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1.
Int J Epidemiol ; 2021 Mar 23.
Artigo em Inglês | MEDLINE | ID: mdl-33755131

RESUMO

BACKGROUND: Rigorous evaluation of the calibration and discrimination of breast-cancer risk-prediction models in prospective cohorts is critical for applications under clinical guidelines. We comprehensively evaluated an integrated model incorporating classical risk factors and a 313-variant polygenic risk score (PRS) to predict breast-cancer risk. METHODS: Fifteen prospective cohorts from six countries with 239 340 women (7646 incident breast-cancer cases) of European ancestry aged 19-75 years were included. Calibration of 5-year risk was assessed by comparing expected and observed proportions of cases overall and within risk categories. Risk stratification for women of European ancestry aged 50-70 years in those countries was evaluated by the proportion of women and future cases crossing clinically relevant risk thresholds. RESULTS: Among women <50 years old, the median (range) expected-to-observed ratio for the integrated model across 15 cohorts was 0.9 (0.7-1.0) overall and 0.9 (0.7-1.4) at the highest-risk decile; among women ≥50 years old, these were 1.0 (0.7-1.3) and 1.2 (0.7-1.6), respectively. The proportion of women identified above a 3% 5-year risk threshold (used for recommending risk-reducing medications in the USA) ranged from 7.0% in Germany (∼841 000 of 12 million) to 17.7% in the USA (∼5.3 of 30 million). At this threshold, 14.7% of US women were reclassified by adding the PRS to classical risk factors, with identification of 12.2% of additional future cases. CONCLUSION: Integrating a 313-variant PRS with classical risk factors can improve the identification of European-ancestry women at elevated risk who could benefit from targeted risk-reducing strategies under current clinical guidelines.

2.
Nature ; 591(7849): 211-219, 2021 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-33692554

RESUMO

Polygenic risk scores (PRSs), which often aggregate results from genome-wide association studies, can bridge the gap between initial discovery efforts and clinical applications for the estimation of disease risk using genetics. However, there is notable heterogeneity in the application and reporting of these risk scores, which hinders the translation of PRSs into clinical care. Here, in a collaboration between the Clinical Genome Resource (ClinGen) Complex Disease Working Group and the Polygenic Score (PGS) Catalog, we present the Polygenic Risk Score Reporting Standards (PRS-RS), in which we update the Genetic Risk Prediction Studies (GRIPS) Statement to reflect the present state of the field. Drawing on the input of experts in epidemiology, statistics, disease-specific applications, implementation and policy, this comprehensive reporting framework defines the minimal information that is needed to interpret and evaluate PRSs, especially with respect to downstream clinical applications. Items span detailed descriptions of study populations, statistical methods for the development and validation of PRSs and considerations for the potential limitations of these scores. In addition, we emphasize the need for data availability and transparency, and we encourage researchers to deposit and share PRSs through the PGS Catalog to facilitate reproducibility and comparative benchmarking. By providing these criteria in a structured format that builds on existing standards and ontologies, the use of this framework in publishing PRSs will facilitate translation into clinical care and progress towards defining best practice.

3.
Breast Cancer Res ; 23(1): 22, 2021 Feb 15.
Artigo em Inglês | MEDLINE | ID: mdl-33588869

RESUMO

BACKGROUND: The Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) and the Tyrer-Cuzick breast cancer risk prediction models are commonly used in clinical practice and have recently been extended to include polygenic risk scores (PRS). In addition, BOADICEA has also been extended to include reproductive and lifestyle factors, which were already part of Tyrer-Cuzick model. We conducted a comparative prospective validation of these models after incorporating the recently developed 313-variant PRS. METHODS: Calibration and discrimination of 5-year absolute risk was assessed in a nested case-control sample of 1337 women of European ancestry (619 incident breast cancer cases) aged 23-75 years from the Generations Study. RESULTS: The extended BOADICEA model with reproductive/lifestyle factors and PRS was well calibrated across risk deciles; expected-to-observed ratio (E/O) at the highest risk decile :0.97 (95 % CI 0.51 - 1.86) for women younger than 50 years and 1.09 (0.66 - 1.80) for women 50 years or older. Adding reproductive/lifestyle factors and PRS to the BOADICEA model improved discrimination modestly in younger women (area under the curve (AUC) 69.7 % vs. 69.1%) and substantially in older women (AUC 64.6 % vs. 56.8%). The Tyrer-Cuzick model with PRS showed evidence of overestimation at the highest risk decile: E/O = 1.54(0.81 - 2.92) for younger and 1.73 (1.03 - 2.90) for older women. CONCLUSION: The extended BOADICEA model identified women in a European-ancestry population at elevated breast cancer risk more accurately than the Tyrer-Cuzick model with PRS. With the increasing availability of PRS, these analyses can inform choice of risk models incorporating PRS for risk stratified breast cancer prevention among women of European ancestry.

