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104 results on '"Guillaume, C."'

1. The ALMA-ALPINE [CII] survey: sub-kpc morphology of 3 main-sequence galaxy systems at z~4.5 revealed by ALMA

Author

Devereaux, T., Cassata, P., Ibar, E., Accard, C., Guillaume, C., Béthermin, M., Dessauges-Zavadsky, M., Faisst, A., Jones, G. C., Zanella, A., Bardelli, S., Boquien, M., D'Onghia, E., Giavalisco, M., Ginolfi, M., Gobat, R., Hayward, C. C., Koekemoer, A. M., Lemaux, B., Magdis, G., Mendez-Hernandez, H., Molina, J., Pozzi, F., Romano, M., Tasca, L., Vergani, D., Zamorani, G., and Zucca, E.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Context: From redshift 6 to redshift $\approx$ 4 galaxies grow rapidly from low mass galaxies towards the more mature massive galaxies we see at the cosmic noon. Growth via gas accretion and mergers undoubtedly shape this evolution - however, there currently exists much uncertainty over the contribution of each of these processes to the overall evolution of galaxies. Furthermore, previous characterisations of the morphology of galaxies in the molecular gas phase has been limited by the coarse resolution of previous observations. Aims: The goal of this paper is to derive the morpho-kinematic properties of 3 main-sequence systems at $z\sim4.5$, drawn from the ALPINE survey, using brand new high-resolution ALMA data in band 7. The objects were previously characterised as one merger with three components, and and two dispersion-dominated galaxies. Methods: We use intensity and velocity maps, position-velocity diagrams and radial profiles of [CII], in combination with dust continuum maps, to analyse the morphology and kinematics of the 3 systems.} Results: In general, we find that the high-resolution ALMA data reveal more complex morpho-kinematic properties. We identify in one galaxy interaction-induced clumps, showing the profound effect that mergers have on the molecular gas in galaxies, consistent with what is suggested in recent simulations. A galaxy that was previously classified as dispersion dominated turned out to show two bright [CII] emission regions, that could either be merging galaxies or massive star-forming regions within the galaxy itself. The high resolution data for the other dispersion dominated object also revealed clumps of [CII] that were not previously identified. Within the sample, we might also detect star-formation powered outflows (or outflows from Active Galactic Nuclei) which appear to be fuelling diffuse gas regions and enriching the circumgalactic medium., Comment: Submitted to A&A, 13 pages

Published
2023
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2. The ALMA-ALPINE [CII] survey: Kennicutt-Schmidt relation in four massive main-sequence galaxies at z~4.5

Author

Béthermin, M., Accard, C., Guillaume, C., Dessauges-Zavadsky, M., Ibar, E., Cassata, P., Devereaux, T., Faisst, A., Freundlich, J., Jones, G. C., Kraljic, K., Algera, H., Amorin, R. O., Bardelli, S., Boquien, M., Buat, V., Donghia, E., Dubois, Y., Ferrara, A., Fudamoto, Y., Ginolfi, M., Guillard, P., Giavalisco, M., Gruppioni, C., Gururajan, G., Hathi, N., Hayward, C. C., Koekemoer, A. M., Lemaux, B. C., Magdis, G. E., Molina, J., Narayanan, D., Mayer, L., Pozzi, F., Rizzo, F., Romano, M., Tasca, L., Theulé, P., Vergani, D., Vallini, L., Zamorani, G., Zanella, A., and Zucca, E.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

The Kennicutt-Schmidt (KS) relation between the gas and the star formation rate (SFR) surface density ($\Sigma_{\rm gas}$-$\Sigma_{\rm SFR}$) is essential to understand star formation processes in galaxies. So far, it has been measured up to z~2.5 in main-sequence galaxies. In this letter, we aim to put constraints at z~4.5 using a sample of four massive main-sequence galaxies observed by ALMA at high resolution. We obtained ~0.3"-resolution [CII] and continuum maps of our objects, which we then converted into gas and obscured SFR surface density maps. In addition, we produced unobscured SFR surface density maps by convolving Hubble ancillary data in the rest-frame UV. We then derived the average $\Sigma_{\rm SFR}$ in various $\Sigma_{\rm gas}$ bins, and estimated the uncertainties using a Monte Carlo sampling. Our galaxy sample follows the KS relation measured in main-sequence galaxies at lower redshift and is slightly lower than predictions from simulations. Our data points probe the high end both in terms of $\Sigma_{\rm gas}$ and $\Sigma_{\rm gas}$, and gas depletion timescales (285-843 Myr) remain similar to z~2 objects. However, three of our objects are clearly morphologically disturbed, and we could have expected shorter gas depletion timescales (~100 Myr) similar to merger-driven starbursts at lower redshifts. This suggests that the mechanisms triggering starbursts at high redshift may be different than in the low- and intermediate-z Universe., Comment: 9 pages, 7 figures, 2 tables, accepted by A&A (letter)

