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  • Proceedings of the National Academy of Sciences  (67)
  • 1
    Online Resource
    Online Resource
    Functional proteogenomics reveals biomarkers and therapeutic targets in lymphomas
    Proceedings of the National Academy of Sciences ; 2017
    In:  Proceedings of the National Academy of Sciences Vol. 114, No. 25 ( 2017-06-20), p. 6581-6586
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 114, No. 25 ( 2017-06-20), p. 6581-6586
    Abstract: Identification of biomarkers and therapeutic targets is a critical goal of precision medicine. N-glycoproteins are a particularly attractive class of proteins that constitute potential cancer biomarkers and therapeutic targets for small molecules, antibodies, and cellular therapies. Using mass spectrometry (MS), we generated a compendium of 1,091 N-glycoproteins (from 40 human primary lymphomas and cell lines). Hierarchical clustering revealed distinct subtype signatures that included several subtype-specific biomarkers. Orthogonal immunological studies in 671 primary lymphoma tissue biopsies and 32 lymphoma-derived cell lines corroborated MS data. In anaplastic lymphoma kinase-positive (ALK + ) anaplastic large cell lymphoma (ALCL), integration of N-glycoproteomics and transcriptome sequencing revealed an ALK-regulated cytokine/receptor signaling network, including vulnerabilities corroborated by a genome-wide clustered regularly interspaced short palindromic screen. Functional targeting of IL-31 receptor β, an ALCL-enriched and ALK-regulated N-glycoprotein in this network, abrogated ALK + ALCL growth in vitro and in vivo. Our results highlight the utility of functional proteogenomic approaches for discovery of cancer biomarkers and therapeutic targets.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1701263114
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2017
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  • 2
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    Specimen collections should have a much bigger role in infectious disease research and response
    Proceedings of the National Academy of Sciences ; 2016
    In:  Proceedings of the National Academy of Sciences Vol. 113, No. 1 ( 2016-01-05), p. 4-7
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 113, No. 1 ( 2016-01-05), p. 4-7
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1522680112
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2016
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
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  • 3
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    Chlamydial IFN-γ immune evasion is linked to host infection tropism
    Proceedings of the National Academy of Sciences ; 2005
    In:  Proceedings of the National Academy of Sciences Vol. 102, No. 30 ( 2005-07-26), p. 10658-10663
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 102, No. 30 ( 2005-07-26), p. 10658-10663
    Abstract: Chlamydiae are obligate intracellular pathogens that can exhibit a broad host range in infection tropism despite maintaining near genomic identity. Here, we have investigated the molecular basis for this unique host-pathogen relationship. We show that human and murine chlamydial infection tropism is linked to unique host and pathogen genes that have coevolved in response to host immunity. This intimate host-pathogen niche revolves around a restricted repertoire of host species-specific IFN-γ-mediated effector responses and chlamydial virulence factors capable of inhibiting these effector mechanisms. In human epithelial cells, IFN-γ induces indoleamine 2,3-dioxygenase expression that inhibits chlamydial growth by depleting host tryptophan pools. Human chlamydial strains, but not the mouse strain, avoid this response by the production of tryptophan synthase that rescues them from tryptophan starvation. Conversely, in murine epithelial cells IFN-γ induces expression of p47 GTPases, but not indoleamine 2,3-dioxygenase. One of these p47 GTPases (Iigp1) was shown by small interfering RNA silencing experiments to specifically inhibit human strains, but not the mouse strain. Like human strains and their host cells, the murine strain has coevolved with its murine host by producing a large toxin possessing YopT homology, possibly to circumvent host GTPases. Collectively, our findings show chlamydial host infection tropism is determined by IFN-γ-mediated immunity.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.0504198102
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2005
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
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  • 4
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    Degradation and remobilization of endogenous retroviruses by recombination during the earliest stages of a germ-line invasion
    Proceedings of the National Academy of Sciences ; 2018
    In:  Proceedings of the National Academy of Sciences Vol. 115, No. 34 ( 2018-08-21), p. 8609-8614
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 115, No. 34 ( 2018-08-21), p. 8609-8614
    Abstract: Endogenous retroviruses (ERVs) are proviral sequences that result from colonization of the host germ line by exogenous retroviruses. The majority of ERVs represent defective retroviral copies. However, for most ERVs, endogenization occurred millions of years ago, obscuring the stages by which ERVs become defective and the changes in both virus and host important to the process. The koala retrovirus, KoRV, only recently began invading the germ line of the koala ( Phascolarctos cinereus ), permitting analysis of retroviral endogenization on a prospective basis. Here, we report that recombination with host genomic elements disrupts retroviruses during the earliest stages of germ-line invasion. One type of recombinant, designated recKoRV1, was formed by recombination of KoRV with an older degraded retroelement. Many genomic copies of recKoRV1 were detected across koalas. The prevalence of recKoRV1 was higher in northern than in southern Australian koalas, as is the case for KoRV, with differences in recKoRV1 prevalence, but not KoRV prevalence, between inland and coastal New South Wales. At least 15 additional different recombination events between KoRV and the older endogenous retroelement generated distinct recKoRVs with different geographic distributions. All of the identified recombinant viruses appear to have arisen independently and have highly disrupted ORFs, which suggests that recombination with existing degraded endogenous retroelements may be a means by which replication-competent ERVs that enter the germ line are degraded.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1807598115
