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Goldstein, D.

Publications and source records attributed to Goldstein, D..

16 recordsLinked to original sources

Longitudinal persistence of EEG brain fingerprints:phase and complex coherency geometry across sessions andfunctional states

EEG connectivity can distinguish individuals, but the persistence of its phase and magnitude structure across visits and functional states remains incompletely understood. We examined two geometric representations of complex coherency: unit phasors and full complex coherency, alongside triangle holonomies and magnitude-only descriptors. Using direct enrollment-probe matching without a trained identity classifier, we analyzed three independent longitudinal cohorts: RestCog (N = 60; approximately one month), L-FAME (N = 44; six weeks), and Dortmund (N = 206; approximately five years). In eyes-closed rest-to-rest matching, alpha phasors identified 81.67% of participants in RestCog (AUC 0.9473) and 79.55% in L-FAME (AUC 0.9735); full complex coherency identified 78.33% and 84.09%, respectively. After five years in Dortmund, fixed row-standardized alpha-beta fusion yielded 77.67% rank-1 identification (AUC 0.9744) for phasors and 70.39% (AUC 0.9527) for full coherency. Changes in functional state exposed different strengths: full coherency preserved higher rank-1 accuracy in some monthly RestCog rest-to-task comparisons, whereas alpha phasors retained higher verification AUC. Switching between eyes-closed and eyes-open recordings in Dortmund substantially weakened identification with both representations. Triangle holonomies also retained individual information across visits. An exact factorization of complex cosine shows how magnitude-pattern alignment and magnitude-weighted phase agreement contribute to full-coherency matching. Together, the results reveal persistent individual structure in both phase and complex coherency over weeks to years, while distinguishing temporal persistence from robustness across functional states.

neuroscience↗

Polar Geometry of Time-Odd EEG Dynamics

Abstract Objective. Longitudinal EEG recordings vary across sessions because of electrode reapplication, referencing, recording conditions, and physiological state. We asked whether multichannel EEG contains a time-odd geometric structure that remains subject-discriminative across repeated recordings and extended inter-session intervals. Approach. We constructed a local state-derivative operator T_ij = corr(m_i, Delta x_j) and isolated its exact skew component, K = 1/2(T - T^T). Polar decomposition, K = Q_K M_K, separated interaction magnitude from normalized orientation. We applied the same decomposition to signed imaginary coherency, Omega = Im(G), providing a frequency-domain test based on a separate estimation procedure. We evaluated cross-session subject matching in four public longitudinal EEG datasets, including the Dortmund cohort of 206 participants with recordings separated by approximately five years. Alpha-beta fusion used fixed equal weights without calibration or learned weighting. Main results. The empirical operator T was already strongly dominated by its skew component, indicating that K isolates rather than creates the observed time-odd structure. Polar orientation improved longitudinal discriminability for K to Q_K in every principal comparison. For the approximately one-month RestCog interval, area under the receiver-operating-characteristic curve (AUC) increased from 0.9222 to 0.9597 and rank-1 identification (CMC@1) from 0.6333 to 0.8167. In Dortmund, AUC increased from 0.8901 to 0.9625 and CMC@1 from 0.4757 to 0.6214. Fixed alpha-beta fusion further increased Dortmund Q_K performance to CMC@1 = 0.8350, AUC = 0.9855, and equal-error rate (EER) = 5.90%. The spectral operator reproduced the raw-to-polar AUC advantage for Omega to Q_Omega in both alpha and beta across all four datasets. Matched-metric controls preserved the polar AUC advantage in all 40 raw-to-polar comparisons. Significance. Across two mathematically linked skew EEG operators obtained using different estimation procedures, removing interaction-magnitude weighting while retaining normalized orientation improved cross-session discriminability. The gain reflects improved genuine-impostor geometry rather than necessarily greater absolute similarity between repeated recordings. Polar orientation provides a compact longitudinal descriptor requiring no performance-tuned internal parameter once preprocessing, temporal support, and frequency band are fixed.

