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Intrapartum hypoxia–ischemia leading to neonatal encephalopathy (NE) results in significant neonatal mortality and morbidity worldwide, with > 85% of cases occurring in low- and middle-income countries (LMIC). Therapeutic hypothermia (HT) is currently the only available safe and effective treatment of HIE in high-income countries (HIC); however, it has shown limited safety or efficacy in LMIC. Therefore, other therapies are urgently required. We aimed to compare the treatment effects of putative neuroprotective drug candidates following neonatal hypoxic-ischemic (HI) brain injury in an established P7 rat Vannucci model. We conducted the first multi-drug randomized controlled preclinical screening trial, investigating 25 potential therapeutic agents using a standardized experimental setting in which P7 rat pups were exposed to unilateral HI brain injury. The brains were analysed for unilateral hemispheric brain area loss after 7 days survival. Twenty animal experiments were performed. Eight of the 25 therapeutic agents significantly reduced brain area loss with the strongest treatment effect for Caffeine, Sonic Hedgehog Agonist (SAG) and Allopurinol, followed by Melatonin, Clemastine, ß-Hydroxybutyrate, Omegaven, and Iodide. The probability of efficacy was superior to that of HT for Caffeine, SAG, Allopurinol, Melatonin, Clemastine, ß-hydroxybutyrate, and Omegaven. We provide the results of the first systematic preclinical screening of potential neuroprotective treatments and present alternative single therapies that may be promising treatment options for HT in LMIC.

Lack of end-to-end, multimodal collaborative data analysis platforms are a key gap to fill for the dementia research community. The vast expanse of neurodegenerative disease data available today offers an unprecedented opportunity for deep analysis to provide the types of groundbreaking insights that could significantly impact Alzheimer's and dementia-related outcomes. The Global Research and Imaging Platform (GRIP) is addressing these challenges via its open access, user-friendly secure cloud environment (www.grip-research.org). GRIP aims to improve productivity by freeing time for researchers to focus on their most important work, optimize spending via open access (no licensing fees), and facilitate far-reaching collaborations and larger-scale analyses that lead to faster results. GRIP's five key primary product components - discovery, access requests, data sharing, workspaces, and workflows - are all supported by a modular, underlying infrastructure built to support biomedical imaging research. To date, GRIP has partnered with 11 leading ADRC institutions and additional partners across the U.S. and Europe to develop a set of 17 modular tools that are incorporated into coherent workflows across imaging, digital, and 'omics data. GRIP's partner institutions are organized into six distinct working groups that meet on a regular cadence to actively collaborate across multiple research centers to build cross-compatible workflows and modules. Through co-creating community data analysis tools with best-in-class partners, we are optimizing GRIP for key researcher needs. GRIP's dementia-focused platform offering, scheduled for launch at the start of Q2 2025, is providing over a dozen analysis workflows for neuroimaging, digital voice, and 'omics data in a streamlined, secure cloud environment for individual researchers and large, international consortia alike. GRIP is intended to save money and time for both researchers and funders. More importantly, it is intended to facilitate cutting-edge research that isn't happening now because the infrastructure for it doesn't exist. That research could lead to insights that result in better options for the 50 million people worldwide living with Alzheimer's and related dementias.

