bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting gene regulatory networks from multi‐omics to link genetic risk variants and neuroimmunology to Alzheimer’s disease phenotypes
Authors: Khullar Saniya , Wang Daifeng 
Published: December 2022

AbstractBackgroundGenome‐wide association studies have found many genetic risk variants associated with Alzheimer’s disease (AD). However, how these risk variants affect deeper phenotypes such as disease progression and immune response remains elusive. Also, our understanding of cellular and molecular mechanisms from disease SNPs to various phenotypes is still limited. To address these problems, we performed an integrative multi‐omics analysis of genotype, transcriptomics, and epigenomics for revealing gene regulatory mechanisms from disease variants to AD phenotypes.MethodFirst, given population gene expression data of a cohort, we construct and cluster its gene co‐expression network to identify modules for various AD phenotypes. Next, we predict transcription factors (TFs) regulating co‐expressed genes and SNPs interrupting TF binding sites on regulatory elements. Finally, we construct a gene regulatory network (GRN) linking SNPs, interrupted TFs, and regulatory elements to target genes and modules for AD phenotypes. This network provides systematic insights into gene regulatory mechanisms from SNPs to phenotypes. We looked at our GRNs relating to genes from shared AD‐Covid pathways (e.g. NFKB Pathway) and used machine learning to prioritize those genes for predicting Covid‐19 severityResultOur analysis predicted cross‐region‐conserved and region‐specific GRNs in 3 regions Hippocampus, Dorsolateral Prefrontal Cortex (DLPFC), Lateral Temporal Lobe (LTL). For instance, SNPs rs13404184 and rs61068452 disrupt SPI1 binding and regulation of INPP5D in Hippocampus and LTL. While rs4802200 disrupts E2F7 regulation of KCNN4 (belongs to AD LTL module), rs117863556 interrupts REST regulation of GAB2 in DLPFC. Further, we used Covid‐19 as a proxy for immune dysregulation to identify possible regulatory mechanisms for AD neuroimmunology. Decision Curve Analysis suggest our AD‐Covid genes along with linked SNPs (that outperform known genes) can be potential novel biomarkers for neuroimmunology. Finally, our results are open‐source available as a comprehensive AD functional genomic map, providing deeper mechanistic understanding of the interplay among multi‐omics, regions, gene functions, phenotypes.ConclusionOur pipeline predicts how non‐coding risk SNPs may be associated with changes in regulation and subsequent expression of genes associated with different phenotypes and pathways in AD. Moreover, we flagged 51 potential AD‐neuroinflammatory risk genes, which may be early biomarkers as neuroinflammation may begin decades before clinical onset.
Translational potential of JAX humanized APOE mice: Peripheral interferon gamma induces systemic immuno‐metabolic dysfunction
Authors: Van Rossum Hannah , Delatorre Nicole , Mishra Aarti , Bhattrai Avnish , Raikes Adam C. , Rodgers Kathleen E. , Brinton Roberta Diaz 
Published: December 2022

AbstractBackgroundInflammation is a well‐documented feature of Alzheimer’s disease (AD) in human brain. Previous findings from our group demonstrated upregulated immune transcripts in the AD brain as well as sex differences in immune transcript levels during pre‐clinical midlife aging. Using our humanized APOE mouse model, we identified elevated immune transcripts in the female brain including interferon signaling genes, CD3, CD4, and MHCII. We hypothesized that activation via increased interferon gamma (IFN‐γ) during endocrine aging may disrupt the immune‐metabolic balance in the brain and therefore advance changes in grey and white matter. With this study, we test the hypothesis that increased levels of peripheral IFN‐γ induces genotype dependent immuno‐metabolic changes in the JAX humanized APOE (hAPOE) mouse model.MethodTo determine the role of IFN‐γ in female midlife aging and AD risk, pre‐menopausal and peri‐menopausal hAPOE mice were intraperitoneally treated with recombinant IFN‐γ for 9 days. Immunophenotyping using multi‐color flow cytometry was conducted microglial reactivity, phagocytosis, neutral lipid content, oxidative stress, and the presence of lymphocytes were determined. Structural and diffusion weighted analysis using MRI was conducted to evaluate grey and white matter structural integrity in the brain. ELISA assays were conducted to assess the presence of beta amyloid 40 and 42 and levels of pro‐inflammatory cytokines.ResultIFN‐γ treated animals exhibited upregulation of markers that perpetuate neuroinflammation and white matter catabolism including MHCII, CD8, pHrodo, and BODIPY. Peripheral immune effects were genotype dependent while immune signaling in brain largely exhibited treatment‐dependent effects. Fasting blood glucose levels were significantly increased by IFN‐γ consistent with an accelerated aging profile. Diffusion metrics including mean and radial kurtosis in addition to mean, axial, and radial diffusivity were greater in IFN‐treated animals.ConclusionPeripheral increase of interferon gamma signaling during female endocrine aging in hAPOE mice induced 1) dysfunction of metabolic systems and neuroinflammatory response and 2) decreases in white and grey matter microstructural integrity throughout the brain. These outcomes support the investigation of therapeutic strategies targeting interferon signaling pathways at the earliest stages of midlife aging to reduce risk of AD or delay AD onset.
