Biomedical subjects

Peter J Park

Publications and source records attributed to Peter J Park.

At least 19 recordsLinked to original sources

PubMed2026

Recurrent patterns of TOP1-mediated neuronal genomic damage shared by major neurodegenerative disorders.

Amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and Alzheimer's disease (AD) represent two major categories of neurodegenerative disorders-TAR DNA-binding protein 43 (TDP-43) and tau proteinopathies-for which the mechanisms driving neuronal death remain unclear. Single-cell whole-genome sequencing of 469 neurons from C9ORF72 ALS, C9ORF72 FTD, AD, and control brains revealed increased somatic single-nucleotide variants (sSNVs) and insertions/deletions (sIndels) in all three diseases. Mutational signature analysis identified a disease-associated sSNV signature consistent with oxidative damage and an sIndel process affecting 22% of ALS, 76% of FTD, and 61% of AD neurons-but only 2% of control neurons-resembling signature ID4, previously linked to topoisomerase 1 (TOP1)-mediated mutagenesis. Rapid approach to DNA adduct recovery (RADAR) assays confirmed increased TOP1-DNA covalent complexes, and duplex sequencing confirmed the increased sIndels and identified single-strand events as likely precursor lesions. TOP1-associated sIndel mutagenesis and genome instability thus represent a mechanism shared by both TDP-43 and tau neurodegeneration.

Humans↗

PubMed2025

Combined somatic mutation and transcriptome analysis reveals region-specific differences in clonal architecture in human cortex.

The human cerebral cortex is specialized into regions, but little is known about how human cellular lineages shape cortical regional variation and neuronal cell-type distribution during development. Here, we map single-cell lineages of human cortical regions and neuronal subtypes using >1,000 somatic single-nucleotide variants (sSNVs) identified from deep bulk whole-genome sequencing and analyzed over 25 regions and >72,000 single cells. In the fronto-parietal cortex, sSNVs are rarely restricted, marking neuron-generating clones that disperse into neighboring regions. In contrast, the primary visual cortex harbors 30%-70% more sSNVs than the neighboring secondary visual cortex. Clones at this border exhibit more restricted dispersion, suggesting late developmental lineage segregation. Single-nucleus sSNV and whole-transcriptome analysis reveal glutamatergic neuron clones with modest regional restrictions that share low-mosaic sSNVs with some GABAergic neurons, suggesting a recent dorsal cortical progenitor. Our analysis reveals human-specific cortical lineage patterns, regional differences in clonal patterns, and late divergence of some glutamatergic/GABAergic lineages.

Humans↗

PubMed2025

The Data Distillery: A Graph Framework for Semantic Integration and Querying of Biomedical Data.

The Data Distillery Knowledge Graph (DDKG) is a framework for semantic integration and querying of biomedical data across domains. Built for the NIH Common Fund Data Ecosystem, it supports translational research by linking clinical and experimental datasets in a unified graph model. Clinical standards such as ICD-10, SNOMED, and DrugBank are integrated through UMLS, while genomics and basic science data are structured using ontologies and standards such as HPO, GENCODE, Ensembl, STRING, and ClinVar. The DDKG uses a property graph architecture based on the UBKG infrastructure and supports ontology-based ingestion, identifier normalization, and graph-native querying. The system is modular and can be extended with new datasets or schema modules. We demonstrate its utility for informatics queries across eight use cases, including regulatory variant analysis, tissue-specific expression, biomarker discovery, and cross-species variant prioritization. The DDKG is accessible via a public interface, a programmatic API, and downloadable builds for local use.

Journal Article↗

PubMed2025

Comprehensive benchmarking of somatic structural variant detection at ultra-low allele fractions.

