Detection and analysis of complex structural variation in human genomes across populations and in brains of donors with psychiatric disorders.

Complex structural variations (cxSVs) are often overlooked in genome analyses due to detection challenges. We developed ARC-SV, a probabilistic and machine-learning-based method that enables accurate detection and reconstruction of cxSVs from standard datasets. By applying ARC-SV across 4,262 genomes representing all continental populations, we identified cxSVs as a significant source of natural human genetic variation. Rare cxSVs have a propensity to occur in neural genes and loci that underwent rapid human-specific evolution, including those regulating corticogenesis. By performing single-nucleus multiomics in postmortem brains, we discovered cxSVs associated with differential gene expression and chromatin accessibility across various brain regions and cell types. Additionally, cxSVs detected in brains of psychiatric cases are enriched for linkage with psychiatric GWAS risk alleles detected in the same brains. Furthermore, our analysis revealed significantly decreased brain-region- and cell-type-specific expression of cxSV genes, specifically for psychiatric cases, implicating cxSVs in the molecular etiology of major neuropsychiatric disorders.

Presynaptic targeting of botulinum neurotoxin type A requires a tripartite PSG-Syt1-SV2 plasma membrane nanocluster for synaptic vesicle entry.

The unique nerve terminal targeting of botulinum neurotoxin type A (BoNT/A) is due to its capacity to bind two receptors on the neuronal plasma membrane: polysialoganglioside (PSG) and synaptic vesicle glycoprotein 2 (SV2). Whether and how PSGs and SV2 may coordinate other proteins for BoNT/A recruitment and internalization remains unknown. Here, we demonstrate that the targeted endocytosis of BoNT/A into synaptic vesicles (SVs) requires a tripartite surface nanocluster. Live-cell super-resolution imaging and electron microscopy of catalytically inactivated BoNT/A wildtype and receptor-binding-deficient mutants in cultured hippocampal neurons demonstrated that BoNT/A must bind coincidentally to a PSG and SV2 to target synaptic vesicles. We reveal that BoNT/A simultaneously interacts with a preassembled PSG-synaptotagmin-1 (Syt1) complex and SV2 on the neuronal plasma membrane, facilitating Syt1-SV2 nanoclustering that controls endocytic sorting of the toxin into synaptic vesicles. Syt1 CRISPRi knockdown suppressed BoNT/A- and BoNT/E-induced neurointoxication as quantified by SNAP-25 cleavage, suggesting that this tripartite nanocluster may be a unifying entry point for selected botulinum neurotoxins that hijack this for synaptic vesicle targeting.

Unlicensed origin DNA melting by MCV and SV40 polyomavirus LT proteins is independent of ATP-dependent helicase activity.

Cellular eukaryotic replication initiation helicases are first loaded as head-to-head double hexamers on double-stranded (ds) DNA origins and then initiate S-phase DNA melting during licensed (once per cell cycle) replication. Merkel cell polyomavirus (MCV) large T (LT) helicase oncoprotein similarly binds and melts its own 98-bp origin but replicates multiple times in a single cell cycle. To examine the actions of this unlicensed viral helicase, we quantitated multimerization of MCV LT molecules as they assembled on MCV DNA origins using real-time single-molecule microscopy. MCV LT formed highly stable double hexamers having 17-fold longer mean lifetime (τ, >1,500 s) on DNA than single hexamers. Unexpectedly, partial MCV LT assembly without double-hexamer formation was sufficient to melt origin dsDNA as measured by RAD51, RPA70, or S1 nuclease cobinding. DNA melting also occurred with truncated MCV LT proteins lacking the helicase domain, but was lost from a protein without the multimerization domain that could bind only as a monomer to DNA. SV40 polyomavirus LT also multimerized to the MCV origin without forming a functional hexamer but still melted origin DNA. MCV origin melting did not require ATP hydrolysis and occurred for both MCV and SV40 LT proteins using the nonhydrolyzable ATP analog, adenylyl-imidodiphosphate (AMP-PNP). LT double hexamers formed in AMP-PNP, and melted DNA, consistent with direct LT hexamer assembly around single-stranded (ss) DNA without the energy-dependent dsDNA-to-ssDNA melting and remodeling steps used by cellular helicases. These results indicate that LT multimerization rather than helicase activity is required for origin DNA melting during unlicensed virus replication.