Published
2023

4. The Effects of Aspirin Intervention on Inflammation-Associated Lingual Bacteria: A Pilot Study from a Randomized Clinical Trial

Author

Guillaume C. Onyeaghala, Shweta Sharma, Mosunmoluwa Oyenuga, Christopher M. Staley, Ginger L. Milne, Ryan T. Demmer, Aasma Shaukat, Bharat Thyagarajan, Robert J. Straka, Timothy R. Church, and Anna E. Prizment

Subjects
oral microbiome, periodontitis, colorectal cancer, aspirin, Biology (General), QH301-705.5
Abstract

Several bacterial taxa enriched in inflammatory bowel diseases and colorectal cancer (CRC) are found in the oral cavity. We conducted a pilot study nested within a six-week aspirin intervention in a randomized placebo-controlled trial to test their response to aspirin intervention. Fifty healthy subjects, 50–75 years old, were randomized to receive 325 mg aspirin (n = 30) or placebo (n = 20) orally once daily for six weeks. Oral tongue swabs were collected at baseline and week six. We estimated the association between aspirin use and the temporal changes in the relative abundance of pre-specified genus level taxa from pre- to post-treatment. The temporal change in relative abundance differed for eight genus level taxa between the aspirin and placebo groups. In the aspirin group, there were significant increases in the relative abundances of Neisseria, Streptococcus, Actinomyces, and Rothia and significant decreases in Prevotella, Veillonella, Fusobacterium, and Porphyromonas relative to placebo. The log ratio of Neisseria to Fusobacterium declined more in the aspirin group than placebo, signaling a potential marker associated with aspirin intervention. These preliminary findings should be validated using metagenomic sequencing and may guide future studies on the role of aspirin on taxa in various oral ecological niches.

Published
2024
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11. The Effects of Aspirin Intervention on Inflammation-Associated Lingual Bacteria: A Pilot Study from a Randomized Clinical Trial.

Author

Onyeaghala, Guillaume C., Sharma, Shweta, Oyenuga, Mosunmoluwa, Staley, Christopher M., Milne, Ginger L., Demmer, Ryan T., Shaukat, Aasma, Thyagarajan, Bharat, Straka, Robert J., Church, Timothy R., and Prizment, Anna E.

Subjects
INFLAMMATORY bowel diseases, CLINICAL trials, ASPIRIN, ECOLOGICAL niche, COLORECTAL cancer
Abstract

Several bacterial taxa enriched in inflammatory bowel diseases and colorectal cancer (CRC) are found in the oral cavity. We conducted a pilot study nested within a six-week aspirin intervention in a randomized placebo-controlled trial to test their response to aspirin intervention. Fifty healthy subjects, 50–75 years old, were randomized to receive 325 mg aspirin (n = 30) or placebo (n = 20) orally once daily for six weeks. Oral tongue swabs were collected at baseline and week six. We estimated the association between aspirin use and the temporal changes in the relative abundance of pre-specified genus level taxa from pre- to post-treatment. The temporal change in relative abundance differed for eight genus level taxa between the aspirin and placebo groups. In the aspirin group, there were significant increases in the relative abundances of Neisseria, Streptococcus, Actinomyces, and Rothia and significant decreases in Prevotella, Veillonella, Fusobacterium, and Porphyromonas relative to placebo. The log ratio of Neisseria to Fusobacterium declined more in the aspirin group than placebo, signaling a potential marker associated with aspirin intervention. These preliminary findings should be validated using metagenomic sequencing and may guide future studies on the role of aspirin on taxa in various oral ecological niches. [ABSTRACT FROM AUTHOR]

Published
2024
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12. Fecal β-glucuronidase activity differs between hematopoietic cell and kidney transplantation and a possible mechanism for disparate dose requirements

Author

Mohammad Haneef Khan, Guillaume C. Onyeaghala, Armin Rashidi, Shernan G. Holtan, Alexander Khoruts, Ajay Israni, Pamala A. Jacobson, and Christopher Staley

Subjects
Beta-glucuronidase, immunosuppression, intestinal microbiota, mycophenolate, MMF, transplantation, Diseases of the digestive system. Gastroenterology, RC799-869
Abstract