4.
Cancer Res ; 81(6): 1607-1615, 2021 Mar 15.
Artigo em Inglês | MEDLINE | ID: mdl-33472890

RESUMO

Lung cancer is the leading cause of cancer-related death globally. An improved risk stratification strategy can increase efficiency of low-dose CT (LDCT) screening. Here we assessed whether individual's genetic background has clinical utility for risk stratification in the context of LDCT screening. On the basis of 13,119 patients with lung cancer and 10,008 controls with European ancestry in the International Lung Cancer Consortium, we constructed a polygenic risk score (PRS) via 10-fold cross-validation with regularized penalized regression. The performance of risk model integrating PRS, including calibration and ability to discriminate, was assessed using UK Biobank data (N = 335,931). Absolute risk was estimated on the basis of age-specific lung cancer incidence and all-cause mortality as competing risk. To evaluate its potential clinical utility, the PRS distribution was simulated in the National Lung Screening Trial (N = 50,772 participants). The lung cancer ORs for individuals at the top decile of the PRS distribution versus those at bottom 10% was 2.39 [95% confidence interval (CI) = 1.92-3.00; P = 1.80 × 10-14] in the validation set (P trend = 5.26 × 10-20). The OR per SD of PRS increase was 1.26 (95% CI = 1.20-1.32; P = 9.69 × 10-23) for overall lung cancer risk in the validation set. When considering absolute risks, individuals at different PRS deciles showed differential trajectories of 5-year and cumulative absolute risk. The age reaching the LDCT screening recommendation threshold can vary by 4 to 8 years, depending on the individual's genetic background, smoking status, and family history. Collectively, these results suggest that individual's genetic background may inform the optimal lung cancer LDCT screening strategy. SIGNIFICANCE: Three large-scale datasets reveal that, after accounting for risk factors, an individual's genetics can affect their lung cancer risk trajectory, thus may inform the optimal timing for LDCT screening.

5.
Int J Epidemiol ; 2021 Jan 04.
Artigo em Inglês | MEDLINE | ID: mdl-33393617

RESUMO

BACKGROUND: Previous studies have often evaluated methods for Mendelian randomization (MR) analysis based on simulations that do not adequately reflect the data-generating mechanisms in genome-wide association studies (GWAS) and there are often discrepancies in the performance of MR methods in simulations and real data sets. METHODS: We use a simulation framework that generates data on full GWAS for two traits under a realistic model for effect-size distribution coherent with the heritability, co-heritability and polygenicity typically observed for complex traits. We further use recent data generated from GWAS of 38 biomarkers in the UK Biobank and performed down sampling to investigate trends in estimates of causal effects of these biomarkers on the risk of type 2 diabetes (T2D). RESULTS: Simulation studies show that weighted mode and MRMix are the only two methods that maintain the correct type I error rate in a diverse set of scenarios. Between the two methods, MRMix tends to be more powerful for larger GWAS whereas the opposite is true for smaller sample sizes. Among the other methods, random-effect IVW (inverse-variance weighted method), MR-Robust and MR-RAPS (robust adjust profile score) tend to perform best in maintaining a low mean-squared error when the InSIDE assumption is satisfied, but can produce large bias when InSIDE is violated. In real-data analysis, some biomarkers showed major heterogeneity in estimates of their causal effects on the risk of T2D across the different methods and estimates from many methods trended in one direction with increasing sample size with patterns similar to those observed in simulation studies. CONCLUSION: The relative performance of different MR methods depends heavily on the sample sizes of the underlying GWAS, the proportion of valid instruments and the validity of the InSIDE assumption. Down-sampling analysis can be used in large GWAS for the possible detection of bias in the MR methods.

