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1. Detection of skewed X-chromosome inactivation in Fragile X syndrome and X chromosome aneuploidy using quantitative melt analysis.

Author

Godler, David E, Inaba, Yoshimi, Schwartz, Charles E, Bui, Quang M, Shi, Elva Z, Li, Xin, Herlihy, Amy S, Skinner, Cindy, Hagerman, Randi J, Francis, David, Amor, David J, Metcalfe, Sylvia A, Hopper, John L, and Slater, Howard R

Subjects
Chromosomes, Human, X, Saliva, Humans, Fragile X Syndrome, Aneuploidy, DNA, DNA Methylation, Gene Expression, CpG Islands, Nucleic Acid Denaturation, Introns, Exons, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Child, Child, Preschool, Infant, Infant, Newborn, Female, Male, X Chromosome Inactivation, Fragile X Mental Retardation Protein, and over, Preschool, Chromosomes, Human, X, Newborn, Biochemistry and Cell Biology, Immunology
Abstract

Methylation of the fragile X mental retardation 1 (FMR1) exon 1/intron 1 boundary positioned fragile X related epigenetic element 2 (FREE2), reveals skewed X-chromosome inactivation (XCI) in fragile X syndrome full mutation (FM: CGG > 200) females. XCI skewing has been also linked to abnormal X-linked gene expression with the broader clinical impact for sex chromosome aneuploidies (SCAs). In this study, 10 FREE2 CpG sites were targeted using methylation specific quantitative melt analysis (MS-QMA), including 3 sites that could not be analysed with previously used EpiTYPER system. The method was applied for detection of skewed XCI in FM females and in different types of SCA. We tested venous blood and saliva DNA collected from 107 controls (CGG

Published
2015

2. A meta-analysis of genome-wide association studies of breast cancer identifies two novel susceptibility loci at 6q14 and 20q11

Author

Siddiq, Afshan, Couch, Fergus J, Chen, Gary K, Lindström, Sara, Eccles, Diana, Millikan, Robert C, Michailidou, Kyriaki, Stram, Daniel O, Beckmann, Lars, Rhie, Suhn Kyong, Ambrosone, Christine B, Aittomäki, Kristiina, Amiano, Pilar, Apicella, Carmel, Investigators, Australian Breast Cancer Tissue Bank, Baglietto, Laura, Bandera, Elisa V, Beckmann, Matthias W, Berg, Christine D, Bernstein, Leslie, Blomqvist, Carl, Brauch, Hiltrud, Brinton, Louise, Bui, Quang M, Buring, Julie E, Buys, Saundra S, Campa, Daniele, Carpenter, Jane E, Chasman, Daniel I, Chang-Claude, Jenny, Chen, Constance, Clavel-Chapelon, Françoise, Cox, Angela, Cross, Simon S, Czene, Kamila, Deming, Sandra L, Diasio, Robert B, Diver, W Ryan, Dunning, Alison M, Durcan, Lorraine, Ekici, Arif B, Fasching, Peter A, Study, Familial Breast Cancer, Feigelson, Heather Spencer, Fejerman, Laura, Figueroa, Jonine D, Fletcher, Olivia, Flesch-Janys, Dieter, Gaudet, Mia M, Consortium, The GENICA, Gerty, Susan M, Rodriguez-Gil, Jorge L, Giles, Graham G, van Gils, Carla H, Godwin, Andrew K, Graham, Nikki, Greco, Dario, Hall, Per, Hankinson, Susan E, Hartmann, Arndt, Hein, Rebecca, Heinz, Judith, Hoover, Robert N, Hopper, John L, Hu, Jennifer J, Huntsman, Scott, Ingles, Sue A, Irwanto, Astrid, Isaacs, Claudine, Jacobs, Kevin B, John, Esther M, Justenhoven, Christina, Kaaks, Rudolf, Kolonel, Laurence N, Coetzee, Gerhard A, Lathrop, Mark, Le Marchand, Loic, Lee, Adam M, Lee, I-Min, Lesnick, Timothy, Lichtner, Peter, Liu, Jianjun, Lund, Eiliv, Makalic, Enes, Martin, Nicholas G, McLean, Catriona A, Meijers-Heijboer, Hanne, Meindl, Alfons, Miron, Penelope, Monroe, Kristine R, Montgomery, Grant W, Müller-Myhsok, Bertram, Nickels, Stefan, Nyante, Sarah J, Olswold, Curtis, Overvad, Kim, Palli, Domenico, Park, Daniel J, Palmer, Julie R, and Pathak, Harsh

Subjects
Biological Sciences, Genetics, Clinical Research, Aging, Human Genome, Breast Cancer, Cancer, Aetiology, 2.1 Biological and endogenous factors, Breast Neoplasms, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Receptors, Estrogen, Australian Breast Cancer Tissue Bank Investigators, Familial Breast Cancer Study, GENICA Consortium, Medical and Health Sciences, Genetics & Heredity
Abstract

