The lack of physiologically relevant human esophageal cancer models has as a result that many esophageal cancer studies are encountering major bottleneck challenges in achieving breakthrough progress. To address the issue, here we engineered a 3D esophageal tumor tissue model using a biomimetic decellularized esophageal matrix in a customized bioreactor. To obtain a biomimetic esophageal matrix, we developed a detergent-free, rapid decellularization method to decellularize porcine esophagus. We characterized the decellularized esophageal matrix (DEM) and utilized the DEM for the growth of esophageal cancer cell KYSE30 in well plates and the bioreactor. We then analyzed the expression of cancer-related markers of KYSE30 cells and compared them with formalin-fixed, paraffin-embedded (FFPE) esophageal squamous cell carcinoma (ESCC) tissue biospecimens. Our results show that the detergent-free decellularization method preserved the esophageal matrix components and effectively removed cell nucleus. KYSE30 cancer cells proliferated well on and inside the DEM. KYSE30 cells cultured on the DEM in the dynamic bioreactor show different cancer marker expressions than those in the static well plate, and also share some similarities to the FFPE-ESCC biospecimens. These findings built a foundation with potential for further study of esophageal cancer behavior in a biomimetic microenvironment using this new esophageal cancer model. Esophageal cancer is currently the sixth most common cancer worldwide and one of the most lethal , due to Most studies on esophageal cancer phenotype, aggressiveness, metastasis, or drug discovery are commonly performed in two-dimensional (2D) well plates or in xenograft animal models ,5,6. A 2Therefore, there is increasing interest in the development of a 3D in vitro culture model for bridging the research gap between 2D culture and animal xenogeneic models ,14. PresAn appropriate tissue-derived decellularized matrix will offer a close resemblance to tissue matrix in vivo to support the cancer cells to interact in a more native environment. A native tissue-derived decellularized matrix may promote the expression of specific cell phenotypes, which synthetic scaffolds are incapable of reproducing ,22. HoweTherefore, in this study we developed a detergent-free protocol for decellularizing porcine esophageal matrix (DEM). The protocol rapidly removed cells while leaving the majority of matrix components intact in a rapid two-step procedure without any particularly specific equipment and harsh chemicals used. The goal of this study was to investigate whether the decellularized pig esophageal matrix can support the growth of esophageal squamous cell carcinoma (ESCC) under a static well plate culturing condition and a customized dynamic culture bioreactor. We evaluated the degree of biological mimicry of DEM in relation to in vivo tumors by comparing the cancer cell markers expressed on the ESCC cultured on the DEM with those markers expressed by esophageal squamous cell carcinoma tissue in formalin-fixed, paraffin-embedded (FFPE) biospecimens.Hematoxylin  and Eosin , and Masson’s trichrome  were obtained from Fisher Scientific . Primary antibodies: Fibronectin (ab23751), Laminin (ab11575) were obtained from Abcam, and Collagen-I and III (2150–2555) were from Bio-Rad . DAPI , LIVE/DEAD Viability/Cytotoxicity Kit, Quant-iT PicoGreen dsDNA assay kit were obtained from Thermo Fisher Scientific . Vectastain ABC Kit and DAB Peroxidase substrate kit (SK-4100) were from Vectorlabs . Alcian Blue was obtained from MilliporeSigma  (TMS010C). DNase I enzyme was purchased from Thermo Scientific  (EN0521).3·H2O) treatment, the tissue was rinsed briefly, once in distilled water. The rinsed tissue was further incubated at 4 °C for 6–8 h or until complete separation of epithelium from the matrix was achieved. Following ammonium hydroxide treatment, the epithelial cell layer should easily separate from the esophagus lumen as a single component, using mild mechanical assistance if needed. Once the epithelial layer was removed, the esophagus tissue was rinsed with distilled water several times to rinse out remaining base ammonium solution. The tissue was then buffered and incubated at 37 °C with 70 U/mL DNase I enzyme on a rotator platform for up to 48 h to remove remaining cell DNA fragments. Porcine esophagi were freshly obtained from a local slaughterhouse  and immediately soaked and preserved in antimycotic (Amphotericin B)/anti-biotics (Pen/Strep) PBS on ice. The outer longitudinal muscularis externa was removed mechanically to expose esophageal submucosa layers for treatment. Tissue was rinsed with distilled water as needed. Esophagus was then cut into segments of 12–18 mm length. A dilute solution of ammonium hydroxide with concentration of 2 M was added to esophagus tissue for 2–4 h with gentle agitation at 4 °C. After ammonium hydroxide  on a fluorescence spectrophotometer . The amount of dsDNA was calculated by comparing the standard curves of the known dsDNA sample according to the manufacturer’s instructions.To determine whether the porcine cell nuclei were removed, the DEM and native esophagus were stained by DAPI solution (5 µg/mL) to visually confirm the removal of cell nuclei. The stained samples were then examined using a Nikon fluorescent microscope (TE-2000). To further confirm the removal of the cell nucleus, hematoxylin and eosin (H&E) staining was used. DEM and native esophageal tissue were subject to a serial of dehydration in ethanol, and a paraffin embedding process was performed based on our previously established protocol. Paraffin block was mounted on a microtome, and 6 μm slides were cut and mounted onto positively charged microscope glass slides. Slides were subsequently stained by H&E and imaged. 2O2 was added for 10 min before being blocked with 5% bovine serum albumin for at least 1 h at room temperature (RT). After epitope retrieval and blocking, the following primary antibodies were added for incubation at least 1 h at RT: collagen I/III , fibronectin , laminin . Afterwards, secondary anti-biotinylated binding IgG was added onto the samples and incubated at RT for 30 min. After rinsing, the samples were incubated with a working ABC solution (Vector Lab) for 5 min at RT and then with working DAB solution (Vector lab) for a few minutes until the sample stained. The sections were then counterstained with hematoxylin and then preserved by mounting medium (Fisher Scientific) with coverslips. Images were then taken using a Nikon TE-2000 microscope.To examine whether the new decellularization method maintained the matrix components, immunohistochemical (IHC) staining on matrix proteins was performed. Slides were deparaffinized and unmasked at 98–99.8 °C using antigen retrieval buffer  for 20 min. After unmasking, 3% HSlides were deparaffinized and hydrated; then, Masson trichrome staining and Alcian staining were performed according to the manufacturer’s protocols. The stained samples were then imaged by a microscope.2 incubator. When cells were grown to near confluence, they were trypsinized and cell suspensions were seeded on the DEM under two culture conditions: static culture and dynamic culture. For static conditions, DEM was placed in 24-well plate and seeded with 1 × 105 KYSE30 cancer cells, and media was changed every 2 days. For dynamic conditions, a 40 µL cell suspension of around 1 × 105 KYSE30 cells was seeded onto the inner lumen surface of the DEM circumference. After cell seeding, DEM was rested for 2 h to allow time for cells to attach and subsequently mounted to circulation jars where culture medium was continually perfused at 15 µL/minute for the remaining duration of experiment. For the dynamic culture system, typical 1000 µL pipette tips were cut to desired lumen diameter and fit for flow orifice, then perforated using a razor blade to allow cell seeding from the sides into lumen (cut ‘windows’ into the pipette tip for cell seeding and diffusion characteristic), and flow/diffusion of culture media to extraneous feature of flow chamber. Solution passively diffused through the perforations and applied flow rate through orifice condition allows consistent nutrition and waste removal, thus enabling dynamic culture conditions with variable flow rate and as needed diameter setting, which accounted for variability in esophageal matrix.To examine whether the DEM supports cell growth of esophageal cancer cells, an esophageal cancer cell line, KYSE30 from Sigma-Aldrich , was used. KYSE30 was cultured in RPMI 1640 Medium  with antibiotics/mycotic  at 37 °C in a CO® Viability/Cytotoxicity Kit for mammalian cells from Invitrogen was conducted. Cells/DEMs were stained with 6 μM EthD-1 and 2 μM Calcein AM and incubated at room temperature for 40 min in the dark, and then washed and stored in PBS before analysis by microscopy. Red indicates dead cells and green indicates alive cells. To verify the cell viability of KYSE30 cultured on the DEM, after 7 days, a Live/DeadAt the end point of culture, cells/DEM were harvested from the static and dynamic culture system and fixed in paraformaldehyde. The fixed samples experienced graded dehydration and paraffin embedding, and were cut at 6 μm with a microtome into slide sections. The sections were stained by H&E staining and Alcian staining. To investigate how KYSE30 cancer cells expressed cancer cell markers under the two conditions, immunohistochemical staining on the following cancer markers was performed on the sections following the protocol described in To compare the expression of cancer markers on the KYSE30 cultured in the static culture condition and the dynamic culture system, in this study formalin fixed paraffin embedded (FFPE) ESCC tissue blocks were obtained from AMSBIO company  and subjected to the same IHC protocols as above for comparison during the same time. Using a semi-quantitative method that compares the staining intensity to number of visible cells, we evaluated the gross appearance of immunohistochemistry staining on a staining intensity/cell-area basis, where total number of cells which express markers at some average intensity is weighted against cells which do not express any markers (if any are present) over the entire area occupied by all cells. At least eight pictures were taken on several regions of interest (ROI) from multiple samples of each group and manual cell counting was employed as needed for accuracy and validity to compare the stained intensity vs. cell-area for the nine cancer markers. With NIH ImageJ Software, a customized computation code for semi-quantitative image processing was written to generate semi-quantitative data from the images taken of ROI  for statistical analysis of results. A Student In this study, we obtained fresh porcine esophagi from a local farmer A. The ouThe H&E staining result further shows that native, untreated tissue exhibits intact cell layers, which are easily identifiable A,C in thWe performed immunohistochemical staining on the DEM and native tissue samples on lumen side and transverse side to qualitatively determine the intact appearance of the main matrix components: collagen, fibronectin, and laminin. From the staining results, collagen I/III in DEM C,D showsTo compare the cell morphologies on DEM under static well plate and dynamic culture systems, human ESCC cell line KYSE30 were seeded. The results show that KYSE30 seeded on the 2D well plate forms tight yet disorganized shapes as colonies of cells which may pile on each other after confluence and do not seem to slow cell growth rate even after reaching a confluence and myriad cell–cell contacts A. They aThe cell viability staining result shows that KYSE30 cells seeded on DEM and placed in a well plate for 7 days E qualitap < 0.05) compared to KYSE30 under static and dynamic cultures . The slides were also rotated to an axis which gave