Postzygotic mosaicism gives rise to somatic structural variants (SVs) at ultra-low variant allele fractions (VAFs), which pose challenges for detection due to the high-coverage sequencing required and noise introduced by sequencing artifacts. Although somatic SV detection has been extensively studied in cancer, these studies are not directly applicable to the study of tissue mosaicism, as they rely on matched normals, target higher VAF ranges, and are enriched for different types of SVs. We present comprehensive benchmark data and best practices for non-cancer somatic SV detection. We created a synthetic mosaic sample by combining six HapMap individuals at varying proportions, generating allele fractions as low as 0.25%. This sample was sequenced to ~2,300x total coverage using Illumina, PacBio, and Nanopore technologies across multiple sequencing centers. A high-confidence benchmark SV set containing over 21,000 pseudo-somatic insertions and deletions ≥50bp was derived from haplotype-resolved assemblies. We evaluated 12 SV discovery pipelines and identified caller-specific strengths and sequencing platform-specific shortcomings. We find that short read-based approaches show reduced recall for insertions and repeat-associated SVs, whereas long-read sequencing achieves high accuracy throughout the genome, increasing linearly with coverage. The best algorithm's sensitivity exceeded 80% for VAFs ≥4% and 15% for VAFs of 0.5-1% with 60x coverage. The publicly available benchmarking data and comparative analysis of current methods provide a foundation for robust discovery of SV mosaicism in non-cancer tissues..

Journal Article↗

PubMed2025

Recurrent patterns of widespread neuronal genomic damage shared by major neurodegenerative disorders.

Amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and Alzheimer's disease (AD) are common neurodegenerative disorders for which the mechanisms driving neuronal death remain unclear. Single-cell whole-genome sequencing of 429 neurons from three C9ORF72 ALS, six C9ORF72 FTD, seven AD, and twenty-three neurotypical control brains revealed significantly increased burdens in somatic single nucleotide variant (sSNV) and insertion/deletion (sIndel) in all three disease conditions. Mutational signature analysis identified a disease-associated sSNV signature suggestive of oxidative damage and an sIndel process, affecting 28% of ALS, 79% of FTD, and 65% of AD neurons but only 5% of control neurons (diseased vs. control: OR=31.20, p = 2.35×10-10). Disease-associated sIndels were primarily two-basepair deletions resembling signature ID4, which was previously linked to topoisomerase 1 (TOP1)-mediated mutagenesis. Duplex sequencing confirmed the presence of sIndels and identified similar single-strand events as potential precursor lesions. TOP1-associated sIndel mutagenesis and resulting genome instability may thus represent a common mechanism of neurodegeneration.

Journal Article↗

PubMed2006

A genome-wide screen reveals functional gene clusters in the cancer genome and identifies EphA2 as a mitogen in glioblastoma.

A novel genome-wide screen that combines patient outcome analysis with array comparative genomic hybridization and mRNA expression profiling was developed to identify genes with copy number alterations, aberrant mRNA expression, and relevance to survival in glioblastoma. The method led to the discovery of physical gene clusters within the cancer genome with boundaries defined by physical proximity, correlated mRNA expression patterns, and survival relatedness. These boundaries delineate a novel genomic interval called the functional common region (FCR). Many FCRs contained genes of high biological relevance to cancer and were used to pinpoint functionally significant DNA alterations that were too small or infrequent to be reliably identified using standard algorithms. One such FCR contained the EphA2 receptor tyrosine kinase. Validation experiments showed that EphA2 mRNA overexpression correlated inversely with patient survival in a panel of 21 glioblastomas, and ligand-mediated EphA2 receptor activation increased glioblastoma proliferation and tumor growth via a mitogen-activated protein kinase-dependent pathway. This novel genome-wide approach greatly expanded the list of target genes in glioblastoma and represents a powerful new strategy to identify the upstream determinants of tumor phenotype in a range of human cancers.

Brain Neoplasms↗

PubMed2006

A multivariate approach for integrating genome-wide expression data and biological knowledge.

MOTIVATION: Several statistical methods that combine analysis of differential gene expression with biological knowledge databases have been proposed for a more rapid interpretation of expression data. However, most such methods are based on a series of univariate statistical tests and do not properly account for the complex structure of gene interactions. RESULTS: We present a simple yet effective multivariate statistical procedure for assessing the correlation between a subspace defined by a group of genes and a binary phenotype. A subspace is deemed significant if the samples corresponding to different phenotypes are well separated in that subspace. The separation is measured using Hotelling's T(2) statistic, which captures the covariance structure of the subspace. When the dimension of the subspace is larger than that of the sample space, we project the original data to a smaller orthonormal subspace. We use this method to search through functional pathway subspaces defined by Reactome, KEGG, BioCarta and Gene Ontology. To demonstrate its performance, we apply this method to the data from two published studies, and visualize the results in the principal component space.