The intestinal microbiota produces β-glucuronidase that plays an essential role in the metabolism of the immunosuppressant mycophenolate mofetil (MMF). This drug is commonly used in organ and hematopoietic cell transplantation (HCT), with variations in dosing across transplant types. We hypothesized that β-glucuronidase activity differs between transplant types, which may account for differences in dosing requirements. We evaluated fecal β-glucuronidase activity in patients receiving MMF post-allogeneic HCT and post-kidney transplant. Kidney transplant patients had significantly greater β-glucuronidase activity (8.48 ± 6.21 nmol/hr/g) than HCT patients (3.50 ± 3.29 nmol/hr/g; P = .001). Microbially mediated β-glucuronidase activity may be a critical determinant in the amount of mycophenolate entering the systemic circulation and an important factor to consider for precision dosing of MMF.

Published
2022
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13. ALMA-ALPINE CII survey: The sub-kpc morphology of three main sequence galaxy systems at zsim 4.5 revealed by ALMA

Author

Devereaux, T., primary, Cassata, P., additional, Ibar, E., additional, Accard, C., additional, Guillaume, C., additional, B'ethermin, M., additional, Dessauges-Zavadsky, M., additional, Faisst, A., additional, Jones, G.C., additional, Zanella, A., additional, Bardelli, S., additional, Boquien, M., additional, D'Onghia, E., additional, Giavalisco, M., additional, Ginolfi, M., additional, Gobat, R., additional, Hayward, C., additional, Koekemoer, A.M., additional, Lemaux, B., additional, Magdis, G., additional, Mendez-Hernandez, H., additional, Molina, J., additional, Pozzi, F., additional, Romano, M., additional, Tasca, L., additional, Vergani, D., additional, Zamorani, G., additional, and Zucca, E., additional

Published
2024
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14. The ALMA-ALPINE [CII] survey: Kennicutt-Schmidt relation in four massive main-sequence galaxies at z ∼ 4.5

Author

Béthermin, M., primary, Accard, C., additional, Guillaume, C., additional, Dessauges-Zavadsky, M., additional, Ibar, E., additional, Cassata, P., additional, Devereaux, T., additional, Faisst, A., additional, Freundlich, J., additional, Jones, G. C., additional, Kraljic, K., additional, Algera, H., additional, Amorín, R. O., additional, Bardelli, S., additional, Boquien, M., additional, Buat, V., additional, Donghia, E., additional, Dubois, Y., additional, Ferrara, A., additional, Fudamoto, Y., additional, Ginolfi, M., additional, Guillard, P., additional, Giavalisco, M., additional, Gruppioni, C., additional, Gururajan, G., additional, Hathi, N., additional, Hayward, C. C., additional, Koekemoer, A. M., additional, Lemaux, B. C., additional, Magdis, G. E., additional, Molina, J., additional, Narayanan, D., additional, Mayer, L., additional, Pozzi, F., additional, Rizzo, F., additional, Romano, M., additional, Tasca, L., additional, Theulé, P., additional, Vergani, D., additional, Vallini, L., additional, Zamorani, G., additional, Zanella, A., additional, and Zucca, E., additional

Published
2023
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15. Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Shuo Wang, Guillaume C. Onyeaghala, Nathan Pankratz, Heather H. Nelson, Bharat Thyagarajan, Weihong Tang, Faye L. Norby, Chinenye Ugoji, Corinne E. Joshu, Christian R. Gomez, David J. Couper, Josef Coresh, Elizabeth A. Platz, and Anna E. Prizment

Subjects
Oncology, Epidemiology
Abstract

Background: The MHC class I chain-related protein A (MICA) and protein B (MICB) participate in tumor immunosurveillance and may be important in colorectal cancer, but have not been examined in colorectal cancer development. Methods: sMICA and sMICB blood levels were measured by SomaScan in Visit 2 (1990–92, baseline) and Visit 3 (1993–95) samples in cancer-free participants in the Atherosclerosis Risk in Communities Study. We selected rs1051792, rs1063635, rs2516448, rs3763288, rs1131896, rs2596542, and rs2395029 that were located in or in the vicinity of MICA or MICB and were associated with cancer or autoimmune diseases in published studies. SNPs were genotyped by the Affymetrix Genome-Wide Human SNP Array. We applied linear and Cox proportional hazards regressions to examine the associations of preselected SNPs with sMICA and sMICB levels and colorectal cancer risk (236 colorectal cancers, 8,609 participants) and of sMICA and sMICB levels with colorectal cancer risk (312 colorectal cancers, 10,834 participants). In genetic analyses, estimates adjusted for ancestry markers were meta-analyzed. Results: Rs1051792-A, rs1063635-A, rs2516448-C, rs3763288-A, rs2596542-T, and rs2395029-G were significantly associated with decreased sMICA levels. Rs2395029-G, in the vicinity of MICA and MICB, was also associated with increased sMICB levels. Rs2596542-T was significantly associated with decreased colorectal cancer risk. Lower sMICA levels were associated with lower colorectal cancer risk in males (HR = 0.68; 95% confidence interval, 0.49–0.96) but not in females (Pinteraction = 0.08). Conclusions: Rs2596542-T associated with lower sMICA levels was associated with decreased colorectal cancer risk. Lower sMICA levels were associated with lower colorectal cancer risk in males. Impact: These findings support an importance of immunosurveillance in colorectal cancer.

