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  • Proceedings of the National Academy of Sciences  (17)
  • 1
    Online-Ressource
    Online-Ressource
    Demographic history and rare allele sharing among human populations
    Proceedings of the National Academy of Sciences ; 2011
    In:  Proceedings of the National Academy of Sciences Vol. 108, No. 29 ( 2011-07-19), p. 11983-11988
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 108, No. 29 ( 2011-07-19), p. 11983-11988
    Kurzfassung: High-throughput sequencing technology enables population-level surveys of human genomic variation. Here, we examine the joint allele frequency distributions across continental human populations and present an approach for combining complementary aspects of whole-genome, low-coverage data and targeted high-coverage data. We apply this approach to data generated by the pilot phase of the Thousand Genomes Project, including whole-genome 2–4× coverage data for 179 samples from HapMap European, Asian, and African panels as well as high-coverage target sequencing of the exons of 800 genes from 697 individuals in seven populations. We use the site frequency spectra obtained from these data to infer demographic parameters for an Out-of-Africa model for populations of African, European, and Asian descent and to predict, by a jackknife-based approach, the amount of genetic diversity that will be discovered as sample sizes are increased. We predict that the number of discovered nonsynonymous coding variants will reach 100,000 in each population after ∼1,000 sequenced chromosomes per population, whereas ∼2,500 chromosomes will be needed for the same number of synonymous variants. Beyond this point, the number of segregating sites in the European and Asian panel populations is expected to overcome that of the African panel because of faster recent population growth. Overall, we find that the majority of human genomic variable sites are rare and exhibit little sharing among diverged populations. Our results emphasize that replication of disease association for specific rare genetic variants across diverged populations must overcome both reduced statistical power because of rarity and higher population divergence.
    Materialart: Online-Ressource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1019276108
    RVK:
    TA 1000
    RVK:
    WA 15000
    Sprache: Englisch
    Verlag: Proceedings of the National Academy of Sciences
    Publikationsdatum: 2011
    ZDB Id: 209104-5
    ZDB Id: 1461794-8
    SSG: 11
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 2
    Online-Ressource
    Online-Ressource
    Characterization of HPV and host genome interactions in primary head and neck cancers
    Proceedings of the National Academy of Sciences ; 2014
    In:  Proceedings of the National Academy of Sciences Vol. 111, No. 43 ( 2014-10-28), p. 15544-15549
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 111, No. 43 ( 2014-10-28), p. 15544-15549
    Kurzfassung: Previous studies have established that a subset of head and neck tumors contains human papillomavirus (HPV) sequences and that HPV-driven head and neck cancers display distinct biological and clinical features. HPV is known to drive cancer by the actions of the E6 and E7 oncoproteins, but the molecular architecture of HPV infection and its interaction with the host genome in head and neck cancers have not been comprehensively described. We profiled a cohort of 279 head and neck cancers with next generation RNA and DNA sequencing and show that 35 (12.5%) tumors displayed evidence of high-risk HPV types 16, 33, or 35. Twenty-five cases had integration of the viral genome into one or more locations in the human genome with statistical enrichment for genic regions. Integrations had a marked impact on the human genome and were associated with alterations in DNA copy number, mRNA transcript abundance and splicing, and both inter- and intrachromosomal rearrangements. Many of these events involved genes with documented roles in cancer. Cancers with integrated vs. nonintegrated HPV displayed different patterns of DNA methylation and both human and viral gene expressions. Together, these data provide insight into the mechanisms by which HPV interacts with the human genome beyond expression of viral oncoproteins and suggest that specific integration events are an integral component of viral oncogenesis.
    Materialart: Online-Ressource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1416074111
    RVK:
    TA 1000
    RVK:
    WA 15000
    Sprache: Englisch
    Verlag: Proceedings of the National Academy of Sciences
    Publikationsdatum: 2014
    ZDB Id: 209104-5
    ZDB Id: 1461794-8
    SSG: 11
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 3
    Online-Ressource
    Online-Ressource
    Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States
    Proceedings of the National Academy of Sciences ; 2022
    In:  Proceedings of the National Academy of Sciences Vol. 119, No. 15 ( 2022-04-12)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 119, No. 15 ( 2022-04-12)
    Kurzfassung: Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub ( https://covid19forecasthub.org/ ) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.