6.
Nat Med ; 27(2): 264-269, 2021 02.
Artigo em Inglês | MEDLINE | ID: mdl-33311702

RESUMO

Reducing COVID-19 burden for populations will require equitable and effective risk-based allocations of scarce preventive resources, including vaccinations1. To aid in this effort, we developed a general population risk calculator for COVID-19 mortality based on various sociodemographic factors and pre-existing conditions for the US population, combining information from the UK-based OpenSAFELY study with mortality rates by age and ethnicity across US states. We tailored the tool to produce absolute risk estimates in future time frames by incorporating information on pandemic dynamics at the community level. We applied the model to data on risk factor distribution from a variety of sources to project risk for the general adult population across 477 US cities and for the Medicare population aged 65 years and older across 3,113 US counties, respectively. Validation analyses using 54,444 deaths from 7 June to 1 October 2020 show that the model is well calibrated for the US population. Projections show that the model can identify relatively small fractions of the population (for example 4.3%) that might experience a disproportionately large number of deaths (for example 48.7%), but there is wide variation in risk across communities. We provide a web-based risk calculator and interactive maps for viewing community-level risks.


Assuntos
/mortalidade , Características de Residência , Adulto , Política de Saúde , Humanos , Mortalidade , Reprodutibilidade dos Testes , Fatores de Risco , Estados Unidos/epidemiologia
7.
PLoS Genet ; 16(12): e1009218, 2020 Dec 08.
Artigo em Inglês | MEDLINE | ID: mdl-33290408

RESUMO

There is increasing evidence that pleiotropy, the association of multiple traits with the same genetic variants/loci, is a very common phenomenon. Cross-phenotype association tests are often used to jointly analyze multiple traits from a genome-wide association study (GWAS). The underlying methods, however, are often designed to test the global null hypothesis that there is no association of a genetic variant with any of the traits, the rejection of which does not implicate pleiotropy. In this article, we propose a new statistical approach, PLACO, for specifically detecting pleiotropic loci between two traits by considering an underlying composite null hypothesis that a variant is associated with none or only one of the traits. We propose testing the null hypothesis based on the product of the Z-statistics of the genetic variants across two studies and derive a null distribution of the test statistic in the form of a mixture distribution that allows for fractions of variants to be associated with none or only one of the traits. We borrow approaches from the statistical literature on mediation analysis that allow asymptotic approximation of the null distribution avoiding estimation of nuisance parameters related to mixture proportions and variance components. Simulation studies demonstrate that the proposed method can maintain type I error and can achieve major power gain over alternative simpler methods that are typically used for testing pleiotropy. PLACO allows correlation in summary statistics between studies that may arise due to sharing of controls between disease traits. Application of PLACO to publicly available summary data from two large case-control GWAS of Type 2 Diabetes and of Prostate Cancer implicated a number of novel shared genetic regions: 3q23 (ZBTB38), 6q25.3 (RGS17), 9p22.1 (HAUS6), 9p13.3 (UBAP2), 11p11.2 (RAPSN), 14q12 (AKAP6), 15q15 (KNL1) and 18q23 (ZNF236).

8.
Circulation ; 2020 Nov 30.
Artigo em Inglês | MEDLINE | ID: mdl-33249881

RESUMO

Background: Recent clinical guidelines support intensive blood pressure (BP) treatment targets. However, observational data suggest that excessive diastolic BP (DBP) lowering might increase the risk of myocardial infarction (MI); reflecting a J- or U-shaped relationship. Methods: We analyzed 47,407 participants from 5 cohorts (median age 60 years). First, to corroborate prior observational analyses, we used traditional statistical methods to test the shape of association between DBP and CVD. Second, we created polygenic risk scores (PRS) of DBP and SBP and generated linear Mendelian randomization (MR) estimates for the effect of DBP on CVD. Third, using novel non-linear MR approaches, we evaluated for non-linearity in the genetic relationship between DBP and CVD. Comprehensive MR interrogation of DBP required us to also model SBP, given the two are strongly correlated. Results: Traditional observational analysis of our cohorts suggested a J-shaped association between DBP and MI. By contrast, linear MR analyses demonstrated an adverse effect of increasing DBP increments on CVD outcomes, including MI (MI Hazard ratio = 1.07 per unit mmHg increase in DBP, p<0.001). Furthermore, non-linear MR analyses found no evidence for a J-shaped relationship, instead confirming that MI risk decreases consistently per unit decrease in DBP, even among individuals with low values of baseline DBP. Conclusions: In this analysis of the genetic effect of DBP, we found no evidence for a non-linear J- or U-shaped relationship between DBP and adverse CVD outcomes; including MI.

