reactomeThe #ReactomeResearchSpotlight
for January is a paper by Tindle et al. that identified two Crohn’s disease (CD) molecular subtypes - immune-deficient infectious CD and stress and senescence-induced fibrostenotic CD - through multi-omics and functional analyses of patient-derived organoids.
Time for #ReactomeResearchSpotlight! Bracha et al. use #Reactome expression analysis to confirm that they successfully delivered multiple large therapeutic proteins across the blood-brain barrier into target neurons in mice using engineered Toxoplasma gondii secretion systems.
See full article here: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11306108/
See our website for more exemplary research done using Reactome!
https://reactome.org/content/reactome-research-spotlight
Contact us with your amazing work to be considered for next month's spotlight!
Engineering Toxoplasma gondii secretion systems for intracellular delivery of multiple large therapeutic proteins to neurons
Delivering macromolecules across biological barriers such as the blood–brain barrier limits their application in vivo. Previous work has demonstrated that Toxoplasma gondii, a parasite that naturally travels from the human gut to the central nervous ...
Have you seen our latest #ReactomeResearchSpotlight? This month's focused on the recent work by
Chen et al.
https://reactome.org/content/reactome-research-spotlight
Chen et al used data simulated based on Reactome pathways to validate their Functional Representation of Gene Signatures (FRoGS) algorithm, a deep learning-based approach that was designed to improve the accuracy of drug target predictions by addressing limitations of gene identity-based pathway analysis.
Read more about this and other #ReactomeResearchSpotlight
Tell us about how you use
@reactome
and #OpenData in your work!
Have you seen our #ReactomeResearchSpotlight? “Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation"
Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation – A meta-analysis - Reactome Pathway Database
Reactome is pathway database which provides intuitive bioinformatics tools for the visualisation, interpretation and analysis of pathway knowledge.
Read more about this and other #ReactomeResearchSpotlight ➡️ https://tinyurl.com/RRSAll
Have you seen our new #ReactomeResearchSpotlight for October?
This month, we are thrilled to highlight a study by Miller et al (2023) that used @reactome to perform an epigenome-wide association study. ➡️ https://tinyurl.com/RRS1023 #Epigenomics #Diabetes #CardiovascularDisease
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This month, we are thrilled to highlight a study by Miller et al (2023) that used @reactome to perform an epigenome-wide association study. ➡️ https://tinyurl.com/RRS1023 #Epigenomics #Diabetes #CardiovascularDisease
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DNA methylation and 28-year cardiovascular disease risk in type 1 diabetes: the Epidemiology of Diabetes Complications (EDC) cohort study - Clinical Epigenetics
Background The potential for DNA methylation (DNAm) as an early marker for cardiovascular disease (CVD) and how such an association might differ by glycemic exposure has not been examined in type 1 diabetes, a population at increased CVD risk. We thus performed a prospective epigenome-wide association study of blood leukocyte DNAm (EPIC array) and time to CVD incidence over 28 years in a childhood-onset (< 17 years) type 1 diabetes cohort, the Pittsburgh Epidemiology of Diabetes Complications (EDC) study (n = 368 with DNA and no CVD at baseline), both overall and separately by glycemic exposure, as measured by HbA1c at baseline (split at the median: < 8.9% and ≥ 8.9%). We also assessed whether DNAm-CVD associations were independent of established cardiometabolic risk factors, including body mass index, estimated glucose disposal rate, cholesterol, triglycerides, blood pressure, pulse rate, albumin excretion rate, and estimated glomerular filtration rate. Results CVD (first instance of CVD death, myocardial infarction, coronary revascularization, ischemic ECG, angina, or stroke) developed in 172 participants (46.7%) over 28 years. Overall, in Cox regression models for time to CVD, none of the 683,597 CpGs examined reached significance at a false discovery rate (FDR) ≤ 0.05. In participants with HbA1c < 8.9% (n = 180), again none reached FDR ≤ 0.05, but three were associated at the a priori nominal significance level FDR ≤ 0.10: cg07147033 in MIB2, cg12324048 (intergenic, chromosome 3), and cg15883830 (intergenic, chromosome 1). In participants with HbA1c ≥ 8.9% (n = 188), two CpGs in loci involved in calcium channel activity were significantly associated with CVD (FDR ≤ 0.05): cg21823999 in GPM6A and cg23621817 in CHRNA9; four additional CpGs were nominally associated (FDR ≤ 0.10). In participants with HbA1c ≥ 8.9%, DNAm-CVD associations were only modestly attenuated after cardiometabolic risk factor adjustment, while attenuation was greater in those with HbA1c < 8.9%. No pathways were enriched in those with HbA1c < 8.9%, while pathways for calcium channel activity and integral component of synaptic membrane were significantly enriched in those with HbA1c ≥ 8.9%. Conclusions These results provide novel evidence that DNAm at loci involved in calcium channel activity and development may contribute to long-term CVD risk beyond known risk factors in type 1 diabetes, particularly in individuals with greater glycemic exposure, warranting further study.