    Materialart: Online-Ressource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2113561119
    RVK:
    TA 1000
    RVK:
    WA 15000
    Sprache: Englisch
    Verlag: Proceedings of the National Academy of Sciences
    Publikationsdatum: 2022
    ZDB Id: 209104-5
    ZDB Id: 1461794-8
    SSG: 11
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 4
    Online-Ressource
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    Identification of tumorigenic cells and therapeutic targets in pancreatic neuroendocrine tumors
    Proceedings of the National Academy of Sciences ; 2016
    In:  Proceedings of the National Academy of Sciences Vol. 113, No. 16 ( 2016-04-19), p. 4464-4469
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 113, No. 16 ( 2016-04-19), p. 4464-4469
    Kurzfassung: Pancreatic neuroendocrine tumors (PanNETs) are a type of pancreatic cancer with limited therapeutic options. Consequently, most patients with advanced disease die from tumor progression. Current evidence indicates that a subset of cancer cells is responsible for tumor development, metastasis, and recurrence, and targeting these tumor-initiating cells is necessary to eradicate tumors. However, tumor-initiating cells and the biological processes that promote pathogenesis remain largely uncharacterized in PanNETs. Here we profile primary and metastatic tumors from an index patient and demonstrate that MET proto-oncogene activation is important for tumor growth in PanNET xenograft models. We identify a highly tumorigenic cell population within several independent surgically acquired PanNETs characterized by increased cell-surface protein CD90 expression and aldehyde dehydrogenase A1 (ALDHA1) activity, and provide in vitro and in vivo evidence for their stem-like properties. We performed proteomic profiling of 332 antigens in two cell lines and four primary tumors, and showed that CD47, a cell-surface protein that acts as a “don’t eat me” signal co-opted by cancers to evade innate immune surveillance, is ubiquitously expressed. Moreover, CD47 coexpresses with MET and is enriched in CD90 hi cells. Furthermore, blocking CD47 signaling promotes engulfment of tumor cells by macrophages in vitro and inhibits xenograft tumor growth, prevents metastases, and prolongs survival in vivo.
    Materialart: Online-Ressource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1600007113
    RVK:
    TA 1000
    RVK:
    WA 15000
    Sprache: Englisch
    Verlag: Proceedings of the National Academy of Sciences
    Publikationsdatum: 2016
    ZDB Id: 209104-5
    ZDB Id: 1461794-8
    SSG: 11
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 5
    Online-Ressource
    Online-Ressource
    Kv1.3 channels are a therapeutic target for T cell-mediated autoimmune diseases
    Proceedings of the National Academy of Sciences ; 2006
    In:  Proceedings of the National Academy of Sciences Vol. 103, No. 46 ( 2006-11-14), p. 17414-17419
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 103, No. 46 ( 2006-11-14), p. 17414-17419
    Kurzfassung: Autoreactive memory T lymphocytes are implicated in the pathogenesis of autoimmune diseases. Here we demonstrate that disease-associated autoreactive T cells from patients with type-1 diabetes mellitus or rheumatoid arthritis (RA) are mainly CD4 + CCR7 − CD45RA − effector memory T cells (T EM cells) with elevated Kv1.3 potassium channel expression. In contrast, T cells with other antigen specificities from these patients, or autoreactive T cells from healthy individuals and disease controls, express low levels of Kv1.3 and are predominantly naïve or central-memory (T CM ) cells. In T EM cells, Kv1.3 traffics to the immunological synapse during antigen presentation where it colocalizes with Kvβ2, SAP97, ZIP, p56 lck , and CD4. Although Kv1.3 inhibitors [ShK(L5)-amide (SL5) and PAP1] do not prevent immunological synapse formation, they suppress Ca 2+ -signaling, cytokine production, and proliferation of autoantigen-specific T EM cells at pharmacologically relevant concentrations while sparing other classes of T cells. Kv1.3 inhibitors ameliorate pristane-induced arthritis in rats and reduce the incidence of experimental autoimmune diabetes in diabetes-prone (DP-BB/W) rats. Repeated dosing with Kv1.3 inhibitors in rats has not revealed systemic toxicity. Further development of Kv1.3 blockers for autoimmune disease therapy is warranted.