9.
Artigo em Inglês | MEDLINE | ID: mdl-33187967

RESUMO

BACKGROUND: Past history of gallstones is associated with increased risk of gallbladder cancer (GBC) in observational studies. We conducted complementary observational and Mendelian Randomization (MR) analyses to determine whether history of gallstones is causally related to development of GBC in an Indian population. METHODS: To investigate associations between history of gallstones and GBC, we used questionnaire and imaging data from a GBC case-control study conducted at Tata Memorial Hospital, Mumbai (cases=1170; controls=2525). We then used 26 genetic variants identified in a genome-wide association study of 27,174 gallstones cases and 736,838 controls of European ancestry in a Mendelian randomization approach to assess causality. The association of these genetic variants with both gallstones and GBC was examined in the GBC case-control study. Various complementary MR approaches were used to evaluate the robustness of our results in the presence of pleiotropy and heterogeneity, and to consider the suitability of the selected SNPs as genetic instruments for gallstones in an Indian population. RESULTS: We found a strong observational association between gallstones and GBC using self-reported history of gallstones (OR=4.5, 95%CI=3.5-5.8) and with objective measures of gallstone presence using imaging techniques (OR=2.0, 95%CI=1.5-2.7). We found consistent causal estimates across all MR techniques, with odds ratios for GBC in the range of 1.3-1.6. CONCLUSIONS: Our findings indicate a causal relationship between history of gallstones and increased risk of GBC, albeit of a smaller magnitude to those found in observational analysis. IMPACT: Our findings emphasise the importance of gallstone treatment for preventing GBC in high risk individuals.

10.
Sci Rep ; 10(1): 18888, 2020 11 03.
Artigo em Inglês | MEDLINE | ID: mdl-33144654

RESUMO

Roads impact wildlife in multiple ways, most conspicuous amongst which are animal-vehicle collisions (AVCs). Mitigation measures to reduce AVCs at the local scale are often centred on species-specific crossing zones and collision hotspots. However, at the road network scale, consideration of interactions among road, species and traffic characteristics influencing AVC occurrence is required to design effective mitigation strategies. We modelled traversability-the probability of an animal successfully crossing a road- across an Indian highway for six large mammal species under different scenarios of road and traffic characteristics. Among the study species, group-living and slow-moving animals had higher AVC probabilities that increased significantly with increasing traffic volume and proportions of heavy vehicles in the traffic flow. The risk of AVC was higher for species that were active near roadside habitat during peak traffic hours. Our approach could help identify roads that pose potential mortality risks to animals using empirical data on animal and traffic characteristics. Results suggest that regulating traffic volume and heterogeneity on existing road stretches could potentially reduce animal mortality and barrier effect. Mitigation on roads expected to carry heavy traffic loads passing through ecologically-sensitive areas should be prioritised to ensure traversability for animal communities.

11.
Artigo em Inglês | MEDLINE | ID: mdl-33000171

RESUMO

BACKGROUND: Objective measures of physical activity (PA) derived from wrist-worn accelerometers are compared with traditional risk factors in terms of mortality prediction performance in the UK Biobank. METHODS: A subset of participants in the UK Biobank study wore a tri-axial wrist-worn accelerometer in a free-living environment for up to 7 days. A total of 82,304 individuals over the age of 50 (439,707 person-years of follow-up, 1,959 deaths) had both accelerometry data that met specified quality criteria and complete data on a set of traditional mortality risk factors. Predictive performance was assessed using cross-validated Concordance (C) for Cox regression models. Forward selection was used to obtain a set of best predictors of mortality. RESULTS: In univariate Cox regression, age was the best predictor of all-cause mortality (C=0.681) followed by twelve PA predictors, led by minutes of moderate to vigorous PA (C=0.661) and total acceleration (C=0.661). Overall, 16 of the top 20 predictors were objective PA measures (C from 0.578 to 0.661). Using a threshold of 0.001 improvement in Concordance, the Concordance for the best model that did not include PA measures was 0.735 (9 covariates) compared with 0.748 (12 covariates) for the best model with PA variables (p-value<0.001). CONCLUSIONS: Objective measures of PA derived from accelerometry outperform traditional predictors of all-cause mortality in the UK Biobank except age and substantially improve the prediction performance of mortality models based on traditional risk factors. Results confirm and complement previous findings in the National Health and Nutrition Examination Survey (NHANES).