Discovery and Characterization of Intracellularly Stable hnRNPA2B1 Specific Nanobodies for Live‐Cell Imaging and Targeted Protein Degradation
Authors: Pirhanov Azady 
Published: December 2022

AbstractBackgroundHeterogeneous nuclear ribonuclear proteins, hnRNPs, play a variety of roles in regulating transcriptional, and post‐transcriptional gene expression. A core member of the hnRNP family, hnRNPA2/B1 proteins are involved in the formation of membraneless‐organelles such as stress granules (SGs) under certain conditions. Mutations in hnRNPA2/B1 proteins are known to cause multisystem proteinopathy (MSP), a pleiotropic group of inherited disorders that cause neurodegeneration, myopathy, and bone disease. Mutations in hnRNPA2/B1 are also risk factors for the development of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Despite growing evidence implicating hnRNPA2/B1 proteins in a multitude of diseases, our ability to study them in live cells is severely limited due to the lack of intracellularly stable hnRNPA2/B1 specific antibodies. Nanobodies (sdAbs) are antibody fragments derived from heavy‐chain‐only antibodies found in camelids and sharks. Owing to their small size (∼15 kDa) and unique biochemical properties, nanobodies emerged as promising alternatives to conventional‐antibody derived protein fragments. Nanobodies have superior stability that facilitate their intracellular expression. Full length antibodies and bulkier antibody‐derived fragments, such as single chain variable fragments (scFvs), are not amenable to intracellular expression, in part due to the reducing cytoplasmic environment that prevents the formation of disulfide bonds needed for their correct folding.MethodWe have developed a high‐throughput nanobody discovery platform from synthetic yeast surface display libraries by using antigen coated magnetics beads. Furthermore, we have developed generalizable and straightforward cellular assays to characterize nanobody specificity in live cells.ResultUsing above described platforms, we have identified novel hnRNPA2/B1 specific nanobodies and characterized their intracellular stability by expressing them in HEK293 cells. In addition to using nanobodies for studying hnRNPA2/B1 biology in live cells, we have also engineered a panel of modular E3 ubiquitin ligases targeting hnRNPA2/B1 for degradation. ∼30% reduction in hnRNPA2/B1 level was observed when targeted for degradation by using hnRNPA2B1 targeting E3 ubiquitin ligase.ConclusionIn summary, we have optimized factors affecting successful high‐throughput antibody discovery using yeast‐surface display antibody libraries. We also developed generalizable methods to characterize nanobody specificity in live cells. Platforms we have developed will help build tools to study protein aggregation and protein stability in live cells.