the best comparison angle for viewing together. Two completely original slides stained separately were brought together as a single slide in the overlay from neighboring slides of the same tissue ESCC tumor biospecimen. They were overlaid together in the figure to show close interactions in the FFPE-ESCC tissue , which iP63 as a transcription factor plays a role in development of squamous epithelium. P63 is localized to basement cells and may be overexpressed in skin-related cancer phenotypes . Furtherp < 0.005) (p > 0.05)  H. Howeve > 0.05) L. E and p > 0.05)  D. C-met  > 0.05) G, but st > 0.05) F and lig > 0.05) E. Semi-qp > 0.05)  lineage is involved with activating NK cell cytotoxicity in response to tumor and viral ligand expression . We chos > 0.05) L.In this study, we developed a new decellularization method to decellularize porcine esophagus rapidly for use in the development of an esophageal cancer model. Porcine esophagus is similar to human esophagus, and cancer cell behavior as it interacts with originally living esophageal matrix may recognize, attach, modify, and experience a familiar environment, which may lead to observing phenomena that may not be found in other synthetic or altered substrate-based esophageal cancer models. The decellularization method was improved, as it brought the ease with which the epithelial layer was detached from the submucosa layer, and allowed complete cell removal without appearing to damage the matrix. This is a significant improvement over the conventional decellularization of such tissues because it removes the majority of epithelial cells in a single step without using any detergents. Most conventional decellularization methods could potentially denature resulting matrix properties ,53, whicCell studies show that our DEM is biocompatible, on which cancer cells proliferated well. The KYSE30 cancer cells seeded on the decellularized matrix were able to rapidly divide, occasionally disseminated throughout the matrix as they are apt to colonize within the matrix. In this study, we also successfully developed a dynamic culture system using a customized bioreactor. This system was easy to set up to perfuse culture media for cells, which provides a dynamic supply of nutrition to cells for proliferation and waste removal. The constant flow of nutritional supply and waste clearance maintained the cell growth expansion rate. This dynamic flow culture mode allowed cells to grow in higher density more efficiently. Dynamic culture also provides a large surface area for extended growth of cell populations more than a typical static culture well plate experiment. Additionally, the benefit of this dynamic culture system is that it can provide longer culture durations without maintenance intervention, since cell culture media is perfused continuously via a predetermined container volume and may be set up in advance for extended experiment conditions in order to gradually grow a larger tumor tissue than would otherwise be possible. Thus, this dynamic culture system brings promising potential to develop a biomimetic esophageal cancer model, mimicking an in vivo esophageal cancer tissue-growing microenvironment in the future. The FFPE-ESCC samples revealed cell phenotypical expression patterns not always seen in the static or dynamic DEM cultures . CD44 isFor the matrix-relevant protein periostin, both FFPE-ESCC biospecimens and DEM samples exhibited periostin expression. This result implies that periostin, as an extracellular secretion protein , may be For the semi-quantitative data, it is noted that at least eight immunohistochemistry pictures taken of multiple ROI were evaluated for each group and their staining intensity/cell-area was averaged together for each quantitative relationship graph; thus, the representative images in Using a cell line such as KYSE30 to perform single cell culture experiments in a decellularized esophageal matrix has some potential drawbacks . Cells oThus, this is the first step for our long-term goal of building a dynamic culture system and decellularization method for esophageal cancer model in vitro. In the future, we may co-culture with multiple cell compartments. It would be valuable to develop an advanced biomimetic esophageal tumor model using the DEM and dynamic culture system developed in this study with other cells for cancer cell progression, invasion, and metastasis mechanistic studies.In this study, we developed a new in vitro model of esophageal cancer using a detergent-free decellularized porcine esophageal matrix in a customized bioreactor. The new decellularization method can effectively remove cells and qualitatively maintain matrix components. The quantitative DNA experiment indicated successful decellularization and DNA removal. The decellularized matrix supported KYSE30 cancer cells to proliferate well in the static well plate and dynamic bioreactor. The esophageal cancer KYSE30 cells cultured on the DEM in the dynamic condition expressed different levels of cancer marker expression, compared to those in the static culture condition, but some similarities appeared compared to the FFPE-ESCC biospecimens. These findings bring new potential to using the decellularized matrix for future experiments in studying cancer behavior and practical applications for esophageal cancer models, as well as non-cancer specific tissue repair.


We subsequently profiled DNA methylation in NeuN+ , SOX10+ (oligodendrocyte-enriched) and NeuN–/SOX10– (microglia- and astrocyte-enriched) nuclei, finding that the majority of DMPs identified in ‘bulk’ cortex tissue reflect DNA methylation differences occurring in non-neuronal cells. Our study highlights the power of utilizing multiple measures of neuropathology to identify epigenetic signatures of AD and the importance of characterizing disease-associated variation in purified cell-types.Alzheimer’s disease (AD) is a chronic neurodegenerative disease characterized by the progressive accumulation of amyloid-beta and neurofibrillary tangles of tau in the neocortex. We profiled DNA methylation in two regions of the cortex from 631 donors, performing an epigenome-wide association study of multiple measures of AD neuropathology. We meta-analyzed our results with those from previous studies of DNA methylation in AD cortex (total  Here the authors identify differences in cortical DNA methylation associated with Alzheimer’s disease pathology, and profiling nuclei from specific cell-types, find that most of these differences reflect variation occurring in non-neuronal cells. Lewy-body (LB) and TDP-43 pathology, for example, are often present alongside tau and amyloid pathology in individuals with AD4. Despite progress in identifying both genetic9 and non-genetic risk factors for AD, the molecular mechanisms driving AD pathology remain elusive.Alzheimer’s disease (AD) is a chronic and incurable neurodegenerative disease that is clinically characterized by progressive memory loss and declining cognition. Although AD is neuropathologically associated with the accumulation of extracellular amyloid-beta (Aβ) plaques and the deposit of intracellular neurofibrillary tangles of tau (NFT)10, we and others have identified DNA methylation differences in several regions of the brain associated with AD and also other forms of dementia including Parkinson’s disease (PD)19. A recent epigenome-wide association study (EWAS) meta-analysis, for example, reported >200 differentially methylated positions (DMPs) in the cortex associated with tau pathology13. There are, however, important limitations to existing studies of epigenetic variation in AD. First, because the cortex comprises a heterogeneous mix of different cell-types—each characterized by a specific epigenetic signature—it is difficult to fully account for differences in cellular proportions between samples derived from “bulk” cortex tissue. Furthermore, because the progression of AD neuropathology is associated with changes in both the number and activation of specific cell-types—for example, AD is associated with both the loss of neurons21 and the proliferation and activation of microglia23—studies performed on bulk cortex cannot identify disease-associated variation occurring within individual cellular populations. Second, the clinical and neuropathological heterogeneity among patients with AD, alongside the high level of comorbidity with other types of dementia, complicates the interpretation of associations between epigenetic variation and pathology. Although existing EWAS analyses of AD have largely focused on a single pathology measure , the simultaneous analysis of multiple measures of different types of pathology is likely to facilitate a better understanding of the molecular mechanisms involved in disease progression.There is growing recognition of the importance of non-sequence-based regulatory variation in health and disease. Building on the hypothesis that epigenomic dysregulation is important in the etiology and progression of AD neuropathology25. First, we performed a systematic EWAS of AD neuropathology, profiling DNA methylation across >800,000 sites in two cortical brain regions  differentially impacted by AD pathology from ~650 well-characterized donors. Second, we meta-analyzed our results with those from previous AD EWAS analyses13, enabling an analysis of AD-associated differential cortical DNA methylation in tissue from over 2000 individuals. Third, we characterized genome-wide patterns of DNA methylation in NeuN+ , SOX10+ (oligodendrocyte-enriched), and NeuN–/SOX10– (microglia- and astrocyte-enriched) nuclei populations from a subset of BDR donors, exploring the extent to which AD-associated cortical differences in DNA methylation are driven by changes within specific cell populations. Our analyses identify neuropathology-associated variation at multiple novel loci not previously implicated in dementia and show that AD-associated methylomic variation in the cortex primarily reflects differences in non-neuronal cell populations. This study highlights the power of utilizing multiple neuropathology measures to understand the molecular pathogenesis of AD and the importance of characterizing disease-associated variation in distinct cell-types.In this study we quantified genome-wide patterns of DNA methylation in the Brains for Dementia Research (BDR) cohort, a clinically and phenotypically well-characterized study established with the aim of integrating standardized measures of neuropathology with detailed phenotypic and multiomic dataP = 2.33E–07), which is consistent with observations from epidemiological studies27. NFT pathology was quantified using Braak NFT staging24  and neuritic plaque density scored using the CERAD classification method29 . In addition, donors were also assessed for several hallmarks of non-AD pathology including both α-synuclein pathology using Braak LB staging30  and TDP-43 status (127 (22%) of 590 tested donors were classified as TDP-43 positive).After stringent data pre-processing and quality control filtering (see Methods), the final BDR dataset comprised of DNA methylation estimates for 800,916 DNA methylation sites profiled in 1221 tissue samples from two cortical brain regions (DLPFC and OCC) dissected from 631 donors  method recently described by our group37 to develop novel DNA methylation reference panels from NeuN+ (neuron-enriched), SOX10+ (oligodendrocyte-enriched), and NeuN–/SOX10– (microglia- and astrocyte-enriched) nuclei populations isolated from the DLPFC from a subset of control (low pathology) BDR donors . Of note, derived relative cell proportions were significantly associated with Braak NFT stage, CERAD score, and Thal phase in the DLPFC but not the OCC  with reduced NeuN+  cell proportion estimates , reduced NeuN–/SOX10–  proportions  and increased SOX10+ (oligodendrocyte) proportions . This pattern was mirrored for the two