12.
Am J Epidemiol ; 2020 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-32870973

RESUMO

Several statistical methods have been proposed for testing gene(G)-environment(E) interactions under additive risk models using genome-wide association study data. However, these approaches have strong assumptions on underlying genetic models such as dominant or recessive effects that are known to be less robust when the true genetic model is unknown. We aim to develop a robust trend test employing a likelihood ratio test for detecting G-E interaction under an additive risk model, while incorporating the G-E independence assumption to increase power. We used a constrained likelihood to impose two sets of constraints for (i) the linear trend effect of genotype and (ii) the additive joint effects of G and E. To incorporate the G-E independence assumption, a retrospective likelihood was used versus a standard prospective likelihood. Numerical investigation suggests that the proposed tests are more powerful than tests assuming dominant, recessive, or general models under various parameter settings and under both likelihoods. Incorporation of the independence assumption enhances efficiency by 2.5- fold. We applied the proposed methods to examine gene-smoking interaction for lung cancer and gene-APOE*4 interaction for Alzheimer's disease, which identified two interactions between APOE*4 and loci MS4A and BIN1 at genome-wide significance that were replicated using independent data.

13.
Zool Stud ; 59: e11, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32760457

RESUMO

In-depth knowledge of distribution and factors influencing it is important for species conservation and management. Many forms of such data have led to the development of new analytical techniques for better interpretation. For mountainous terrains with certain limitations, species data are obtained in the presence-only form. The point process model is one of the recent approaches for modelling such data, taking care of pseudo-absences and spatial independence. For conservation in regions with limited resources and species with similar ecological requirements, it is important to properly assess the extent of competition extent between wild and domestic species. We attempted to use point process framework to estimate the function of resource selection in blue sheep (Pseudois nayaur) in areas influenced by pastoralism in a western Himalayan region. Our study is the first attempt to use this framework to estimate resource selection on a dataset not collected using radio-telemetry. Spatial locations of blue sheep and livestock and a background sample of random points with six topographic covariates were used to model resource selection probability via intensity function. Blue sheep showed its predicted presence in areas with open vegetation coinciding with alpine meadows, influenced by southern aspect keeping a threshold distance of 600-1000 m from cliffs (escape terrain). Livestock, also showed presence probability in open vegetation, but at lower altitudes, mainly on valley floors. Our results suggest that though blue sheep continued to use the same habitat type after livestock arrival, they selected different resources based on topographic factors. Livestock were in areas where it was convenient for pastoralists to establish campsites and where nutritious grasses were present, making it feasible to graze. Thus, we argue that the probable shift in habitat for blue sheep from optimal areas occurs due to livestock presence, which might disturb their nutritional balance. Our study provides helpful insights for managing rangelands, which when tied with dietary patterns will give a better idea for proper conservation measures in the future.

14.
Am J Hum Genet ; 107(3): 418-431, 2020 09 03.
Artigo em Inglês | MEDLINE | ID: mdl-32758451

RESUMO

While genome-wide association studies have identified susceptibility variants for numerous traits, their combined utility for predicting broad measures of health, such as mortality, remains poorly understood. We used data from the UK Biobank to combine polygenic risk scores (PRS) for 13 diseases and 12 mortality risk factors into sex-specific composite PRS (cPRS). These cPRS were moderately associated with all-cause mortality in independent data within the UK Biobank: the estimated hazard ratios per standard deviation were 1.10 (95% confidence interval: 1.05, 1.16) and 1.15 (1.10, 1.19) for women and men, respectively. Differences in life expectancy between the top and bottom 5% of the cPRS were estimated to be 4.79 (1.76, 7.81) years and 6.75 (4.16, 9.35) years for women and men, respectively. These associations were substantially attenuated after adjusting for non-genetic mortality risk factors measured at study entry (i.e., middle age for most participants). The cPRS may be useful in counseling younger individuals at higher genetic risk of mortality on modification of non-genetic factors.