Algorithms↗

PubMed2006

Postmeiotic sex chromatin in the male germline of mice.

In mammals, the X and Y chromosomes are subject to meiotic sex chromosome inactivation (MSCI) during prophase I in the male germline, but their status thereafter is currently unclear. An abundance of X-linked spermatogenesis genes has spawned the view that the X must be active . On the other hand, the idea that the imprinted paternal X of the early embryo may be preinactivated by MSCI suggests that silencing may persist longer . To clarify this issue, we establish a comprehensive X-expression profile during mouse spermatogenesis. Here, we discover that the X and Y occupy a novel compartment in the postmeiotic spermatid and adopt a non-Rabl configuration. We demonstrate that this postmeiotic sex chromatin (PMSC) persists throughout spermiogenesis into mature sperm and exhibits epigenetic similarity to the XY body. In the spermatid, 87% of X-linked genes remain suppressed postmeiotically, while autosomes are largely active. We conclude that chromosome-wide X silencing continues from meiosis to the end of spermiogenesis, and we discuss implications for proposed mechanisms of imprinted X-inactivation.

Animals↗

PubMed2006

High-resolution ChIP-chip analysis reveals that the Drosophila MSL complex selectively identifies active genes on the male X chromosome.

X-chromosome dosage compensation in Drosophila requires the male-specific lethal (MSL) complex, which up-regulates gene expression from the single male X chromosome. Here, we define X-chromosome-specific MSL binding at high resolution in two male cell lines and in late-stage embryos. We find that the MSL complex is highly enriched over most expressed genes, with binding biased toward the 3' end of transcription units. The binding patterns are largely similar in the distinct cell types, with approximately 600 genes clearly bound in all three cases. Genes identified as clearly bound in one cell type and not in another indicate that attraction of MSL complex correlates with expression state. Thus, sequence alone is not sufficient to explain MSL targeting. We propose that the MSL complex recognizes most X-linked genes, but only in the context of chromatin factors or modifications indicative of active transcription. Distinguishing expressed genes from the bulk of the genome is likely to be an important function common to many chromatin organizing and modifying activities.

Animals↗

PubMed2006

Angiogenic profile of soft tissue sarcomas based on analysis of circulating factors and microarray gene expression.

BACKGROUND: Broader understanding of diverse angiogenic pathways in a particular cancer can lead to better utilization of anti-angiogenic therapies. The aim of this study was to develop profiles of angiogenesis-related gene and protein expression for various histologic subtypes of soft tissue sarcomas (STS) growing in different sites. MATERIALS AND METHODS: Plasma levels of vascular endothelial growth factor (VEGF), basic fibroblast growth factor (bFGF), angiopoietin 2 (Ang2), and leptin were determined in 108 patients with primary STS. Gene expression patterns were analyzed in 38 STS samples and 13 normal tissues using oligonucleotide microarrays. RESULTS: VEGF and bFGF plasma levels were elevated 10-13 fold in STS patients compared to controls. VEGF levels were broadly elevated while bFGF levels were higher in patients with fibrosarcomas and leiomyosarcomas. Ang2 levels correlated with tumor size and were most elevated for tumors located in the trunk, while leptin levels were highest in patients with liposarcomas. Hierarchical clustering of microarray data based on angiogenesis-related gene expression demonstrated that histologic subtypes of STS often shared similar expression patterns, and these patterns were distinctly different from those of normal tissues. Matrix metalloproteinase 2, platelet-derived growth factor receptor, alpha and Notch 4 were among several genes that were up-regulated at least 7-fold in STS. CONCLUSIONS: STS demonstrate significant heterogeneity in their angiogenic profiles based on size, histologic subtype, and location of tumor growth, which may have implications for anti-angiogenic strategies. Comparison of STS to normal tissues reveals a panel of upregulated genes that may be targets for future therapies.

