RNA-based therapeutics hold great promise for treating diseases and lipid nanoparticles (LNPs) represent the most advanced platform for RNA delivery. However, the fate of the LNP-mRNA after endosome-engulfing and escape from the autophagy-lysosomal pathway remains unclear. To investigate this, mRNA (encoding human erythropoietin) was delivered to cells using LNPs, which shows, for the first time, a link between LNP-mRNA endocytosis and its packaging into extracellular vesicles (endo-EVs: secreted after the endocytosis of LNP-mRNA). Endosomal escape of LNP-mRNA is dependent on the molar ratio between ionizable lipids and mRNA nucleotides. Our results show that fractions of ionizable lipids and mRNA (1:1 molar ratio of hEPO mRNA nucleotides:ionizable lipids) of endocytosed LNPs were detected in endo-EVs. Importantly, these EVs can protect the exogenous mRNA during in vivo delivery to produce human protein in mice, detected in plasma and organs. Compared to LNPs, endo-EVs cause lower expression of inflammatory cytokines.

Background: Inflammation contributes both to the pathogenesis of stroke and the response to brain injury. We aimed to identify proteins reflecting the acute-phase response and proteins more likely to reflect proinflammatory processes present before stroke by broadly profiling inflammation-related plasma proteins in a longitudinal ischemic stroke study. Methods: Participants were from a Swedish ischemic stroke cohort (SAHLSIS [Sahlgrenska Academy Study on Ischemic Stroke], n=600 cases and n=600 controls). Plasma levels of 65 proteins including chemokines, interleukins, surface molecules, and immune receptors were measured once in controls and at 3× in cases: during the acute phase, after 3 months, and for a subgroup (n=223) at 7-year follow-up. Associations between proteins and ischemic stroke or subtype were investigated in multivariable binary regression models corrected for age, sex, vascular risk factors, and multiple testing. Results: In the acute phase, 48 proteins were significantly and independently associated with ischemic stroke (false discovery rate adjusted P <0.05). At 3-month follow-up, 51 proteins and at 7-year follow-up 50 proteins were associated with ischemic stroke. The majority of proteins were upregulated in cases compared with controls (n=34 at all time points) and the most upregulated were CXCL5 (CXC chemokine ligand 5) and OSM (oncostatin M). Generally, large artery and cardioembolic stroke had the highest protein levels. However, several interesting subtype-specific differences were also detected at each time point. Conclusions: We found inflammation-related proteins that were differentially regulated in ischemic stroke cases compared with controls only in the acute phase and others that remained elevated also at later time points. This latter group of proteins could reflect underlying pathophysiological processes of relevance. Future studies both in terms of disease risk and prognostication are warranted.

DNA methylation has become increasingly recognized in the etiology of complex diseases, including thrombotic disorders. Blood is often collected in epidemiological studies for genotyping and has recently also been used to examine DNA methylation in epigenome-wide association studies. DNA methylation patterns are often tissue-specific, thus, peripheral blood may not accurately reflect the methylation pattern in the tissue of relevance. Here, we collected paired liver and blood samples concurrently from 27 individuals undergoing liver surgery. We performed targeted bisulfite sequencing for a set of 35 hemostatic genes primarily expressed in liver to analyze DNA methylation levels of >10,000 cytosine-phosphate-guanine (CpG) dinucleotides. We evaluated whether DNA methylation in blood could serve as a proxy for DNA methylation in liver at individual CpGs. Approximately 30% of CpGs were nonvariable and were predominantly hypo- (<25%) or hypermethylated (>70%) in both tissues. While blood can serve as a proxy for liver at these CpGs, the low variability renders these unlikely to explain phenotypic differences. We therefore focused on CpG sites with variable methylation levels in liver. The level of blood–liver tissue correlation varied widely across these variable CpGs; moderate correlations (0.5 ≤ r < 0.75) were detected for 6% and strong correlations (r ≥ 0.75) for a further 4%. Our findings indicate that it is essential to study the concordance of DNA methylation between blood and liver at individual CpGs. This paired blood–liver dataset is intended as a resource to aid interpretation of blood-based DNA methylation results.