Genome-wide association studies (GWAS) of breast cancer defined by hormone receptor status have revealed loci contributing to susceptibility of estrogen receptor (ER)-negative subtypes. To identify additional genetic variants for ER-negative breast cancer, we conducted the largest meta-analysis of ER-negative disease to date, comprising 4754 ER-negative cases and 31 663 controls from three GWAS: NCI Breast and Prostate Cancer Cohort Consortium (BPC3) (2188 ER-negative cases; 25 519 controls of European ancestry), Triple Negative Breast Cancer Consortium (TNBCC) (1562 triple negative cases; 3399 controls of European ancestry) and African American Breast Cancer Consortium (AABC) (1004 ER-negative cases; 2745 controls). We performed in silico replication of 86 SNPs at P ≤ 1 × 10(-5) in an additional 11 209 breast cancer cases (946 with ER-negative disease) and 16 057 controls of Japanese, Latino and European ancestry. We identified two novel loci for breast cancer at 20q11 and 6q14. SNP rs2284378 at 20q11 was associated with ER-negative breast cancer (combined two-stage OR = 1.16; P = 1.1 × 10(-8)) but showed a weaker association with overall breast cancer (OR = 1.08, P = 1.3 × 10(-6)) based on 17 869 cases and 43 745 controls and no association with ER-positive disease (OR = 1.01, P = 0.67) based on 9965 cases and 22 902 controls. Similarly, rs17530068 at 6q14 was associated with breast cancer (OR = 1.12; P = 1.1 × 10(-9)), and with both ER-positive (OR = 1.09; P = 1.5 × 10(-5)) and ER-negative (OR = 1.16, P = 2.5 × 10(-7)) disease. We also confirmed three known loci associated with ER-negative (19p13) and both ER-negative and ER-positive breast cancer (6q25 and 12p11). Our results highlight the value of large-scale collaborative studies to identify novel breast cancer risk loci.

Published
2012

4. Appendix from Use of a Novel Nonparametric Version of DEPTH to Identify Genomic Regions Associated with Prostate Cancer Risk

Author

MacInnis, Robert J., primary, Schmidt, Daniel F., primary, Makalic, Enes, primary, Severi, Gianluca, primary, FitzGerald, Liesel M., primary, Reumann, Matthias, primary, Kapuscinski, Miroslaw K., primary, Kowalczyk, Adam, primary, Zhou, Zeyu, primary, Goudey, Benjamin, primary, Qian, Guoqi, primary, Bui, Quang M., primary, Park, Daniel J., primary, Freeman, Adam, primary, Southey, Melissa C., primary, Al Olama, Ali Amin, primary, Kote-Jarai, Zsofia, primary, Eeles, Rosalind A., primary, Hopper, John L., primary, and Giles, Graham G., primary

Published
2023
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5. Supplementary Table 1 from Use of a Novel Nonparametric Version of DEPTH to Identify Genomic Regions Associated with Prostate Cancer Risk

Author

MacInnis, Robert J., primary, Schmidt, Daniel F., primary, Makalic, Enes, primary, Severi, Gianluca, primary, FitzGerald, Liesel M., primary, Reumann, Matthias, primary, Kapuscinski, Miroslaw K., primary, Kowalczyk, Adam, primary, Zhou, Zeyu, primary, Goudey, Benjamin, primary, Qian, Guoqi, primary, Bui, Quang M., primary, Park, Daniel J., primary, Freeman, Adam, primary, Southey, Melissa C., primary, Al Olama, Ali Amin, primary, Kote-Jarai, Zsofia, primary, Eeles, Rosalind A., primary, Hopper, John L., primary, and Giles, Graham G., primary

Published
2023
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6. Supplementary Figure 1 from Use of a Novel Nonparametric Version of DEPTH to Identify Genomic Regions Associated with Prostate Cancer Risk

Author

MacInnis, Robert J., primary, Schmidt, Daniel F., primary, Makalic, Enes, primary, Severi, Gianluca, primary, FitzGerald, Liesel M., primary, Reumann, Matthias, primary, Kapuscinski, Miroslaw K., primary, Kowalczyk, Adam, primary, Zhou, Zeyu, primary, Goudey, Benjamin, primary, Qian, Guoqi, primary, Bui, Quang M., primary, Park, Daniel J., primary, Freeman, Adam, primary, Southey, Melissa C., primary, Al Olama, Ali Amin, primary, Kote-Jarai, Zsofia, primary, Eeles, Rosalind A., primary, Hopper, John L., primary, and Giles, Graham G., primary

Published
2023
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8. Autism Spectrum Phenotype in Males and Females with Fragile X Full Mutation and Premutation

Author

Clifford, Sally, Dissanayake, Cheryl, and Bui, Quang M.

Abstract

The behavioural phenotype of autism was assessed in individuals with full mutation and premutation fragile X syndrome (FXS) using the Autism Diagnostic Observation Scale-Generic (ADOS-G) and the Autism Diagnostic Interview (ADI-R). The participants, aged 5-80 years, comprised 33 males and 31 females with full mutation, 7 males and 43 females with premutation, and 38 non-fragile X relatives (29 males, 9 females). In the full mutation group, a total of 67% males and 23% females met either the Autism Disorder (AD) or the Autism Spectrum Disorder (ASD) criteria on at least one of the diagnostic tests. In the premutation group, 14% males and 5% females met the ADOS-G criteria for ASD. The presence of autism manifestations in males and females with full mutation and premutation provide support for a spectrum view.