An In Vivo High-Resolution Human Brain Atlas of Synaptic Density.

Synapses are fundamental to the function of the central nervous system and are implicated in a number of brain disorders. Despite their pivotal role, a comprehensive imaging resource detailing the distribution of synapses in the human brain has been lacking until now. Here, we employ high-resolution PET neuroimaging in healthy humans (17F/16M) to create a 3D atlas of the synaptic marker Synaptic Vesicle glycoprotein 2A (SV2A). Calibration to absolute density values (pmol/ml) was achieved by leveraging postmortem human brain autoradiography data. The atlas unveils distinctive cortical and subcortical gradients of synapse density that reflect functional topography and hierarchical order from core sensory to higher-order integrative areas-a distribution that diverges from SV2A mRNA patterns. Furthermore, we found a positive association between IQ and SV2A density in several higher-order cortical areas. This new resource will help advance our understanding of brain physiology and the pathogenesis of brain disorders, serving as a pivotal tool for future neuroscience research.

Structural variation discovery in wheat using PacBio high-fidelity sequencing.

Structural variations (SVs) pervade plant genomes and contribute substantially to the phenotypic diversity. However, most SVs were ineffectively assayed due to their complex nature and the limitations of early genomic technologies. By applying the PacBio high-fidelity (HiFi) sequencing for wheat genomes, we performed a comprehensive evaluation of mainstream long-read aligners and SV callers in SV detection. The results indicated that the accuracy of deletion discovery is markedly influenced by callers, accounting for 87.73% of the variance, whereas both aligners (38.25%) and callers (49.32%) contributed substantially to the accuracy variance for insertions. Among the aligners, Winnowmap2 and NGMLR excelled in detecting deletions and insertions, respectively. For SV callers, SVIM achieved the best performance. We demonstrated that combining the aligners and callers mentioned above is optimal for SV detection. Furthermore, we evaluated the effect of sequencing depth on the accuracy of SV detection, revealing that low-coverage HiFi sequencing is sufficiently robust for high-quality SV discovery. This study thoroughly evaluated SV discovery approaches and established optimal workflows for investigating structural variations using low-coverage HiFi sequencing in the wheat genome, which will advance SV discovery and decipher the biological functions of SVs in wheat and many other plants.

Variant Impact Predictor database (VIPdb), version 2: trends from three decades of genetic variant impact predictors.

BACKGROUND: Variant interpretation is essential for identifying patients' disease-causing genetic variants amongst the millions detected in their genomes. Hundreds of Variant Impact Predictors (VIPs), also known as Variant Effect Predictors (VEPs), have been developed for this purpose, with a variety of methodologies and goals. To facilitate the exploration of available VIP options, we have created the Variant Impact Predictor database (VIPdb). RESULTS: The Variant Impact Predictor database (VIPdb) version 2 presents a collection of VIPs developed over the past three decades, summarizing their characteristics, ClinGen calibrated scores, CAGI assessment results, publication details, access information, and citation patterns. We previously summarized 217 VIPs and their features in VIPdb in 2019. Building upon this foundation, we identified and categorized an additional 190 VIPs, resulting in a total of 407 VIPs in VIPdb version 2. The majority of the VIPs have the capacity to predict the impacts of single nucleotide variants and nonsynonymous variants. More VIPs tailored to predict the impacts of insertions and deletions have been developed since the 2010s. In contrast, relatively few VIPs are dedicated to the prediction of splicing, structural, synonymous, and regulatory variants. The increasing rate of citations to VIPs reflects the ongoing growth in their use, and the evolving trends in citations reveal development in the field and individual methods. CONCLUSIONS: VIPdb version 2 summarizes 407 VIPs and their features, potentially facilitating VIP exploration for various variant interpretation applications. VIPdb is available at  https://genomeinterpretation.org/vipdb.

Identification of Ppy-lineage cells as a novel origin of pancreatic ductal adenocarcinoma.

