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Sökning: (WFRF:(Hsing A. W.)) > (2020-2023)

  • Resultat 1-6 av 6
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1.
  • Wang, Anqi, et al. (författare)
  • Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants
  • 2023
  • Ingår i: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 55:12, s. 2065-2074
  • Tidskriftsartikel (refereegranskat)abstract
    • The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.
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  • Conti, David, V, et al. (författare)
  • Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction
  • 2021
  • Ingår i: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 53:1, s. 65-75
  • Tidskriftsartikel (refereegranskat)abstract
    • Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction. A meta-analysis of genome-wide association studies across different populations highlights new risk loci and provides a genetic risk score that can stratify prostate cancer risk across ancestries.
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4.
  • Axfors, Cathrine, et al. (författare)
  • Mortality outcomes with hydroxychloroquine and chloroquine in COVID-19 from an international collaborative meta-analysis of randomized trials
  • 2021
  • Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 12:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Substantial COVID-19 research investment has been allocated to randomized clinical trials (RCTs) on hydroxychloroquine/chloroquine, which currently face recruitment challenges or early discontinuation. We aim to estimate the effects of hydroxychloroquine and chloroquine on survival in COVID-19 from all currently available RCT evidence, published and unpublished. We present a rapid meta-analysis of ongoing, completed, or discontinued RCTs on hydroxychloroquine or chloroquine treatment for any COVID-19 patients (protocol: https://osf.io/QESV4/). We systematically identified unpublished RCTs (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform, Cochrane COVID-registry up to June 11, 2020), and published RCTs (PubMed, medRxiv and bioRxiv up to October 16, 2020). All-cause mortality has been extracted (publications/preprints) or requested from investigators and combined in random-effects meta-analyses, calculating odds ratios (ORs) with 95% confidence intervals (CIs), separately for hydroxychloroquine and chloroquine. Prespecified subgroup analyses include patient setting, diagnostic confirmation, control type, and publication status. Sixty-three trials were potentially eligible. We included 14 unpublished trials (1308 patients) and 14 publications/preprints (9011 patients). Results for hydroxychloroquine are dominated by RECOVERY and WHO SOLIDARITY, two highly pragmatic trials, which employed relatively high doses and included 4716 and 1853 patients, respectively (67% of the total sample size). The combined OR on all-cause mortality for hydroxychloroquine is 1.11 (95% CI: 1.02, 1.20; I-2=0%; 26 trials; 10,012 patients) and for chloroquine 1.77 (95%CI: 0.15, 21.13, I-2=0%; 4 trials; 307 patients). We identified no subgroup effects. We found that treatment with hydroxychloroquine is associated with increased mortality in COVID-19 patients, and there is no benefit of chloroquine. Findings have unclear generalizability to outpatients, children, pregnant women, and people with comorbidities. Hydroxychloroquine and chloroquine have been investigated as a potential treatment for Covid-19 in several clinical trials. Here the authors report a meta-analysis of published and unpublished trials, and show that treatment with hydroxychloroquine for patients with Covid-19 was associated with increased mortality, and there was no benefit from chloroquine.
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5.
  • Do, A., et al. (författare)
  • High spatial resolution and contrast radiography of hydrodynamic instabilities at the National Ignition Facility
  • 2022
  • Ingår i: Physics of Plasmas. - : AIP Publishing. - 1070-664X .- 1089-7674. ; 29:8
  • Tidskriftsartikel (refereegranskat)abstract
    • We are developing techniques for studying the Rayleigh-Taylor (RT) and Richtmyer-Meshkov (RM) instabilities in a planar geometry at high-energy-densities at the National Ignition Facility (NIF). In particular, through the improvement of experimental imaging quality, we are progressing toward the study of the turbulent regime of the mixing regions in capsule implosion experiments for inertial confinement fusion, which requires few micrometers resolution. Using 60 NIF beams, a solid shock tube is driven launching a shock wave that crosses the interface between a dense and a light material pre-machined in the target to obtain sinusoidal ripples, which results in RM and RT instabilities that are imaged using the NIF Crystal Backlighter Imager. High-quality images were obtained with a mean resolution of 7 μm and improved contrast. While the obtained resolution does not allow the observation of the smallest scale of the "turbulent"energy spectrum, the generated image encompasses 63% of the total flow energy, a 50% improvement over previous studies, which is observed for the first time a roll-up feature in a high energy density-type RT experiment.
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6.
  • Wan, Guihong, et al. (författare)
  • Prediction of early-stage melanoma recurrence using clinical and histopathologic features
  • 2022
  • Ingår i: NPJ precision oncology. - : Springer Science and Business Media LLC. - 2397-768X. ; 6:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Prognostic analysis for early-stage (stage I/II) melanomas is of paramount importance for customized surveillance and treatment plans. Since immune checkpoint inhibitors have recently been approved for stage IIB and IIC melanomas, prognostic tools to identify patients at high risk of recurrence have become even more critical. This study aims to assess the effectiveness of machine-learning algorithms in predicting melanoma recurrence using clinical and histopathologic features from Electronic Health Records (EHRs). We collected 1720 early-stage melanomas: 1172 from the Mass General Brigham healthcare system (MGB) and 548 from the Dana-Farber Cancer Institute (DFCI). We extracted 36 clinicopathologic features and used them to predict the recurrence risk with supervised machine-learning algorithms. Models were evaluated internally and externally: (1) five-fold cross-validation of the MGB cohort; (2) the MGB cohort for training and the DFCI cohort for testing independently. In the internal and external validations, respectively, we achieved a recurrence classification performance of AUC: 0.845 and 0.812, and a time-to-event prediction performance of time-dependent AUC: 0.853 and 0.820. Breslow tumor thickness and mitotic rate were identified as the most predictive features. Our results suggest that machine-learning algorithms can extract predictive signals from clinicopathologic features for early-stage melanoma recurrence prediction, which will enable the identification of patients that may benefit from adjuvant immunotherapy.
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