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  • Proceedings of the National Academy of Sciences  (13)
  • English  (13)
  • 2020-2024  (13)
  • Biodiversity Research  (13)
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  • Proceedings of the National Academy of Sciences  (13)
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  • English  (13)
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  • 2020-2024  (13)
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  • 1
    Online Resource
    Online Resource
    Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium
    Proceedings of the National Academy of Sciences ; 2023
    In:  Proceedings of the National Academy of Sciences Vol. 120, No. 14 ( 2023-04-04)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 120, No. 14 ( 2023-04-04)
    Abstract: Left–right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case–control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case–control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case–control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case–control status. Subtle case–control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2213880120
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2023
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    SSG: 11
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  • 2
    Online Resource
    Online Resource
    Host–parasite coevolution and the stability of genetic kin recognition
    Proceedings of the National Academy of Sciences ; 2023
    In:  Proceedings of the National Academy of Sciences Vol. 120, No. 30 ( 2023-07-25)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 120, No. 30 ( 2023-07-25)
    Abstract: Crozier’s paradox suggests that genetic kin recognition will not be evolutionarily stable. The problem is that more common tags (markers) are more likely to be recognized and helped. This causes common tags to increase in frequency, eliminating the genetic variability that is required for genetic kin recognition. Two potential solutions to this problem have been suggested: host–parasite coevolution and multiple social encounters. We show that the host–parasite coevolution hypothesis does not work as commonly assumed. Host–parasite coevolution only stabilizes kin recognition at a parasite resistance locus if parasites adapt rapidly to hosts and cause intermediate or high levels of damage (virulence). Additionally, when kin recognition is stabilized at a parasite resistance locus, this can have an additional cost of making hosts more susceptible to parasites. However, we show that if the genetic architecture is allowed to evolve, meaning natural selection can choose the recognition locus, genetic kin recognition is more likely to be stable. The reason for this is that host–parasite coevolution can maintain tag diversity at another (neutral) locus by genetic hitchhiking, allowing that other locus to be used for genetic kin recognition. These results suggest a way that host–parasite coevolution can resolve Crozier’s paradox, without making hosts more susceptible to parasites. However, the opportunity for multiple social encounters may provide a more robust resolution of Crozier’s paradox.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2220761120
    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
    detail.hit.zdb_id: 1461794-8
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  • 3
    Online Resource
    Online Resource
    Experimentally simulating the evolution-to-ecology connection: Divergent predator morphologies alter natural food webs
    Proceedings of the National Academy of Sciences ; 2023
    In:  Proceedings of the National Academy of Sciences Vol. 120, No. 24 ( 2023-06-13)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 120, No. 24 ( 2023-06-13)
    Abstract: The idea that changing environmental conditions drive adaptive evolution is a pillar of evolutionary ecology. But, the opposite—that adaptive evolution alters ecological processes—has received far less attention yet is critical for eco-evolutionary dynamics. We assessed the ecological impact of divergent values in a key adaptive trait using 16 populations of the brown anole lizard ( Anolis sagrei ). Mirroring natural variation, we established islands with short- or long-limbed lizards at both low and high densities. We then monitored changes in lower trophic levels, finding that on islands with a high density of short-limbed lizards, web-spider densities decreased and plants grew more via an indirect positive effect, likely through an herbivore-mediated trophic cascade. Our experiment provides strong support for evolution-to-ecology connections in nature, likely closing an otherwise well-characterized eco-evolutionary feedback loop.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2221691120
    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
    detail.hit.zdb_id: 1461794-8
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  • 4
    Online Resource
    Online Resource
    Efficacy of a spatial repellent for control of Aedes -borne virus transmission: A cluster-randomized trial in Iquitos, Peru
    Proceedings of the National Academy of Sciences ; 2022
    In:  Proceedings of the National Academy of Sciences Vol. 119, No. 26 ( 2022-06-28)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 119, No. 26 ( 2022-06-28)
    Abstract: Over half the world’s population is at risk for viruses transmitted by Aedes mosquitoes, such as dengue and Zika. The primary vector, Aedes aegypti , thrives in urban environments. Despite decades of effort, cases and geographic range of Aedes -borne viruses (ABVs) continue to expand. Rigorously proven vector control interventions that measure protective efficacy against ABV diseases are limited to Wolbachia in a single trial in Indonesia and do not include any chemical intervention. Spatial repellents, a new option for efficient deployment, are designed to decrease human exposure to ABVs by releasing active ingredients into the air that disrupt mosquito–human contact. A parallel, cluster-randomized controlled trial was conducted in Iquitos, Peru, to quantify the impact of a transfluthrin-based spatial repellent on human ABV infection. From 2,907 households across 26 clusters (13 per arm), 1,578 participants were assessed for seroconversion (primary endpoint) by survival analysis. Incidence of acute disease was calculated among 16,683 participants (secondary endpoint). Adult mosquito collections were conducted to compare Ae. aegypti abundance, blood-fed rate, and parity status through mixed-effect difference-in-difference analyses. The spatial repellent significantly reduced ABV infection by 34.1% (one-sided 95% CI lower limit, 6.9%; one-sided P value = 0.0236, z = 1.98). Aedes aegypti abundance and blood-fed rates were significantly reduced by 28.6 (95% CI 24.1%, ∞); z = −9.11) and 12.4% (95% CI 4.2%, ∞); z = −2.43), respectively. Our trial provides conclusive statistical evidence from an appropriately powered, preplanned cluster-randomized controlled clinical trial of the impact of a chemical intervention, in this case a spatial repellent, to reduce the risk of ABV transmission compared to a placebo.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2118283119
