Displaying publications 1 - 20 of 79 in total

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  1. Fulltext A review of drug delivery systems based on nanotechnology and green chemistry: green nanomedicine
    Jahangirian H, Lemraski EG, Webster TJ, Rafiee-Moghaddam R, Abdollahi Y
    Int J Nanomedicine, 2017;12:2957-2978.
    PMID: 28442906 DOI: 10.2147/IJN.S127683
    This review discusses the impact of green and environmentally safe chemistry on the field of nanotechnology-driven drug delivery in a new field termed "green nanomedicine". Studies have shown that among many examples of green nanotechnology-driven drug delivery systems, those receiving the greatest amount of attention include nanometal particles, polymers, and biological materials. Furthermore, green nanodrug delivery systems based on environmentally safe chemical reactions or using natural biomaterials (such as plant extracts and microorganisms) are now producing innovative materials revolutionizing the field. In this review, the use of green chemistry design, synthesis, and application principles and eco-friendly synthesis techniques with low side effects are discussed. The review ends with a description of key future efforts that must ensue for this field to continue to grow.
  2. Fulltext The influence of Arctic Fe and Atlantic fixed N on summertime primary production in Fram Strait, North Greenland Sea
    Krisch S, Browning TJ, Graeve M, Ludwichowski KU, Lodeiro P, Hopwood MJ, et al.
    Sci Rep, 2020 Sep 17;10(1):15230.
    PMID: 32943713 DOI: 10.1038/s41598-020-72100-9
    Climate change has led to a ~ 40% reduction in summer Arctic sea-ice cover extent since the 1970s. Resultant increases in light availability may enhance phytoplankton production. Direct evidence for factors currently constraining summertime phytoplankton growth in the Arctic region is however lacking. GEOTRACES cruise GN05 conducted a Fram Strait transect from Svalbard to the NE Greenland Shelf in summer 2016, sampling for bioessential trace metals (Fe, Co, Zn, Mn) and macronutrients (N, Si, P) at ~ 79°N. Five bioassay experiments were conducted to establish phytoplankton responses to additions of Fe, N, Fe + N and volcanic dust. Ambient nutrient concentrations suggested N and Fe were deficient in surface seawater relative to typical phytoplankton requirements. A west-to-east trend in the relative deficiency of N and Fe was apparent, with N becoming more deficient towards Greenland and Fe more deficient towards Svalbard. This aligned with phytoplankton responses in bioassay experiments, which showed greatest chlorophyll-a increases in + N treatment near Greenland and + N + Fe near Svalbard. Collectively these results suggest primary N limitation of phytoplankton growth throughout the study region, with conditions potentially approaching secondary Fe limitation in the eastern Fram Strait. We suggest that the supply of Atlantic-derived N and Arctic-derived Fe exerts a strong control on summertime nutrient stoichiometry and resultant limitation patterns across the Fram Strait region.
  3. Fulltext DeepNC: a framework for drug-target interaction prediction with graph neural networks
    Tran HNT, Thomas JJ, Ahamed Hassain Malim NH
    PeerJ, 2022;10:e13163.
    PMID: 35578674 DOI: 10.7717/peerj.13163
    The exploration of drug-target interactions (DTI) is an essential stage in the drug development pipeline. Thanks to the assistance of computational models, notably in the deep learning approach, scientists have been able to shorten the time spent on this stage. Widely practiced deep learning algorithms such as convolutional neural networks and recurrent neural networks are commonly employed in DTI prediction projects. However, they can hardly utilize the natural graph structure of molecular inputs. For that reason, a graph neural network (GNN) is an applicable choice for learning the chemical and structural characteristics of molecules when it represents molecular compounds as graphs and learns the compound features from those graphs. In an effort to construct an advanced deep learning-based model for DTI prediction, we propose Deep Neural Computation (DeepNC), which is a framework utilizing three GNN algorithms: Generalized Aggregation Networks (GENConv), Graph Convolutional Networks (GCNConv), and Hypergraph Convolution-Hypergraph Attention (HypergraphConv). In short, our framework learns the features of drugs and targets by the layers of GNN and 1-D convolution network, respectively. Then, representations of the drugs and targets are fed into fully-connected layers to predict the binding affinity values. The models of DeepNC were evaluated on two benchmarked datasets (Davis, Kiba) and one independently proposed dataset (Allergy) to confirm that they are suitable for predicting the binding affinity of drugs and targets. Moreover, compared to the results of baseline methods that worked on the same problem, DeepNC proves to improve the performance in terms of mean square error and concordance index.