neuroscience↗

Spectral Geometry of Infant Resting-State fNIRS Connectivity: Bilingual vs Monolingual

Functional-connectivity matrices mix pairwise association strength, spectral weighting, and eigenspace orientation, making it difficult to determine which components carry stable information about network organization. We develop a spectral-geometric framework that uses rank-k orthogonal projector matrices as subject-level representations of functional operators. The projector preserves eigenspace orientation in measurement coordinates while removing relative eigen-value weighting. We further compare two noncommuting temporal constructions--projecting a temporally integrated operator and averaging projectors estimated from local operators-- and examine how the resulting representations depend on temporal scale and retained rank. We demonstrate the framework in resting-state fNIRS recordings from 99 four-month-old infants exposed to monolingual or bilingual language environments. Pearson correlation favored temporal integration before projection and exhibited a localized intermediate-rank regime at shorter scales, whereas multitaper coherence favored projection before integration and showed a broader regime at longer scales. Reverse engineering of the Pearson representation showed that the intermediate-rank regime was carried primarily by angular relations among channel embeddings, whereas a secondary near-full-rank regime corresponded to a distinct bottom-of-spectrum channel-occupancy carrier. A fully nested two-rank analysis repeatedly retained both regimes. These results show that temporally integrated functional-network organization depends jointly on operator definition, temporal support, projection order, and retained rank. The framework provides an interpretable way to separate complementary spectral carriers of network structure, with group labels used only for cross-fitted validation rather than for representation construction. Key PointsO_LIRank-k spectral projectors provide an interpretable, basis-invariant representation of functional-network eigenspace geometry in the original measurement coordinates. C_LIO_LITemporal integration and spectral projection are noncommuting operations, and their relative informativeness depends on the functional operator and temporal scale. C_LIO_LIDistinct retained-rank regimes reveal complementary geometric carriers of functional-network organization, including relational dominant-subspace structure and bottom-of-spectrum channel occupancy. C_LI

neuroscience↗

Asymmetric increase in episodic and procedural memory interference in older adults

In younger adults, newly formed procedural memories are weakened by the subsequent formation of episodic memories (E[->]P interference) and vice versa (P[->]E interference; "cross-memory interference"). Older adults experience significant decline in episodic memory but maintain relatively intact procedural memory. This asymmetric decline in memory may also cause an asymmetric change in cross-memory interference compared to younger adults. For example, older adults may experience a significant increase in one type of cross-memory interference while leaving the other unchanged. Additionally, decline in episodic memory may cause E[->]P interference to either increase or decrease depending on how the episodic and procedural memory systems interact. However, no study to our knowledge has compared cross-memory interference between younger and older adults. We investigated cross-memory interference in younger and older adults by measuring E[->]P (Exp. 1) and P[->]E (Exp. 2) interference in 40 younger (18-40 years old) and 40 older ([≥] 55 years old) adults. Compared to younger adults, the results show that older adults experience significantly stronger E[->]P interference while P[->]E interference was statistically indistinguishable between groups. These results confirm that older adults experience an asymmetric increase in cross-memory interference and suggest that the increase in E[->]P interference is related to the asymmetric decline in episodic memory relative to procedural memory.

neuroscience↗

Pan-cancer N-glycoproteomic atlas of patient derived xenografts uncovers FAT2 as a therapeutic target for head and neck cancers