measures of amyloid pathology   and amyloid  pathology. We first conducted an analysis of combined AD pathology incorporating all three AD pathology measures in a model including matched DLPFC and OCC DNA methylation data from individual donors that controlled for age, sex, derived cellular proportions, experimental batch, and principal component (PC) 1 (see Methods). We identified 67 DMPs annotated to 45 genes that were associated with the overall burden of core AD neuropathology at a stringent experiment-wide significance threshold (08) Fig. . Of noteP < 9E–08)  reflecting the enrichment of hypermethylated loci observed in previous studies of tau pathology16. The top-ranked DMP (cg16021126) is annotated to SERP2, and was significantly hypermethylated with elevated Braak NFT stage  iPSC-derived neurons40. A total of 16 (62%) of the 26 tau-associated DMPs identified in the BDR dataset were tested in a recent meta-analysis of tau pathology performed across sites on the Illumina 450 K array13; effect sizes for these sites were perfectly consistent across all tau-associated DMPs  in the previous meta-analysis and 14 (88%) reached Bonferroni significance correcting for 16 sites (Bonferroni P = 0.00313). Likewise, of the 220 DMPs identified in the tau pathology meta-analysis, 208 are included on the Illumina EPIC array and tested in the BDR dataset. These were characterized by highly consistent effect sizes observed across both analyses . First, we identified 26 DMPs annotated to 21 genes associated with tau pathology at an experiment-wide significance threshold  with effect sizes at the same DNA methylation sites in analyses of the other neuropathological measures in BDR  for each specific measure, further indicating the presence of common effects with consistent differences in DNA methylation across the different measures of AD neuropathology.It is well established that the neuropathological signatures of AD are correlated and higher levels of NFTs are associated with elevated amyloid burdenn = 386, 72%) and TDP-43 negative —and we therefore had limited power to identify novel DMPs associated with either type of pathology. Elevated TDP-43 status was associated with significant hypomethylation at a single DMP . Although this site is not directly annotated to any gene, it resides ~50 kb from STK38L that encodes a protein kinase involved in neuronal cell division and morphology and has been identified to control axonal growth in mouse hippocampal neurons43. Overall, effect sizes for the 67 AD pathology DMPs were found to be highly consistent between analyses of the AD  and non-AD (Braak LB stage and TDP-43 status) neuropathology measures . We also performed an EWAS of AD pathology (including the same three measures of tau and amyloid pathology) independently in each cortical region  being identified in both the DLPFC and OCC. Of note, PDLIM2 encodes a protein that suppresses anchorage-dependent growth and promotes cell migration and adhesion, and has been implicated in PD by GWAS45. The consistency of findings between DLPFC and OCC suggests that variable DNA methylation at the identified DMPs is unlikely to simply reflect a consequence of neuropathology or neural cell loss.Our initial EWAS model leveraged matched DNA methylation data from both the DLPFC and OCC for each donor to maximize power to detect cortical DMPs associated with AD pathology. As expected, pathology-associated DNA methylation differences were highly consistent between both cortical regions across the 67 DMPs identified using this cross-cortex analysis model  meta-analysis of the Braak NFT stage including data for 403,763 DNA methylation sites from 2013 donors derived from seven independent cohorts  annotated to 171 genes  of the 334 meta-analysis DMPs are annotated to this genomic region  that has been robustly associated with AD pathology in previous EWAS studies of AD16 and was characterized by elevated DNA methylation with increased tau pathology  pathway analysis of the 171 genes annotated to the significant DMPs in the cross-cortex meta-analysis using methylGSA (see Methods) identifying significant enrichment of multiple pathways including pathways related to immune and inflammatory processes  and the deposition and highly insoluble proteins such as Aβ and NFTs49. Of particular interest was an enrichment of DMPs associated with genes involved in metalloproteinase activity pathways ; these proteins are important in neuroinflammation and have been strongly linked to neurodegenerative disease50. Other GO categories enriched amongst genes annotated to DMPs associated with tau pathology include pathways implicated in AD including several related to mitochondrial function  and “unfolded protein binding” . We subsequently repeated the meta-analysis focusing only on DLPFC samples from 1545 individuals from four independent cohorts  and DLPFC DMPs (P = 4.91E–91)  and “high” pathology  donors (Supplementary Data n = 327 DMPs). First, we looked at between-group effect sizes in the “total” nuclei population finding highly consistent DNA methylation differences to those seen in the large DLPFC meta-analysis despite the small number of samples, confirming the validity of our EWAS results . We then examined high vs low Braak score differences in DNA methylation at the 327 DLPFC DMPs finding a striking difference in the consistency and magnitude of effect sizes across each of the nuclei populations  and was also characterized by a dramatic increase in effect sizes compared to those observed in bulk DLPFC  again with an elevated effect sizes compared to bulk DLPFC, albeit to a lesser extent ) of tested DMPs , SOX10+ (oligodendrocyte-enriched), and NeuN–/SOX10– (microglia- and astrocyte-enriched) nuclei populations, our EWAS approach could not identify AD-associated differences occurring within specific cell populations. We therefore used our FANS protocol (see Methods) to profile DNA methylation in purified NeuN+, SOX10+, and NeuN–/SOX10– nuclei populations - in addition to a “total” nuclei population reflecting the cellular makeup of bulk cortex—from DLPFC tissue from a subset of “low” pathology . We subsequently combined our results with those from previous studies of DNA methylation in AD cortex47. The HOXA cluster is involved in the control of neuronal development, neuronal circuit organization, and the regulation of post-mitotic neurons52, and in addition to AD methylomic variation across the HOX region has been associated with other neurodegenerative diseases including PD, Huntington’s disease, and C9ORF72-related dementia55. AD pathology-associated DMPs were also annotated to many immune-related genes  with GO pathway analyses finding an enrichment of immune and inflammatory pathways. These findings build on existing evidence that immune dysregulation plays a key role in the etiology of AD and other dementias49. In addition, differential DNA methylation in the vicinity of the SPI1 gene was identified in our cortical meta-analysis of AD pathology. SPI1 has been identified in recent AD GWAS56 and EWAS13 analyses and encodes the transcription factor PU.1, a pioneer factor for myeloid macrophages and microglial populations that has been implicated in regulating genes leading to inflammatory response in AD57. This is particularly interesting in the context of our analyses of sorted nuclei populations which identified that the majority of methylomic differences associated with AD pathology occur in the NeuN–/SOX10– population that is enriched for microglia.Many of the pathology-associated DMPs identified in this study are annotated to genes that have previously been implicated in dementia. This includes multiple DMPs annotated to the HOXA region which has been previously identified in EWAS analyses of AD pathology58. In addition, mutations in familial early-onset AD genes  are also observed in PD cases highlighting the pleiotropic effects associated with monogenic forms of neurodegeneration59. Previous EWAS analyses have also identified methylomic similarities between different neurodegenerative diseases60 reporting significant over-representation in pathways related to brain function and immune response. The evidence for pleiotropy suggests that common pathological mechanisms likely underlie neurodegenerative disorders. Although neurodegenerative diseases differ in their neuropathological hallmarks and the specific brain regions involved, a common feature is the progressive accumulation of toxic protein deposits that ultimately lead to neuronal cell death and brain atrophy61. One key strength of the BDR dataset is that multiple neuropathology measures have been collected for each individual, enabling us to identify DMPs robustly associated with overall levels of AD neuropathology and leveraging greater power than analyses based on single pathology measures. Of note, although the findings suggest there are general methylomic signatures of neuropathological burden, we cannot exclude the presence of differential DNA methylation associated with specific types of neuropathology. Interestingly the BDR effect sizes are larger than those observed in our recent meta-analysis of tau pathology13; this could potentially reflect cohort differences, the reduced heterogeneity in BDR, array platform differences, or by the fact that association statistics for variants meeting an experiment-wide threshold tend to be overestimated62. In addition, the consistency in the direction of effect demonstrates how robust the EWAS results for AD pathology are across studies.The high overlap of DMPs and consistency of differences in DNA methylation across the different types of neuropathology assessed in BDR donors suggests that they may reflect some common signatures of neurodegeneration. This could imply that these differences are a common consequence of pathology or that they reflect the known pleiotropy between different types of dementia. For example, SNPs within the HLA region, MAPT, and APOE all contribute to increased risk for FTD, AD, and PD63; with the activation of microglia colocalized with amyloid plaques in the brains of individuals with AD. The larger effect sizes observed at AD-associated DMPs in the microglial-enriched population might reflect the elevated reactivity of microglia in AD compared to other cell-types, presumably driven by cell-type-specific transcriptional signatures64.A major strength of our study is our use of FANS to purify immunolabeled nuclei populations from a subset of donors prior to DNA methylation profiling. This enabled us to develop a refined cell-type deconvolution model that better controls for cellular heterogeneity in bulk cortex measurements of DNA methylation than previous models that only estimate the proportion of neuronal cells. Even when controlling for cell-type proportions, the bulk cortex analysis does not enable the identification of pathology-associated DNA methylation differences occurring in specific cell-types. We therefore profiled DNA methylation in FANS-purified nuclei populations from individuals with high and low AD pathology to explore the extent to which differences identified in bulk tissue were driven by variation in specific cell-types. Our analyses showed that most of the DMPs identified in the bulk cortex reflect variation in non-neuronal cell-types, with the biggest effect sizes identified in nuclei from NeuN–/SOX10– cells that we found to be relatively enriched for microglial (IRF8+) nuclei. These results support recent work highlighting a key role for microglia in AD65; although co-staining with the microglial marker IRF8 highlighted that this population is relatively enriched for microglial cells , TV and radio coverage as well as at memory clinics and support groups. There were no exclusion or inclusion criteria for individuals with specific diagnoses or those carrying genetic variants associated with neurodegenerative diseases; the