  4. Fulltext Synthesis, characterization, and performance evaluation of multilayered photoanodes by introducing mesoporous carbon and TiO2 for humic acid adsorption
    Hosseini S, Jahangirian H, Webster TJ, Soltani SM, Aroua MK
    Int J Nanomedicine, 2016;11:3969-78.
    PMID: 27574426 DOI: 10.2147/IJN.S96558
    Nanostructured photoanodes were prepared via a novel combination of titanium dioxide (TiO2) nanoparticles and mesoporous carbon (C). Four different photoanodes were synthesized by sol-gel spin coating onto a glassy substrate of fluorine-doped tin oxide. The photocatalytic activities of TiO2, TiO2/C/TiO2, TiO2/C/C/TiO2, and TiO2/C/TiO2/C/TiO2 photoanodes were evaluated by exposing the synthesized photoanodes to UV-visible light. The photocurrent density observed in these photoanodes confirmed that an additional layer of mesoporous carbon could successfully increase the photocurrent density. The highest photocurrent density of ~1.022 mA cm(-2) at 1 V/saturated calomel electrode was achieved with TiO2/C/C/TiO2 under an illumination intensity of 100 mW cm(-2) from a solar simulator. The highest value of surface roughness was measured for a TiO2/C/C/TiO2 combination owing to the presence of two continuous layers of mesoporous carbon. The resulting films had a thickness ranging from 1.605 µm to 5.165 µm after the calcination process. The presence of double-layer mesoporous carbon resulted in a 20% increase in the photocurrent density compared with the TiO2/C/TiO2 combination when only a single mesoporous carbon layer was employed. The improved performance of these photoanodes can be attributed to the enhanced porosity and increased void space due to the presence of mesoporous carbon. For the first time, it has been demonstrated here that the photoelectrochemical performance of TiO2 can be improved by integrating several layers of mesoporous carbon. Comparison of the rate of removal of humic acid by the prepared photoanodes showed that the highest performance from TiO2/C/C/TiO2 was due to the highest photocurrent density generated. Therefore, this study showed that optimizing the sequence of mesoporous carbon layers can be a viable and inexpensive method for enhanced humic acid removal.
  5. Fulltext Forests and Their Canopies: Achievements and Horizons in Canopy Science
    Nakamura A, Kitching RL, Cao M, Creedy TJ, Fayle TM, Freiberg M, et al.
    Trends Ecol Evol, 2017 06;32(6):438-451.
    PMID: 28359572 DOI: 10.1016/j.tree.2017.02.020
    Forest canopies are dynamic interfaces between organisms and atmosphere, providing buffered microclimates and complex microhabitats. Canopies form vertically stratified ecosystems interconnected with other strata. Some forest biodiversity patterns and food webs have been documented and measurements of ecophysiology and biogeochemical cycling have allowed analyses of large-scale transfer of CO2, water, and trace gases between forests and the atmosphere. However, many knowledge gaps remain. With global research networks and databases, and new technologies and infrastructure, we envisage rapid advances in our understanding of the mechanisms that drive the spatial and temporal dynamics of forests and their canopies. Such understanding is vital for the successful management and conservation of global forests and the ecosystem services they provide to the world.
  6. Medical student knowledge and critical appraisal of machine learning: a multicentre international cross-sectional study
    Blacketer C, Parnis R, B Franke K, Wagner M, Wang D, Tan Y, et al.
    Intern Med J, 2021 Sep;51(9):1539-1542.
    PMID: 34541769 DOI: 10.1111/imj.15479
    To utilise effectively tools that employ machine learning (ML) in clinical practice medical students and doctors will require a degree of understanding of ML models. To evaluate current levels of understanding, a formative examination and survey was conducted across three centres in Australia, New Zealand and the United States. Of the 245 individuals who participated in the study (response rate = 45.4%), the majority had difficulty with identifying weaknesses in model performance analysis. Further studies examining educational interventions addressing such ML topics are warranted.
  7. Microbial engineering strategies for synthetic microplastics clean up: A review on recent approaches
    Kumar V, Sharma N, Duhan L, Pasrija R, Thomas J, Umesh M, et al.
    Environ Toxicol Pharmacol, 2023 Mar;98:104045.
    PMID: 36572198 DOI: 10.1016/j.etap.2022.104045
    Microplastics are the small fragments of the plastic molecules which find their applications in various routine products such as beauty products. Later, it was realized that it has several toxic effects on marine and terrestrial organisms. This review is an approach in understanding the microplastics, their origin, dispersal in the aquatic system, their biodegradation and factors affecting biodegradation. In addition, the paper discusses the major engineering approaches applied in microbial biotechnology. Specifically, it reviews microbial genetic engineering, such as PET-ase engineering, MHET-ase engineering, and immobilization approaches. Moreover, the major challenges associated with the plastic removal are presented by evaluating the recent reports available.