Cell surface proteins offer significant cancer therapeutic potential attributable to their accessible membrane localization and central role in cellular signaling. Despite this, their promise remains largely untapped due to the technical challenges inherent to profiling cell surface proteins. Here, we employed N-glycoproteomics to analyze 85 patient-derived xenografts (PDX), constructing Glyco PDXplorer - an in vivo pan-cancer atlas of cancer-derived cell surface proteins. We developed a target discovery pipeline to prioritize proteins with favorable expression profiles for immunotherapeutic targeting and validated FAT2 as a head and neck squamous cancer (HNSC) enriched surface protein with limited expression in normal tissue. Functional studies revealed that FAT2 is essential for HNSC growth and adhesion through regulation of surface architecture and integrin-PI3K signaling. Chimeric antigen receptor (CAR) T cells targeting FAT2 demonstrated potent anti-tumor activity in HNSC models. This work lays the foundation for developing FAT2-targeted therapies and represents a pivotal resource to inform therapeutic target discovery for multiple cancers. HIGHLIGHTSO_LIPan-cancer landscape of cancer-derived cell surface proteins detected in vivo C_LIO_LIDevelopment of a multi-omic discovery pipeline to prioritize proteins with optimal expression profiles as immunotherapy targets C_LIO_LIIdentification and validation of FAT2 as a head and neck squamous cancer enriched surface protein with minimal expression in normal tissues C_LIO_LIFAT2 coordinates cell surface organization, adhesion, growth and survival through the integrin-PI3K-AKT pathway C_LIO_LIFAT2 CAR T cells demonstrate anti-tumour activity in pre-clinical models C_LI

cancer biology↗

Paradoxical SERCA dysregulation contributes to atrial fibrillation in a model of diet-induced obesity

Obesity is a major risk factor for atrial fibrillation (AF) the most common serious cardiac arrhythmia, but the molecular mechanisms underlying diet-induced AF remain unclear. In this study, we subjected mice to a chronic high-fat diet and acute sympathetic activation ( two-hit model) to study the mechanisms by which diet-induced obesity promotes AF. Surface electrocardiography revealed that diet-induced obesity and sympathetic activation synergize during intracardiac tachypacing to induce AF. At the cellular level, diet-induced obesity and acute adrenergic stimulation facilitate the formation of delayed afterdepolarizations in atrial myocytes, implicating altered Ca2+ dynamics as the underlying cause of AF. We found that diet-induced obesity does not alter the expression of major Ca2+-handling proteins in atria, including the sarcoplasmic reticulum Ca2+-ATPase (SERCA), a major component of beat-to-beat Ca2+ cycling in the heart. Paradoxically, obesity reduces phospholamban phosphorylation, suggesting decreased SERCA activity, yet atrial myocytes from obese mice showed a significantly increased Ca2+ transient amplitude and SERCA-mediated Ca2+ uptake. Adrenergic stimulation further increases the Ca2+ transient amplitude but does not affect Ca2+ reuptake in atrial myocytes from obese mice. Transcriptomics analysis showed that a high-fat diet prompts upregulation of neuronatin, a protein that has been implicated in obesity and is known to stimulate SERCA activity. We propose a mechanism in which obesity primes SERCA for paradoxical activation, and adrenergic stimulation facilitates AF conversion through a Ca2+-induced Ca2+ release gain in atrial myocytes. Overall, this study links obesity, altered Ca2+ signaling, and AF, and targeting this mechanism may prove effective for treating obesity-induced AF.

physiology↗

The landscape of regional missense mutational intolerance quantified from 125,748 exomes

Missense variants can have a range of functional impacts depending on factors such as the specific amino acid substitution and location within the gene. To interpret their deleteriousness, studies have sought to identify regions within genes that are specifically intolerant of missense variation. Here, we leverage the patterns of rare missense variation in 730,947 exome sequenced individuals in the Genome Aggregation Database (gnomAD v4.1.1) against a null mutational model to identify transcripts with regional differences in missense constraint. Missense-depleted regions are enriched for ClinVar pathogenic variants, de novo missense variants from individuals with neurodevelopmental disorders, and complex trait heritability. Following ClinGen calibration recommendations for the ACMG/AMP variant classification guidelines, we establish that variants within regions with <36% of their expected missense variation achieve moderate support for pathogenicity. We integrate this regional constraint measure into a missense deleteriousness metric (named MPC) that effectively stratifies rare and de novo missense variants in individuals with early-onset developmental conditions from controls. These results provide additional tools to aid in missense variant interpretation.