cohort includes those with and without dementia and covers the full range of dementia diagnoses. Participants underwent a series of longitudinal cognitive and psychometric assessments and gave written informed consent for the use of tissue samples and clinical information for research purposes. Ethical approval for the study was granted by the University of Exeter Medical School Research Ethics Committee (13/02/009).The BDR cohort was established in 2008 and represents a network of six dementia research centers across England and Wales  and five brain banks (brain donations from Cardiff are banked at King’s College London)68. This protocol was used to generate a description of the regional pathology within the brain together with standardized scoring. Five variables representing four neuropathological features were used in the analyses presented in this paper: (1) Braak NFT stage that captures the progression of NFT pathology24, (2) Thal phase that captures the regional distribution of Aβ plaques2, (3) CERAD score that quantifies neuritic plaque density29, (4) Braak LB stage that captures the progression of α-synuclein throughout the brain69, and (5) TDP-43 status—a binary indicator of the TDP-43 inclusions, which was assessed using immunohistochemistry to identify the presence of phosphorylated TDP-43 in the amygdala, hippocampus, and adjacent temporal cortex.Braak NFT stage, Thal phase, CERAD score, and Braak LB stage were analyzed as continuous variables, utilizing the semi-quantitative nature of these measures to identify dose-dependent relationships of increasing neuropathology with variable DNA methylation. TDP-43 status was analyzed as a binary variable.Post-mortem brain donations to BDR undergo full neuropathological dissection, sampling, and characterization by experienced neuropathologists in each of the five network brain banks using a standardized BDR protocol based on the BrainNet Europe initiative70. After stringent data quality control (see below) the BDR dataset consisted of DNA methylation estimates for 800,916 DNA methylation sites profiled in 1221 samples  from each BDR donor. DNA was isolated from ~100 mg of tissue using the Qiagen AllPrep DNA/RNA 96 Kit  following tissue disruption using BeadBug 1.5 mm Zirconium beads  in a 96-well Deep Well Plate  shaking at 2500 rpm for 5 min. Genome-wide DNA methylation was profiled using the Illumina EPIC DNA methylation array (Illumina Inc.), which interrogates >850,000 DNA methylation sites across the genome37. First, nuclei populations were isolated from 12 donors with low neuropathology  to simultaneously collect populations of NeuN+   and SOX10+ (oligodendrocyte-enriched)  immunolabeled populations from bulk DLPFC tissue prior to genomic profiling, with the double-negative fraction and an aliquot of the “total” nuclei fraction  also being collected from each tissue sample  checking methylated and unmethylated signal intensities and excluding poorly performing samples; (2) assessing the chemistry of the experiment by calculating a bisulphite conversion statistic for each sample, excluding samples with a conversion rate <80%; (3) identifying the fully methylated control sample included on each plate was in the correct location; (4) multidimensional scaling of sites on the X and Y chromosomes separately to confirm reported sex; (5) using the 59 SNP probes present on the Illumina EPIC array to confirm that matched samples from the same individual (but different brain regions or nuclei populations) were genetically identical and to check for sample duplications and mismatches; (6) using the pfilter function in wateRmelon to exclude samples with >1% of probes with a detection P value > 0.05 and probes with >1% of samples with detection P value >0.05; (8) using PC analysis on data from each tissue to exclude outliers based on any of the first three PCs; and (9) the removal of cross-hybridizing and SNP probes73. The subsequent normalization of the DNA methylation data was performed using the dasen function with the default options in either wateRmelon or bigmelon74. DNA methylation data generated on the purified nuclei populations were normalized separately for each cell-type.Raw Illumina EPIC data were processed using the 75. As DNA methylation data for each donor was derived from two cortical regions, a mixed effects regression model was used, implemented with the lme476 and lmerTest77 packages  from 12 DLPFC samples  between the different cell-types and selects 100 sites per cell-type (50 hypermethylated and 50 hypomethylated). These sites are then used to derive cellular proportions using quadratic programming, in essence, a least squares minimization, with the constraint that all the proportions are greater than or equal to 0 and the sum of the three proportions is less than or equal to 1. Two of the three estimated proportions (NeuN+ and NeuN–/SOX10–) were included in the model to eliminate the effects of multicollinearity. To generate P values, an ANOVA was conducted, comparing the full model including the three AD neuropathology measures to a null model in which the three measures were excluded. We next conducted an EWAS for each of the five neuropathology measures separately  using the same set of covariates. In addition, we ran analyses where cell proportions were regressed against neuropathology in each brain region using linear regression models, controlling for age and sex. To identify tissue-specific effects, linear regression models were run in each brain region for the three main AD neuropathology measures controlling for age, sex, experimental batch, PC1, and derived cell proportions. Finally, to further explore if there was an effect present in one cortical region and not the other we ran a heterogeneity test, where we included an interaction between neuropathology and brain region in the mixed effects models, controlling for age, sex, experimental batch, brain region, PC1, derived cell proportions and individual. EWAS results were subsequently processed using the bacon R package78, which applies a Bayesian method to adjust for inflation in EWAS.To identify associations between variable DNA methylation and neuropathology we fitted regression models using the R (version 4.1) statistical environment13; this paper includes detail on each of the individual cohorts included in the overall meta-analysis and information about each cohort is also provided in Supplementary Data N = 14) samples that overlapped with samples included in the LBB1 cohort described in the Smith et al meta-analysis13. In the cross-cortex meta-analysis, a total of 2939 samples (from 2013 donors) were included  and the P value was Bonferroni corrected to control for this number of sites tested . P values are from two-sided tests and significant DMPs were taken from a fixed effects model. Pathway analyses were subsequently performed on the significant DMPs using the methylglm function within the methylGSA package developed by Ren and Kuan80 using the default parameters.Cross-cortex and DLPFC-specific meta-analyses of the Braak NFT stage were conducted incorporating the BDR with cohort-level summary statistics from a recent meta-analysis published by Smith et al.N = 13]; Braak low ≤ II [N = 15]) (Braak score), which was modeled as a binary variable, in the four FANS sorted nuclei populations . The results were then compared to the meta-analysis results where a binomial test (sign test) was used to statistically evaluate consistency in direction of effect across the analyses.To determine whether associations identified in the bulk cortex are primarily driven by alterations in specific cell-types we used data generated on purified nuclei populations from individuals with high or low AD pathology. Briefly, we conducted an analysis of DNA methylation differences for significant sites from the bulk cortex meta-analyses comparing high and low pathology (defined as Braak high ≥V [Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7Supplementary Data 8Supplementary Data 9Supplementary Data 10Supplementary Data 11Supplementary Data 12Supplementary Data 13Supplementary Data 14Reporting Summary


CACNA1S gene , such as autosomal dominant hypokalemic periodic paralysis 1 and autosomal dominant malignant hyperthermia susceptibility and are associated with autosomal dominant and recessive congenital myopathy. Recently, an interesting case of a 58-year-old male patient was published describing an unusual clinical presentation of hypokalemic periodic paralysis where a late-onset limb-girdle myopathy had developed 41 years after paralysis occurred when the patient was 11 years old. Muscle biopsy results were consistent with myopathic changes and revealed the presence of vacuoles, without inflammatory reaction. Later, molecular analysis revealed a pathogenic variant c.3716G>A (p.Arg1239His) in exon 30 of the CACNA1S gene. This technical report provides an extension of the molecular findings and evaluates the clinical and histopathological relationship previously published regarding this case.Several clinical phenotypes have been described related to the  Hypokalemic periodic paralysis (HypoPP) is a neuromuscular disorder caused by pathogenic variants in calcium or sodium channels with an autosomal dominant inheritance characterized by recurrent hypokalemia episodes and muscle weakness. The disease onset occurs in the first two decades of life and the most frequent symptom is paroxysmal muscle weakness secondary to strenuous physical activity or intake of carbohydrate-rich meals, followed by myopathy in limb-girdle pattern months or years after the onset of the first muscle weakness crisis ,2.SCN4A gene and tubular aggregates in their muscular biopsies to date ); in the RETREG1 gene ([c.17C>T [p.Pro6Leu]), and the SPG11 gene (c.5650C>T [p.Arg1884Cys]), in a heterozygous state in each one. PRX, RETREG1, and SPG11 genes are associated with autosomal recessive Charcot-Marie-Tooth disease type 4F, autosomal recessive hereditary sensory and autonomic neuropathy type 2B, and autosomal recessive hereditary spastic paraplegia 11 (SPG11), juvenile amyotrophic lateral sclerosis 5 and Charcot-Marie-Tooth disease type 2X, respectively. Therefore, these entities did not correlate clinically with our case because of their inheritance pattern. It is important to mention that the absence of detection of different variants does not rule out other vacuolar myopathies, since the analysis carried out was through a panel with 201 genes related to neuromuscular diseases and not by other techniques such as an exome or whole-genome sequencing. This analysis could not be performed on his siblings because they expressed the desire not to know their molecular status.Finally, we assessed a panel of 201 of our patient’s genes related to neuromuscular conditions, and we identified additional variants of uncertain significance in the PRX gene (c.3186G>T [The presence of vacuoles in the muscle biopsy in our patient was an unusual finding. Our case confirms that myopathy could progress independently of episodes of muscle weakness, and histopathological findings in muscle biopsy may develop despite the absence of persistent weakness. Because HypoPP is an extremely rare condition, it should be considered part of the differential diagnosis in a patient with symptoms of acute crises of muscle weakness or nonspecific myopathy.Molecular genetic analyses are an important diagnostic tool in the clinical approach to neuromuscular diseases because these are difficult to diagnose by routine tests and biopsy. Hence genetic analysis is mandatory to diagnose and assess prognosis. These analyses indicate that a specific mutation in any gene can manifest various clinical phenotypes, such as that seen in pathogenic variants in the CACNA1S gene, and in the future, this could be a guide to novel treatments as well as promote more research in this field.