  8. Fulltext Virus-like Particles Identify an HIV V1V2 Apex-Binding Neutralizing Antibody that Lacks a Protruding Loop
    Cale EM, Gorman J, Radakovich NA, Crooks ET, Osawa K, Tong T, et al.
    Immunity, 2017 05 16;46(5):777-791.e10.
    PMID: 28514685 DOI: 10.1016/j.immuni.2017.04.011
    Most HIV-1-specific neutralizing antibodies isolated to date exhibit unusual characteristics that complicate their elicitation. Neutralizing antibodies that target the V1V2 apex of the HIV-1 envelope (Env) trimer feature unusually long protruding loops, which enable them to penetrate the HIV-1 glycan shield. As antibodies with loops of requisite length are created through uncommon recombination events, an alternative mode of apex binding has been sought. Here, we isolated a lineage of Env apex-directed neutralizing antibodies, N90-VRC38.01-11, by using virus-like particles and conformationally stabilized Env trimers as B cell probes. A crystal structure of N90-VRC38.01 with a scaffolded V1V2 revealed a binding mode involving side-chain-to-side-chain interactions that reduced the distance the antibody loop must traverse the glycan shield, thereby facilitating V1V2 binding via a non-protruding loop. The N90-VRC38 lineage thus identifies a solution for V1V2-apex binding that provides a more conventional B cell pathway for vaccine design.
  9. Evidence for the Higgs Boson Decay to a Z Boson and a Photon at the LHC
    Aad G, Abbott B, Abeling K, Abicht NJ, Abidi SH, Aboulhorma A, et al.
    Phys Rev Lett, 2024 Jan 12;132(2):021803.
    PMID: 38277607 DOI: 10.1103/PhysRevLett.132.021803
    The first evidence for the Higgs boson decay to a Z boson and a photon is presented, with a statistical significance of 3.4 standard deviations. The result is derived from a combined analysis of the searches performed by the ATLAS and CMS Collaborations with proton-proton collision datasets collected at the CERN Large Hadron Collider (LHC) from 2015 to 2018. These correspond to integrated luminosities of around 140  fb^{-1} for each experiment, at a center-of-mass energy of 13 TeV. The measured signal yield is 2.2±0.7 times the standard model prediction, and agrees with the theoretical expectation within 1.9 standard deviations.
  10. Erratum to: Methods for evaluating medical tests and biomarkers
    Gopalakrishna G, Langendam M, Scholten R, Bossuyt P, Leeflang M, Noel-Storr A, et al.
    Diagn Progn Res, 2017;1:11.
    PMID: 31095132 DOI: 10.1186/s41512-017-0011-4
    [This corrects the article DOI: 10.1186/s41512-016-0001-y.].
  11. Fulltext In COVID-19 Health Messaging, Loss Framing Increases Anxiety with Little-to-No Concomitant Benefits: Experimental Evidence from 84 Countries
    Dorison CA, Lerner JS, Heller BH, Rothman AJ, Kawachi II, Wang K, et al.
    Affect Sci, 2022 Sep;3(3):577-602.
    PMID: 36185503 DOI: 10.1007/s42761-022-00128-3
    The COVID-19 pandemic (and its aftermath) highlights a critical need to communicate health information effectively to the global public. Given that subtle differences in information framing can have meaningful effects on behavior, behavioral science research highlights a pressing question: Is it more effective to frame COVID-19 health messages in terms of potential losses (e.g., "If you do not practice these steps, you can endanger yourself and others") or potential gains (e.g., "If you practice these steps, you can protect yourself and others")? Collecting data in 48 languages from 15,929 participants in 84 countries, we experimentally tested the effects of message framing on COVID-19-related judgments, intentions, and feelings. Loss- (vs. gain-) framed messages increased self-reported anxiety among participants cross-nationally with little-to-no impact on policy attitudes, behavioral intentions, or information seeking relevant to pandemic risks. These results were consistent across 84 countries, three variations of the message framing wording, and 560 data processing and analytic choices. Thus, results provide an empirical answer to a global communication question and highlight the emotional toll of loss-framed messages. Critically, this work demonstrates the importance of considering unintended affective consequences when evaluating nudge-style interventions.
  12. Pontamine fast scarlet 4B bifluorescence and measurements of cellulose microfibril angles
    Thomas J, Idris NA, Collings DA
    J Microsc, 2017 10;268(1):13-27.