The Ppy gene encodes pancreatic polypeptide (PP) secreted by PP- or γ-cells, which are a subtype of endocrine cells localised mainly in the islet periphery. For a detailed characterisation of PP cells, we aimed to establish PP cell lines. To this end, we generated a mouse model harbouring the SV40 large T antigen (TAg) in the Rosa26 locus, which is expressed upon Ppy-promoter-mediated Cre-loxP recombination. Whereas Insulin1-CreERT-mediated TAg expression in beta cells resulted in insulinoma, surprisingly, Ppy-Cre-mediated TAg expression resulted in the malignant transformation of Ppy-lineage cells. These mice showed distorted islet structural integrity at 5 days of age compared with normal islets. CK19+ duct-like lesions contiguous with the islets were observed at 2 weeks of age, and mice developed aggressive pancreatic ductal adenocarcinoma (PDAC) at 4 weeks of age, suggesting that PDAC can originate from the islet/endocrine pancreas. This was unexpected as PDAC is believed to originate from the exocrine pancreas. RNA-sequencing analysis of Ppy-lineage islet cells from 7-day-old TAg+ mice showed a downregulation and an upregulation of endocrine and exocrine genes, respectively, in addition to the upregulation of genes and pathways associated with PDAC. These results suggest that the expression of an oncogene in Ppy-lineage cells induces a switch from endocrine cell fate to PDAC. Our findings demonstrate that Ppy-lineage cells may be an origin of PDAC and may provide novel insights into the pathogenesis of pancreatic cancer, as well as possible therapeutic strategies. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

SV40 T-antigen uses a DNA shearing mechanism to initiate origin unwinding.

Duplication of DNA genomes requires unwinding of the double-strand (ds) DNA so that each single strand (ss) can be copied by a DNA polymerase. The genomes of eukaryotic cells are unwound by two ring-shaped hexameric helicases that initially encircle dsDNA but transition to ssDNA for function as replicative helicases. How the duplex is initially unwound, and the role of the two helicases in this process, is poorly understood. We recently described an initiation mechanism for eukaryotes in which the two helicases are directed inward toward one another and shear the duplex open by pulling on opposite strands of the duplex while encircling dsDNA [L. D. Langston, M. E. O'Donnell, eLife 8, e46515 (2019)]. Two head-to-head T-Antigen helicases are long known to be loaded at the SV40 origin. We show here that T-Antigen tracks head (N-tier) first on ssDNA, opposite the direction proposed for decades. We also find that SV40 T-Antigen tracks directionally while encircling dsDNA and mainly tracks on one strand of the duplex in the same orientation as during ssDNA translocation. Further, two inward directed T-Antigen helicases on dsDNA are able to melt a 150-bp duplex. These findings explain the "rabbit ear" DNA loops observed at the SV40 origin by electron microscopy and reconfigure how the DNA loops emerge from the double hexamer relative to earlier models. Thus, the mechanism of DNA shearing by two opposing helicases is conserved in a eukaryotic viral helicase and may be widely used to initiate origin unwinding of dsDNA genomes.

Hypoxia regulate developmental coronary angiogenesis potentially through VEGF-R2- and SOX17-mediated signaling.

BACKGROUND: The development of coronary vessels in embryonic mouse heart involves various progenitor populations, including sinus venosus (SV), endocardium, and proepicardium. ELA/APJ signaling is known to regulate coronary growth from the SV, whereas VEGF-A/VEGF-R2 signaling controls growth from the endocardium. Previous studies suggest hypoxia might regulate coronary growth, but its specific downstream pathways are unclear. In this study, we further investigated the role of hypoxia and have identified SOX17- and VEGF-R2-mediated signaling as the potential downstream pathways in its regulation of developmental coronary angiogenesis. RESULTS: HIF-1α stabilization by knocking out von Hippel Lindau (VHL) protein in the myocardium (cKO) disrupted normal coronary angiogenesis in embryonic mouse hearts, resembling patterns of accelerated coronary growth. VEGF-R2 expression was increased in coronary endothelial cells under hypoxia in vitro and in VHL cKO hearts in vivo. Similarly, SOX17 expression was increased in the VHL cKO hearts, while its knockout in the endocardium disrupted normal coronary growth. CONCLUSION: These findings provide further evidence that hypoxia regulates developmental coronary growth potentially through VEGF-R2 and SOX17 pathways, shedding light on mechanisms of coronary vessel development.