genomics↗

The Scalable Variant Call Representation: Enabling Genetic Analysis Beyond One Million Genomes

The Variant Call Format (VCF) is widely used in genome sequencing but scales poorly. For instance, we estimate a 150,000 genome VCF would occupy 900 TiB, making it both costly and complicated to produce and analyze. The issue stems from VCFs requirement to densely represent both reference-genotypes and allele-indexed arrays. These requirements lead to unnecessary data duplication and, ultimately, very large files. To address these challenges, we introduce the Scalable Variant Call Representation (SVCR). This representation reduces file sizes by ensuring they scale linearly with samples. SVCR achieves this by adopting reference blocks from the Genomic Variant Call Format (GVCF) and employing local allele indices. SVCR is also lossless and mergeable, allowing for N+1 and N+K incremental joint-calling. We present two implementations of SVCR: SVCR-VCF, which encodes SVCR in VCF format, and VDS, which uses Hails native format. Our experiments confirm the linear scalability of SVCR-VCF and VDS, in contrast to the super-linear growth seen with standard VCF files. We also discuss the VDS Combiner, a scalable, open-source tool for producing a VDS from GVCFs and unique features of VDS which enable rapid data analysis. SVCR, and VDS in particular, ensure the scientific community can generate, analyze, and disseminate genetics datasets with millions of samples.

bioinformatics↗

Aberrant Local Synchrony in Distinct Mouse Models of Epileptic Encephalopathy

Identifying and quantifying synchronous activity of primary neuronal networks using multielectrode arrays (MEAs) can potentially provide a medium-throughput platform to screen potential therapeutics for genetic epileptic encephalopathies (EEs). However, successfully identifying screenable synchrony phenotypes in vitro poses significant experimental and analytical challenges. Primary neuronal cultures quickly become highly synchronous and certain measures of synchrony tend to peak and plateau, while other network activity features remain dynamic. High levels of synchrony may confound the ability to identify reproducible phenotypes in vitro for a subset of EEs. Reducing, or delaying the onset of, high levels of synchrony in vitro may increase the dynamic range of global synchrony measures to identify disease-relevant phenotypes in vitro, but such measures have not been established. We hypothesized that an emphasis on local (nearby) connectivity could elucidate reproducible disease-relevant synchrony phenotypes in cortical cultures not identified by current approaches. We show clear evidence of enriched local synchrony in 48-well MEAs that varies in amplitude during development of neuronal networks. Then, we show new topological-based measures are capable of identifying novel phenotypes of aberrant synchrony in distinct mouse models of EEs. Such topological synchrony measures may provide screenable phenotypes for certain brain diseases and may be further enhanced by experimental innovation reducing global levels of synchrony in primary neuronal networks. SignificanceIn vitro synchrony phenotypes may provide disease-relevant features that can be used for screening potential therapeutic candidates for epileptic encephalopathies. Here, we incorporate inter-electrode distance to generate tools capable of identifying novel synchrony phenotypes in distinct neurodevelopmental disorders. We additionally report robust topological and global in vitro synchrony phenotypes, alongside in vivo synchrony phenotypes in Stxbp1+/- mice. While singular features of disease in an in vitro model are unlikely to effectively test therapeutic candidates, compounds that reverse a larger subset of distinct features may translate to human patients, suggesting such a model may be ideally suited for therapeutic development using MEAs. Across multiple disease models, the topological tools developed here are complimentary to and expand upon those within meaRtools (Gelfman 2018), which is a suite of computational tools to identify network phenotypes using MEAs.

