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Search: WFRF:(Drew David A.) > (2020-2024)

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1.
  • The Seventeenth Data Release of the Sloan Digital Sky Surveys : Complete Release of MaNGA, MaStar, and APOGEE-2 Data
  • 2022
  • In: Astrophysical Journal Supplement Series. - : Institute of Physics (IOP). - 0067-0049 .- 1538-4365. ; 259:2
  • Journal article (peer-reviewed)abstract
    • This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 survey that publicly releases infrared spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the subsurvey Time Domain Spectroscopic Survey data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey subsurvey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated value-added catalogs. This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper, Local Volume Mapper, and Black Hole Mapper surveys.
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2.
  • Crous, Pedro W., et al. (author)
  • Fungal Planet description sheets: 1383–1435
  • 2022
  • In: Persoonia: Molecular Phylogeny and Evolution of Fungi. - : Naturalis Biodiversity Center. - 0031-5850 .- 1878-9080. ; 48, s. 261-371
  • Journal article (peer-reviewed)abstract
    • Novel species of fungi described in this study include those from various countries as follows: Australia, Agaricus albofoetidus, Agaricus aureoelephanti and Agaricus parviumbrus on soil, Fusarium ramsdenii from stem cankers of Araucaria cunninghamii, Keissleriella sporoboli from stem of Sporobolus natalensis, Leptosphaerulina queenslandica and Pestalotiopsis chiaroscuro from leaves of Sporobolus natalensis, Serendipita petricolae as endophyte from roots of Eriochilus petricola, Stagonospora tauntonensis from stem of Sporobolus natalensis, Teratosphaeria carnegiei from leaves of Eucalyptus grandis × E. camaldulensis and Wongia ficherai from roots of Eragrostis curvula. Canada, Lulworthia fundyensis from intertidal wood and Newbrunswickomyces abietophilus (incl. Newbrunswickomyces gen. nov.) on buds of Abies balsamea. Czech Republic, Geosmithia funiculosa from a bark beetle gallery on Ulmus minor and Neoherpotrichiella juglandicola (incl. Neoherpotrichiella gen. nov.) from wood of Juglans regia. France, Aspergillus rouenensis and Neoacrodontium gallica (incl. Neoacrodontium gen. nov.) from bore dust of Xestobium rufovillosum feeding on Quercus wood, Endoradiciella communis (incl. Endoradiciella gen. nov.) endophytic in roots of Microthlaspi perfoliatum and Entoloma simulans on soil. India, Amanita konajensis on soil and Keithomyces indicus from soil. Israel, Microascus rothbergiorum from Stylophora pistillata. Italy, Calonarius ligusticus on soil. Netherlands, Appendopyricularia juncicola (incl. Appendopyricularia gen. nov.), Eriospora juncicola and Tetraploa juncicola on dead culms of Juncus effusus, Gonatophragmium physciae on Physcia caesia and Paracosmospora physciae (incl. Paracosmospora gen. nov.) on Physcia tenella, Myrmecridium phragmitigenum on dead culm of Phragmites australis, Neochalara lolae on stems of Pteridium aquilinum, Niesslia nieuwwulvenica on dead culm of undetermined Poaceae, Nothodevriesia narthecii (incl. Nothodevriesia gen. nov.) on dead leaves of Narthecium ossifragum and Parastenospora pini (incl. Parastenospora gen. nov.) on dead twigs of Pinus sylvestris. Norway, Verticillium bjoernoeyanum from sand grains attached to a piece of driftwood on a sandy beach. Portugal, Collybiopsis cimrmanii on the base of living Quercus ilex and amongst dead leaves of Laurus and herbs. South Africa, Paraproliferophorum hyphaenes (incl. Paraproliferophorum gen. nov.) on living leaves of Hyphaene sp. and Saccothecium widdringtoniae on twigs of Widdringtonia wallichii. Spain, Cortinarius dryosalor on soil, Cyphellophora endoradicis endophytic in roots of Microthlaspi perfoliatum, Geoglossum laurisilvae on soil, Leptographium gemmatum from fluvial sediments, Physalacria auricularioides from a dead twig of Castanea sativa, Terfezia bertae and Tuber davidlopezii in soil. Sweden, Alpova larskersii, Inocybe alpestris and Inocybe boreogodeyi on soil. Thailand, Russula banwatchanensis, Russula purpureoviridis and Russula lilacina on soil. Ukraine, Nectriella adonidis on overwintered stems of Adonis vernalis. USA, Microcyclus jacquiniae from living leaves of Jacquinia keyensis and Penicillium neoherquei from a minute mushroom sporocarp. Morphological and culture characteristics are supported by DNA barcodes.
