13 research outputs found

    Relationships Between Borders, Management Agencies, and the Likelihood of Watershed Impairment

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    In the United States, the Clean Water Act (CWA) establishes water quality standards important for maintaining healthy freshwater ecosystems. Within the CWA framework, states define their own water quality criteria, leading to a potential fragmentation of standards between states. This fragmentation can influence the management of shared water resources and produce spillover effects of pollutants crossing state lines and other political boundaries. We used numerical simulations to test the null prediction of no difference in impairment between watersheds that cross political boundaries (i.e. state lines, national or coastal borders, hereafter termed “transboundary”) and watersheds that cross no boundaries (hereafter “internal”). We found that transboundary watersheds are more likely to be impaired than internal watersheds. Further, we examined possible causes for this relationship based on both geographic and sociopolitical drivers. Though geographic variables such as human-modified land cover and the amount of upstream catchment area are associated with watershed impairment, the number and type of agencies managing land within a watershed better explained the different impairment levels between transboundary and internal watersheds. Watersheds primarily consisting of public lands are less impaired than watersheds consisting of private lands. Similarly, watersheds primarily managed by federal agencies are less impaired than state-managed watersheds. Our results highlight the importance of considering Integrated Watershed Management strategies for water resources within a fragmented policy framework

    Polygenic transcriptome risk scores for COPD and lung function improve cross-ethnic portability of prediction in the NHLBI TOPMed program

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    While polygenic risk scores (PRSs) enable early identification of genetic risk for chronic obstructive pulmonary disease (COPD), predictive performance is limited when the discovery and target populations are not well matched. Hypothesizing that the biological mechanisms of disease are shared across ancestry groups, we introduce a PrediXcan-derived polygenic transcriptome risk score (PTRS) to improve cross-ethnic portability of risk prediction. We constructed the PTRS using summary statistics from application of PrediXcan on large-scale GWASs of lung function (forced expiratory volume in 1 s [FEV1] and its ratio to forced vital capacity [FEV1/FVC]) in the UK Biobank. We examined prediction performance and cross-ethnic portability of PTRS through smoking-stratified analyses both on 29,381 multi-ethnic participants from TOPMed population/family-based cohorts and on 11,771 multi-ethnic participants from TOPMed COPD-enriched studies. Analyses were carried out for two dichotomous COPD traits (moderate-to-severe and severe COPD) and two quantitative lung function traits (FEV1 and FEV1/FVC). While the proposed PTRS showed weaker associations with disease than PRS for European ancestry, the PTRS showed stronger association with COPD than PRS for African Americans (e.g., odds ratio [OR] = 1.24 [95% confidence interval [CI]: 1.08-1.43] for PTRS versus 1.10 [0.96-1.26] for PRS among heavy smokers with ≥ 40 pack-years of smoking) for moderate-to-severe COPD. Cross-ethnic portability of the PTRS was significantly higher than the PRS (paired t test p < 2.2 Ă— 10-16 with portability gains ranging from 5% to 28%) for both dichotomous COPD traits and across all smoking strata. Our study demonstrates the value of PTRS for improved cross-ethnic portability compared to PRS in predicting COPD risk
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