Published
2023

16. Supplementary Table 2 from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Wang, Shuo, primary, Onyeaghala, Guillaume C., primary, Pankratz, Nathan, primary, Nelson, Heather H., primary, Thyagarajan, Bharat, primary, Tang, Weihong, primary, Norby, Faye L., primary, Ugoji, Chinenye, primary, Joshu, Corinne E., primary, Gomez, Christian R., primary, Couper, David J., primary, Coresh, Josef, primary, Platz, Elizabeth A., primary, and Prizment, Anna E., primary

Published
2023
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17. Supplementary Table 3 from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Wang, Shuo, primary, Onyeaghala, Guillaume C., primary, Pankratz, Nathan, primary, Nelson, Heather H., primary, Thyagarajan, Bharat, primary, Tang, Weihong, primary, Norby, Faye L., primary, Ugoji, Chinenye, primary, Joshu, Corinne E., primary, Gomez, Christian R., primary, Couper, David J., primary, Coresh, Josef, primary, Platz, Elizabeth A., primary, and Prizment, Anna E., primary

Published
2023
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18. Supplementary Table 6 from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Wang, Shuo, primary, Onyeaghala, Guillaume C., primary, Pankratz, Nathan, primary, Nelson, Heather H., primary, Thyagarajan, Bharat, primary, Tang, Weihong, primary, Norby, Faye L., primary, Ugoji, Chinenye, primary, Joshu, Corinne E., primary, Gomez, Christian R., primary, Couper, David J., primary, Coresh, Josef, primary, Platz, Elizabeth A., primary, and Prizment, Anna E., primary

Published
2023
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19. Supplementary Table 5 from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Wang, Shuo, primary, Onyeaghala, Guillaume C., primary, Pankratz, Nathan, primary, Nelson, Heather H., primary, Thyagarajan, Bharat, primary, Tang, Weihong, primary, Norby, Faye L., primary, Ugoji, Chinenye, primary, Joshu, Corinne E., primary, Gomez, Christian R., primary, Couper, David J., primary, Coresh, Josef, primary, Platz, Elizabeth A., primary, and Prizment, Anna E., primary

Published
2023
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20. Supplementary Table 8 from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Wang, Shuo, primary, Onyeaghala, Guillaume C., primary, Pankratz, Nathan, primary, Nelson, Heather H., primary, Thyagarajan, Bharat, primary, Tang, Weihong, primary, Norby, Faye L., primary, Ugoji, Chinenye, primary, Joshu, Corinne E., primary, Gomez, Christian R., primary, Couper, David J., primary, Coresh, Josef, primary, Platz, Elizabeth A., primary, and Prizment, Anna E., primary

Published
2023
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21. Supplementary Table 1 from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Wang, Shuo, primary, Onyeaghala, Guillaume C., primary, Pankratz, Nathan, primary, Nelson, Heather H., primary, Thyagarajan, Bharat, primary, Tang, Weihong, primary, Norby, Faye L., primary, Ugoji, Chinenye, primary, Joshu, Corinne E., primary, Gomez, Christian R., primary, Couper, David J., primary, Coresh, Josef, primary, Platz, Elizabeth A., primary, and Prizment, Anna E., primary

Published
2023
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22. Data from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Wang, Shuo, primary, Onyeaghala, Guillaume C., primary, Pankratz, Nathan, primary, Nelson, Heather H., primary, Thyagarajan, Bharat, primary, Tang, Weihong, primary, Norby, Faye L., primary, Ugoji, Chinenye, primary, Joshu, Corinne E., primary, Gomez, Christian R., primary, Couper, David J., primary, Coresh, Josef, primary, Platz, Elizabeth A., primary, and Prizment, Anna E., primary