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3.
  • Thomas, Minta, et al. (author)
  • Response to Li and Hopper
  • 2021
  • In: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 108:3, s. 527-529
  • Journal article (peer-reviewed)
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4.
  • Thomas, Minta, et al. (author)
  • Genome-wide Modeling of Polygenic Risk Score in Colorectal Cancer Risk.
  • 2020
  • In: American Journal of Human Genetics. - Cambridge : Elsevier BV. - 0002-9297 .- 1537-6605. ; 107:3, s. 432-444
  • Journal article (peer-reviewed)abstract
    • Accurate colorectal cancer (CRC) risk prediction models are critical for identifying individuals at low and high risk of developing CRC, as they can then be offered targeted screening and interventions to address their risks of developing disease (if they are in a high-risk group) and avoid unnecessary screening and interventions (if they are in a low-risk group). As it is likely that thousands of genetic variants contribute to CRC risk, it is clinically important to investigate whether these genetic variants can be used jointly for CRC risk prediction. In this paper, we derived and compared different approaches to generating predictive polygenic risk scores (PRS) from genome-wide association studies (GWASs) including 55,105 CRC-affected case subjects and 65,079 control subjects of European ancestry. We built the PRS in three ways, using (1) 140 previously identified and validated CRC loci; (2) SNP selection based on linkage disequilibrium (LD) clumping followed by machine-learning approaches; and (3) LDpred, a Bayesian approach for genome-wide risk prediction. We tested the PRS in an independent cohort of 101,987 individuals with 1,699 CRC-affected case subjects. The discriminatory accuracy, calculated by the age- and sex-adjusted area under the receiver operating characteristics curve (AUC), was highest for the LDpred-derived PRS (AUC = 0.654) including nearly 1.2 M genetic variants (the proportion of causal genetic variants for CRC assumed to be 0.003), whereas the PRS of the 140 known variants identified from GWASs had the lowest AUC (AUC = 0.629). Based on the LDpred-derived PRS, we are able to identify 30% of individuals without a family history as having risk for CRC similar to those with a family history of CRC, whereas the PRS based on known GWAS variants identified only top 10% as having a similar relative risk. About 90% of these individuals have no family history and would have been considered average risk under current screening guidelines, but might benefit from earlier screening. The developed PRS offers a way for risk-stratified CRC screening and other targeted interventions.
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5.