ProcaryaSV: structural variation detection pipeline for bacterial genomes using short-read sequencing.

BACKGROUND: Structural variations play an important role in bacterial genomes. They can mediate genome adaptation quickly in response to the external environment and thus can also play a role in antibiotic resistance. The detection of structural variations in bacteria is challenging, and the recognition of even small rearrangements can be important. Even though most detection tools are aimed at and benchmarked on eukaryotic genomes, they can also be used on prokaryotic genomes. The key features of detection are the ability to detect small rearrangements and support haploid genomes. Because of the limiting performance of a single detection tool, combining the detection abilities of multiple tools can lead to more robust results. There are already available workflows for structural variation detection for long-reads technologies and for the detection of single-nucleotide variation and indels, both aimed at bacteria. Yet we are unaware of structural variations detection workflows for the short-reads sequencing platform. Motivated by this gap we created our workflow. Further, we were interested in increasing the detection performance and providing more robust results. RESULTS: We developed an open-source bioinformatics pipeline, ProcaryaSV, for the detection of structural variations in bacterial isolates from paired-end short sequencing reads. Multiple tools, starting with quality control and trimming of sequencing data, alignment to the reference genome, and multiple structural variation detection tools, are integrated. All the partial results are then processed and merged with an in-house merging algorithm. Compared with a single detection approach, ProcaryaSV has improved detection performance and is a reproducible easy-to-use tool. CONCLUSIONS: The ProcaryaSV pipeline provides an integrative approach to structural variation detection from paired-end next-generation sequencing of bacterial samples. It can be easily installed and used on Linux machines. It is publicly available on GitHub at https://github.com/robinjugas/ProcaryaSV .

Systematic evaluation of multiple NGS platforms for structural variants detection.

Structural variations (SV) are critical genome changes affecting human diseases. Although many hybridization-based methods exist, evaluating SVs through next-generation sequencing (NGS) data is still necessary for broader research exploration. Here, we comprehensively compared the performance of 16 SV callers and multiple NGS platforms using NA12878 whole genome sequencing (WGS) datasets. The results indicated that several SV callers performed well relatively, such as Manta, GRIDSS, LUMPY, TARDIS, FermiKit, and Wham. Meanwhile, all NGS platforms have a similar performance using a single software. Additionally, we found that the source of undetected SVs was mostly from long reads datasets, therefore, the more appropriate strategy for accurate SV detection will be an integration of long and shorter reads in the future. At present, in the period of NGS as a mainstream method in bioinformatics, our study would provide helpful and comprehensive guidelines for specific categories of SV research.

High-resolution sequencing of nine elite upland cotton cultivars uncovers genic variations and breeding improvement targets.

Structural variations (SVs) are critical factors affecting genome evolution and important traits. However, identification results and functional analyses of SVs in upland cotton are rare. Here, based on the genetic relationships, breeding history and cumulative planting area of upland cotton in China, nine predominant cultivars from the past 60 years (1950s-2010s) were selected for long read sequencing to uncover genic variations and breeding improvement targets for this crop. Based on the ZM24 reference genome, 0.88-1.47 × 104 SVs per cultivar were identified, and an SV set was constructed. SVs affected the expression of a large number of genes during fiber elongation, and a transposable element insertion resulted in the glandless phenotype in upland cotton. Six widespread inversions were identified based on nine draft genomes and high-throughput chromosome conformation capture data. Multiple haplotype blocks that were always associated with aggregated SVs were demonstrated to play a pivotal role in the agronomic traits of upland cotton and drove its adaptation to the northern planting region. Exotic introgression was the source of these haplotype blocks and increased the genetic diversity of upland cotton. Our results enrich the genome resources of upland cotton, and the identified SVs will promote genetic and breeding research in cotton.

HiFi long-read amplicon sequencing for full-spectrum variants of human mtDNA.