Background Limited understanding of biological mechanisms behind the onset and progression of major Neurodegenerative Disorders diseases [Alzheimer's Disease (AD), Parkinsons's Disease (PD), Amyotrophic Lateral Sclerosis (ALS), and Frontotemporal Dementia (FTD)] has been a burden for the discovery of novel biomarkers and treatments. Large, harmonized, patient‐derived datasets will be key in unraveling the complex biology leading to neurodegeneration. The Global Neurodegeneration Proteomics Consortium (GNPC), a public‐private partnership, undertook the legal and technical work to address these challenges and created one of the largest proteomic data sets in the world with ∼300 million unique protein measures from, at inception, 23 partners and nearly 40,000 biosample analyses with an associated 50 clinical data features. Method The GNPC first worked to harmonize 23 individual datasets with heterogeneous clinical and proteomic data. Developing the GNPC's large data set required addressing several barriers to open data and data sharing including legal, technological, and incentive and norms‐based barriers. The complete harmonized dataset was securely provided to consortium members via the Alzheimer's Disease Data Initiative's online platform, the AD Workbench for data refinement and analysis. After one year of embargoed intra‐consortium analysis, the HDS will be made accessible by the broader research community as a shared, global resource (July 2025). Result The first version of the Harmonized Dataset (HDS) includes approximately 40,000 unique proteomic analyses on the SomaScan 5k and/or 7k proteomics array platform, in addition to a smaller subset studied with Olink and mass spectrometry methods. All samples are accompanied by 50 phenotypic indicators including demographic, cognitive data, clinical scores, and disease‐specific genotype. Central hosting of de‐identified and harmonized data occurs within the secure AD Workbench environment, including scalable compute resources for >100 active researchers. Conclusion With over 300,000,000 unique protein measures, the GNPC represents the one of the largest protein biomarker discovery efforts for neurodegenerative diseases—or any specific disease area—to date. Results of preliminary analyses from the consortium's distinct workstreams (cross‐sectional profiling, longitudinal profiling, proteogenomic mapping, multivariate prediction & modeling) will be summarized, including diagnostic and predictive proteomic biomarker signatures for pan‐neurodegeneration and disease‐specific states.

Limited understanding of biological mechanisms behind the onset and progression of major Neurodegenerative Disorders diseases [Alzheimer's Disease (AD), Parkinsons's Disease (PD), Amyotrophic Lateral Sclerosis (ALS), and Frontotemporal Dementia (FTD)] has been a burden for the discovery of novel biomarkers and treatments. Large, harmonized, patient-derived datasets will be key in unraveling the complex biology leading to neurodegeneration. The Global Neurodegeneration Proteomics Consortium (GNPC), a public-private partnership, undertook the legal and technical work to address these challenges and created one of the largest proteomic data sets in the world with ∼300 million unique protein measures from, at inception, 23 partners and nearly 40,000 biosample analyses with an associated 50 clinical data features. The GNPC first worked to harmonize 23 individual datasets with heterogeneous clinical and proteomic data. Developing the GNPC's large data set required addressing several barriers to open data and data sharing including legal, technological, and incentive and norms-based barriers. The complete harmonized dataset was securely provided to consortium members via the Alzheimer's Disease Data Initiative's online platform, the AD Workbench for data refinement and analysis. After one year of embargoed intra-consortium analysis, the HDS will be made accessible by the broader research community as a shared, global resource (July 2025). The first version of the Harmonized Dataset (HDS) includes approximately 40,000 unique proteomic analyses on the SomaScan 5k and/or 7k proteomics array platform, in addition to a smaller subset studied with Olink and mass spectrometry methods. All samples are accompanied by 50 phenotypic indicators including demographic, cognitive data, clinical scores, and disease-specific genotype. Central hosting of de-identified and harmonized data occurs within the secure AD Workbench environment, including scalable compute resources for >100 active researchers. With over 300,000,000 unique protein measures, the GNPC represents the one of the largest protein biomarker discovery efforts for neurodegenerative diseases-or any specific disease area-to date. Results of preliminary analyses from the consortium's distinct workstreams (cross-sectional profiling, longitudinal profiling, proteogenomic mapping, multivariate prediction & modeling) will be summarized, including diagnostic and predictive proteomic biomarker signatures for pan-neurodegeneration and disease-specific states.