    Materialart: Online-Ressource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.0605136103
    RVK:
    TA 1000
    RVK:
    WA 15000
    Sprache: Englisch
    Verlag: Proceedings of the National Academy of Sciences
    Publikationsdatum: 2006
    ZDB Id: 209104-5
    ZDB Id: 1461794-8
    SSG: 11
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 6
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    Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter
    Proceedings of the National Academy of Sciences ; 2018
    In:  Proceedings of the National Academy of Sciences Vol. 115, No. 38 ( 2018-09-18), p. 9592-9597
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 115, No. 38 ( 2018-09-18), p. 9592-9597
    Kurzfassung: Exposure to ambient fine particulate matter (PM 2.5 ) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM 2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM 2.5 -mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM 2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries—the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5–10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9–8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3–4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM 2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.
    Materialart: Online-Ressource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1803222115
    RVK:
    TA 1000
    RVK:
    WA 15000
    Sprache: Englisch
    Verlag: Proceedings of the National Academy of Sciences
    Publikationsdatum: 2018
    ZDB Id: 209104-5
    ZDB Id: 1461794-8
    SSG: 11
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 7
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    Anti-SIRPα antibody immunotherapy enhances neutrophil and macrophage antitumor activity
    Proceedings of the National Academy of Sciences ; 2017
    In:  Proceedings of the National Academy of Sciences Vol. 114, No. 49 ( 2017-12-05)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 114, No. 49 ( 2017-12-05)
    Kurzfassung: Cancer immunotherapy has emerged as a promising therapeutic intervention. However, complete and durable responses are only seen in a fraction of patients who have cancer. A key factor that limits therapeutic success is the infiltration of tumors by cells of the myeloid lineage. The inhibitory receptor signal regulatory protein-α (SIRPα) is a myeloid-specific immune checkpoint that engages the “don’t eat me” signal CD47 expressed on tumors and normal tissues. We therefore developed the monoclonal antibody KWAR23, which binds human SIRPα with high affinity and disrupts its binding to CD47. Administered by itself, KWAR23 is inert, but given in combination with tumor-opsonizing monoclonal antibodies, KWAR23 greatly augments myeloid cell-dependent killing of a collection of hematopoietic and nonhematopoietic human tumor-derived cell lines. Following KWAR23 antibody treatment in a human SIRPA knockin mouse model, both neutrophils and macrophages infiltrate a human Burkitt’s lymphoma xenograft and inhibit tumor growth, generating complete responses in the majority of treated animals. We further demonstrate that a bispecific anti-CD70/SIRPα antibody outperforms individually delivered antibodies in specific types of cancers. These studies demonstrate that SIRPα blockade induces potent antitumor activity by targeting multiple myeloid cell subsets that frequently infiltrate tumors. Thus, KWAR23 represents a promising candidate for combination therapy.
    Materialart: Online-Ressource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1710877114
    RVK:
    TA 1000
    RVK:
    WA 15000
    Sprache: Englisch
    Verlag: Proceedings of the National Academy of Sciences
    Publikationsdatum: 2017
    ZDB Id: 209104-5
    ZDB Id: 1461794-8
    SSG: 11
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 8
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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)
    Kurzfassung: 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.