Assuntos
Doenças Genéticas Inatas/mortalidade , Predisposição Genética para Doença , Herança Multifatorial/genética , Medição de Risco/estatística & dados numéricos , Bancos de Espécimes Biológicos , Feminino , Doenças Genéticas Inatas/genética , Doenças Genéticas Inatas/patologia , Estudo de Associação Genômica Ampla , Humanos , Masculino , Pessoa de Meia-Idade , Fenótipo , Polimorfismo de Nucleotídeo Único/genética , Modelos de Riscos Proporcionais , Fatores de Risco , Reino Unido
15.
Hypertension ; 76(3): 699-706, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32713275

RESUMO

The 2017 American College of Cardiology/American Heart Association guideline defines hypertension as a blood pressure ≥130/80 mm Hg, whereas the 2018 European Society of Cardiology (ESC) and 2019 National Institute for Health and Care Excellence (NICE) guidelines use a ≥140/90 mm Hg threshold. Our objective was to study the associations between isolated diastolic hypertension (IDH), diagnosed using these 2 blood pressure thresholds, and cardiovascular disease (CVD) in a large cohort of UK adults. We analyzed data from UK Biobank, which enrolled participants between 2006 and 2010 with follow-up through March 2019. We excluded persons with systolic hypertension or baseline CVD. We defined incident CVD as a composite of nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. We used Cox regression to quantify associations between IDH and CVD, as well as the individual outcomes included in the composite outcome. We studied 151 831 participants with normal systolic blood pressure (mean age 54 years, 40% male). Overall, 24.5% had IDH by the American College of Cardiology/American Heart Association definition compared with 6% by the ESC/NICE definition. Compared with normal diastolic blood pressure, IDH by the American College of Cardiology/American Heart Association definition was not significantly associated with CVD risk (hazard ratio, 1.08 [95% CI, 0.98-1.18]) whereas IDH by the ESC/NICE definition was significantly associated with a modest increase in CVD (hazard ratio, 1.15 [95% CI, 1.04-1.29]). Similar results were found by sex and among participants not taking baseline antihypertensives. Furthermore, neither IDH definition was associated with the individual outcomes of nonfatal myocardial infarction or stroke. In conclusion, the proportion of UK Biobank participants with IDH was significantly higher by the American College of Cardiology/American Heart Association definition compared with the ESC/NICE definitions; however, only the ESC/NICE definition was statistically associated with increased CVD risk.

16.
PLoS One ; 15(6): e0233569, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32497053

RESUMO

Despite appreciable advances in carnivore ecology, studies on small cats remain limited with carnivore research in India being skewed towards large cats. Small cats are more specialized than their larger cousins in terms of resource selection. Studies on small cat population and habitat preference are critical to evaluate their status to ensure better management and conservation. We estimated abundance of two widespread small cats, the jungle cat, and the rusty-spotted cat, and investigated their habitat associations based on camera trap captures from a central Indian tiger reserve. We predicted fine-scale habitat segregation between these sympatric species as a driver of coexistence. We used an extension of the spatial count model in a Bayesian framework approach to estimate the population density of jungle cat and rusty-spotted cat and used generalized linear models to explore their habitat associations. Densities of rusty-spotted cat and jungle cat were estimated as 6.67 (95% CI 4.07-10.74) and 4.01 (95% CI 2.65-6.12) individuals/100 km2 respectively. Forest cover and evapotranspiration were positively associated with rusty-spotted cat occurrence whereas both factors had a significant negative relation with jungle cat occurrence. The results directed habitat segregation between these small cats with affinities of rusty-spotted cat and jungle cat towards well-forested and open scrubland areas respectively. Our estimates highlight the widespread applicability of this model for density estimation of species with no individual identification. Moreover, the study outcomes can aid in targeted management decisions and serve as the baseline for species conservation as these models allow robust population estimation of elusive species along with predicting their habitat preferences.


Assuntos
Felidae/fisiologia , Florestas , Simpatria/fisiologia , Animais , Teorema de Bayes , Gatos , Conservação dos Recursos Naturais , Ecologia/métodos , Índia , Modelos Lineares , Movimento/fisiologia , Densidade Demográfica
17.
J Natl Cancer Inst ; 2020 May 02.
Artigo em Inglês | MEDLINE | ID: mdl-32359158

RESUMO

We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72,284 cases and 80,354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression, and a newly developed case-only method, for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history), and on average 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.