Angiopoietin-2↗

PubMed2005

Global regulation of X chromosomal genes by the MSL complex in Drosophila melanogaster.

A long-standing model postulates that X-chromosome dosage compensation in Drosophila occurs by twofold up-regulation of the single male X, but previous data cannot exclude an alternative model, in which male autosomes are down-regulated to balance gene expression. To distinguish between the two models, we used RNA interference to deplete Male-Specific Lethal (MSL) complexes from male-like tissue culture cells. We found that expression of many genes from the X chromosome decreased, while expression from the autosomes was largely unchanged. We conclude that the primary role of the MSL complex is to up-regulate the male X chromosome.

Animals↗

PubMed2005

Discovering statistically significant pathways in expression profiling studies.

Accurate and rapid identification of perturbed pathways through the analysis of genome-wide expression profiles facilitates the generation of biological hypotheses. We propose a statistical framework for determining whether a specified group of genes for a pathway has a coordinated association with a phenotype of interest. Several issues on proper hypothesis-testing procedures are clarified. In particular, it is shown that the differences in the correlation structure of each set of genes can lead to a biased comparison among gene sets unless a normalization procedure is applied. We propose statistical tests for two important but different aspects of association for each group of genes. This approach has more statistical power than currently available methods and can result in the discovery of statistically significant pathways that are not detected by other methods. This method is applied to data sets involving diabetes, inflammatory myopathies, and Alzheimer's disease, using gene sets we compiled from various public databases. In the case of inflammatory myopathies, we have correctly identified the known cytotoxic T lymphocyte-mediated autoimmunity in inclusion body myositis. Furthermore, we predicted the presence of dendritic cells in inclusion body myositis and of an IFN-alpha/beta response in dermatomyositis, neither of which was previously described. These predictions have been subsequently corroborated by immunohistochemistry.

Algorithms↗

PubMed2005

Comparative analysis of algorithms for identifying amplifications and deletions in array CGH data.

MOTIVATION: Array Comparative Genomic Hybridization (CGH) can reveal chromosomal aberrations in the genomic DNA. These amplifications and deletions at the DNA level are important in the pathogenesis of cancer and other diseases. While a large number of approaches have been proposed for analyzing the large array CGH datasets, the relative merits of these methods in practice are not clear. RESULTS: We compare 11 different algorithms for analyzing array CGH data. These include both segment detection methods and smoothing methods, based on diverse techniques such as mixture models, Hidden Markov Models, maximum likelihood, regression, wavelets and genetic algorithms. We compute the Receiver Operating Characteristic (ROC) curves using simulated data to quantify sensitivity and specificity for various levels of signal-to-noise ratio and different sizes of abnormalities. We also characterize their performance on chromosomal regions of interest in a real dataset obtained from patients with Glioblastoma Multiforme. While comparisons of this type are difficult due to possibly sub-optimal choice of parameters in the methods, they nevertheless reveal general characteristics that are helpful to the biological investigator.

Algorithms↗

PubMed2005

CrossChip: a system supporting comparative analysis of different generations of Affymetrix arrays.

SUMMARY: To increase compatibility between different generations of Affymetrix GeneChip arrays, we propose a method of filtering probes based on their sequences. Our method is implemented as a web-based service for downloading necessary materials for converting the raw data files (*.CEL) for comparative analysis. The user can specify the appropriate level of filtering by setting the criteria for the minimum overlap length between probe sequences and the minimum number of usable probe pairs per probe set. Our website supports a within-species comparison for human and mouse GeneChip arrays. AVAILABILITY: http://www.crosschip.org

Algorithms↗

PubMed2004

Combining gene expression data from different generations of oligonucleotide arrays.

