. Using seven bulk brain RNAseq cohorts, we confirmed the preservation of coexpression modules across blood and brain. Enrichment analyses of Gene Ontology (GO) terms and cell‐types were performed using significant and/or hub genes. The MCSA transcriptome was further deconvoluted to obtain cell‐type proportions and cell‐type specific expression. Result Blood transcriptome modules M5 and M8 are upregulated in AD/MCI and associate with worse cognition, whereas M1, M10, M13, M16, and M21 are downregulated in AD/MCI and associate with better cognition. M17 associates with more microhemorrhages. Cell‐type enrichment analysis revealed that M5 is enriched in basophils, monocytes, and neutrophils; M8 in monocytes and neutrophils; M13 in natural kills cells; M17 in megakaryocytes; M21 in B cells. GO analysis shows broad consistency with the cell‐type enrichment analysis. M1, 5, and 8 are preserved in the brain network modules. From these modules, we prioritized transcripts significantly associated with at least one AD‐related phenotype in both blood and brain. Cell‐type deconvolution analysis shows that prioritized transcripts in M1 associate with better cognition and higher metabolic activity in B cells. Conclusion We identified blood transcripts and modules associated with AD/MCI, cognition, or neuroimaging, with three preserved in brain networks. These three modules represent centrally linked peripheral molecular signatures that can reveal perturbed brain pathways and cell level transcriptional changes in AD/MCI. We aim to further investigate the prioritized transcripts in additional datasets to establish them as potential novel biomarkers and therapeutic targets.

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.

Abstract Background More than 85% of Alzheimer's disease (AD) donor brains exhibit some degree of cerebral amyloid angiopathy (CAA), which is characterized predominantly by Aβ40 deposits in the brain vasculature and can cause blood brain barrier (BBB) leakage. CAA is associated with risk of infarcts, cerebral hemorrhages, and cognitive decline. Brain cell type‐specific mechanisms that influence CAA pathology, as well as related measures such as Aβ40 biochemical measures and tight junction proteins, an indicator of BBB integrity, are still elusive. Method We performed single‐nucleus RNA sequencing (snRNAseq) of temporal cortex tissue from 79 AD donors, with varying levels of CAA co‐pathology. Measurements of soluble, insoluble and membrane‐associated fractions of brain Aβ40 and tight junction protein (claudin‐5, occludin) levels were available for these donors. We correlated these measures with cell proportions. We also conducted differential gene expression and analyses for intercellular communications and regulatory networks. Result We identified 25 clusters and annotated them with major brain cell types. There were 3 oligodendrocyte, 7 excitatory and 7 inhibitory neuronal, 2 microglial, 2 astrocytic, and 1 each for endothelial, pericytic, fibroblast, and oligodendrocyte precursor cell clusters. We found that higher CAA and Aβ40 levels correlate with reduced neuronal and increased microglial, astrocytic and vascular cell proportions. Increased tight junction proteins correlate with increased inhibitory neuronal and reduced microglial, astrocytic and vascular cell proportions. Among all clusters, one microglial, both astrocytic and the pericytic clusters have greater number of genes significantly associated with CAA, Aβ40 and tight junction protein levels. Most significant genes have negative associations with CAA and membrane‐bound Aβ40 and positive with tight junction protein measures. Using these genes as input for intercellular communications analysis, we prioritized ligand‐target interactions from microglia or astrocytes to pericytes. Some of the prioritized targets are transcription factors in pericytes. Using regulon analysis, we identified genes downstream of these transcription factors that are also significantly associated with lower CAA and membrane‐bound Aβ40 and higher tight junction protein levels. Conclusion We revealed glia‐to‐pericytes intercellular interactions and pericytic gene regulatory networks that are potentially perturbed by CAA and BBB breakdown. Future directions include analyzing external snRNAseq datasets and performing functional validations.

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.