18.
Kidney Int ; 98(3): 708-716, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32454124

RESUMO

Blood pressure and kidney function have a bidirectional relation. Hypertension has long been considered as a risk factor for kidney function decline. However, whether intensive blood pressure control could promote kidney health has been uncertain. The kidney is known to have a major role in affecting blood pressure through sodium extraction and regulating electrolyte balance. This bidirectional relation makes causal inference between these two traits difficult. Therefore, to examine the causal relations between these two traits, we performed two-sample Mendelian randomization analyses using summary statistics of large-scale genome-wide association studies. We selected genetic instruments more likely to be specific for kidney function using meta-analyses of complementary kidney function biomarkers (glomerular filtration rate estimated from serum creatinine [eGFRcr], and blood urea nitrogen from the CKDGen Consortium). Systolic and diastolic blood pressure summary statistics were from the International Consortium for Blood Pressure and UK Biobank. Significant evidence supported the causal effects of higher kidney function on lower blood pressure. Based on the mode-based Mendelian randomization method, the effect estimates for one standard deviation (SD) higher in log-transformed eGFRcr was -0.17 SD unit (95 % confidence interval: -0.09 to -0.24) in systolic blood pressure and -0.15 SD unit (95% confidence interval: -0.07 to -0.22) in diastolic blood pressure. In contrast, the causal effects of blood pressure on kidney function were not statistically significant. Thus, our results support causal effects of higher kidney function on lower blood pressure and suggest preventing kidney function decline can reduce the public health burden of hypertension.

19.
Cancer Epidemiol Biomarkers Prev ; 29(6): 1196-1203, 2020 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-32277002

RESUMO

BACKGROUND: Independent validation of risk prediction models in prospective cohorts is required for risk-stratified cancer prevention. Such studies often have a two-phase design, where information on expensive biomarkers are ascertained in a nested substudy of the original cohort. METHODS: We propose a simple approach for evaluating model discrimination that accounts for incomplete follow-up and gains efficiency by using data from all individuals in the cohort irrespective of whether they were sampled in the substudy. For evaluating the AUC, we estimated probabilities of risk-scores for cases being larger than those in controls conditional on partial risk-scores, computed using partial covariate information. The proposed method was compared with an inverse probability weighted (IPW) approach that used information only from the subjects in the substudy. We evaluated age-stratified AUC of a model including questionnaire-based risk factors and inflammation biomarkers to predict 10-year risk of lung cancer using data from the Prostate, Lung, Colorectal, and Ovarian Cancer (1993-2009) trial (30,297 ever-smokers, 1,253 patients with lung cancer). RESULTS: For estimating age-stratified AUC of the combined lung cancer risk model, the proposed method was 3.8 to 5.3 times more efficient compared with the IPW approach across the different age groups. Extensive simulation studies also demonstrated substantial efficiency gain compared with the IPW approach. CONCLUSIONS: Incorporating information from all individuals in a two-phase cohort study can substantially improve precision of discrimination measures of lung cancer risk models. IMPACT: Novel, simple, and practically useful methods are proposed for evaluating risk models, a critical step toward risk-stratified cancer prevention.

20.
Nat Commun ; 11(1): 1122, 2020 02 28.
Artigo em Inglês | MEDLINE | ID: mdl-32111823

RESUMO

Heart failure is a major public health problem affecting over 23 million people worldwide. In this study, we present the results of a large scale meta-analysis of heart failure GWAS and replication in a comparable sized cohort to identify one known and two novel loci associated with heart failure. Heart failure sub-phenotyping shows that a new locus in chromosome 1 is associated with left ventricular adverse remodeling and clinical heart failure, in response to different initial cardiac muscle insults. Functional characterization and fine-mapping of that locus reveal a putative causal variant in a cardiac muscle specific regulatory region activated during cardiomyocyte differentiation that binds to the ACTN2 gene, a crucial structural protein inside the cardiac sarcolemma (Hi-C interaction p-value = 0.00002). Genome-editing in human embryonic stem cell-derived cardiomyocytes confirms the influence of the identified regulatory region in the expression of ACTN2. Our findings extend our understanding of biological mechanisms underlying heart failure.


Assuntos
Actinina/genética , Predisposição Genética para Doença/genética , Insuficiência Cardíaca/genética , Sistema ABO de Grupos Sanguíneos/genética , Fibrilação Atrial/genética , Cromossomos Humanos Par 1 , Elementos Facilitadores Genéticos , Regulação da Expressão Gênica , Estudo de Associação Genômica Ampla , Insuficiência Cardíaca/patologia , Células-Tronco Embrionárias Humanas/citologia , Humanos , Doenças Musculoesqueléticas/genética , Miócitos Cardíacos/citologia , Polimorfismo de Nucleotídeo Único , Locos de Características Quantitativas
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