Learning good therapeutic targets in ALS, neurodegeneration, using observational studies DOI Creative Commons
Mohammadali Alidoost, Jeremy Huang,

Georgia Dermentzaki

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 13, 2024

Abstract Analysis of real-world data (RWD) is attractive for its applicability to scenarios but RWD typically used drug repurposing and not therapeutic target discovery. Repurposing studies have identified few effective options in neuroinflammatory diseases with relatively patients such as amyotrophic lateral sclerosis (ALS), which characterized by progressive muscle weakness death no disease-modifying treatments available. We previously reclassified drugs their simulated effects on proteins downstream targets observed class-level the EHR, implicating protein source effect. Here, we developed a novel ALS-focused pathways model using from patient samples, public domain, consortia. With this model, ALS measured class overall survival retrospective EHR studies. an increased non-significant risk taking associated complement system experimentally validated activation. repeated six classes, three which, including multiple chemokine receptors, were significant death, suggesting that targeting receptors could be advantageous these patients. recovered activation Parkinson’s Myasthenia Gravis demonstrated utility network medicine testing believe approach may accelerate discovery diseases, addressing critical need new options.

Language: Английский

Recent advances in Alzheimer’s disease: Mechanisms, clinical trials and new drug development strategies DOI Creative Commons
Jifa Zhang, Yinglu Zhang, Jiaxing Wang

et al.

Signal Transduction and Targeted Therapy, Journal Year: 2024, Volume and Issue: 9(1)

Published: Aug. 23, 2024

Abstract Alzheimer’s disease (AD) stands as the predominant form of dementia, presenting significant and escalating global challenges. Its etiology is intricate diverse, stemming from a combination factors such aging, genetics, environment. Our current understanding AD pathologies involves various hypotheses, cholinergic, amyloid, tau protein, inflammatory, oxidative stress, metal ion, glutamate excitotoxicity, microbiota-gut-brain axis, abnormal autophagy. Nonetheless, unraveling interplay among these pathological aspects pinpointing primary initiators require further elucidation validation. In past decades, most clinical drugs have been discontinued due to limited effectiveness or adverse effects. Presently, available primarily offer symptomatic relief often accompanied by undesirable side However, recent approvals aducanumab ( 1 ) lecanemab 2 Food Drug Administration (FDA) present potential in disrease-modifying Nevertheless, long-term efficacy safety need Consequently, quest for safer more effective persists formidable pressing task. This review discusses pathogenesis, advances diagnostic biomarkers, latest updates trials, emerging technologies drug development. We highlight progress discovery selective inhibitors, dual-target allosteric modulators, covalent proteolysis-targeting chimeras (PROTACs), protein-protein interaction (PPI) modulators. goal provide insights into prospective development application novel drugs.

Language: Английский

Citations

135
DeepDrug as an expert guided and AI driven drug repurposing methodology for selecting the lead combination of drugs for Alzheimer’s disease DOI Creative Commons
Victor O. K. Li, Yang Han,

Tushar Kaistha

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 15, 2025

Language: Английский

Citations

2
Utilization of precision medicine digital twins for drug discovery in Alzheimer's disease DOI Creative Commons
Yunxiao Ren, Andrew A. Pieper,

Feixiong Cheng

et al.

Neurotherapeutics, Journal Year: 2025, Volume and Issue: unknown, P. e00553 - e00553

Published: Feb. 1, 2025

Alzheimer's disease (AD) presents significant challenges in drug discovery and development due to its complex poorly understood pathology etiology. Digital twins (DTs) are recently developed virtual real-time representations of physical entities that enable rapid assessment the bidirectional interaction between domains. With recent advances artificial intelligence (AI) growing accumulation multi-omics clinical data, application DTs healthcare is gaining traction. twin technology, form multiscale models patients or organ systems, can track health status real time with continuous feedback, thereby driving model updates enhance decision-making. Here, we posit an additional role for discovery, particular utility diseases like AD. In this review, discuss salient AD development, including comorbidities, difficulty early diagnosis, current high failure rate trials. We also review potential applications predicting progression, discovering biomarkers, identifying new targets opportunities repurposing, facilitating trials, advancing precision medicine. Despite hurdles area, such as integration standardization dynamic medical data issues security privacy, represent a promising approach revolutionizing

Language: Английский

Citations

1
Artificial Intelligence for Drug Discovery: An Update and Future Prospects DOI
Harrison Howell, Jeremy McGale,

Aurélie Choucair

et al.

Seminars in Nuclear Medicine, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

Citations

1
Systematic characterization of multi-omics landscape between gut microbial metabolites and GPCRome in Alzheimer’s disease DOI Creative Commons
Yunguang Qiu, Yuan Hou, Dhruv Gohel

et al.

Cell Reports, Journal Year: 2024, Volume and Issue: 43(5), P. 114128 - 114128

Published: April 21, 2024

Shifts in the magnitude and nature of gut microbial metabolites have been implicated Alzheimer's disease (AD), but host receptors that sense respond to these are largely unknown. Here, we develop a systems biology framework integrates machine learning multi-omics identify molecular relationships with non-olfactory G-protein-coupled (termed "GPCRome"). We evaluate 1.09 million metabolite-protein pairs connecting 408 human GPCRs 335 metabolites. Using genetics-derived Mendelian randomization integrative analyses brain transcriptomic proteomic profiles, orphan (i.e., GPR84) as potential drug targets AD triacanthine experimentally activates GPR84. demonstrate phenethylamine agmatine significantly reduce tau hyperphosphorylation (p-tau181 p-tau205) patient induced pluripotent stem cell-derived neurons. This study demonstrates uncover GPCR microbiota other complex diseases if broadly applied.