BACKGROUND: Mitochondrial diseases (MDs) can be caused by single nucleotide variants (SNVs) and structural variants (SVs) in the mitochondrial genome (mtDNA). Presently, identifying deletions in small to medium-sized fragments and accurately detecting low-percentage variants remains challenging due to the limitations of next-generation sequencing (NGS). METHODS: In this study, we integrated targeted long-range polymerase chain reaction (LR-PCR) and PacBio HiFi sequencing to analyze 34 participants, including 28 patients and 6 controls. Of these, 17 samples were subjected to both targeted LR-PCR and to compare the mtDNA variant detection efficacy. RESULTS: Among the 28 patients tested by long-read sequencing (LRS), 2 patients were found positive for the m.3243 A > G hotspot variant, and 20 patients exhibited single or multiple deletion variants with a proportion exceeding 4%. Comparison between the results of LRS and NGS revealed that both methods exhibited similar efficacy in detecting SNVs exceeding 5%. However, LRS outperformed NGS in detecting SNVs with a ratio below 5%. As for SVs, LRS identified single or multiple deletions in 13 out of 17 cases, whereas NGS only detected single deletions in 8 cases. Furthermore, deletions identified by LRS were validated by Sanger sequencing and quantified in single muscle fibers using real-time PCR. Notably, LRS also effectively and accurately identified secondary mtDNA deletions in idiopathic inflammatory myopathies (IIMs). CONCLUSIONS: LRS outperforms NGS in detecting various types of SNVs and SVs in mtDNA, including those with low frequencies. Our research is a significant advancement in medical comprehension and will provide profound insights into genetics.

Factors contributing to organelle genomes size variation and the intracellular DNA transfer in Polygonaceae.

The use of complete organelle genomes, including chloroplast and mitochondrial genomes, is a powerful molecular method for studying biological evolution and gene transfer. However, in the case of Polygonaceae, an important family with numerous edible, medicinal, and ornamental species, the mitochondrial genomes of only three species have been sequenced and analyzed. In this study, we present the mitochondrial and chloroplast genomes of two important Tibetan medicinal plants, Bistorta viviparum and B. macrophyllum. All the organelle genomes are assembled into a single circular structure and contain a common set of 32 protein-coding genes (PCGs). Some genes such as rps2 and ndhF were found to have high nucleotide polymorphism (Pi) in the chloroplast genomes, while cox1, mttB and rps12 showed pronounced Pi values in the mitochondrial genomes. Furthermore, our analysis revealed that most chloroplast genes and mitochondrial PCGs in Polygonaceae plants are under purifying selection. However, a few genes, including the chloroplast gene psaJ and the mitochondrial genes ccmFc, atp8 and nad4, showed positive selection in certain Polygonaceae plants, as indicated by a Ka/Ks ratio greater than one. Structural variation analysis revealed a wealth of differences between the mitochondrial genomes of five Polygonaceae species, with a particularly notable large-scale inversion observed between Reynoutria japonica and Fallopia aubertii. Furthermore, an analysis of the homologous sequences in the chloroplast and mitochondrial genomes revealed that the rps7 has been transferred from the chloroplast to the mitochondrial genome in all five Polygonaceae species. Finally, ecological niche models were constructed for B. viviparum and B. macrophyllum, indicating that mean annual temperature and altitude are the main climatic factors influencing the distribution of both species. Although the current distribution of B. viviparum is significantly wider than that of B. macrophyllum, projections suggest that the optimal growth ranges of both species will expand in the future, with B. macrophyllum potentially exceeding B. viviparum. This study not only contributes to the plastid genome database for Polygonaceae plants, but also provides theoretical insights into the adaptive evolution of these plants.

Comprehensive evaluation and guidance of structural variation detection tools in chicken whole genome sequence data.