Smoking Gun? Effect of smoking history on cognition in AD and MCI
Authors: Crawford‐Holland Lucas M , Rabin Jennifer S. , Fornazzari Luis R , Schweizer Tom A. , Fischer Corinne E. , Munoz David G. , Kumar Sanjeev , Black Sandra E. , Freedman Morris , Borrie Michael , Frank Andrew R , Pasternak Stephen H , Pollock Bruce G. , Rajji Tarek K. , Seitz Dallas , Tang‐Wai David F. , Tartaglia Carmela , Kwan Donna , Tan Brian 
Published: December 2022

AbstractBackgroundMany lifestyle factors have been associated with lower rates of cognitive decline in AD and MCI patients, however the effect of tobacco smoking remains unclear. This study examined how longitudinal cognitive performance in AD and MCI patients varied for those with versus without smoking history.MethodThe study included all 126 patients from the Ontario Neurodegenerative Disease Research Initiative (ONDRI) AD/MCI cohort. The patients were divided into those with a history of cigarette smoking (n = 67) vs without (n = 59), defined as greater than two years of daily smoking. To measure longitudinal cognition, MoCA scores were taken three times with one year elapsing between assessments.ResultLinear mixed effects models were performed, with MoCA score as the dependent variable. Time point, smoking history, sex, education, age, clinical diagnosis (AD vs MCI) and number of languages spoken were fixed effects and subject was a random effect. The presence of smoking history had a significant effect on MoCA score (χ2(1) = 4.5, p = 0.034), improving the average score by 1.37 points ± 0.66 (standard errors). A strong interaction was also found between smoking history and time point (χ2(1) = 8.2, p = 0.0042), as the positive effect of smoking history on MoCA score increased with time. No other significant interactions were found.ConclusionOur findings indicate that smoking history may improve longitudinal cognition in AD and MCI patients. It is unclear whether smoking history is simply a mediating variable for another protective factor, or whether these results arise from cigarette smoking itself affecting some stage of disease progression. Smoking has been consistently associated with a lower risk of developing Parkinson’s disease (PD), however the mechanism for such protection remains unclear. Further research into any association between smoking history and longitudinal cognition in AD and MCI might indicate whether a similar protective association is found in AD and MCI as exists in PD. However, it must be remembered that smoking is associated with many serious diseases, particularly lung cancer, and remains one of the biggest causes of preventable death worldwide.
A Target Enablement Package for the Inhibition of SHIP1 as a Therapeutic Strategy for the Treatment of Alzheimer’s Disease
Authors: Richardson Timothy I , Jesudason Cynthia D , Lobb Karen L , Durst Gregory L , Clayton Brent , Massey Steven M , Beck Daniel E , Zhang Zhong‐Yin , Dong Jiajun , Lin Jianping , Miao Jinmin , Putt Karson S , Mesecar Andrew D , Hamdani Adam K , Lendy Emma K , Souza Sarah , Jacobson Marlene , Salvo Jerry Di , Chu Shaoyou , Mason Emily R , Oblak Adrian L , Soni Disha , Quinney Sara K , Silva Larissa L , Kandasamy Murugesh , Masters Andrea R , Rizzo Stacey J Sukoff , Doolen Suzanne , Huang Kun , Zhang Jie , Lamb Bruce T , Palkowitz Alan D 
Published: December 2022

AbstractBackgroundRecent evidence including GWAS and differential gene expression comparing normal to affected Alzheimer’s brain tissue have identified risk and protective variants in genes such as TREM2, PLCG2 and INPP5D that are essential to microglia function. INPP5D encodes SHIP1, a multi‐domain protein with a phosphatase that converts PI(3,4,5)P3 to PI(3,4)P2, a SH2 domain that interacts with receptor ITAMs and competes with SYK, and a proline rich region that binds many other proteins. SHIP1 therefore limits microglia activation in multiple ways. Inhibition of SHIP1 early in disease would increase microglial protective functions and reduce the rate of disease progression and cognitive decline in Alzheimer’s patients.MethodWe performed a screen of 50K compounds at the SHIP1 phosphatase, analyzed a publicly available fragment‐based screen, and evaluated inhibitors reported in the literature. We utilized the malachite green assay with PtdIns(3,4,5)P3‐diC8 and SHIP1 Ptase‐C2 to measure inhibitory potency. A Cellular Thermal Shift Assay was used to confirm target engagement in cells. A high‐content imaging assay measuring phagocytosis, cell number, and nuclear intensity was implemented using the BV2 and HMC3 cell lines to characterize cellular pharmacology and cytotoxicity. Mouse microglia were assayed to demonstrate similar activity in primary cells. Inhibitors predicted to have drug‐like properties were subjected to assays measuring solubility, cellular permeability, and mouse microsomal stability. A physiological based pharmacokinetic model was compared to measured exposure in vivo for select compounds upon oral administration in mice.ResultSHIP1 inhibitors have been compared head‐to‐head in a set of assays relevant to both enzyme inhibition and microglia activation. Structurally distinct, novel, and selective SHIP1 inhibitors have been discovered. The enzyme mode of action, cellular activity and drug‐like properties were determined. Pharmacokinetic profiles were determined for inhibitors with sufficient cellular potency and drug‐like properties for in vivo studies in mice.ConclusionInhibition of SHIP1 is a novel therapeutic strategy for treatment of Alzheimer’s. We identified structurally distinct molecular scaffolds with varying degrees of enzyme inhibition, cellular activity, and exposure in mice. Recommendations for use of probe molecules in target validation studies and the development of lead‐like molecules for clinical studies will be made.