neuroscience↗

βIII-Tubulin is a Brake on Extrinsic Cell-Death in Pancreatic Cancer

The microtubule protein, {beta}III-tubulin, has been implicated as a prognostic, pro-survival, and chemoresistance factor in some of the most lethal malignancies including pancreatic ductal adenocarcinoma (PDAC). However, precise survival mechanisms controlled by {beta}III-tubulin in cancer cells are unknown. Here, we report an unexpected role of {beta}III-tubulin as a brake on extrinsic caspase 8-dependent apoptosis in PDAC. We show that {beta}III-tubulin knockdown frees death-receptor DR5 to increase its membrane diffusion, clustering, and activation of cell-death. We demonstrate that {beta}III-ubulin silencing increases sensitivity of PDAC cells to chemotherapeutic and microenvironment-derived extrinsic cell-death signals including TRAIL, TNF, and FasL. Finally, nanoparticle delivery of {beta}III-tubulin siRNA to mouse orthotopic PDAC tumours in vivo and human patient-derived PDAC tumour explants ex vivo increases extrinsic apoptosis and reduces tumour progression. Thus, silencing of {beta}III-tubulin represents an innovative strategy to unleash a suicide signal in PDAC cells and render them sensitive to microenvironment and chemotherapy-derived death signals.

cancer biology↗

Efficient ancestry and mutation simulation with msprime 1.0

Stochastic simulation is a key tool in population genetics, since the models involved are often analytically intractable and simulation is usually the only way of obtaining ground-truth data to evaluate inferences. Because of this necessity, a large number of specialised simulation programs have been developed, each filling a particular niche, but with largely overlapping functionality and a substantial duplication of effort. Here, we introduce msprime version 1.0, which efficiently implements ancestry and mutation simulations based on the succinct tree sequence data structure and tskit library. We summarise msprimes many features, and show that its performance is excellent, often many times faster and more memory efficient than specialised alternatives. These high-performance features have been thoroughly tested and validated, and built using a collaborative, open source development model, which reduces duplication of effort and promotes software quality via community engagement.

genetics↗

Bringing the pancreas patient back to the bench: Ex vivo culture of intact human patient derived pancreatic tumour tissue

The poor prognosis of pancreatic ductal adenocarcinoma (PDAC) is attributed to the highly fibrotic stroma and complex multi-cellular microenvironment that is difficult to fully recapitulate in pre-clinical human models. To fast-track translation of therapies and to inform personalised medicine, we aimed to develop a whole-tissue ex vivo explant model that maintains viability, 3D multicellular architecture, and microenvironmental cues present in human pancreatic tumours. Patient-derived surgically-resected PDAC tissue was cut into 2 mm explants, cultured on gelatin sponges, and grown for 12 days. Immunohistochemistry revealed that human PDAC tissue explants were viable for 12 days and maintained their original tumour, stromal and extracellular matrix architecture. As proof-of-principle, human PDAC tissue explants responded to Abraxane(R) treatment with a 3.7-fold increase in cell-death (p=0.0007). PDAC explants were also transfected with polymeric nanoparticles+Cy5-siRNA and we observed abundant cytoplasmic distribution of nanoparticle+Cy5-siRNA throughout the PDAC explant tissue. Our novel model retains the 3D architecture of human pancreatic tumours and has several advantages over standard organoids: presence of functional multi-cellular stroma and fibrosis and no tissue manipulation, digestion, or artificial propagation of organoids. This provides an unprecedented opportunity to study PDAC biology, tumour-stromal interactions and rapidly assess therapeutic response that could drive personalised treatment for PDAC.

cancer biology↗

Neurodevelopmental deficits and cell-type-specific transcriptomic perturbations in a mouse model of HNRNPU haploinsufficiency