BACKGROUND: Structural variations (SVs) are widespread across genome and have a great impact on evolution, disease, and phenotypic diversity. Despite the development of numerous bioinformatic tools, commonly referred to as SV callers, tailored for detecting SVs using whole genome sequence (WGS) data and employing diverse algorithms, their performance necessitates rigorous evaluation with real data and validated SVs. Moreover, a considerable proportion of these tools have been primarily designed and optimized using human genome data. Consequently, their applicability and performance in Avian species, characterized by smaller genomes and distinct genomic architectures, remain inadequately assessed. RESULTS: We performed a comprehensive assessment of the performance of ten widely used SV callers using population-level real genomic data with the validated five common types of SVs. The performance of SV callers varies with the types and sizes of SVs. As compared with other tools, GRIDSS, Lumpy, Wham, and Manta present better detection accuracy. Pindel can detect more small SVs than others. CNVnator and CNVkit can detect more medium and large copy number variations. Given the poor consistency among different SV callers, the combination calling strategy is not recommended. All tools show poor ability in the detection of insertions (especially with size > 150 bp). At least 50× read depth is required to detect more than 80% of the SVs for most tools. CONCLUSIONS: This study highlights the importance and necessity of using real sequencing data, rather than simulated data only, with validated SVs for SV caller evaluation. Some practical guidance and suggestions are provided for SV detection in future researches.

SV2A controls the surface nanoclustering and endocytic recruitment of Syt1 during synaptic vesicle recycling.

Following exocytosis, the recapture of plasma membrane-stranded vesicular proteins into recycling synaptic vesicles (SVs) is essential for sustaining neurotransmission. Surface clustering of vesicular proteins has been proposed to act as a 'pre-assembly' mechanism for endocytosis that ensures high-fidelity retrieval of SV cargo. Here, we used single-molecule imaging to examine the nanoclustering of synaptotagmin-1 (Syt1) and synaptic vesicle protein 2A (SV2A) in hippocampal neurons. Syt1 forms surface nanoclusters through the interaction of its C2B domain with SV2A, which are sensitive to mutations in this domain (Syt1K326A/K328A) and SV2A knockdown. SV2A co-clustering with Syt1 is reduced by blocking SV2A's cognate interaction with Syt1 (SV2AT84A). Surprisingly, impairing SV2A-Syt1 nanoclustering enhanced the plasma membrane recruitment of key endocytic protein dynamin-1, causing accelerated Syt1 endocytosis, altered intracellular sorting and decreased trafficking of Syt1 to Rab5-positive endocytic compartments. Therefore, SV2A and Syt1 are segregated from the endocytic machinery in surface nanoclusters, limiting dynamin recruitment and negatively regulating Syt1 entry into recycling SVs.

Synaptic vesicle glycoprotein 2C enhances vesicular storage of dopamine and counters dopaminergic toxicity.

Dopaminergic neurons of the substantia nigra exist in a persistent state of vulnerability resulting from high baseline oxidative stress, high-energy demand, and broad unmyelinated axonal arborisations. Impairments in the storage of dopamine compound this stress because of cytosolic reactions that transform the vital neurotransmitter into an endogenous neurotoxicant, and this toxicity is thought to contribute to the dopamine neuron degeneration that occurs Parkinson's disease. We have previously identified synaptic vesicle glycoprotein 2C (SV2C) as a modifier of vesicular dopamine function, demonstrating that genetic ablation of SV2C in mice results in decreased dopamine content and evoked dopamine release in the striatum. Here, we adapted a previously published in vitro assay utilising false fluorescent neurotransmitter 206 (FFN206) to visualise how SV2C regulates vesicular dopamine dynamics and determined that SV2C promotes the uptake and retention of FFN206 within vesicles. In addition, we present data indicating that SV2C enhances the retention of dopamine in the vesicular compartment with radiolabelled dopamine in vesicles isolated from immortalised cells and from mouse brain. Further, we demonstrate that SV2C enhances the ability of vesicles to store the neurotoxicant 1-methyl-4-phenylpyridinium (MPP+) and that genetic ablation of SV2C results in enhanced 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced vulnerability in mice. Together, these findings suggest that SV2C functions to enhance vesicular storage of dopamine and neurotoxicants and helps maintain the integrity of dopaminergic neurons.

PET imaging of synaptic density in Parkinsonian disorders.