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2022
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
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  • 5
    Online Resource
    Online Resource
    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
    detail.hit.zdb_id: 1461794-8
    SSG: 11
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  • 6
    Online Resource
    Online Resource
    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
    SSG: 11
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  • 7
    Online Resource
    Online Resource
    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)
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2113561119
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2022
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
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  • 8
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    Online Resource
    Genome-wide analyses of individual differences in quantitatively assessed reading- and language-related skills in up to 34,000 people
    Proceedings of the National Academy of Sciences ; 2022
    In:  Proceedings of the National Academy of Sciences Vol. 119, No. 35 ( 2022-08-30)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 119, No. 35 ( 2022-08-30)
    Abstract: The use of spoken and written language is a fundamental human capacity. Individual differences in reading- and language-related skills are influenced by genetic variation, with twin-based heritability estimates of 30 to 80% depending on the trait. The genetic architecture is complex, heterogeneous, and multifactorial, but investigations of contributions of single-nucleotide polymorphisms (SNPs) were thus far underpowered. We present a multicohort genome-wide association study (GWAS) of five traits assessed individually using psychometric measures (word reading, nonword reading, spelling, phoneme awareness, and nonword repetition) in samples of 13,633 to 33,959 participants aged 5 to 26 y. We identified genome-wide significant association with word reading (rs11208009, P = 1.098 × 10 −8 ) at a locus that has not been associated with intelligence or educational attainment. All five reading-/language-related traits showed robust SNP heritability, accounting for 13 to 26% of trait variability. Genomic structural equation modeling revealed a shared genetic factor explaining most of the variation in word/nonword reading, spelling, and phoneme awareness, which only partially overlapped with genetic variation contributing to nonword repetition, intelligence, and educational attainment. A multivariate GWAS of word/nonword reading, spelling, and phoneme awareness maximized power for follow-up investigation. Genetic correlation analysis with neuroimaging traits identified an association with the surface area of the banks of the left superior temporal sulcus, a brain region linked to the processing of spoken and written language. Heritability was enriched for genomic elements regulating gene expression in the fetal brain and in chromosomal regions that are depleted of Neanderthal variants. Together, these results provide avenues for deciphering the biological underpinnings of uniquely human traits.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2202764119
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2022
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
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  • 9
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    Online Resource
    The Earth BioGenome Project 2020: Starting the clock
    Proceedings of the National Academy of Sciences ; 2022
    In:  Proceedings of the National Academy of Sciences Vol. 119, No. 4 ( 2022-01-25)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 119, No. 4 ( 2022-01-25)
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    URL: Article
    DOI: 10.1073/pnas.2115635118
    DOI: 10.37473/fic/10.1073/pnas.2115635118
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2022
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
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  • 10
    Online Resource
    Online Resource
    Exploring the landscape of model representations
    Proceedings of the National Academy of Sciences ; 2020
    In:  Proceedings of the National Academy of Sciences Vol. 117, No. 39 ( 2020-09-29), p. 24061-24068
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 117, No. 39 ( 2020-09-29), p. 24061-24068
    Abstract: The success of any physical model critically depends upon adopting an appropriate representation for the phenomenon of interest. Unfortunately, it remains generally challenging to identify the essential degrees of freedom or, equivalently, the proper order parameters for describing complex phenomena. Here we develop a statistical physics framework for exploring and quantitatively characterizing the space of order parameters for representing physical systems. Specifically, we examine the space of low-resolution representations that correspond to particle-based coarse-grained (CG) models for a simple microscopic model of protein fluctuations. We employ Monte Carlo (MC) methods to sample this space and determine the density of states for CG representations as a function of their ability to preserve the configurational information, I , and large-scale fluctuations, Q , of the microscopic model. These two metrics are uncorrelated in high-resolution representations but become anticorrelated at lower resolutions. Moreover, our MC simulations suggest an emergent length scale for coarse-graining proteins, as well as a qualitative distinction between good and bad representations of proteins. Finally, we relate our work to recent approaches for clustering graphs and detecting communities in networks.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2000098117
    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
    SSG: 11
    SSG: 12
    Location Call Number Limitation Availability
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    Online Resource
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