  • Carreras-Torres, Robert, et al. (author)
  • Genome-wide interaction study with smoking for colorectal cancer risk identifies novel genetic loci related to tumor suppression, inflammation, and immune response
  • 2023
  • In: Cancer Epidemiology, Biomarkers and Prevention. - : American association for cancer research. - 1055-9965 .- 1538-7755. ; 32:3, s. 315-328
  • Journal article (peer-reviewed)abstract
    • BACKGROUND: Tobacco smoking is an established risk factor for colorectal cancer. However, genetically defined population subgroups may have increased susceptibility to smoking-related effects on colorectal cancer.METHODS: A genome-wide interaction scan was performed including 33,756 colorectal cancer cases and 44,346 controls from three genetic consortia.RESULTS: Evidence of an interaction was observed between smoking status (ever vs. never smokers) and a locus on 3p12.1 (rs9880919, P = 4.58 × 10-8), with higher associated risk in subjects carrying the GG genotype [OR, 1.25; 95% confidence interval (CI), 1.20-1.30] compared with the other genotypes (OR <1.17 for GA and AA). Among ever smokers, we observed interactions between smoking intensity (increase in 10 cigarettes smoked per day) and two loci on 6p21.33 (rs4151657, P = 1.72 × 10-8) and 8q24.23 (rs7005722, P = 2.88 × 10-8). Subjects carrying the rs4151657 TT genotype showed higher risk (OR, 1.12; 95% CI, 1.09-1.16) compared with the other genotypes (OR <1.06 for TC and CC). Similarly, higher risk was observed among subjects carrying the rs7005722 AA genotype (OR, 1.17; 95% CI, 1.07-1.28) compared with the other genotypes (OR <1.13 for AC and CC). Functional annotation revealed that SNPs in 3p12.1 and 6p21.33 loci were located in regulatory regions, and were associated with expression levels of nearby genes. Genetic models predicting gene expression revealed that smoking parameters were associated with lower colorectal cancer risk with higher expression levels of CADM2 (3p12.1) and ATF6B (6p21.33).CONCLUSIONS: Our study identified novel genetic loci that may modulate the risk for colorectal cancer of smoking status and intensity, linked to tumor suppression and immune response.IMPACT: These findings can guide potential prevention treatments.
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6.
  • Tian, Yu, et al. (author)
  • Genetic risk impacts the association of menopausal hormone therapy with colorectal cancer risk
  • 2024
  • In: British Journal of Cancer. - : Springer Nature. - 0007-0920 .- 1532-1827.
  • Journal article (peer-reviewed)abstract
    • Background: Menopausal hormone therapy (MHT), a common treatment to relieve symptoms of menopause, is associated with a lower risk of colorectal cancer (CRC). To inform CRC risk prediction and MHT risk-benefit assessment, we aimed to evaluate the joint association of a polygenic risk score (PRS) for CRC and MHT on CRC risk.Methods: We used data from 28,486 postmenopausal women (11,519 cases and 16,967 controls) of European descent. A PRS based on 141 CRC-associated genetic variants was modeled as a categorical variable in quartiles. Multiplicative interaction between PRS and MHT use was evaluated using logistic regression. Additive interaction was measured using the relative excess risk due to interaction (RERI). 30-year cumulative risks of CRC for 50-year-old women according to MHT use and PRS were calculated.Results: The reduction in odds ratios by MHT use was larger in women within the highest quartile of PRS compared to that in women within the lowest quartile of PRS (p-value = 2.7 × 10−8). At the highest quartile of PRS, the 30-year CRC risk was statistically significantly lower for women taking any MHT than for women not taking any MHT, 3.7% (3.3%–4.0%) vs 6.1% (5.7%–6.5%) (difference 2.4%, P-value = 1.83 × 10−14); these differences were also statistically significant but smaller in magnitude in the lowest PRS quartile, 1.6% (1.4%–1.8%) vs 2.2% (1.9%–2.4%) (difference 0.6%, P-value = 1.01 × 10−3), indicating 4 times greater reduction in absolute risk associated with any MHT use in the highest compared to the lowest quartile of genetic CRC risk.Conclusions: MHT use has a greater impact on the reduction of CRC risk for women at higher genetic risk. These findings have implications for the development of risk prediction models for CRC and potentially for the consideration of genetic information in the risk-benefit assessment of MHT use.
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7.