Single domain antibody‐based non‐invasive in vivo imaging of tau pathology
Authors: Jiang Yixiang , Lin Yan , Krishnaswamy Senthilkumar , Wu Qian , Pan Ruimin , Liu Mengyu , Kuo Min‐Hao , Kong Xiang‐Peng , Congdon Erin E. , Sigurdsson Einar M. 
Published: December 2022

AbstractBackgroundNumerous studies have shown that the extent of pathological tau protein in the brain correlates strongly with the severity of Alzheimer’s dementia at the time of death, and similar association with functional phenotypes have been seen in other tauopathies. In recent years, several dye‐based imaging probes with selectivity for tau aggregates have been developed. However, all are β‐sheet binders with varying affinity for different amyloids, and thereby lack specificity for tau lesions. In contrast, single domain antibodies (sdAbs) are specific for their target and because of their small size have much greater access into the brain than standard whole antibodies.MethodTo examine sdAbs’ suitability as non‐invasive in vivo imaging probes for tauopathies, we immunized a llama with a full‐length recombinant tau protein followed by boosters with human brain‐derived pathological tau proteins. Phage display libraries were generated from its peripheral blood mononuclear cells and screened for binding to tau proteins using various assays, resulting in a prototype sdAb deemed promising for in vivo imaging. Subsequently, this anti‐tau sdAb was labeled with a near‐infrared tag (680 nm), and injected intravenously in tauopathy and control mice, followed by imaging using an In Vivo Imaging System (IVIS). After the imaging, brains were extracted for tissue analysis.ResultIntravenous injection of labeled sdAb resulted in a strong in vivo brain signal detected through the intact head in two different models of transgenic tauopathy mice, but not in wild‐type or transgenic α‐synucleinopathy mice. Importantly, the in vivo brain signal correlated strongly with insoluble (r = 0.9839, p < 0.0001) and soluble (human tau (CP27) and phospho‐tau (PHF1): r = 0.9603 and 0.9459, p < 0.0001) tau protein within the brain. Furthermore, postmortem analysis revealed extensive co‐localization of the sdAb imaging probe with tau aggregates within neurons in the endosomal‐lysosomal system, indicating their interaction in these degradation pathways.ConclusionOverall, this specific sdAb imaging ligand has great potential as an in vivo diagnostic marker for Alzheimer's disease and related tauopathies, and sdAb‐based imaging may be applicable to a variety of protein conformational disorders.