Published
2023
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23. Supplementary Table 7 from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Wang, Shuo, primary, Onyeaghala, Guillaume C., primary, Pankratz, Nathan, primary, Nelson, Heather H., primary, Thyagarajan, Bharat, primary, Tang, Weihong, primary, Norby, Faye L., primary, Ugoji, Chinenye, primary, Joshu, Corinne E., primary, Gomez, Christian R., primary, Couper, David J., primary, Coresh, Josef, primary, Platz, Elizabeth A., primary, and Prizment, Anna E., primary

Published
2023
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24. Supplementary Table 4 from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Wang, Shuo, primary, Onyeaghala, Guillaume C., primary, Pankratz, Nathan, primary, Nelson, Heather H., primary, Thyagarajan, Bharat, primary, Tang, Weihong, primary, Norby, Faye L., primary, Ugoji, Chinenye, primary, Joshu, Corinne E., primary, Gomez, Christian R., primary, Couper, David J., primary, Coresh, Josef, primary, Platz, Elizabeth A., primary, and Prizment, Anna E., primary

Published
2023
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25. Supplementary Table 9 from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Wang, Shuo, primary, Onyeaghala, Guillaume C., primary, Pankratz, Nathan, primary, Nelson, Heather H., primary, Thyagarajan, Bharat, primary, Tang, Weihong, primary, Norby, Faye L., primary, Ugoji, Chinenye, primary, Joshu, Corinne E., primary, Gomez, Christian R., primary, Couper, David J., primary, Coresh, Josef, primary, Platz, Elizabeth A., primary, and Prizment, Anna E., primary

Published
2023
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26. Supplementary Table 2 from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Anna E. Prizment, Elizabeth A. Platz, Josef Coresh, David J. Couper, Christian R. Gomez, Corinne E. Joshu, Chinenye Ugoji, Faye L. Norby, Weihong Tang, Bharat Thyagarajan, Heather H. Nelson, Nathan Pankratz, Guillaume C. Onyeaghala, and Shuo Wang

Abstract

Supplemental Table 2 shows the associations between pre-selected SNPs and Visit 2 sMICA and sMICB levels (continuous variables) stratified by sex, race, or diabetes status.

Published
2023

27. Supplementary Table 4 from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Anna E. Prizment, Elizabeth A. Platz, Josef Coresh, David J. Couper, Christian R. Gomez, Corinne E. Joshu, Chinenye Ugoji, Faye L. Norby, Weihong Tang, Bharat Thyagarajan, Heather H. Nelson, Nathan Pankratz, Guillaume C. Onyeaghala, and Shuo Wang

Abstract

Supplemental Table 4 shows the associations of Visit 2 sMICA and sMICB levels (in quartiles) with CRC risk.

Published
2023

28. Supplementary Table 3 from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Anna E. Prizment, Elizabeth A. Platz, Josef Coresh, David J. Couper, Christian R. Gomez, Corinne E. Joshu, Chinenye Ugoji, Faye L. Norby, Weihong Tang, Bharat Thyagarajan, Heather H. Nelson, Nathan Pankratz, Guillaume C. Onyeaghala, and Shuo Wang

Abstract

Supplemental Table 3 shows the associations between pre-selected SNPs and CRC risk stratified by sex, race, or diabetes status.

Published
2023

29. Supplementary Table 8 from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Anna E. Prizment, Elizabeth A. Platz, Josef Coresh, David J. Couper, Christian R. Gomez, Corinne E. Joshu, Chinenye Ugoji, Faye L. Norby, Weihong Tang, Bharat Thyagarajan, Heather H. Nelson, Nathan Pankratz, Guillaume C. Onyeaghala, and Shuo Wang

Abstract

Supplemental Table 8 shows the associations of pre-selected SNPs with Visit 2 sMICA and sMICB levels and CRC risk without adjustment for ancestry markers.

Published
2023

30. Data from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Anna E. Prizment, Elizabeth A. Platz, Josef Coresh, David J. Couper, Christian R. Gomez, Corinne E. Joshu, Chinenye Ugoji, Faye L. Norby, Weihong Tang, Bharat Thyagarajan, Heather H. Nelson, Nathan Pankratz, Guillaume C. Onyeaghala, and Shuo Wang