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2018
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
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  • 5
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    Anatomically interpretable deep learning of brain age captures domain-specific cognitive impairment
    Proceedings of the National Academy of Sciences ; 2023
    In:  Proceedings of the National Academy of Sciences Vol. 120, No. 2 ( 2023-01-10)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 120, No. 2 ( 2023-01-10)
    Abstract: The gap between chronological age (CA) and biological brain age, as estimated from magnetic resonance images (MRIs), reflects how individual patterns of neuroanatomic aging deviate from their typical trajectories. MRI-derived brain age (BA) estimates are often obtained using deep learning models that may perform relatively poorly on new data or that lack neuroanatomic interpretability. This study introduces a convolutional neural network (CNN) to estimate BA after training on the MRIs of 4,681 cognitively normal (CN) participants and testing on 1,170 CN participants from an independent sample. BA estimation errors are notably lower than those of previous studies. At both individual and cohort levels, the CNN provides detailed anatomic maps of brain aging patterns that reveal sex dimorphisms and neurocognitive trajectories in adults with mild cognitive impairment (MCI, N  = 351) and Alzheimer’s disease (AD, N  = 359). In individuals with MCI (54% of whom were diagnosed with dementia within 10.9 y from MRI acquisition), BA is significantly better than CA in capturing dementia symptom severity, functional disability, and executive function. Profiles of sex dimorphism and lateralization in brain aging also map onto patterns of neuroanatomic change that reflect cognitive decline. Significant associations between BA and neurocognitive measures suggest that the proposed framework can map, systematically, the relationship between aging-related neuroanatomy changes in CN individuals and in participants with MCI or AD. Early identification of such neuroanatomy changes can help to screen individuals according to their AD risk.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2214634120
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 209104-5
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  • 6
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    Statistical tests and identifiability conditions for pooling and analyzing multisite datasets
    Proceedings of the National Academy of Sciences ; 2018
    In:  Proceedings of the National Academy of Sciences Vol. 115, No. 7 ( 2018-02-13), p. 1481-1486
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 115, No. 7 ( 2018-02-13), p. 1481-1486
    Abstract: When sample sizes are small, the ability to identify weak (but scientifically interesting) associations between a set of predictors and a response may be enhanced by pooling existing datasets. However, variations in acquisition methods and the distribution of participants or observations between datasets, especially due to the distributional shifts in some predictors, may obfuscate real effects when datasets are combined. We present a rigorous statistical treatment of this problem and identify conditions where we can correct the distributional shift. We also provide an algorithm for the situation where the correction is identifiable. We analyze various properties of the framework for testing model fit, constructing confidence intervals, and evaluating consistency characteristics. Our technical development is motivated by Alzheimer’s disease (AD) studies, and we present empirical results showing that our framework enables harmonizing of protein biomarkers, even when the assays across sites differ. Our contribution may, in part, mitigate a bottleneck that researchers face in clinical research when pooling smaller sized datasets and may offer benefits when the subjects of interest are difficult to recruit or when resources prohibit large single-site studies.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1719747115
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2018
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
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  • 7
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    Identification of genetic risk factors in the Chinese population implicates a role of immune system in Alzheimer’s disease pathogenesis
    Proceedings of the National Academy of Sciences ; 2018
    In:  Proceedings of the National Academy of Sciences Vol. 115, No. 8 ( 2018-02-20), p. 1697-1706
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 115, No. 8 ( 2018-02-20), p. 1697-1706
    Abstract: Alzheimer’s disease (AD) is a leading cause of mortality among the elderly. We performed a whole-genome sequencing study of AD in the Chinese population. In addition to the variants identified in or around the APOE locus (sentinel variant rs73052335, P = 1.44 × 10 −14 ), two common variants, GCH1 (rs72713460, P = 4.36 × 10 −5 ) and KCNJ15 (rs928771, P = 3.60 × 10 −6 ), were identified and further verified for their possible risk effects for AD in three small non-Asian AD cohorts. Genotype–phenotype analysis showed that KCNJ15 variant rs928771 affects the onset age of AD, with earlier disease onset in minor allele carriers. In addition, altered expression level of the KCNJ15 transcript can be observed in the blood of AD subjects. Moreover, the risk variants of GCH1 and KCNJ15 are associated with changes in their transcript levels in specific tissues, as well as changes of plasma biomarkers levels in AD subjects. Importantly, network analysis of hippocampus and blood transcriptome datasets suggests that the risk variants in the APOE , GCH1 , and KCNJ15 loci might exert their functions through their regulatory effects on immune-related pathways. Taking these data together, we identified common variants of GCH1 and KCNJ15 in the Chinese population that contribute to AD risk. These variants may exert their functional effects through the immune system.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1715554115
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2018
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