Recent research indicates that T cells react to CAF signalling and establish bidirectional crosstalk that plays a significant role in the tumour immune response. This review discusses the various mechanisms by which the CAF/T cell crosstalk may impede anti-cancer immunity.The presence of functionally efficient cytotoxic T lymphocytes (CTL) in the Tumour nest is crucial in mediating a successful immune response to cancer. The detection and elimination of cancer cells by CTL can be impaired by cancer-mediated immune evasion. In recent years, it has become increasingly clear that not only neoplastic cells themselves, but also cells of the tumour microenvironment (TME) exert immunosuppressive functions and thereby play an integral part in the immune escape of cancer. The most abundant stromal cells of the TME, cancer associated fibroblasts (CAFs), promote tumour progression  CAFs secrete angiogenic factors [e.g. vascular endothelial growth factor (VEGF)], factors degrading the basal membrane [matrix metallopeptidases (MMPs)], which promotes metastasis, and even alter their metabolic profile to produce energy metabolites  useful for cancer cells (“reverse Warburg effect”) . Fibroblasts are typically activated during wound healing and revert to their quiescent state after exerting their function. However, in cancer, they remain perpetually activated by a number of factors including the presence of cancer cells, as indicated by their expression of activation markers  and promote tumour progression effect”) . Furthereffect”) , 3.CAFs employ immunosuppressive functions that involve various immune cells and stages of antitumoral immunity. In this review, we aim to establish a framework to understand the part CAFs play in inhibiting an efficient T cell response. An efficient T cell response relies on a number of orchestrated steps involving many cell types in the TME and results in cancer cell killing by cytotoxic T cells. In an ideal scenario, antigen presenting cells (APCs) present tumour antigen to naive T cells within tumour draining lymph nodes, inciting their activation, differentiation into cytotoxic T cells and travel to the tumour site. Here supported by a Th-1 mediated response of CD4+ T helper cells, primed activated cytotoxic T cells recognize their cognate antigen on the surface of cancer cells leading to clonal expansion of tumour specific effector T cells. This is followed by secretion of cytotoxic granules containing perforin and granzymes and killing of target cells in an antigen directed manner . SuccessVarious cell types can give rise to CAFs if exposed to environmental triggers such as TGF-β, platelet derived growth factor (PDGF) and fibroblast growth factor (FGF) . The absIt is now widely recognised that CAFs display high heterogeneity , 8. KnowThe most notable subsets investigated are the CAF-S1 and CAF-S4 as they have been found to be associated with cancer cell invasion and poor prognosis in breast cancer , 13. CAFMed FAPHi FSP1Low-Hi αSMAHi PDGFRbMed-Hi CAV1Low) promotes the activation and differentiation of CD25+ T cells to FoxP3+ Treg, whereas CAF S4 (CD29Hi FAPNeg FSP1Low-Med αSMAHi PDGFRbLow-Med CAV1Neg-Low) does not, even though both are αSMAhigh and could therefore be classified as CAFs. Significant differences in their inhibitory capacity were also seen regarding cytokine production and migration of T cells ] or do not effectively infiltrate the tumour islands, as they are either restricted to the invasive margins or the stromal regions of the tumour, unable to be in physical contact with cancer cells [“excluded” (3)]. Factors determining the immunophenotype of a tumour include tumour mutational burden (TMB) and MHCI expression and recent research indicates a crucial role of CAFs , tumours are characterised by T cell infiltration and associated with enhanced response to checkpoint inhibition . It is w of CAFs .in vitro. Added TILs accumulated at 5x higher numbers in the tumour stroma compared to tumour islets and travelled along linear tracks parallel to stromal fibres. They further showed that T cell counts were negatively correlated with ECM density and that fibronectin rich regions, such as areas immediately surrounding tumour islets, inhibited T cell motility , co-localises with CAF activation markers FAP and αSMA and was associated with low TIL counts. PS1 silencing reduced the expression of FAP and αSMA on CAFs and reduced tumour burden in an ovarian tumour mouse model via increased CTL infiltration, indicating that PS1 has a significant role in CAF mediated T cell exclusion from the tumour nest, likely upstream via promoting CAF activation  resistance using CAF rich murine tumour models. They previously reported that the downstream target of TGF-β1, NADPH oxidase 4 (NOX4), which generates reactive oxygen species (ROS), can regulate fibroblast differentiation into myofibroblasts . Using se tumour . These s+CAFs in the TME binds to its receptor CXCR4, expressed by T cells, thereby trapping TIL in the tumour stroma and restricting their access to tumour areas containing cancer cells (+ T cell infiltration into the tumour (Fibroblastic reticular cells (FRCs) employ chemotactic strategies to modulate T cell trafficking in the healthy lymph node by expression of lymphocyte attractants CCL19 and CCL21 which bind to CCR7 on naïve T cells . Similarer cells . Feig ete tumour .+ T cell infiltration could be partly mediated by a negative regulation of CAFs via FGFR inhibition (Another factor attenuating CD8 T cell infiltration is Fibroblast growth factor-β (FGF2) a cytokine released by cancer cells that activates quiescent fibroblasts and upregulates CAF marker expression like αSMA and FAP . In a mohibition .high CAFs  in breast cancer and a dominant feature of an inflammatory CAF phenotype in pancreatic ductal adenocarcinoma  from healthy donor PBMCs to supernatant from CAFs from Treg-high lung tumours and did see a significant increase in FOXP3+ cells compared to supernatant from CAFs from Treg-low tumours that was mirrored by treatment with TGF-β suggesting true induction of Tregs via CAF secreted TGF-β  and central (CD45RA-CCR7+) – memory T cells amongst proliferating T cells is significantly reduced. Instead a larger pool of T cells remains in their naïve state (CD45RA+CCR7+)  . In addieg ratio . In linen cancer . To conc+T cell activation reduces the percentage of cells exhibiting the early T cell activation marker CD69. Additionally, in PBMCs co-culture, CAFs promote an increase in cytokines typical for Tregs, such as IL-10 and TGF-β in line with their positive influence on Treg differentiation, and thereby add to the consequent anti-inflammatory environment. In fact, when pre-exposed to the CAF subtype CAF-S1, CD25HighCD127lowCD45RAlow T cells increased the ability to inhibit the proliferation of effector T cells. CAFs thereby equip Tregs with increased suppressive activity against effector T cells  in response to signals from activated T cells which enhances IL-2 and TNF-α production by activated CD8 T cells. Conversely, in cancer, some studies indicate that CAFs reduce CTL activation. The presence of melanoma CAFs during CD8+ T cells during co-culture  and OX40 and markers of cytotoxicity (granzyme and perforin)  .However, while Nazareth et al. report a suppressive effect of CAFs on T cell activation in 3/8 NSCLC tumours, in the other five tumours, CAFs surprisingly produced IFN-γ, and induced the activation of T cells, which increased their response to TCR stimulation, a phenomenon that could be partially reversed by TGF-β . Interes+TIL in pancreatic cancer , via the cell-surface enzyme CD39, into adenosine monophosphate (AMP), which is further converted into adenosine by CD73 (via suppressing the immune response. It enhances the immunosuppressive effects of tumour associated macrophages (TAM), myeloid derived suppressor cells (MDSC) and regulatory T cells while dampening immunostimulatory effects of neutrophils, NK cells and inhibits T cell priming by inhibiting the activation of dendritic cells (DCs)  . Further+ T cells than each cell type alone and additionally upregulate CD73 expression on CD4+ T cells , CTLA4 and MHC expression, where they are in bidirectional crosstalk with CAFs. This results in reduced proliferation, activation, and differentiation of cytotoxic T cells in an environment that instead nurtures immunosuppressive cells. The reduced number of cytotoxic T cells that do remain are incapacitated by upregulation of co-IR, while their presence causes CAFs to upregulate the corresponding ligands, likely to limit their residual function further.In conclusion, it has become evident that CAFs significantly impede effective cytotoxic T cell immunity across cancer types. Current knowledge paints the picture that the TME establishes an environment, that promotes the development of hyperactive fibroblasts, CAFs, that perpetually secrete ECM thereby producing a dense web of collagen with high interstitial pressure to protect cancer cells from infiltrating T cells. T cells are trapped in the stroma, physically and CAFs affect a multitude of changes in T cell biology, and it seems T cells in turn elicit changes in CAF secretome and surface marker expression. These feedback mechanisms highlight the complex bidirectional crosstalk between CAFs and TILs, illustrating the need for further investigation. However, variable definitions of CAFs and their subtypes remain a challenge in the field as they cause a lack of comparability between studies. Increased understanding of CAF subtypes and whether they are found across cancer types is key to disentangle CAF – TIL interactions. The significant role of CAFs in all steps of the tumour immunity cycle as well as the fact that CAF inhibition resulting in delayed tumour growth was entirely dependent on CTL, underscore that CAFs might present a target to relieve environmental pressures on cytotoxic T cells to increase the efficacy of therapies aimed to revive the cytotoxic T cell response.LK and LM drafted the initial version of the review. All authors edited and revised the review and approved the final manuscript.AA is funded by a Cancer Research UK Clinician Scientist Fellowship (A24867). LM is funded through a EPSRC and MRC Centre for Doctoral Training in Optical Medical Imaging (EP/L016559/1). LK is supported by a GlaxoSmithKline-NPL studentship. The funders were not involved in the review design, interpretation or the writing of this article or the decision to submit it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Drosophila models engineered to express differing levels of ELAV activity in the course of development. We show that the ELAV-mediated establishment of a subset of neuronal mRNA isoforms at the onset of neuron differentiation constitutes a developmental bottleneck that cannot be overcome later by the nuclear activation of the paralog found in neurons (FNE). Loss of ELAV function outside of that critical time window results in neurological defects. We find that FNE, when activated early enough, can restore ELAV-dependent neuronal mRNA isoforms and fully rescue development. Our findings demonstrate the essential role of robust cellular strategies to maintain ELAV activity and intact neuronal signatures in neurogenesis and neuronal function.Cell-type-specific gene regulatory programs are essential for cell differentiation and function. In animal neurons, the highly conserved ELAV/Hu family of proteins promotes alternative splicing and polyadenylation of mRNA precursors to create unique neuronal transcript isoforms. Here, we assess transcriptome profiles and neurogenesis success in   •Drosophila ELAV establishes alternative mRNAs at the onset of neuronal differentiation•Loss of early neuronal mRNA isoforms irremediably impairs neurogenesis•in vivoAfter the critical time window, nuclear activation of FNE rescues ELAV loss •If activated at differentiation onset, FNE fully restores neuronal RNAs and development Carrasco et al. show that neuronal differentiation depends on the establishment of a subset of alternative mRNA isoforms by one single effector, ELAV, as soon as the first post-mitotic neurons are born. Outside of this developmental window, nuclear activation of the paralog FNE fully rescues neuronal RNA signatures and neurogenesis. Cells adopt many strategies to increase the coding and regulatory potential of their genetic content. In the nervous system, a tissue displaying an astonishing transcriptome diversity, the production of multiple mRNA isoforms from a single protein-coding gene is particularly prevalent . HundredDrosophila, the three ELAV/Hu paralogs appear consecutively in the course of development: found in neurons (FNE) expression follows ELAV’s during embryogenesis  and neuroglian (nrg) depends on ELAV-dependent APA (Down syndrome cell adhesion molecule 1 (Dscam1) impairs axon outgrowth  compensates for the loss of ELAV activity in that it restores neuronal signatures  was disrupted  in elavmin stage 16 (14–16 h after egg laying [AEL]) embryos and compared neuronal transcript signatures with those of Δelav null mutants. Interestingly, in elavmin embryos, ELAV-dependent 3′ UTRs were severely depleted and showed the expression drop downstream of the proximal poly(A) site characteristic of Δelav , before FNE expression begins. We detected 31 neuronal 3′ UTRs  ELAV, the expression of these early transcript signatures was significantly improved  in late, but not early, embryos; however, the downregulation of Comm in Δelav mutants results in early differentiation defects  complex CFIm25/68, in which the concomitant binding of two CFIm25 subunits to two separate UGUA motifs facilitates RNA looping and inhibits poly(A) site usage  and physiological (phenotypic outcomes) functions of ELAV were fully rescued by nFNE when it was expressed in the correct developmental window .Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Valérie Hilgers . Flies denoted as Δfne are of the genotype Df(1)fne and were obtained from Matthias Soller  targeted the elav coding region and non-homologous end joining repair introduced an indel at Q420, resulting in a shift in the ELAV ORF (ORF +2). To generate the fnenFNE fly, two guide RNAs  and a template sequence were designed to replace the endogenous intron containing the n-fne mini-exon, by the n-fne mini-exon without the adjacent intronic sequence; the two guide RNAs, the 1.09-kb donor homology sequence and DNA encoding Cas9 were co-injected into fneFLAG  were co embryos  to generAll flies used in this study were raised in heterozygosis with GFP-marked balancer chromosomes. Embryos were collected on agar plates and aged for the appropriate time at 25°C. Embryos were dechorionated following standard procedures and placed on a plate containing halocarbon oil. Male mutant embryos were selected according to embryonic age, morphology, and against GFP signal.Embryonic viability was calculated as the fraction of embryos that successfully completed embryogenesis and hatched into first instar larvae. Dechorionated embryos coated with halocarbon oil were placed on agar plates. Starting at 20–22 h AEL, the count of unhatched embryos was recorded every two hours for fourteen hours and one last time at 46–48 h AEL. Hatching delay was calculated as the difference in hatching time between a given embryo and that of the median time in the control (wild type) group.ImageJ.Recently-hatched L1 larvae were transferred to agar plates containing yeast paste (2:3 ratio reconstitution of dry yeast in water). Larvae were kept at 25°C for 48 h, after which the survival and developmental stage of each larva was assessed visually using a stereoscope. To measure larval growth, recently-hatched L1 larvae were placed in agar plates coated with a fine layer of yeast solution (2:4 ratio reconstitution of dry yeast in water) and allowed to age in a humid chamber at 25°C. Images of crawling or dead larvae were captured using a Leica M165FC stereoscope and head-to-tail length was measured using Δelav,fnenFNE, the number of scored adult flies appears very low. Eclosion delay was calculated as the difference in eclosion time between a given fly and that of the median time in the control group.Adult viability was calculated as the fraction of mutant flies from a heterozygous stock compared to expected Mendelian ratios and normalized to ratios in the control (wild type) group. Virgin females heterozygous for a given mutation were crossed with males hemizygous for a balancer chromosome and were allowed to lay eggs for 24 h. Afterward, flies were discarded and eggs were allowed to develop for ten days at 25°C. The genotypes of eclosed flies - including those dead shortly after eclosion - were recorded every day for ten days. Hence, for genotypes with very low viability, like Δelav,fnenFNE flies, due to very low viability that precludes harvesting high numbers of age-matched flies, 49 males were collected and distributed in three vials. Flies were transferred to fresh food and the number of dead flies was recorded every 48 h until all flies had died. Survival probability was calculated using the survival package in R and plotted using the ggsurvplot function from survminer . Primary antibodies were used at concentration of 1:200 (rabbit anti-ELAV and mouse anti-FLAG (Sigma F1804)) and incubated together with fluorophore-conjugated anti-HRP 1:100  overnight at 4°C. Other fluorophore conjugated secondary antibodies were used at concentrations 1:500 and incubated for 1 h at room temperature. Confocal imaging was performed on a Zeiss LSM 780 microscope.fne-RA were used to detect fne alternative splicing. DNA fragments were resolved in a 2% agarose gel.Total RNA was extracted from biological samples using 12 heads or 15 embryos per condition in biological triplicates and quadruplicates, respectively. Samples were homogenized directly in TRIzol (Invitrogen) and RNA was extracted following the manufacturer’s instructions. RNA integrity was assessed using the 2100 Bioanalyzer (Agilent Technologies). 300 ng of total RNA was used for reverse transcription using iScript gDNA Clear cDNA Synthesis Kit (Bio-Rad). qRT-PCR was performed in a LightCycler 480 II instrument using FastStart SYBR Green Master (Roche). qRT-PCR primer sequences are listed in 100 ng of total RNA were used to prepare mRNA-seq libraries using the Stranded mRNA Prep reagents  according to the manufacturer’s instructions. Paired-end sequencing was performed using the NovaSeq6000 (Illumina) and 150-bp or 100-bp reads for data shown in featurecount  were counted using HTSeq . PotentiplotHeatmap from deepTools (Fold change expression in ELAV-dependent neuronal 3′ UTRs and alternatively spliced exons were visualized using eepTools . Exons sth and 90th percentiles. Statistical tests and data visualization were performed, unless otherwise indicated in the respective methods section, using GraphPad Prism 8 for macOS.Statistical parameters and tests, sample sizes and number of biological and/or technical replicates are reported in the respective figure legends. Boxplots display boxes with interquartile ranges from first to third quartile; whiskers represent the 10


Obesity is a multifactorial and chronic condition of growing universal concern. It has recently been reported that bariatric surgery is a more successful treatment for severe obesity than other noninvasive interventions, resulting in rapid significant weight loss and associated chronic disease remission. The identification of distinct epigenetic patterns in patients who are obese or have metabolic imbalances has suggested a potential role for epigenetic alterations in causal or mediating pathways in the development of obesity-related pathologies. Specific changes in the epigenome (DNA methylome), associated with metabolic disorders, can be detected in the blood. We investigated whether such epigenetic changes are reversible after weight loss using genome-wide DNA methylome analysis of blood samples from individuals with severe obesity (mean BMI ~ 45) undergoing bariatric surgery.p < 0.05) and 1169  suggestive differentially methylated positions (DMPs) associated with weight loss due to bariatric surgery. Among the 41 significant DMPs, 5 CpGs were replicated in an independent cohort of BMI-discordant monozygotic twins (the heavier twin underwent diet-induced weight loss). The effect sizes of these 5 CpGs were consistent across discovery and replication sets (p < 0.05). We also identified 192 differentially methylated regions (DMRs) among which SMAD6 and PFKFB3 genes were the top hypermethylated and hypomethylated regions, respectively. Pathway enrichment analysis of the DMR-associated genes showed that functional pathways related to immune function and type 1 diabetes were significant. Weight loss due to bariatric surgery also significantly decelerated epigenetic age 12 months after the intervention .Our analysis revealed 41 significant (Bonferroni We identified weight loss-associated DNA-methylation alterations targeting immune and inflammatory gene pathways in blood samples from bariatric-surgery patients. The top hits were replicated in samples from an independent cohort of BMI-discordant monozygotic twins following a hypocaloric diet. Energy restriction and bariatric surgery thus share CpGs that may represent early indicators of response to the metabolic effects of weight loss. The analysis of bariatric surgery-associated DMRs suggests that epigenetic regulation of genes involved in endothelial and adipose tissue function is key in the pathophysiology of obesity.The online version contains supplementary material available at 10.1186/s13148-022-01401-9. Generally, people having a body mass index (BMI) of 25–30 kg/mnd obese . The incnd obese . This exnd obese , 7.Obesity and cancer development are strongly associated: obesity contributes to 40% of all cancers and 60% of endometrial, postmenopausal breast, and colorectal cancers (the latter being more common in women 9.6%) than men (4.7%)) . Cytokin.6% than Treatment approaches include lifestyle changes , cognitive behavioral therapy, pharmacotherapy, and surgery. Bariatric surgery results in sustainable and substantial weight loss and has proven to be more effective than other treatments . MoreoveWhile genetic factors play an important role in determining individual susceptibility to weight gain and obesity , they doOne significant epigenetic modulator is DNA methylation, which is readily altered by environmental and lifestyle factors , 21. RecIn the present study, we investigated the effect of bariatric surgery-induced weight loss on clinical parameters and epigenetic alterations in individuals with severe obesity. We collected blood samples and follow-up data and performed DNA methylome analysis to identify differentially methylated genes and pathways linked to weight loss. To substantiate our results, we included a replication set of samples from BMI-discordant monozygotic twins. The obese twins in the replication set lost weight due to caloric restriction, thus serving as a control group that did not undergo bariatric surgery. We also explored the association between weight loss and aging through the epigenetic clock . The weiWe collected blood samples and clinical data from 22 subjects with obesity before they underwent bariatric surgery, and during two follow-up visits at 6 and 12 months after surgery  and 1169 suggestive differentially methylated CpGs  associated with weight loss due to bariatric surgery  on chromosome 1     between BMI and time. Therefore, our results are strongly associated with BMI change and not influenced by time.To examine whether the association between BMI and methylation is influenced by time, we performed an additional linear mixed model (LMM) with an interaction term between BMI and time as fixed effects. The analysis showed that the interaction did not reach genome-wide statistical significance for any of the CpGs tested  were used to test the results in an independent replication set consisting of peripheral blood mononuclear cells (PBMCs) from eight healthy pairs of monozygotic BMI-discordant twins undergoing a hypocaloric diet. As expected, a low-calorie diet induced fewer epigenetic changes than did bariatric surgery, in line with the modest BMI change associated with dieting (< 10%); however, 5 CpGs were replicated at p < 0.05 in the replication set. The effect sizes were consistent across the discovery and replication sets, meaning that the percentage β value change per unit BMI decrease was similar among the 5 CpGs in both the sample sets , cg15473329 (SAMD4B), cg18257485 (NOP14), and cg15690696 (ARHGEF12) exhibited methylation changes of − 0.63%, − 0.43%, − 0.37% and − 0.47% in the discovery set vs − 1.21%, − 0.51%, − 0.40% and − 0.67% in the replication set, respectively, per unit change in BMI . Due to the small sample size in the replication set, we also compared the effect sizes of association in the discovery and replication sets and observed a significant correlation . Both these top DMRs overlap with sites of histone H3K27 acetylation, which is a marker of active chromatin  were hypomethylated and 72/192 (37.5%) were hypermethylated   has been associated with susceptibility to various pathological conditions , 32 incl02) Fig. A. Our fi02) Fig. B and supFor people with severe obesity, bariatric surgery is becoming one of the most effective clinical interventions to achieve considerable and sustained weight loss together with restoration of metabolic homeostasis and overall health profile , althougIn this study of the clinical and metabolic effects of bariatric surgery in patients with severe obesity (mean BMI ~ 45), we analyzed epigenetic alterations and molecular aging in PBMCs collected before and 6 and 12 months after surgery. The main advantage of our study was that we collected samples at three different time points, minimizing the effects of other confounding variables, and we note that the sample size was limited and the timing of follow up did not take into account long-term effects after surgery, such as potential weight regain after 12 months. Blood was selected as the target tissue, being easily accessible and a useful tool for the performance of longitudinal epigenetic studies to identify obesity-related biomarkers for intervention strategies. Our methylome analysis was performed with Illumina Methylation EPIC arrays that interrogate more than 850,000 CpGs across the genome, with almost double the coverage of previous studies .p-value) weight loss-specific differentially methylated positions (DMPs) across autosomes, preferentially located in the intergenic regions (IGRs). Gradual hypomethylation was observed across the differentially methylated CpGs in association with the restoration of clinical and metabolic health. Many other studies have also reported that methylation level, mostly hypomethylation, at CpG sites changes with BMI value [In the study population, restoration of metabolic health, as indicated by improvement in glycemic control, hypertension, and dyslipidemia, was observed in association with rapid and significant reduction (30% reduction) in body weight, mostly occurring within 6 months after surgery. DNA methylome analysis of PBMCs isolated before and after surgery identified 41  is a well-characterized inflammasome responsible for inflammation and insulin-resistance development , 45 and The calcium-signaling pathway is also associated with the progression of obesity and many other diseases. Calcium ions can impede obesity development by facilitating the differentiation of adipocytes and metabolism to enhance energy consumption , 51. Calhttps://www.genecards.org/).Another open question in the field is whether the weight-loss strategy selected, in particular, energy restriction vs bariatric surgery, has a differential effect on the DNA-methylation profile and which genes are involved. To address this question, we used a small cohort of monozygotic twins who were discordant for BMI as replication for our discovery set of Bonferroni-corrected CpGs. The obese twin lost weight by caloric restriction, and the inclusion of the corresponding healthy lean twin in the analysis nullified the effect of time. In addition to confirming that bariatric surgery has a broader impact on the methylation profile than does a hypocaloric diet , we idenARL4C identified in both the discovery and the replication set deserves a comment. Recent studies show that expression of ARL4C induces proliferation in endometrial cancer cells; expression is significantly decreased after exposure to metformin (the most common anti-diabetic drug), leading to reduced proliferation [ARL4C methylation may be a promising obesity-related epigenetic marker.These findings indicate that specific epigenetic changes occur as early events in response to weight loss, even when the loss does not exceed 10% of the initial body weight . The weight loss-specific significant hypermethylation of feration . Recent feration , 57. OveSMAD6 and PFKFB3, which have pleiotropic functions in the maintenance of tissue homeostasis. Both genes play a role in endothelial and adipose tissue dysfunction in obesity. Several studies indicate that aberrant expression of SMAD6, a negative regulator of TGF-α signaling, affects homeostasis of the cardiovascular system [. The PFKFB3 gene, which encodes a key glycolytic activator, also plays a crucial role in maintaining endothelial function and, when defective, reduces pathological angiogenesis in mice [SMAD6 and PFKFB3 after surgery observed in our study might be the underlying mechanism for the reduction in cardiovascular risk associated with bariatric surgery [In this study, we identified weight loss-specific DMRs associated with bariatric surgery. Pathway enrichment analysis showed modulation of pathways involved in the immune system and in type 1 diabetes. The first two closest DMR genes identified were r system , 59 and r system . The PFK in mice . On the  surgery .PFKB3 in adipose tissue affect both inflammation and insulin sensitivity [In addition, both genes are implicated in adipose tissue dysfunction, which characterizes severe obesity. TGF-α/SMAD6 signaling is implicated in the white adipocyte commitment of mesenchymal stem cells  and levesitivity , 65. AltOur results confirm that bariatric surgery-induced weight loss results in an improvement in clinical and metabolic parameters and leads to epigenetic changes in response to the establishment of a new equilibrium. The changes in methylome pattern and clinical profiles observed after weight loss strongly suggest that epigenetics might play a crucial role in the health improvements observed in our cohort. We also replicated the top targets identified from the discovery set in a small group of BMI-discordant monozygotic twins who followed a hypocaloric diet. Partial overlap of 5 DMPs was observed, suggesting that these particular changes are due to weight loss per se regardless of how it was achieved. Our findings confirm the association between bariatric surgery-induced methylation changes and decelerated epigenetic aging, thus reinforcing the concept that obesity has numerous biological similarities to the normal aging process.Further studies are needed to investigate the role of these epigenetic changes at the functional level to gain insight into a potential physiopathological role in obesity. Our results could aid the identification and monitoring of DNA methylation-based biomarkers of obesity and associated complications for therapeutic and diagnostic usage in the future.2); individuals with hypertension and liver steatosis were also included. Among the exclusion criteria were: patients with type 2 diabetes mellitus or taking hypoglycemic drugs; chronic liver or kidney disease, infections, malignancy, or other acute or chronic systemic or degenerative diseases; or use of glucocorticoids, non-steroidal anti-inflammatory medications, or antibiotics prebiotics, and probiotics in the month before enrollment; any intake of drugs with known major impact on the gastrointestinal tract in the 3 months before enrollment; and pregnant or lactating women. All patients signed informed consent for participation in the study and all relevant information on family and medical history, current drug consumption, dietary, smoking habits, physical activity, and psychological state were recorded by a validated detailed questionnaire. On the surgery day, an interview was carried out for the collection of anamnestic data, and anthropometric  and clinical  parameters were recorded. After surgery, patients received periodic counseling about long-term dietary modifications, focusing on the adaptation of eating behavior to the surgical procedure and the general qualitative aspects of a healthy nutrient-dense diet. Protein intake up to 1.5 g/kg ideal body weight per day and regular physical activity were encouraged and long-term mineral and multivitamin supplementation prescribed as recommended [A discovery cohort of 22 severely obese patients undergoing bariatric surgery, either sleeve gastrectomy 19/22, 86%) or Roux-en-Y gastric bypass (3/22 (4%), was enrolled from February 2017 to March 2019 at the Obesity Center of University Hospital Policlinico Tor Vergata, . All surgical procedures were performed laparoscopically. All patients underwent a comprehensive medical and anthropometric evaluation, as well as a body composition analysis. Blood samples were collected and PBMCs were isolated at baseline  and 6 months (T6) and 12 months (T12) after sleeve gastrectomy and processed. The study design and follow-up procedures are described in Fig. 9/22, 86%ommended . PatientThis study was approved by the ethical committees of Istituto Superiore di Sanità  and of University Hospital Policlinico Tor Vergata (protocol of the study connecting DNA 169/15) and a written informed consent was obtained from all subjects.A cohort of 8 healthy pairs of twins discordant for BMI  underwent a diet regimen or caloric restriction for a weight loss of 10% of the original weight in approximately 6 months. This cohort was used as a replication set and the clinical characteristics are shown in Additional file The Norgen genomic DNA isolation kit  was used to isolate total DNA from PBMC according to the manufacturer's instructions. DNA was quantified using a Qubit 3 Fluorometer with the Qubit dsDNA BR Assay Kit (Thermo Fisher Scientific) according to the manufacturer’s protocol. Around 500 ng of DNA, from each sample, was then processed for bisulfite conversion using the EZ-DNAMethylation Kit (Zymo Research) and hybridized using the Infinium Methylation EPIC Kit  or HM850K as illustrated by the manufacturer , 68. Thep-value (detection p > 0.05), probes associated with single-nucleotide polymorphisms [The HM850K array can interrogate DNA-methylation status of > 850,000 CpG sites at single-base resolution. The raw IDAT files were pre-processed and normalized using the “minfi” Bioconductor package in R programming language with the R-Studio as described previously . We exclorphisms , cross-rorphisms , and proorphisms . After torphisms .p-values obtained using the lmerTest package implemented in R [p-values to account for multiple testing. For replication, we used a more stringent Bonferroni corrected p < 0.05 in the discovery set to select differentially methylated positions (DMP) to be taken forward for replication. The differential methylated regions (DMR) were obtained using the DMRcate package by considering ≥ 2 CpGs within a 500-bp window that were differentially methylated due to weight loss.To examine the effect of weight loss on the DNA methylome in PBMC after bariatric surgery, we used linear mixed models (LMM) with random intercepts and slopes for subjects to study the association between BMI and methylation over time. We used BMI as a proxy for weight to perform regression analysis with DNA methylation. The use of BMI considers the baseline differences in weight due to variation in height of the individuals. To test if the association between BMI and methylation is modified by time, we constructed additional LMM with an interaction term between BMI and time as fixed effects. Since multiple measurements were obtained per participant over time, LMM systematically accounts for within-subject variability while calculating the variation within groups over time. LMMs were constructed using the lme4 package and ted in R . For easp-values for pathway enrichment were adjusted for multiple testing using a false discovery rate (FDR < 5%) to identify significantly enriched Kyoto Encyclopedia of Genes and Genomes pathways.To identify functional pathways affected by weight loss, we performed pathway enrichment analysis using the online resource Enrichr . For thep-values < 0.05 were considered significant. We also used LMM to study the extent of decrease in EAA with time in response to weight loss.DNA methylome predicted age was calculated using the Hannum method as the sum of the beta values multiplied by the respective regression coefficients reported by Hannum et al. . This prAdditional file 1: Figure S1. Manhattan plot for EWAS, p-values of BMI x time interactions. Figure S2. Correlation of effect sizes of the 41 significant CpGs in discovery and replication sets. Figure S3. Genomic localization of the top DMR associated with SMAD6 and PFKFB3 genes.Additional file 2: Table T1. Subject characteristics of replication set. Table T2. List od FDR (p<0.05) corrected DMP. Table T3. DMR list.