Abstract

Background:The MHC class I chain-related protein A (MICA) and protein B (MICB) participate in tumor immunosurveillance and may be important in colorectal cancer, but have not been examined in colorectal cancer development.Methods:sMICA and sMICB blood levels were measured by SomaScan in Visit 2 (1990–92, baseline) and Visit 3 (1993–95) samples in cancer-free participants in the Atherosclerosis Risk in Communities Study. We selected rs1051792, rs1063635, rs2516448, rs3763288, rs1131896, rs2596542, and rs2395029 that were located in or in the vicinity of MICA or MICB and were associated with cancer or autoimmune diseases in published studies. SNPs were genotyped by the Affymetrix Genome-Wide Human SNP Array. We applied linear and Cox proportional hazards regressions to examine the associations of preselected SNPs with sMICA and sMICB levels and colorectal cancer risk (236 colorectal cancers, 8,609 participants) and of sMICA and sMICB levels with colorectal cancer risk (312 colorectal cancers, 10,834 participants). In genetic analyses, estimates adjusted for ancestry markers were meta-analyzed.Results:Rs1051792-A, rs1063635-A, rs2516448-C, rs3763288-A, rs2596542-T, and rs2395029-G were significantly associated with decreased sMICA levels. Rs2395029-G, in the vicinity of MICA and MICB, was also associated with increased sMICB levels. Rs2596542-T was significantly associated with decreased colorectal cancer risk. Lower sMICA levels were associated with lower colorectal cancer risk in males (HR = 0.68; 95% confidence interval, 0.49–0.96) but not in females (Pinteraction = 0.08).Conclusions:Rs2596542-T associated with lower sMICA levels was associated with decreased colorectal cancer risk. Lower sMICA levels were associated with lower colorectal cancer risk in males.Impact:These findings support an importance of immunosurveillance in colorectal cancer.

Published
2023

31. Supplementary Table 1 from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Anna E. Prizment, Elizabeth A. Platz, Josef Coresh, David J. Couper, Christian R. Gomez, Corinne E. Joshu, Chinenye Ugoji, Faye L. Norby, Weihong Tang, Bharat Thyagarajan, Heather H. Nelson, Nathan Pankratz, Guillaume C. Onyeaghala, and Shuo Wang

Abstract

Supplemental Table 1 shows the results from previous studies that found significant associations between the pre-selected SNPs and risk of cancers or autoimmune diseases.

Published
2023

32. Supplementary Table 7 from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Anna E. Prizment, Elizabeth A. Platz, Josef Coresh, David J. Couper, Christian R. Gomez, Corinne E. Joshu, Chinenye Ugoji, Faye L. Norby, Weihong Tang, Bharat Thyagarajan, Heather H. Nelson, Nathan Pankratz, Guillaume C. Onyeaghala, and Shuo Wang

Abstract

Supplemental Table 7 shows the association of sMICA and sMICB levels (continuous variables) and pre-selected SNPsa with risk of CRC stratified by family history of CRC.

Published
2023

33. Supplementary Table 9 from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Anna E. Prizment, Elizabeth A. Platz, Josef Coresh, David J. Couper, Christian R. Gomez, Corinne E. Joshu, Chinenye Ugoji, Faye L. Norby, Weihong Tang, Bharat Thyagarajan, Heather H. Nelson, Nathan Pankratz, Guillaume C. Onyeaghala, and Shuo Wang

Abstract

Supplemental Table 9 shows the associations between pre-selected SNPs and mean of Visit 2 and Visit 3 sMICA and sMICB levels (continuous variables).

Published
2023

34. Supplementary Table 6 from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Anna E. Prizment, Elizabeth A. Platz, Josef Coresh, David J. Couper, Christian R. Gomez, Corinne E. Joshu, Chinenye Ugoji, Faye L. Norby, Weihong Tang, Bharat Thyagarajan, Heather H. Nelson, Nathan Pankratz, Guillaume C. Onyeaghala, and Shuo Wang

Abstract

Supplemental Table 6 shows the associations of sMICA and sMICB levels (continuous variables) and pre-selected SNPsb with risk of CRC and subtypes of CRC.

Published
2023

35. Supplementary Table 5 from Associations between MICA and MICB Genetic Variants, Protein Levels, and Colorectal Cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Anna E. Prizment, Elizabeth A. Platz, Josef Coresh, David J. Couper, Christian R. Gomez, Corinne E. Joshu, Chinenye Ugoji, Faye L. Norby, Weihong Tang, Bharat Thyagarajan, Heather H. Nelson, Nathan Pankratz, Guillaume C. Onyeaghala, and Shuo Wang

Abstract

Supplemental table 5 shows the associations between pre-selected SNPs and risk of CRC with and without adjustment for sMICA and sMICB levels.