BACKGROUND: One of the important challenges in microarray analysis is to take full advantage of previously accumulated data, both from one's own laboratory and from public repositories. Through a comparative analysis on a variety of datasets, a more comprehensive view of the underlying mechanism or structure can be obtained. However, as we discover in this work, continual changes in genomic sequence annotations and probe design criteria make it difficult to compare gene expression data even from different generations of the same microarray platform. RESULTS: We first describe the extent of discordance between the results derived from two generations of Affymetrix oligonucleotide arrays, as revealed in cluster analysis and in identification of differentially expressed genes. We then propose a method for increasing comparability. The dataset we use consists of a set of 14 human muscle biopsy samples from patients with inflammatory myopathies that were hybridized on both HG-U95Av2 and HG-U133A human arrays. We find that the use of the probe set matching table for comparative analysis provided by Affymetrix produces better results than matching by UniGene or LocusLink identifiers but still remains inadequate. Rescaling of expression values for each gene across samples and data filtering by expression values enhance comparability but only for few specific analyses. As a generic method for improving comparability, we select a subset of probes with overlapping sequence segments in the two array types and recalculate expression values based only on the selected probes. We show that this filtering of probes significantly improves the comparability while retaining a sufficient number of probe sets for further analysis. CONCLUSIONS: Compatibility between high-density oligonucleotide arrays is significantly affected by probe-level sequence information. With a careful filtering of the probes based on their sequence overlaps, data from different generations of microarrays can be combined more effectively.

Biopsy↗

PubMed2004

Current issues for DNA microarrays: platform comparison, double linear amplification, and universal RNA reference.

DNA microarray technology has been widely used to simultaneously determine the expression levels of thousands of genes. A variety of approaches have been used, both in the implementation of this technology and in the analysis of the large amount of expression data. However, several practical issues still have not been resolved in a satisfactory manner, and among the most critical is the lack of agreement in the results obtained in different array platforms. In this study, we present a comparison of several microarray platforms [Affymetrix oligonucleotide arrays, custom complementary DNA (cDNA) arrays, and custom oligo arrays printed with oligonucleotides from three different sources] as well as analysis of various methods used for microarray target preparation and the reference design. The results indicate that the pairwise correlations of expression levels between platforms are relative low overall but that the log ratios of the highly expressed genes are strongly correlated, especially between Affymetrix and cDNA arrays. The microarray measurements were compared with quantitative real-time-polymerase chain reaction (QRT-PCR) results for 23 genes, and the varying degrees of agreement for each platform were characterized. We have also developed and tested a double amplification method which allows the use of smaller amounts of starting material. The added round of amplification produced reproducible results as compared to the arrays hybridized with single round amplified targets. Finally, the reliability of using a universal RNA reference for two-channel microarrays was tested and the results suggest that comparisons of multiple experimental conditions using the same control can be accurate.

Benchmarking↗

PubMed2004

Improving identification of differentially expressed genes in microarray studies using information from public databases.

We demonstrate that the process of identifying differentially expressed genes in microarray studies with small sample sizes can be substantially improved by extracting information from a large number of datasets accumulated in public databases. The improvement comes from more reliable estimates of gene-specific variances based on other datasets. For a two-group comparison with two arrays in each group, for example, the result of our method was comparable to that of a t-test analysis with five samples in each group or to that of a regularized t-test analysis with three samples in each group. Our results are further improved by weighting the results of our approach with the regularized t-test results in a hybrid method.

Databases, Genetic↗

PubMed2003

Human decidual natural killer cells are a unique NK cell subset with immunomodulatory potential.

Natural killer cells constitute 50-90% of lymphocytes in human uterine decidua in early pregnancy. Here, CD56(bright) uterine decidual NK (dNK) cells were compared with the CD56(bright) and CD56(dim) peripheral NK cell subsets by microarray analysis, with verification of results by flow cytometry and RT-PCR. Among the approximately 10,000 genes studied, 278 genes showed at least a threefold change with P < or = 0.001 when comparing the dNK and peripheral NK cell subsets, most displaying increased expression in dNK cells. The largest number of these encoded surface proteins, including the unusual lectinlike receptors NKG2E and Ly-49L, several killer cell Ig-like receptors, the integrin subunits alpha(D), alpha(X), beta1, and beta5, and multiple tetraspanins (CD9, CD151, CD53, CD63, and TSPAN-5). Additionally, two secreted proteins, galectin-1 and progestagen-associated protein 14, known to have immunomodulatory functions, were selectively expressed in dNK cells.

CD56 Antigen↗