We report the discovery of two compounds, TKD150 andTKD152, thatpromote the aggregation of α-synuclein (aSN) using a real-timequaking-induced conversion (RT-QuIC) assay to detect abnormal aSN.By utilizing a Pd-catalyzed C–H arylation of benzoxazole withiodoarenes and implementing a planar conformation to the design, wesuccessfully identified TKD150 and TKD152 as proaggregators for aSN.In comparison to a previously reported proaggregator, PA86, the twoidentified compounds were able to promote aggregation of aSN at twicethe rate. Application of TKD150 and TKD152 to the RT-QuIC assay willshorten the inherent lag time and may allow wider use of this assayin clinical settings for the diagnosis of α-synucleinopathy-relateddiseases. Although the mechanism ofLewy body formation and its pathogenesis remains elusive, it is wellrecognized that abnormal α-synuclein (aSN) such as insolubleaSN aggregates and aSN fibrils are the major components of LB.2 Detection and quantification of abnormal aSNthat is present in a miniscule amount as a biomarker for disease prognosishas attracted attention, and the development of such technology holdspotential for early diagnosis of PD and DLB.5In a world with an aging population,neurodegenerative disorders such as Parkinson’s disease (PD)and dementia with Lewy bodies (DLB) has a prevalence of up to 1% ofthe population for those who are over the age of 60.6 This assay is based on a phenomenon where agitationof aSN facilitates aggregation to form fibrils, which thioflavin Tbinds to and generates a fluorescence signal. The aggregation occursfaster in the presence of abnormal aSN, thus attracting interest forits application as a prognostic tool for synucleopathy-related diseasessuch as PD and DLB.9 Despite the potential utility of this methodology,the inherent lag time (70–140 h) to acquire the results hasbeen a drawback of the RT-QuIC assay.10 The lag phaseis attributed to the slow aggregation of abnormal aSN and requiresa long time to accumulate sufficient fluorescence signal for detection.If the assay could be chemically expedited by using compounds to promotethe aggregation process, the RT-QuIC assay would become more useful,especially in a clinical setting. Although several small moleculeshave been reported to inhibit the aggregation of aSN, a compound thatfunctions as a proaggregator is much rarer. To our knowledge, onlyone report by the Otzen group demonstrated the ability of 2-arylbenzoxazole to promote the aggregation of aSN.11 Inspired by Otzen’s finding, we saw anopportunity to further develop the compound’s ability to promoteaSN aggregation. Herein we report the discovery of two compounds,TKD150 and TKD152, which can promote the aggregation of aSN monomerstwice as fast as PA86.Recently,an application of a real-time quaking-induced conversion(RT-QuIC) assay for the detection of abnormal aSN present in the brainand cerebrospinal fluid of PD and DLB patients has been published1.6 This 12 While this synthesis wouldbe applicable to evaluate and improve the biological activity of thecompound, we sought for a shorter synthetic route as well as avoidingthe use of moisture-sensitive acid chlorides.To carry out a rapid and diversified synthesisof PA86 analogues,we envisioned a C–H arylation strategy to construct the 2-arylbenzoxazole framework 1, bottom20 between benzoxazoles and haloarenes. With a bromo substituent presenton the benzoxazole in PA86 (1), we sought for reactionconditions that suppresses undesired competitive reactions at thebromine atom. We noticed that Miura’s C–H arylationconditions using Pd(OAc)2/PPh3/Cs2CO3 catalysis showed high reactivity for iodoarenes comparedwith bromoarenes.21 With a slight modificationof Miura’s C–H arylation conditions, we succeeded inassembling benzoxazoles with iodoarenes to deliver a variety of 2-arylbenzoxazoles without the loss of the bromine atom (1) and a variety of analogues 2–16 (see the Supporting Information for details).We first investigatedappropriate reaction conditions for the C–Harylationine atom 2A. After1–16 were then assessed for their ability to promote aggregationof themonomeric αSN protein by RT-QuIC assay. Specifically, compounds 1–16 were incubated in the presence ofaSN preformed fibrils (PFF), thioflavin T, and a soluble aSN monomerand agitated for 60 h. Three control runs in the absence of compoundwere performed in parallel for every experiment, which indicated thatpresence of dimethyl sulfoxide (DMSO) had only a marginal effect onPFF-dependent aggregation in comparison to the control without DMSO(see the Supporting Information for details).The compound’s aggregation promoting activity was evaluatedby measuring the t2000 value, the timerequired to reach fluorescence intensity of 2000 arbitrary unit (au),and then expressing it as a ratio by comparing with t2000 value of PA86  to the meta-position (TKD125) improved theaggregation ability. Introduction of an additional methyl substituent(TKD149) did not show any improvement in activity. The effect of thedihydroxy phenyl group was negligible, where a similar aggregationactivity to PA86 was observed for TKD66 and TKD147. With only onehydroxy group present on the right aryl group, TKD129 showed similaraggregation activity as PA86. TKD100, which has a trihydroxy phenylgroup, resulted in significant reduction of aggregation ability. Asimilar compound bearing a trisubstituted phenyl moiety (TKD146) showedweaker aggregation ability than PA86. Surprisingly, an unexpectedimprovement of aggregation ability was realized when the two methylsubstituents were placed at the meta-position (TKD152).Finally, TKD150 bearing a mono substituted alkyl phenol showed comparableaggregation ability with TKD152.We then focusedour attention to alter the substitution patternand number of hydroxy groups present on the phenyl ring. Changingthe position of the hydroxy group from the ortho substituent was crucial.It has been reported that thioflavin T binds to β-sheet motifsand amyloids by achieving a planar conformation to give an intensefluorescence signal that is detected during the RT-QuIC assay.23 We reasoned that the achievement of a planar conformation by themolecule may play a role to interact with aSN monomers or fibrilsto promote its aggregation. To investigate on the planarity of thecompound, the dihedral angle of minimized energy structures of selectedcompounds was determined .26 Furthermore, TKD150 was experimentally verifiedto be void of colloids by conducting a particle size analysis of asample prepared in the same buffer solution used in the RT-QuIC assay as 18.4 and 18.67 μM, respectivelyectively4.30 Howe31 Taken together with the RT-QuIC assay results, the obtainedTEM images corroborates the role of benzoxazole compounds as proaggregatorfor aSN monomer into aSN fibril.Lastly, we confirmed that the addition of proaggregatorcompoundsresulted in aggregation of soluble aSN monomers into aSN fibrils byobtaining transmission electron microscopy (TEM) images. TKD149 andTKD150 were selected based on their varying ability to promote aggregationof the aSN monomer. A sample of the soluble aSN monomer and proaggregatorcompound was shaken in the absence of thioflavin T for 60 h, and thenTEM images of the resulting aggregates were obtained 5. As exportho substituent, presumablyto achieve a planar conformation that is necessary to interact withaSN fibril. Lastly, TEM images of aSN monomer treated with proaggregatorcompounds were obtained to confirm the formation of aSN fibril. Furtherstudies using patient-derived cerebrospinal fluid is in progress toascertain the compound’s value in a clinical setting. Resultsfrom these investigations will be reported in due course.In summary, we have discovered TKD152 and TKD150,which can promotethe aggregation of monomeric aSN into fibril twice as fast as a previouslyknown proaggregator, PA86. The identification of these two compoundswas made possible by employing a Pd-catalyzed C–H arylationreaction, allowing rapid preparation of PA86 analogues. A crucialrequirement for the compound to promote aggregation has been identifiedas the absence of an


L9LS, a potent and safe antimalarial monoclonal antibody, demonstrated 88% protective efficacy against infection in a phase 1 trial in healthy adults. 1 These promising results are the first of many to usher in a potential new era of malaria prevention.L9LS, a potent and safe antimalarial monoclonal antibody, demonstrated 88% protective efficacy against infection in a phase 1 trial in healthy adults. A phase 1 clinical trial of L9LS, a next-generation antimalarial monoclonal antibody (mAb), demonstrated safety and protective efficacy of 88% of against malaria infection as detected by PCR at day 21.Plasmodium falciparum circumsporozoite protein (PfCSP) found on the surface of infecting sporozoites (SPZ) by blocking cleavage and preventing invasion of hepatocytes and subsequent invasion of erythrocytes, the symptom- and disease-inducing phase of human malaria infection. PfCSP has highly conserved domains favoring it for first- and next-generation malaria vaccine development as well as neutralizing mAb therapeutics.In the past 5 years, advancements in mAb therapeutics, particularly for COVID-19 and RSV, have helped accelerate development for malaria prevention. Currently, two mAbs for malaria have undergone phase 1 clinical trial testing for safety and efficacy, one of which has just completed phase 2 testing in Malian adults under natural exposure.PfSPZ Vaccine, an attenuated whole SPZ vaccine. Investigators identified four mAbs with dose-dependent binding and inhibition of SPZ infection and three PfCSP-specific antibodies in vitro from the serum.PfCSP.The first-generation malaria mAbs were isolated from a malaria vaccine trial participant who had high antibody titers following immunization with Sanaria PfCSP showed preferential binding of L9 to minor repeats to the NPNV mofits.PfCSP mAbs from a participant in a CHMI study with high antibody titers against S02, a junctional epitope mimic to isolate CIS43-like mAbs. L9 demonstrated two high-affinity binding events and the highest sterile protection in mice compared to other mAbs, including CIS43. Additionally, L9 demonstrated higher potency with the lowest ED50 and EC50 among all tested mAbs against mosquito bite challenges and three times higher potency than CIS43.in vivo by modifying their Fc domain with leucine and serine amino acid (LS) mutations.,,Subsequent studies to isolate mAbs binding to the junctional epitope of CIS43LS was the first mAb to be administered to healthy malaria-naive adults intravenously and subcutaneously to three dose groups.Wu et al. conducted a similar phase 1 CHMI study with L9LS.,L9LS has the potential to significantly influence the roadmap for adoption of novel malaria mAbs. Safety in adults allows age de-escalation to children who bear the major burden of malaria in sub-Saharan Africa. Phase 2 trials of L9LS in children 5 months to 10 years old are planned in Mali and Kenya in the coming year.PfCSP mechanism of action of mAbs is highly conserved, mass administration of such a highly effective intervention raises the potential concern of creating selection pressure on parasites to evade the mechanism of action. Genomic screening of parasite genetic polymorphisms in study sites should be conducted in parallel.Scaling-up malaria mAb interventions will be a major challenge. Achieving high potency like L9LS will allow for lower volumes to be given with subcutaneous administration across different target populations, improving delivery and potential costs. L9LS or other future prevention mAbs could be potential additional elimination tools if sufficient protection is provided in the second season after a single administration; however, meeting the volume needs would be challenging since elimination requires both child and adult populations to be targeted by prevention tools. Trials conducted in perennial settings with longer follow-up times into the second year will be essential to understanding whether L9LS or other mAbs can achieve such extended protection. While it is hoped anti-L9LS has shown that very potent malaria mAbs can be developed rapidly, yet several unanswered questions need to be addressed before L9LS or future mAbs are implemented successfully in endemic settings. First, deployment strategies and target populations for administration of prevention mAbs alone or alongside other interventions need to be evaluated by national programs and stakeholders. Second, addressing cost of goods and likely cost changes with increased potency and manufacturing improvements will be critical to updating value propositions and investments in mAbs. Finally, however crucial to success, designing phase 2 clinical trials with appropriate endpoints, follow-up times, and trial site selection will be required to better understand the protection that mAbs provide over time. These trials will be essential to informing priority candidate selection, accelerating time to large phase 3 trials, and providing needed data to improve model estimates of potential public health impact for different use-cases and settings. Answers to these questions will inform the World Health Organization’s Preferred Product Characteristics and Target Product Profiles for funders and developers, which are designed to accelerate the candidate selection process and regulatory approval of novel malaria mAbs.