Background Lack of end‐to‐end, multimodal collaborative data analysis platforms are a key gap to fill for the dementia research community. The vast expanse of neurodegenerative disease data available today offers an unprecedented opportunity for deep analysis to provide the types of groundbreaking insights that could significantly impact Alzheimer's and dementia‐related outcomes. The Global Research and Imaging Platform (GRIP) is addressing these challenges via its open access, user‐friendly secure cloud environment (www.grip‐research.org). Method GRIP aims to improve productivity by freeing time for researchers to focus on their most important work, optimize spending via open access (no licensing fees), and facilitate far‐reaching collaborations and larger‐scale analyses that lead to faster results. GRIP's five key primary product components – discovery, access requests, data sharing, workspaces, and workflows – are all supported by a modular, underlying infrastructure built to support biomedical imaging research. To date, GRIP has partnered with 11 leading ADRC institutions and additional partners across the U.S. and Europe to develop a set of 17 modular tools that are incorporated into coherent workflows across imaging, digital, and ‘omics data. GRIP's partner institutions are organized into six distinct working groups that meet on a regular cadence to actively collaborate across multiple research centers to build cross‐compatible workflows and modules. Through co‐creating community data analysis tools with best‐in‐class partners, we are optimizing GRIP for key researcher needs. Result GRIP's dementia‐focused platform offering, scheduled for launch at the start of Q2 2025, is providing over a dozen analysis workflows for neuroimaging, digital voice, and ‘omics data in a streamlined, secure cloud environment for individual researchers and large, international consortia alike. Conclusion GRIP is intended to save money and time for both researchers and funders. More importantly, it is intended to facilitate cutting‐edge research that isn’t happening now because the infrastructure for it doesn’t exist. That research could lead to insights that result in better options for the 50 million people worldwide living with Alzheimer's and related dementias.

Chromatin signature of pluripotency To study the changes in chromatin structure that accompany zygotic genome activation and pluripotency during the maternal–zygotic transition (MZT), the genomic locations of histone H3 modifications and RNA polymerase II have been mapped during this transition in zebrafish embryos. H3 lysine 27 trimethylation and H3 lysine 4 trimethylation are only detected after MZT, and evidence is provided that the bivalent chromatin domains in cultured ES cells also exist in embryos. To study the changes in chromatin structure that accompany zygotic genome activation and pluripotency during the maternal–zygotic transition (MZT), the genomic locations of histone H3 modifications and RNA polymerase II have been mapped during this transition in zebrafish embryos. H3 lysine 27 trimethylation and H3 lysine 4 trimethylation are only detected after MZT; evidence is provided that the bivalent chromatin domains found in cultured embryonic stem cells also exist in embryos. After fertilization the embryonic genome is inactive until transcription is initiated during the maternal–zygotic transition 1 , 2 , 3 . This transition coincides with the formation of pluripotent cells, which in mammals can be used to generate embryonic stem cells. To study the changes in chromatin structure that accompany pluripotency and genome activation, we mapped the genomic locations of histone H3 molecules bearing lysine trimethylation modifications before and after the maternal–zygotic transition in zebrafish. Histone H3 lysine 27 trimethylation (H3K27me3), which is repressive, and H3K4me3, which is activating, were not detected before the transition. After genome activation, more than 80% of genes were marked by H3K4me3, including many inactive developmental regulatory genes that were also marked by H3K27me3. Sequential chromatin immunoprecipitation demonstrated that the same promoter regions had both trimethylation marks. Such bivalent chromatin domains also exist in embryonic stem cells and are thought to poise genes for activation while keeping them repressed 4 , 5 , 6 , 7 , 8 . Furthermore, we found many inactive genes that were uniquely marked by H3K4me3. Despite this activating modification, these monovalent genes were neither expressed nor stably bound by RNA polymerase II. Inspection of published data sets revealed similar monovalent domains in embryonic stem cells. Moreover, H3K4me3 marks could form in the absence of both sequence-specific transcriptional activators and stable association of RNA polymerase II, as indicated by the analysis of an inducible transgene. These results indicate that bivalent and monovalent domains might poise embryonic genes for activation and that the chromatin profile associated with pluripotency is established during the maternal–zygotic transition.

