Exploring Biomarkers Related to Autophagy in Alzheimer's Disease Based on Pathway Crosstalk Analysis

The pathological mechanism of Alzheimer's disease (AD) involves multiple pathways, and the crosstalk between autophagy and other pathways plays an increasingly prominent role in AD. However, current methods are primarily based on single-gene analysis or a single signal pathway to find therapeutic targets for AD, which are somewhat limited. The aim of our study is to identify autophagy-related biomarkers in AD based on the crosstalk between autophagy and other pathways. The pathway analysis method (PAGI) was applied to find the feature mRNAs involved in the crosstalk between autophagy and many other AD-related pathways. Then, the weighted gene co-expression network analysis (WGCNA) was used to construct a co-expression module of feature mRNAs and differential lncRNAs. Finally, clinical information was used to screen the biomarkers related to the prognosis of AD in the co-expressed gene modules. The experiment finally identified 8 mRNAs and 2 lncRNAs (TLN1, ARRB1, FZD4, AKT1, JMJD7-PLA2G4B, STAT5A, SMAD7, ZNF274; AC113349.1, AC015878.2) as biomarkers of AD, and they all interact directly or indirectly with autophagy. In summary, we provide an effective method for extracting autophagy-related biomarkers based on pathway crosstalk in AD. This method enriches the therapeutic targets of AD and provides new insights into the molecular mechanism of autophagy in AD.

Fatty Acids Metabolism: The Bridge Between Ferroptosis and Ionizing Radiation

Exposure of tumor cells to ionizing radiation (IR) alters the microenvironment, particularly the fatty acid (FA) profile and activity. Moreover, abnormal FA metabolism, either catabolism or anabolism, is essential for synthesizing biological membranes and delivering molecular signals to induce ferroptotic cell death. The current review focuses on the bistable regulation characteristics of FA metabolism and explains how FA catabolism and anabolism pathway crosstalk harmonize different ionizing radiation-regulated ferroptosis responses, resulting in pivotal cell fate decisions. In summary, targeting key molecules involved in lipid metabolism and ferroptosis may amplify the tumor response to IR.

Identifying Novel Psoriatic Disease Drug Targets Using a Genetics-Based Priority Index Pipeline

Background: Despite numerous genome-wide association studies conducted in psoriasis and psoriatic arthritis, only a small fraction of the identified genes has been therapeutically targeted. Objective: We sought to identify and analyze potential therapeutic targets for psoriasis and psoriatic arthritis (PsA) using the priority index (Pi), a genetics-dependent drug target prioritization approach. Methods: Significant genetic variants from GWAS for psoriasis, PsA, and combined psoriatic disease were annotated and run through the Pi pipeline. Potential drug targets were identified based on genomic predictors, annotation predictors, pathway enrichment, and pathway crosstalk. Results: Several gene targets were identified for psoriasis and PsA that demonstrated biological associations to their respective diseases. Some are currently being explored as potential therapeutic targets (i.e. ICAM1, NF-kB, REV3 L, ADRA1B for psoriasis; CCL11 for PsA); others have not yet been investigated (i.e. LNPEP, LCE3 for psoriasis; UBLCP1 for PsA). Additionally, many nodal points of potential intervention were identified as promising therapeutic targets. Of these, some are currently being studied such as TYK2 for psoriasis, and others have yet to be explored (i.e. PPP2CA, YAP1, PI3 K, AKT, FOXO1, RELA, CSF2, IFNGR1, IFNGR2 for psoriasis; GNAQ, PLCB1, GNAI2 for PsA). Conclusion: Through Pi, we identified data-driven candidate therapeutic gene targets and pathways for psoriasis and PsA. Given the sparse PsA specific genetic studies and PsA specific drug targets, this analysis could prove to be particularly valuable in the pipeline for novel psoriatic therapies.

MyD88 Is Not Required for Muscle Injury-Induced Endochondral Heterotopic Ossification in a Mouse Model of Fibrodysplasia Ossificans Progressiva

Excess inflammation and canonical BMP receptor (BMPR) signaling are coinciding hallmarks of the early stages of injury-induced endochondral heterotopic ossification (EHO), especially in the rare genetic disease fibrodysplasia ossificans progressiva (FOP). Multiple inflammatory signaling pathways can synergistically enhance BMP-induced Smad1/5/8 activity in multiple cell types, suggesting the importance of pathway crosstalk in EHO and FOP. Toll-like receptors (TLRs) and IL-1 receptors mediate many of the earliest injury-induced inflammatory signals largely via MyD88-dependent pathways. Thus, the hypothesis that MyD88-dependent signaling is required for EHO was tested in vitro and in vivo using global or Pdgfrα-conditional deletion of MyD88 in FOP mice. As expected, IL-1β or LPS synergistically increased Activin A (ActA)-induced phosphorylation of Smad 1/5 in fibroadipoprogenitors (FAPs) expressing Alk2R206H. However, conditional deletion of MyD88 in Pdgfrα-positive cells of FOP mice did not significantly alter the amount of muscle injury-induced EHO. Even more surprisingly, injury-induced EHO was not significantly affected by global deletion of MyD88. These studies demonstrate that MyD88-dependent signaling is dispensable for injury-induced EHO in FOP mice.

Predicting COVID-19—Comorbidity Pathway Crosstalk-Based Targets and Drugs: Towards Personalized COVID-19 Management

It is well established that pre-existing comorbid conditions such as hypertension, diabetes, obesity, cardiovascular diseases (CVDs), chronic kidney diseases (CKDs), cancers, and chronic obstructive pulmonary disease (COPD) are associated with increased severity and fatality of COVID-19. The increased death from COVID-19 is due to the unavailability of a gold standard therapeutic and, more importantly, the lack of understanding of how the comorbid conditions and COVID-19 interact at the molecular level, so that personalized management strategies can be adopted. Here, using multi-omics data sets and bioinformatics strategy, we identified the pathway crosstalk between COVID-19 and diabetes, hypertension, CVDs, CKDs, and cancers. Further, shared pathways and hub gene-based targets for COVID-19 and its associated specific and combination of comorbid conditions are also predicted towards developing personalized management strategies. The approved drugs for most of these identified targets are also provided towards drug repurposing. Literature supports the involvement of our identified shared pathways in pathogenesis of COVID-19 and development of the specific comorbid condition of interest. Similarly, shared pathways- and hub gene-based targets are also found to have potential implementations in managing COVID-19 patients. However, the identified targets and drugs need further careful evaluation for their repurposing towards personalized treatment of COVID-19 cases having pre-existing specific comorbid conditions we have considered in this analysis. The method applied here may also be helpful in identifying common pathway components and targets in other disease-disease interactions too.