    Materialart: Online-Ressource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2214634120
    RVK:
    TA 1000
    RVK:
    WA 15000
    Sprache: Englisch
    Verlag: Proceedings of the National Academy of Sciences
    Publikationsdatum: 2023
    ZDB Id: 209104-5
    ZDB Id: 1461794-8
    SSG: 11
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
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  • 9
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    Crop pests and predators exhibit inconsistent responses to surrounding landscape composition
    Proceedings of the National Academy of Sciences ; 2018
    In:  Proceedings of the National Academy of Sciences Vol. 115, No. 33 ( 2018-08-14)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 115, No. 33 ( 2018-08-14)
    Kurzfassung: The idea that noncrop habitat enhances pest control and represents a win–win opportunity to conserve biodiversity and bolster yields has emerged as an agroecological paradigm. However, while noncrop habitat in landscapes surrounding farms sometimes benefits pest predators, natural enemy responses remain heterogeneous across studies and effects on pests are inconclusive. The observed heterogeneity in species responses to noncrop habitat may be biological in origin or could result from variation in how habitat and biocontrol are measured. Here, we use a pest-control database encompassing 132 studies and 6,759 sites worldwide to model natural enemy and pest abundances, predation rates, and crop damage as a function of landscape composition. Our results showed that although landscape composition explained significant variation within studies, pest and enemy abundances, predation rates, crop damage, and yields each exhibited different responses across studies, sometimes increasing and sometimes decreasing in landscapes with more noncrop habitat but overall showing no consistent trend. Thus, models that used landscape-composition variables to predict pest-control dynamics demonstrated little potential to explain variation across studies, though prediction did improve when comparing studies with similar crop and landscape features. Overall, our work shows that surrounding noncrop habitat does not consistently improve pest management, meaning habitat conservation may bolster production in some systems and depress yields in others. Future efforts to develop tools that inform farmers when habitat conservation truly represents a win–win would benefit from increased understanding of how landscape effects are modulated by local farm management and the biology of pests and their enemies.
    Materialart: Online-Ressource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1800042115
    RVK:
    TA 1000
    RVK:
    WA 15000
    Sprache: Englisch
    Verlag: Proceedings of the National Academy of Sciences
    Publikationsdatum: 2018
    ZDB Id: 209104-5
    ZDB Id: 1461794-8
    SSG: 11
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
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    Online-Ressource
  • 10
    Online-Ressource
    Online-Ressource
    An open challenge to advance probabilistic forecasting for dengue epidemics
    Proceedings of the National Academy of Sciences ; 2019
    In:  Proceedings of the National Academy of Sciences Vol. 116, No. 48 ( 2019-11-26), p. 24268-24274
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 116, No. 48 ( 2019-11-26), p. 24268-24274
    Kurzfassung: A wide range of research has promised new tools for forecasting infectious disease dynamics, but little of that research is currently being applied in practice, because tools do not address key public health needs, do not produce probabilistic forecasts, have not been evaluated on external data, or do not provide sufficient forecast skill to be useful. We developed an open collaborative forecasting challenge to assess probabilistic forecasts for seasonal epidemics of dengue, a major global public health problem. Sixteen teams used a variety of methods and data to generate forecasts for 3 epidemiological targets (peak incidence, the week of the peak, and total incidence) over 8 dengue seasons in Iquitos, Peru and San Juan, Puerto Rico. Forecast skill was highly variable across teams and targets. While numerous forecasts showed high skill for midseason situational awareness, early season skill was low, and skill was generally lowest for high incidence seasons, those for which forecasts would be most valuable. A comparison of modeling approaches revealed that average forecast skill was lower for models including biologically meaningful data and mechanisms and that both multimodel and multiteam ensemble forecasts consistently outperformed individual model forecasts. Leveraging these insights, data, and the forecasting framework will be critical to improve forecast skill and the application of forecasts in real time for epidemic preparedness and response. Moreover, key components of this project—integration with public health needs, a common forecasting framework, shared and standardized data, and open participation—can help advance infectious disease forecasting beyond dengue.
    Materialart: Online-Ressource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1909865116
    RVK:
    TA 1000
    RVK:
    WA 15000
    Sprache: Englisch
    Verlag: Proceedings of the National Academy of Sciences
    Publikationsdatum: 2019
    ZDB Id: 209104-5
    ZDB Id: 1461794-8
    SSG: 11
    SSG: 12
    Standort Signatur Einschränkungen Verfügbarkeit
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    Online-Ressource
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