  • Tian, Yu, et al. (author)
  • Genome-Wide Interaction Analysis of Genetic Variants With Menopausal Hormone Therapy for Colorectal Cancer Risk
  • 2022
  • In: Journal of the National Cancer Institute. - : Oxford University Press. - 0027-8874 .- 1460-2105. ; 114:8, s. 1135-1148
  • Journal article (peer-reviewed)abstract
    • BACKGROUND: The use of menopausal hormone therapy (MHT) may interact with genetic variants to influence colorectal cancer (CRC) risk. METHODS: We conducted a genome-wide, gene-environment interaction between single nucleotide polymorphisms and the use of any MHT, estrogen only, and combined estrogen-progestogen therapy with CRC risk, among 28 486 postmenopausal women (11 519 CRC patients and 16 967 participants without CRC) from 38 studies, using logistic regression, 2-step method, and 2- or 3-degree-of-freedom joint test. A set-based score test was applied for rare genetic variants. RESULTS: The use of any MHT, estrogen only and estrogen-progestogen were associated with a reduced CRC risk (odds ratio [OR] = 0.71, 95% confidence interval [CI] = 0.64 to 0.78; OR = 0.65, 95% CI = 0.53 to 0.79; and OR = 0.73, 95% CI = 0.59 to 0.90, respectively). The 2-step method identified a statistically significant interaction between a GRIN2B variant rs117868593 and MHT use, whereby MHT-associated CRC risk was statistically significantly reduced in women with the GG genotype (OR = 0.68, 95% CI = 0.64 to 0.72) but not within strata of GC or CC genotypes. A statistically significant interaction between a DCBLD1 intronic variant at 6q22.1 (rs10782186) and MHT use was identified by the 2-degree-of-freedom joint test. The MHT-associated CRC risk was reduced with increasing number of rs10782186-C alleles, showing odds ratios of 0.78 (95% CI = 0.70 to 0.87) for TT, 0.68 (95% CI = 0.63 to 0.73) for TC, and 0.66 (95% CI = 0.60 to 0.74) for CC genotypes. In addition, 5 genes in rare variant analysis showed suggestive interactions with MHT (2-sided P < 1.2 × 10-4). CONCLUSION: Genetic variants that modify the association between MHT and CRC risk were identified, offering new insights into pathways of CRC carcinogenesis and potential mechanisms involved.
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8.
  • Zaidi, Syed H., et al. (author)
  • Landscape of somatic single nucleotide variants and indels in colorectal cancer and impact on survival
  • 2020
  • In: Nature Communications. - : Nature Publishing Group. - 2041-1723. ; 11:1
  • Journal article (peer-reviewed)abstract
    • Colorectal cancer (CRC) is a biologically heterogeneous disease. To characterize its mutational profile, we conduct targeted sequencing of 205 genes for 2,105 CRC cases with survival data. Our data shows several findings in addition to enhancing the existing knowledge of CRC. We identify PRKCI, SPZ1, MUTYH, MAP2K4, FETUB, and TGFBR2 as additional genes significantly mutated in CRC. We find that among hypermutated tumors, an increased mutation burden is associated with improved CRC-specific survival (HR=0.42, 95% CI: 0.21-0.82). Mutations in TP53 are associated with poorer CRC-specific survival, which is most pronounced in cases carrying TP53 mutations with predicted 0% transcriptional activity (HR=1.53, 95% CI: 1.21-1.94). Furthermore, we observe differences in mutational frequency of several genes and pathways by tumor location, stage, and sex. Overall, this large study provides deep insights into somatic mutations in CRC, and their potential relationships with survival and tumor features. Large scale sequencing study is of paramount importance to unravel the heterogeneity of colorectal cancer. Here, the authors sequenced 205 cancer genes in more than 2000 tumours and identified additional mutated driver genes, determined that mutational burden and specific mutations in TP53 are associated with survival odds.
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9.