Synaptic dysfunction and altered synaptic pruning are present in people with Parkinsonian disorders. Dopamine loss and alpha-synuclein accumulation, two hallmarks of Parkinson's disease (PD) pathology, contribute to synaptic dysfunction and reduced synaptic density in PD. Atypical Parkinsonian disorders are likely to have unique spatiotemporal patterns of synaptic density, differentiating them from PD. Therefore, quantification of synaptic density has the potential to support diagnoses, monitor disease progression, and treatment efficacy. Novel radiotracers for positron emission tomography which target the presynaptic vesicle protein SV2A have been developed to quantify presynaptic density. The radiotracers have successfully investigated synaptic density in preclinical models of PD and people with Parkinsonian disorders. Therefore, this review will summarize the preclinical and clinical utilization of SV2A radiotracers in people with Parkinsonian disorders. We will evaluate how SV2A abundance is associated with other imaging modalities and the considerations for interpreting SV2A in Parkinsonian pathology.

Comprehensive mapping of synaptic vesicle protein 2A (SV2A) in health and neurodegenerative diseases: a comparative analysis with synaptophysin and ground truth for PET-imaging interpretation.

Synaptic dysfunction and loss are central to neurodegenerative diseases and correlate with cognitive decline. Synaptic Vesicle Protein 2A (SV2A) is a promising PET-imaging target for assessing synaptic density in vivo, but comprehensive mapping in the human brain is needed to validate its biomarker potential. This study used quantitative immunohistochemistry and Western blotting to map SV2A and synaptophysin (SYP) densities across six cortical regions in healthy controls and patients with early-onset Alzheimer's disease (EOAD), late-onset Alzheimer's disease (LOAD), progressive supranuclear palsy (PSP), and frontotemporal lobar degeneration with TDP-43 inclusions (FTLD-GRN). We identified region in SV2A density among controls and observed disease- and region-specific reductions, with the most severe in FTLD-GRN (up to 59.5%) and EOAD. EOAD showed a 49% reduction in the middle frontal gyrus (MFG), while LOAD had over 30% declines in the inferior frontal gyrus (IFG) and hippocampus (CA1). In PSP, smaller but significant reductions were noted in the hippocampal formation, with the inferior temporal gyrus (ITG) relatively unaffected. A strong positive correlation between SV2A and SYP densities confirmed SV2A's reliability as a synaptic integrity marker. This study supports the use of SV2A PET imaging for early diagnosis and monitoring of neurodegenerative diseases, providing essential data for interpreting in vivo PET results. Further research should explore SV2A as a therapeutic target and validate these findings in larger, longitudinal studies.

The regional pattern of age-related synaptic loss in the human brain differs from gray matter volume loss: in vivo PET measurement with [11C]UCB-J.

PURPOSE: Aging is a major societal concern due to age-related functional losses. Synapses are crucial components of neural circuits, and synaptic density could be a sensitive biomarker to evaluate brain function. [11C]UCB-J is a positron emission tomography (PET) ligand targeting synaptic vesicle glycoprotein 2A (SV2A), which can be used to evaluate brain synaptic density in vivo. METHODS: We evaluated age-related changes in gray matter synaptic density, volume, and blood flow using [11C]UCB-J PET and magnetic resonance imaging (MRI) in a wide age range of 80 cognitive normal subjects (21-83 years old). Partial volume correction was applied to the PET data. RESULTS: Significant age-related decreases were found in 13, two, and nine brain regions for volume, synaptic density, and blood flow, respectively. The prefrontal cortex showed the largest volume decline (4.9% reduction per decade: RPD), while the synaptic density loss was largest in the caudate (3.6% RPD) and medial occipital cortex (3.4% RPD). The reductions in caudate are consistent with previous SV2A PET studies and likely reflect that caudate is the site of nerve terminals for multiple major tracts that undergo substantial age-related neurodegeneration. There was a non-significant negative relationship between volume and synaptic density reductions in 16 gray matter regions. CONCLUSION: MRI and [11]C-UCB-J PET showed age-related decreases of gray matter volume, synaptic density, and blood flow; however, the regional patterns of the reductions in volume and SV2A binding were different. Those patterns suggest that MR-based measures of GM volume may not be directly representative of synaptic density.