Heterozygous de novo loss-of-function mutations in the gene expression regulator HNRNPU cause an early-onset developmental and epileptic encephalopathy. To gain insight into pathological mechanisms and lay the potential groundwork for developing targeted therapies, we characterized the neurophysiologic and cell-type-specific transcriptomic consequences of a mouse model of HNRNPU haploinsufficiency. Heterozygous mutants demonstrated neuroanatomical abnormalities, global developmental delay, impaired ultrasonic vocalizations and increased seizure susceptibility, thus modeling aspects of the human disease. Single-cell RNA-sequencing of hippocampal and neocortical cells revealed widespread, yet modest, dysregulation of gene expression across mutant neuronal subtypes. We observed an increased burden of differentially-expressed genes in mutant excitatory neurons of the subiculum--a region of the hippocampus implicated in temporal lobe epilepsy. Evaluation of transcriptomic signature reversal as a therapeutic strategy highlights the potential importance of generating cell-type-specific signatures. Overall, this work provides insight into HNRNPU-mediated disease mechanisms, and provides a framework for using single-cell RNA-sequencing to study transcriptional regulators implicated in disease.

neuroscience↗

Ancestry adjustment improves genome-wide estimates of regional intolerance

Genomic regions subject to purifying selection are more likely to carry disease causing mutations. Cross species conservation is often used to identify such regions but has limited resolution to detect selection on short evolutionary timescales such as that occurring in only one species. In contrast, intolerance looks for depletion of variation relative to expectation within a species, allowing species specific features to be identified. When estimating the intolerance of noncoding sequence methods strongly leverage variant frequency distributions. As the expected distributions depend on demography, if not properly controlled for, ancestral population source may obfuscate signals of selection. We demonstrate that properly incorporating demography in intolerance estimation greatly improved variant classification (13% increase in AUC relative to comparison constraint test, CDTS; and 9% relative to conservation). We provide a genome-wide intolerance map that is conditional on demographic history that is likely to be particularly valuable for variant prioritization.

genetics↗

Improved Pathogenic Variant Localization using a Hierarchical Model of Sub-regional Intolerance

Different parts of a gene can be of differential importance to development and health. This regional heterogeneity is also apparent in the distribution of disease mutations which often cluster in particular regions of disease genes. The ability to precisely estimate functionally important sub-regions of genes will be key in correctly deciphering relationships between genetic variation and disease. Previous methods have had some success using standing human variation to characterize this variability in importance by measuring sub-regional intolerance, i.e., the depletion in functional variation from expectation within a given region of a gene. However, the ability to precisely estimate local intolerance was restricted by the fact that only information within a given sub-region is used, leading to instability in local estimates, especially for small regions. We show that borrowing information across regions using a Bayesian hierarchical model, stabilizes estimates, leading to lower variability and improved predictive utility. Specifically, our approach more effectively identifies regions enriched for ClinVar pathogenic variants. We also identify significant correlations between sub-region intolerance and the distribution of pathogenic variation in disease genes, with AUCs for classifying de novo missense variants in Online Mendelian Inheritance in Man (OMIM) genes of up to 0.86 using exonic sub-regions and 0.91 using sub-regions defined by protein domains. This result immediately suggests that considering the intolerance of regions in which variants are found may improve diagnostic interpretation. We also illustrate the utility of integrating regional intolerance into gene-level disease association tests with a study of known disease genes for epileptic encephalopathy.

genetics↗

Enrichment of rare protein truncating variants in amyotrophic lateral sclerosis patients

To discover novel genetic risk factors underlying amyotrophic lateral sclerosis (ALS), we aggregated exomes from 3,864 cases and 7,839 ancestry matched controls. We observed a significant excess of ultra-rare and rare protein-truncating variants (PTV) among ALS cases, which was primarily concentrated in constrained genes; however, a significant enrichment in PTVs does persist in the remaining exome. Through gene level analyses, known ALS genes, SOD1, NEK1, and FUS, were the most strongly associated with disease status. We also observed suggestive statistical evidence for multiple novel genes including DNAJC7, which is a highly constrained gene and a member of the heat shock protein family (HSP40). HSP40 proteins, along with HSP70 proteins, facilitate protein homeostasis, such as folding of newly synthesized polypeptides, and clearance of degraded proteins. When these processes are not regulated, misfolding and accumulation of degraded proteins can occur leading to aberrant protein aggregation, one of the pathological hallmarks of neurodegeneration.

genomics↗