BackgroundTransport protein particle (TRAPP) is a multisubunit complex that regulates membrane trafficking through the Golgi apparatus. The clinical phenotype associated with mutations in various TRAPP subunits has allowed elucidation of their functions in specific tissues. The role of some subunits in human disease, however, has not been fully established, and their functions remain uncertain.ObjectiveWe aimed to expand the range of neurodevelopmental disorders associated with mutations in TRAPP subunits by exome sequencing of consanguineous families.MethodsLinkage and homozygosity mapping and candidate gene analysis were used to identify homozygous mutations in families. Patient fibroblasts were used to study splicing defect and zebrafish to model the disease.ResultsWe identified six individuals from three unrelated families with a founder homozygous splice mutation in TRAPPC6B, encoding a core subunit of the complex TRAPP I. Patients manifested a neurodevelopmental disorder characterised by microcephaly, epilepsy and autistic features, and showed splicing defect. Zebrafish trappc6b morphants replicated the human phenotype, displaying decreased head size and neuronal hyperexcitability, leading to a lower seizure threshold.ConclusionThis study provides clinical and functional evidence of the role of TRAPPC6B in brain development and function.

Severe hypoxia is a common cause of major brain, heart, and kidney injury in adults, children, and newborns. However, mild hypoxia can be protective against later, more severe hypoxia exposure via “hypoxic preconditioning,” a phenomenon that is not yet fully understood. Accordingly, we have established and optimized an embryonic zebrafish model to study hypoxic preconditioning. Using a functional genomic approach, we used this zebrafish model to identify and validate five novel hypoxia-protective genes, including irs2, crtc3, and camk2g2, which have been previously implicated in metabolic regulation. These results extend our understanding of the mechanisms of hypoxic preconditioning and affirm the discovery potential of this novel vertebrate hypoxic stress model.

The Global Neurodegeneration Proteomics Consortium (GNPC) is a multifaceted open-data resource of about 250 million protein measurements for biomarker discovery and mechanistic research across several neurodegenerative diseases. By harmonizing large-scale proteomic datasets with clinical data across 23 studies, the GNPC offers an important resource for neurodegenerative disease research and a template for large-scale data sharing in other scientific endeavors.

Background Limited understanding of biological mechanisms behind the onset and progression of Neurodegenerative Disorders has been a burden for the discovery of novel biomarkers and treatments. Large, harmonized, patient‐derived datasets will be key in unraveling the complex biology leading to neurodegeneration. The Global Neurodegeneration Proteomics Consortium (GNPC) is a major biomarker discovery effort to unite and expand the available proteomic data for thousands of patient samples from leading dementia cohorts from around the world and comprises, to our knowledge, the largest discovery proteomics dataset to date. Method The GNPC has brought together over 40,000 samples from over 20 different international cohorts to create and collaborate on a fully anonymized Harmonized Dataset (HDS). The HDS spans multiple neurodegenerative disorders including Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Secure access to GNPC data is facilitated through the Alzheimer’s Disease Data Initiative ‘s online platform, the AD Workbench. De‐identified datasets submitted by each participating cohort were harmonized and further anonymized by professional data vendors. After one year of intra‐consortium analysis, the HDS will be accessible by the broader research community as a shared, global resource. Result The first version of the Harmonized Dataset (HDS) includes over 40,000 unique samples on the SomaScan 5k and/or 7k proteomics array platform. All samples are accompanied by >40 phenotypic indicators including demographic, cognitive data, clinical scores, and disease‐specific genotype. Central hosting of de‐identified and harmonized data within the secure cloud environment provides the necessary data security, access to scalable compute resources, and facilitated collaboration between participants in diverse geographies and regulatory environments. Conclusion With over 300,000,000 unique protein measures, the GNPC represents the largest protein biomarker discovery effort for neurodegenerative diseases to date. Initial research underway is organized via several core workstreams, including cross‐sectional and longitudinal profiling, proteogenomic mapping, multivariate prediction, and combinatorial analysis across a single disease area.