Published
2023

36. Associations between MICA and MICB genetic variants, protein levels, and colorectal cancer: Atherosclerosis Risk in Communities (ARIC)

Author

Wang, Shuo, primary, Onyeaghala, Guillaume C., additional, Pankratz, Nathan, additional, Nelson, Heather H., additional, Thyagarajan, Bharat, additional, Tang, Weihong, additional, Norby, Faye L., additional, Ugoji, Chinenye, additional, Joshu, Corinne E., additional, Gomez, Christian R., additional, Couper, David J., additional, Coresh, Josef, additional, Platz, Elizabeth A., additional, and Prizment, Anna E., additional

Published
2023
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42. The NADPH oxidase NOX2 is a marker of adverse prognosis involved in chemoresistance of Acute Myeloid Leukemias

Author

Rawan H, Jérome M, Guillaume B, Marc P, Mathias B, Elise Gueret, Marion Dt, Rosa P, Pierre G, Ludovic G, Denis T, Hayeon B, Guillaume C, Jean-Emmanuel S, Christian R, Institut de Génétique Moléculaire de Montpellier (IGMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Institut de génétique humaine (IGH), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Institut de Génomique Fonctionnelle - Montpellier GenomiX (IGF MGX), Institut de Génomique Fonctionnelle (IGF), Université de Montpellier (UM)-Université Montpellier 1 (UM1)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Montpellier 2 - Sciences et Techniques (UM2)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Université Montpellier 1 (UM1)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Montpellier 2 - Sciences et Techniques (UM2)-Centre National de la Recherche Scientifique (CNRS), CHU Toulouse [Toulouse], Centre de Recherches en Cancérologie de Toulouse (CRCT), Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Montpellier, Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Service d'Hématologie [IUCT Toulouse], Université Fédérale Toulouse Midi-Pyrénées-Institut Universitaire du Cancer de Toulouse - Oncopole (IUCT Oncopole - UMR 1037), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Universitaire de Montpellier (CHU Montpellier ), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-BioCampus (BCM), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Service d'Hématologie [CHU Toulouse]

Subjects
Daunorubicin, [SDV]Life Sciences [q-bio], Inflammation, [SDV.CAN]Life Sciences [q-bio]/Cancer, [SDV.BC.BC]Life Sciences [q-bio]/Cellular Biology/Subcellular Processes [q-bio.SC], 03 medical and health sciences, 0302 clinical medicine, Downregulation and upregulation, medicine, CYBB, Gene, 030304 developmental biology, 0303 health sciences, Oxidase test, NADPH oxidase, biology, business.industry, 3. Good health, 030220 oncology & carcinogenesis, Cytarabine, biology.protein, Cancer research, [SDV.IMM]Life Sciences [q-bio]/Immunology, medicine.symptom, business, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, medicine.drug
Abstract

Resistance to chemotherapeutic drugs is a major cause of treatment failure in Acute Myeloid Leukemias (AML). To better characterize the mechanisms of chemoresistance, we first identified genes whose expression is dysregulated in AML cells resistant to daunorubicin (DNR) or cytarabine (Ara-C), the main drugs used for the induction therapy. The genes found activated are mostly linked to immune signaling and inflammation. Among them, we identified a strong up-regulation of the NOX2 NAPDH oxidase subunit genes (CYBB, CYBA, NCF1, NCF2, NCF4 and RAC2). The ensuing increase in NADPH oxidase activity, which is particularly strong in DNR-resistant cells, participates in the acquisition and/or maintenance of resistance to DNR. In addition, analyzing gp91phox (CYBB-encoded Nox2 catalytic sub-unit) expression at the surface of leukemic blasts from 74 patients at diagnosis showed that NOX2 is generally more expressed and active in leukemic cells from the FAB M4/M5 subtypes compared to FAB M0-M2 ones. Using a gene expression-based score we demonstrate that high NOX2 subunit genes expression is a marker of adverse prognosis, independent of the cytogenetic-based risk classification, in AML patients.

Published
2021

43. Evaluation of Cu2+ doping potential to control the calcium-phosphate particles-induced acute inflammatory response in bone site

Author

Thoraval, L., Thiebault, E., Siboni, R., Moniot, A., Guillaume, C., Jacobs, A., Nedelec, J.-M., Renaudin, G., Descamps, S., Marchat, D., Gangloff, S. C., Braux, J., Velard, F., Institut de Chimie de Clermont-Ferrand (ICCF), Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)-Institut national polytechnique Clermont Auvergne (INP Clermont Auvergne), Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), and Bonnefoy, Stéphanie

Subjects
[SDV] Life Sciences [q-bio], [SDV]Life Sciences [q-bio], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2021

45. Association Between Mycophenolic Acid (MPA) Pharmacokinetics and In Vitro MPA Glucuronide (MPAG) Turnover by Gut Microbiota of Kidney Transplant Recipients

Author

Onyeaghala, Guillaume C., Vo, Duy, Mohamed, Moataz, Saqr, Abdelrahman, Sanchez, Bryan P. Brito, Elmer, Sarah, Hunter, Ryan C., Teigen, Levi, Dorr, Casey R., Staley, Christopher, Wu, Baolin, Guan, Weihua, El-Rifai, Rasha, Matas, Arthur J., Oetting, William S., Jacobson, Pamala A., and Israni, Ajay K.