Unsupervised learning on electronic health records to uncover heterogeneity in Alzheimer’s disease and related dementias
Authors: West Matthew , Magdamo Colin G. , Serrano‐Pozo Alberto , Blacker Deborah , Hyman Bradley T. , Das Sudeshna 
Published: December 2022

AbstractBackgroundAlzheimer’s Disease (AD) is a heterogenous disease with distinct etiologies, disease courses, and/or age of onset, which may be associated with different clinical features. Here, we aim to use unsupervised learning techniques on electronic health records (EHRs) from a group of memory clinic patients to characterize heterogeneity in this disease population.MethodWe identify a patient dataset (N = 9,249) within the Mass General Brigham (MGB) system who had at least two encounters at the memory clinic, and were 50 years or older at their last visit. We also define a subset (N = 3,638) of these patients with at least one substantial visit note by an MGB memory specialist. Pre‐trained embeddings for associated ICD codes are used to encode patient EHRs in the first dataset, and transformer‐derived Clinical BERT embeddings of free text are used to encode the patient notes dataset.1,2 For each dataset, we cluster these patient representations using hierarchical clustering and test for enrichment of ICD codes within clusters using chi‐squared tests. Significant codes following Bonferroni correction are retained, and clusters are then characterized based on their most significantly enriched codes.ResultWe identify four clusters within the ICD dataset and three clusters within the patient notes dataset. In the ICD dataset, clusters of patients are identified with increased prevalence of type 2 diabetes and kidney disease (N = 205), chronic pain (N = 669), cardiovascular and other age‐related diseases (N = 2,149), as well as a cluster mostly defined by focal neurological diseases (N = 6,226). In the notes dataset, clusters were identified by enrichment of codes for hydrocephalus and Lewy body disease (N = 1,565), and again with cardiovascular and other age‐related diseases (N = 336), and focal neurological diseases (N = 1,737).ConclusionIn this study, we demonstrate the potential to leverage pre‐trained embeddings from both structured and unstructured data in EHRs to characterize patient heterogeneity in a group of patients with Alzheimer’s Disease and related dementias. In the future, we plan to further characterize these clusters in terms of disease course and underlying mechanism.1. Choi et al., Learning low‐dimensional representations of medical concepts. AMIA Summits. Transl. Sci. Proc. 2016, 41 (2016).2. Alsentzer et al., Publicly available clinical BERT embeddings. arXiv:1904.03323 (2019).
The Carer Assessment of medicaTion management guidanCe for people living with dementia at Hospital discharge (CATCH): Preliminary analysis for a national cross‐sectional survey
Authors: Sawan Mouna J , Jeon Yun‐Hee , Chen Timothy , Gnjidic Danijela 
Published: December 2022

AbstractIntroductionMedication therapy management for people living with dementia is a major contributing factor to adverse events after discharge from hospital. Carers play an important role in overseeing medication management for the person with dementia. We aimed to evaluate medication management guidance provided to carers of people with dementia at hospital discharge.MethodsThis was a cross‐sectional survey disseminated across Australia. Data was captured using the Carer Assessment of medicaTion management guidanCe for people with dementia at Hospital discharge (CATCH) tool. The CATCH tool included 30 items and was developed using a multi‐method approach involving content validation and pretesting with carers of people with dementia. The tool utilized a 5‐point Likert scale, and multiple‐choice responses. We included carers responsible for managing the medications of the person with dementia, and the person with dementia has had at least one discharge from the hospital. Electronic and hardcopy distribution of the survey occurred Australia wide through advertisement. Data collection started on April 24th, 2022, and is currently ongoing. Quantitative data was descriptively analyzed.ResultsTo date, 30 participants completed the survey with a median age 66 (IQR 16.5) and 28 were female. Most participants (n = 21) were provided guidance on the day of discharge by the doctor (n = 12) or nurse (n = 7) in written form. Most (n = 18) found that discharge summary and medication list was easy to understand. The most common medication information provided related to administration instructions (n = 13), medication purpose (n = 11) and possible benefits of medications (n = 8). However, some participants reported that they were not given information about possible side effects (n = 8), medications that might increase confusion (n = 7) and how long the medication should be used for (n = 12). Some (n = 12) reported that they were not asked if the person with dementia had any problems taking their medications.. Most (n = 20) stated that medication management guidance could be improved.ConclusionOur preliminary findings suggest that there are opportunities to improve guidance in medication therapy management provided to carers at discharge. Targets for interventions around comprehensive guidance on all aspects of medication use tailored specifically for the people with dementia are needed.