    PMID: 28654160 DOI: 10.1111/jmi.12582
    Pontamine fast scarlet 4B is a red paper and textiles dye that has recently been introduced as a fluorescent probe for plant cell walls. Pontamine exhibits bifluorescence, or fluorescence dependent on the polarization of the excitation light: Because cellulose is aligned within the cell wall, pontamine-labelled cell walls exhibit variable fluorescence as the excitation polarization is modulated. Thus, bifluorescence measurements require polarized excitation that can be directly or indirectly modulated. In our confocal microscopy observations of various cellulose samples labelled with pontamine, we modulated excitation polarization either through sample rotation or by the confocal's scanfield rotation function. This variably rotated laser polarizations on Leica confocal microscopes, but not those from other makers. Beginning with samples with directly observable microfibril orientations, such as purified bacterial cellulose, the velamen of orchid roots and the inner S2 layer of radiata pine compression wood, we demonstrate that modelling the variations in pontamine fluorescence with a sine curve can be used to measure the known microfibril angles. We then measured average local microfibril angles in radiata pine samples, and showed similar microfibril angles in compression and normal (opposite) wood. Significantly, bifluorescence measurements might also be used to understand the degree of local cellulose alignment within the cell wall, as opposed to variations in the overall cellulose angle.
  13. Global guideline for the diagnosis and management of rare mould infections: an initiative of the European Confederation of Medical Mycology in cooperation with the International Society for Human and Animal Mycology and the American Society for Microbiology
    Hoenigl M, Salmanton-García J, Walsh TJ, Nucci M, Neoh CF, Jenks JD, et al.
    Lancet Infect Dis, 2021 Aug;21(8):e246-e257.
    PMID: 33606997 DOI: 10.1016/S1473-3099(20)30784-2
    With increasing numbers of patients needing intensive care or who are immunosuppressed, infections caused by moulds other than Aspergillus spp or Mucorales are increasing. Although antifungal prophylaxis has shown effectiveness in preventing many invasive fungal infections, selective pressure has caused an increase of breakthrough infections caused by Fusarium, Lomentospora, and Scedosporium species, as well as by dematiaceous moulds, Rasamsonia, Schizophyllum, Scopulariopsis, Paecilomyces, Penicillium, Talaromyces and Purpureocillium species. Guidance on the complex multidisciplinary management of infections caused by these pathogens has the potential to improve prognosis. Management routes depend on the availability of diagnostic and therapeutic options. The present recommendations are part of the One World-One Guideline initiative to incorporate regional differences in the epidemiology and management of rare mould infections. Experts from 24 countries contributed their knowledge and analysed published evidence on the diagnosis and treatment of rare mould infections. This consensus document intends to provide practical guidance in clinical decision making by engaging physicians and scientists involved in various aspects of clinical management. Moreover, we identify areas of uncertainty and constraints in optimising this management.
  14. Fulltext Triallelic and epigenetic-like inheritance in human disorders of telomerase
    Collopy LC, Walne AJ, Cardoso S, de la Fuente J, Mohamed M, Toriello H, et al.
    Blood, 2015 Jul 09;126(2):176-84.
    PMID: 26024875 DOI: 10.1182/blood-2015-03-633388
    Dyskeratosis congenita (DC) and related diseases are a heterogeneous group of disorders characterized by impaired telomere maintenance, known collectively as the telomeropathies. Disease-causing variants have been identified in 10 telomere-related genes including the reverse transcriptase (TERT) and the RNA component (TERC) of the telomerase complex. Variants in TERC and TERT can impede telomere elongation causing stem cells to enter premature replicative senescence and/or apoptosis as telomeres become critically short. This explains the major impact of the disease on highly proliferative tissues such as the bone marrow and skin. However, telomerase variants are not always fully penetrant and in some families disease-causing variants are seen in asymptomatic family members. As a result, determining the pathogenic status of newly identified variants in TERC or TERT can be quite challenging. Over a 3-year period, we have identified 26 telomerase variants (16 of which are novel) in 23 families. Additional investigations (including family segregation and functional studies) enabled these to be categorized into 3 groups: (1) disease-causing (n = 15), (2) uncertain status (n = 6), and (3) bystanders (n = 5). Remarkably, this process has also enabled us to identify families with novel mechanisms of inheriting human telomeropathies. These include triallelic mutations, involving 2 different telomerase genes, and an epigenetic-like inheritance of short telomeres in the absence of a telomerase mutation. This study therefore highlights that telomerase variants have highly variable functional and clinical manifestations and require thorough investigation to assess their pathogenic contribution.