Published
2023
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48. Unexpected discovery of Trypanosoma brucei gambiense on CSF in a western country: About a case.

Author

Francois LA, Bret L, Wong So J, Gubavu C, Touafek F, Vinsonneau M, Kochbati K, Avettand-Fenoel V, Guillaume C, Carbonnelle E, Guinard J, and Mchantaf G

Subjects
Humans, Male, Trypanosoma brucei gambiense, Trypanosomiasis, African drug therapy, Trypanosomiasis, African cerebrospinal fluid
Abstract

Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Published
2024
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49. Human iPSC-derived photoreceptor transplantation in the cone dominant 13-lined ground squirrel.

Author

Yu CT, Kandoi S, Periasamy R, Reddy LVK, Follett HM, Summerfelt P, Martinez C, Guillaume C, Bowie O, Connor TB, Lipinski DM, Allen KP, Merriman DK, Carroll J, and Lamba DA

Subjects
Animals, Humans, Retinal Cone Photoreceptor Cells transplantation, Retina, Sciuridae, Induced Pluripotent Stem Cells transplantation, Retinal Degeneration therapy
Abstract

Several retinal degenerations affect the human central retina, which is primarily comprised of cones and is essential for high acuity and color vision. Transplanting cone photoreceptors is a promising strategy to replace degenerated cones in this region. Although this approach has been investigated in a handful of animal models, commonly used rodent models lack a cone-rich region and larger models can be expensive and inaccessible, impeding the translation of therapies. Here, we transplanted dissociated GFP-expressing photoreceptors from retinal organoids differentiated from human induced pluripotent stem cells into the subretinal space of damaged and undamaged cone-dominant 13-lined ground squirrel eyes. Transplanted cell survival was documented via noninvasive high-resolution imaging and immunohistochemistry to confirm the presence of human donor photoreceptors for up to 4 months posttransplantation. These results demonstrate the utility of a cone-dominant rodent model for advancing the clinical translation of cell replacement therapies., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Published
2024
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50. Portability of genomic predictions trained on sparse factorial designs across two maize silage breeding cycles.

Author

Lorenzi A, Bauland C, Pin S, Madur D, Combes V, Palaffre C, Guillaume C, Touzy G, Mary-Huard T, Charcosset A, and Moreau L

Subjects
Genomics methods, Plant Breeding, Silage, Hybridization, Genetic, Zea mays genetics
Abstract

Key Message: We validated the efficiency of genomic predictions calibrated on sparse factorial training sets to predict the next generation of hybrids and tested different strategies for updating predictions along generations. Genomic selection offers new prospects for revisiting hybrid breeding schemes by replacing extensive phenotyping of individuals with genomic predictions. Finding the ideal design for training genomic prediction models is still an open question. Previous studies have shown promising predictive abilities using sparse factorial instead of tester-based training sets to predict single-cross hybrids from the same generation. This study aims to further investigate the use of factorials and their optimization to predict line general combining abilities (GCAs) and hybrid values across breeding cycles. It relies on two breeding cycles of a maize reciprocal genomic selection scheme involving multiparental connected reciprocal populations from flint and dent complementary heterotic groups selected for silage performances. Selection based on genomic predictions trained on a factorial design resulted in a significant genetic gain for dry matter yield in the new generation. Results confirmed the efficiency of sparse factorial training sets to predict candidate line GCAs and hybrid values across breeding cycles. Compared to a previous study based on the first generation, the advantage of factorial over tester training sets appeared lower across generations. Updating factorial training sets by adding single-cross hybrids between selected lines from the previous generation or a random subset of hybrids from the new generation both improved predictive abilities. The CDmean criterion helped determine the set of single-crosses to phenotype to update the training set efficiently. Our results validated the efficiency of sparse factorial designs for calibrating hybrid genomic prediction experimentally and showed the benefit of updating it along generations., (© 2024. The Author(s).)

Published
2024
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