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  • 8
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    Morphometricity as a measure of the neuroanatomical signature of a trait
    Proceedings of the National Academy of Sciences ; 2016
    In:  Proceedings of the National Academy of Sciences Vol. 113, No. 39 ( 2016-09-27)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 113, No. 39 ( 2016-09-27)
    Abstract: Complex physiological and behavioral traits, including neurological and psychiatric disorders, often associate with distributed anatomical variation. This paper introduces a global metric, called morphometricity, as a measure of the anatomical signature of different traits. Morphometricity is defined as the proportion of phenotypic variation that can be explained by macroscopic brain morphology. We estimate morphometricity via a linear mixed-effects model that uses an anatomical similarity matrix computed based on measurements derived from structural brain MRI scans. We examined over 3,800 unique MRI scans from nine large-scale studies to estimate the morphometricity of a range of phenotypes, including clinical diagnoses such as Alzheimer’s disease, and nonclinical traits such as measures of cognition. Our results demonstrate that morphometricity can provide novel insights about the neuroanatomical correlates of a diverse set of traits, revealing associations that might not be detectable through traditional statistical techniques.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1604378113
    RVK:
    TA 1000
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    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2016
    detail.hit.zdb_id: 209104-5
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  • 9
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    De novo mutations across 1,465 diverse genomes reveal mutational insights and reductions in the Amish founder population
    Proceedings of the National Academy of Sciences ; 2020
    In:  Proceedings of the National Academy of Sciences Vol. 117, No. 5 ( 2020-02-04), p. 2560-2569
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 117, No. 5 ( 2020-02-04), p. 2560-2569
    Abstract: De novo mutations (DNMs), or mutations that appear in an individual despite not being seen in their parents, are an important source of genetic variation whose impact is relevant to studies of human evolution, genetics, and disease. Utilizing high-coverage whole-genome sequencing data as part of the Trans-Omics for Precision Medicine (TOPMed) Program, we called 93,325 single-nucleotide DNMs across 1,465 trios from an array of diverse human populations, and used them to directly estimate and analyze DNM counts, rates, and spectra. We find a significant positive correlation between local recombination rate and local DNM rate, and that DNM rate explains a substantial portion (8.98 to 34.92%, depending on the model) of the genome-wide variation in population-level genetic variation from 41K unrelated TOPMed samples. Genome-wide heterozygosity does correlate with DNM rate, but only explains 〈 1% of variation. While we are underpowered to see small differences, we do not find significant differences in DNM rate between individuals of European, African, and Latino ancestry, nor across ancestrally distinct segments within admixed individuals. However, we did find significantly fewer DNMs in Amish individuals, even when compared with other Europeans, and even after accounting for parental age and sequencing center. Specifically, we found significant reductions in the number of C→A and T→C mutations in the Amish, which seem to underpin their overall reduction in DNMs. Finally, we calculated near-zero estimates of narrow sense heritability ( h 2 ), which suggest that variation in DNM rate is significantly shaped by nonadditive genetic effects and the environment.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1902766117
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2020
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
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  • 10
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    Bayesian model reveals latent atrophy factors with dissociable cognitive trajectories in Alzheimer’s disease
    Proceedings of the National Academy of Sciences ; 2016
    In:  Proceedings of the National Academy of Sciences Vol. 113, No. 42 ( 2016-10-18)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 113, No. 42 ( 2016-10-18)
    Abstract: We used a data-driven Bayesian model to automatically identify distinct latent factors of overlapping atrophy patterns from voxelwise structural MRIs of late-onset Alzheimer’s disease (AD) dementia patients. Our approach estimated the extent to which multiple distinct atrophy patterns were expressed within each participant rather than assuming that each participant expressed a single atrophy factor. The model revealed a temporal atrophy factor (medial temporal cortex, hippocampus, and amygdala), a subcortical atrophy factor (striatum, thalamus, and cerebellum), and a cortical atrophy factor (frontal, parietal, lateral temporal, and lateral occipital cortices). To explore the influence of each factor in early AD, atrophy factor compositions were inferred in beta-amyloid–positive (Aβ+) mild cognitively impaired (MCI) and cognitively normal (CN) participants. All three factors were associated with memory decline across the entire clinical spectrum, whereas the cortical factor was associated with executive function decline in Aβ+ MCI participants and AD dementia patients. Direct comparison between factors revealed that the temporal factor showed the strongest association with memory, whereas the cortical factor showed the strongest association with executive function. The subcortical factor was associated with the slowest decline for both memory and executive function compared with temporal and cortical factors. These results suggest that distinct patterns of atrophy influence decline across different cognitive domains. Quantification of this heterogeneity may enable the computation of individual-level predictions relevant for disease monitoring and customized therapies. Factor compositions of participants and code used in this article are publicly available for future research.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1611073113
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2016
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
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