  15. Fulltext Induction of apoptosis in cancer cells by NiZn ferrite nanoparticles through mitochondrial cytochrome C release
    Al-Qubaisi MS, Rasedee A, Flaifel MH, Ahmad SH, Hussein-Al-Ali S, Hussein MZ, et al.
    Int J Nanomedicine, 2013;8:4115-29.
    PMID: 24204141 DOI: 10.2147/IJN.S50061
    The long-term objective of the present study was to determine the ability of NiZn ferrite nanoparticles to kill cancer cells. NiZn ferrite nanoparticle suspensions were found to have an average hydrodynamic diameter, polydispersity index, and zeta potential of 254.2 ± 29.8 nm, 0.524 ± 0.013, and -60 ± 14 mV, respectively. We showed that NiZn ferrite nanoparticles had selective toxicity towards MCF-7, HepG2, and HT29 cells, with a lesser effect on normal MCF 10A cells. The quantity of Bcl-2, Bax, p53, and cytochrome C in the cell lines mentioned above was determined by colorimetric methods in order to clarify the mechanism of action of NiZn ferrite nanoparticles in the killing of cancer cells. Our results indicate that NiZn ferrite nanoparticles promote apoptosis in cancer cells via caspase-3 and caspase-9, downregulation of Bcl-2, and upregulation of Bax and p53, with cytochrome C translocation. There was a concomitant collapse of the mitochondrial membrane potential in these cancer cells when treated with NiZn ferrite nanoparticles. This study shows that NiZn ferrite nanoparticles induce glutathione depletion in cancer cells, which results in increased production of reactive oxygen species and eventually, death of cancer cells.
  16. Fulltext Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life Years for 29 Cancer Groups From 2010 to 2019: A Systematic Analysis for the Global Burden of Disease Study 2019
    Global Burden of Disease 2019 Cancer Collaboration, Kocarnik JM, Compton K, Dean FE, Fu W, Gaw BL, et al.
    JAMA Oncol, 2022 Mar 01;8(3):420-444.
    PMID: 34967848 DOI: 10.1001/jamaoncol.2021.6987
    IMPORTANCE: The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden.

    OBJECTIVE: To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019.

    EVIDENCE REVIEW: The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs).

    FINDINGS: In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles.

    CONCLUSIONS AND RELEVANCE: The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.

  17. Fulltext Genome-wide gain-of-function screen for genes that induce epithelial-to-mesenchymal transition in breast cancer
    Škalamera D, Dahmer-Heath M, Stevenson AJ, Pinto C, Shah ET, Daignault SM, et al.
    Oncotarget, 2016 Sep 20;7(38):61000-61020.
    PMID: 27876705 DOI: 10.18632/oncotarget.11314
    Epithelial to mesenchymal transition (EMT) is a developmental program that has been implicated in progression, metastasis and therapeutic resistance of some carcinomas. To identify genes whose overexpression drives EMT, we screened a lentiviral expression library of 17000 human open reading frames (ORFs) using high-content imaging to quantitate cytoplasmic vimentin. Hits capable of increasing vimentin in the mammary carcinoma-derived cell line MDA-MB-468 were confirmed in the non-tumorigenic breast-epithelial cell line MCF10A. When overexpressed in this model, they increased the rate of cell invasion through Matrigel™, induced mesenchymal marker expression and reduced expression of the epithelial marker E-cadherin. In gene-expression datasets derived from breast cancer patients, the expression of several novel genes correlated with expression of known EMT marker genes, indicating their in vivo relevance. As EMT-associated properties are thought to contribute in several ways to cancer progression, genes identified in this study may represent novel targets for anti-cancer therapy.
  18. Publisher Correction: Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction
    Conti DV, Darst BF, Moss LC, Saunders EJ, Sheng X, Chou A, et al.
    Nat Genet, 2021 Mar;53(3):413.
    PMID: 33473200 DOI: 10.1038/s41588-021-00786-2
  19. Fulltext Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction
    Conti DV, Darst BF, Moss LC, Saunders EJ, Sheng X, Chou A, et al.
    Nat Genet, 2021 Jan;53(1):65-75.
    PMID: 33398198 DOI: 10.1038/s41588-020-00748-0
    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.
  20. Fulltext Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants
    Wang A, Shen J, Rodriguez AA, Saunders EJ, Chen F, Janivara R, et al.
    Nat Genet, 2023 Dec;55(12):2065-2074.
    PMID: 37945903 DOI: 10.1038/s41588-023-01534-4
    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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