Language: Английский

Citations

7
Glutamate: Molecular Mechanisms and Signaling Pathway in Alzheimer’s Disease, a Potential Therapeutic Target DOI Creative Commons
Nidhi Puranik, Minseok Song

Molecules, Journal Year: 2024, Volume and Issue: 29(23), P. 5744 - 5744

Published: Dec. 5, 2024

Gamma-glutamate is an important excitatory neurotransmitter in the central nervous system (CNS), which plays role transmitting synapses, plasticity, and other brain activities. Nevertheless, alterations glutamatergic signaling pathway are now accepted as a element Alzheimer's disease (AD) pathophysiology. One of most prevalent types dementia older adults AD, progressive neurodegenerative illness brought on by persistent decline cognitive function. Since AD has been shown to be multifactorial, variety pharmaceutical targets may used treat condition. N-methyl-D-aspartic acid receptor (NMDAR) antagonists acetylcholinesterase inhibitors (AChEIs) two drug classes that Food Drug Administration authorized for treatment AD. The AChEIs approved galantamine, donepezil, rivastigmine. However, memantine only non-competitive NMDAR antagonist This review aims outline involvement glutamate (GLU) at molecular level pathways associated with demonstrate target therapeutic potential its receptor. We will also consider opinion leading authorities working this area, drawback existing strategies, direction further investigation.

Language: Английский

Citations

5
A Deep Subgrouping Framework for Precision Drug Repurposing via Emulating Clinical Trials on Real-world Patient Data DOI
Seungyeon Lee, Ruoqi Liu, Feixiong Cheng

et al.

Published: April 4, 2025

Drug repurposing identifies new therapeutic uses for existing drugs, reducing the time and costs compared to traditional de novo drug discovery. Most studies using real-world patient data often treat entire population as homogeneous, ignoring heterogeneity of treatment responses across subgroups. This approach may overlook promising drugs that benefit specific subgroups but lack notable effects population, potentially limiting number repurposable candidates identified. To address this, we introduce STEDR, a novel framework integrates subgroup analysis with effect estimation. Our first by emulating multiple clinical trials on then characterizes learning subgroup-specific effects. We deploy \model Alzheimer's Disease (AD), condition few approved known in responses. emulate over one thousand medications large-scale database covering 8 million patients, identifying 14 beneficial AD characterized Experiments demonstrate STEDR's superior capability approaches. Additionally, our method can characterize clinically relevant associated important AD-related risk factors, paving way precision repurposing.

Language: Английский

Citations

0
A network-based systems genetics framework identifies pathobiology and drug repurposing in Parkinson’s disease DOI Creative Commons

Lijun Dou,

Zhenxing Xu,

Jielin Xu

et al.

npj Parkinson s Disease, Journal Year: 2025, Volume and Issue: 11(1)

Published: Jan. 22, 2025

Parkinson's disease (PD) is the second most prevalent neurodegenerative disorder. However, current treatments only manage symptoms and lack ability to slow or prevent progression. We utilized a systems genetics approach identify potential risk genes repurposable drugs for PD. First, we leveraged non-coding genome-wide association studies (GWAS) loci effects on five types of brain-specific quantitative trait (xQTLs, including expression, protein, splicing, methylation histone acetylation) under protein–protein interactome (PPI) network. then prioritized 175 PD likely (pdRGs), such as SNCA, CTSB, LRRK2, DGKQ, CD44, which are enriched in druggable targets differentially expressed across multiple human cell types. Integrating network proximity-based drug repurposing patient electronic health record (EHR) data observations, identified Simvastatin being significantly associated with reduced incidence (hazard ratio (HR) = 0.91 fall outcome, 95% confidence interval (CI): 0.87–0.94; HR 0.88 dementia CI: 0.86–0.89) after adjusting 267 covariates. In summary, our network-based framework identifies other diseases if broadly applied.

Language: Английский

Citations

0
How to advance the pharmacological management of cognitive impairment in Parkinson's disease DOI Creative Commons
Carla Abdelnour, Lucy L. Gibson, Lucia Batzu

et al.

Journal of Parkinson s Disease, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 2, 2025

Cognitive impairment is a common non-motor symptom in people with Parkinson's disease (PD) and associated to poor clinical outcomes. Currently, rivastigmine the only approved medication for PD dementia, there are no treatments available mild cognitive impairment. To advance pharmacological management of PD, it essential optimize trial design. This includes refining outcome measures, ensuring longer study durations, incorporating PD-specific assessments. Biomarkers offer valuable opportunities screening, stratification, enrichment, monitoring trials, increasing likelihood detecting treatment effects. Additionally, adopting patient-centered approaches that prioritize inclusivity can enhance validity address current lack diversity studies. Digital assessments promising tool improving participation enabling longitudinal monitoring, especially underrepresented mobility-challenged populations. By tackling these challenges, this review outlines strategies advancing PD. It emphasizes need precise, inclusive, biomarker-driven trials accelerate drug development.

Language: Английский

Citations

0
Drug repurposing for Alzheimer’s disease and other neurodegenerative disorders DOI Creative Commons
Jeffrey L. Cummings, Yadi Zhou,

Alexandra Stone

et al.

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: Feb. 19, 2025

Repurposed drugs provide a rich source of potential therapies for Alzheimer's disease (AD) and other neurodegenerative disorders (NDD). have information from non-clinical studies, phase 1 dosing, safety tolerability data collected with the original indication. Computational approaches, "omic" drug databases, electronic medical records help identify candidate therapies. Generic repurposed agents lack intellectual property protection are rarely advanced to late-stage trials AD/NDD. In this review we define repurposing, describe advantages challenges offer strategies overcoming obstacles, key contributions repurposing development ecosystem. review, authors discuss obstacles development.

Language: Английский

Citations

0