  • Thomas, Claire E., et al. (author)
  • Epidemiologic factors in relation to colorectal cancer risk and survival by genotoxic colibactin mutational signature
  • 2024
  • In: Cancer Epidemiology, Biomarkers and Prevention. - : American Association For Cancer Research (AACR). - 1055-9965 .- 1538-7755. ; 33:4, s. 534-546
  • Journal article (peer-reviewed)abstract
    • BACKGROUND: The genotoxin colibactin causes a tumor single-base substitution (SBS) mutational signature, SBS88. It is unknown whether epidemiologic factors' association with colorectal cancer risk and survival differs by SBS88.METHODS: Within the Genetic Epidemiology of Colorectal Cancer Consortium and Colon Cancer Family Registry, we measured SBS88 in 4,308 microsatellite stable/microsatellite instability low tumors. Associations of epidemiologic factors with colorectal cancer risk by SBS88 were assessed using multinomial regression (N = 4,308 cases, 14,192 controls; cohort-only cases N = 1,911), and with colorectal cancer-specific survival using Cox proportional hazards regression (N = 3,465 cases).RESULTS: 392 (9%) tumors were SBS88 positive. Among all cases, the highest quartile of fruit intake was associated with lower risk of SBS88-positive colorectal cancer than SBS88-negative colorectal cancer [odds ratio (OR) = 0.53, 95% confidence interval (CI) 0.37-0.76; OR = 0.75, 95% CI 0.66-0.85, respectively, Pheterogeneity = 0.047]. Among cohort studies, associations of body mass index (BMI), alcohol, and fruit intake with colorectal cancer risk differed by SBS88. BMI ≥30 kg/m2 was associated with worse colorectal cancer-specific survival among those SBS88-positive [hazard ratio (HR) = 3.40, 95% CI 1.47-7.84], but not among those SBS88-negative (HR = 0.97, 95% CI 0.78-1.21, Pheterogeneity = 0.066).CONCLUSIONS: Most epidemiologic factors did not differ by SBS88 for colorectal cancer risk or survival. Higher BMI may be associated with worse colorectal cancer-specific survival among those SBS88-positive; however, validation is needed in samples with whole-genome or whole-exome sequencing available.IMPACT: This study highlights the importance of identification of tumor phenotypes related to colorectal cancer and understanding potential heterogeneity for risk and survival.
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10.
  • Aglago, Elom K., et al. (author)
  • A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk
  • 2023
  • In: Cancer Research. - : American Association For Cancer Research (AACR). - 0008-5472 .- 1538-7445. ; 83:15, s. 2572-2583
  • Journal article (peer-reviewed)abstract
    • Colorectal cancer risk can be impacted by genetic, environmental, and lifestyle factors, including diet and obesity. Gene-environment interactions (G × E) can provide biological insights into the effects of obesity on colorectal cancer risk. Here, we assessed potential genome-wide G × E interactions between body mass index (BMI) and common SNPs for colorectal cancer risk using data from 36,415 colorectal cancer cases and 48,451 controls from three international colorectal cancer consortia (CCFR, CORECT, and GECCO). The G × E tests included the conventional logistic regression using multiplicative terms (one degree of freedom, 1DF test), the two-step EDGE method, and the joint 3DF test, each of which is powerful for detecting G × E interactions under specific conditions. BMI was associated with higher colorectal cancer risk. The two-step approach revealed a statistically significant G×BMI interaction located within the Formin 1/Gremlin 1 (FMN1/GREM1) gene region (rs58349661). This SNP was also identified by the 3DF test, with a suggestive statistical significance in the 1DF test. Among participants with the CC genotype of rs58349661, overweight and obesity categories were associated with higher colorectal cancer risk, whereas null associations were observed across BMI categories in those with the TT genotype. Using data from three large international consortia, this study discovered a locus in the FMN1/GREM1 gene region that interacts with BMI on the association with colorectal cancer risk. Further studies should examine the potential mechanisms through which this locus modifies the etiologic link between obesity and colorectal cancer.SIGNIFICANCE: This gene-environment interaction analysis revealed a genetic locus in FMN1/GREM1 that interacts with body mass index in colorectal cancer risk, suggesting potential implications for precision prevention strategies.
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Drew, David A. (29)
Chan, Andrew T. (28)
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Newcomb, Polly A. (15)
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