Published
2007
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9. Identification and characterization of novel associations in the CASP8/ALS2CR12 region on chromosome 2 with breast cancer risk

Author

Lin, Wei-Yu, Camp, Nicola J., Ghoussaini, Maya, Beesley, Jonathan, Michailidou, Kyriaki, Hopper, John L., Apicella, Carmel, Southey, Melissa C., Stone, Jennifer, Schmidt, Marjanka K., Broeks, Annegien, Vanʼt Veer, Laura J., Th Rutgers, Emiel J., Muir, Kenneth, Lophatananon, Artitaya, Stewart-Brown, Sarah, Siriwanarangsan, Pornthep, Fasching, Peter A., Haeberle, Lothar, Ekici, Arif B., Beckmann, Matthias W., Peto, Julian, Dos-Santos-Silva, Isabel, Fletcher, Olivia, Johnson, Nichola, Bolla, Manjeet K., Wang, Qin, Dennis, Joe, Sawyer, Elinor J., Cheng, Timothy, Tomlinson, Ian, Kerin, Michael J., Miller, Nicola, Marmé, Frederik, Surowy, Harald M., Burwinkel, Barbara, Guénel, Pascal, Truong, Thérèse, Menegaux, Florence, Mulot, Claire, Bojesen, Stig E., Nordestgaard, Børge G., Nielsen, Sune F., Flyger, Henrik, Benitez, Javier, Zamora, M. Pilar, Arias Perez, Jose Ignacio, Menéndez, Primitiva, González-Neira, Anna, Pita, Guillermo, Alonso, M. Rosario, Álvarez, Nuria, Herrero, Daniel, Anton-Culver, Hoda, Brenner, Hermann, Dieffenbach, Aida Karina, Arndt, Volker, Stegmaier, Christa, Meindl, Alfons, Lichtner, Peter, Schmutzler, Rita K., Müller-Myhsok, Bertram, Brauch, Hiltrud, Brüning, Thomas, Ko, Yon-Dschun, Tessier, Daniel C., Vincent, Daniel, Bacot, Francois, Nevanlinna, Heli, Aittomäki, Kristiina, Blomqvist, Carl, Khan, Sofia, Matsuo, Keitaro, Ito, Hidemi, Iwata, Hiroji, Horio, Akiyo, Bogdanova, Natalia V., Antonenkova, Natalia N., Dörk, Thilo, Lindblom, Annika, Margolin, Sara, Mannermaa, Arto, Kataja, Vesa, Kosma, Veli-Matti, Hartikainen, Jaana M., Wu, Anna H., Tseng, Chiu-Chen, Van Den Berg, David, Stram, Daniel O., Neven, Patrick, Wauters, Els, Wildiers, Hans, Lambrechts, Diether, Chang-Claude, Jenny, Rudolph, Anja, Seibold, Petra, Flesch-Janys, Dieter, Radice, Paolo, Peterlongo, Paolo, Manoukian, Siranoush, Bonanni, Bernardo, Couch, Fergus J., Wang, Xianshu, Vachon, Celine, Purrington, Kristen, Giles, Graham G., Milne, Roger L., Mclean, Catriona, Haiman, Christopher A., Henderson, Brian E., Schumacher, Fredrick, Le Marchand, Loic, Simard, Jacques, Goldberg, Mark S., Labrèche, France, Dumont, Martine, Teo, Soo Hwang, Yip, Cheng Har, Hassan, Norhashimah, Vithana, Eranga Nishanthie, Kristensen, Vessela, Zheng, Wei, Deming-Halverson, Sandra, Shrubsole, Martha J., Long, Jirong, Winqvist, Robert, Pylkäs, Katri, Jukkola-Vuorinen, Arja, Kauppila, Saila, Andrulis, Irene L., Knight, Julia A., Glendon, Gord, Tchatchou, Sandrine, Devilee, Peter, Tollenaar, Robert A.E.M., Seynaeve, Caroline, Van Asperen, Christi J., García-Closas, Montserrat, Figueroa, Jonine, Lissowska, Jolanta, Brinton, Louise, Czene, Kamila, Darabi, Hatef, Eriksson, Mikael, Brand, Judith S., Hooning, Maartje J., Hollestelle, Antoinette, Van Den Ouweland, Ans M.W., Jager, Agnes, Li, Jingmei, Liu, Jianjun, Humphreys, Keith, Shu, Xiao-Ou, Lu, Wei, Gao, Yu-Tang, Cai, Hui, Cross, Simon S., Reed, Malcolm W. R., Blot, William, Signorello, Lisa B., Cai, Qiuyin, Pharoah, Paul D.P., Perkins, Barbara, Shah, Mitul, Blows, Fiona M., Kang, Daehee, Yoo, Keun-Young, Noh, Dong-Young, Hartman, Mikael, Miao, Hui, Chia, Kee Seng, Putti, Thomas Choudary, Hamann, Ute, Luccarini, Craig, Baynes, Caroline, Ahmed, Shahana, Maranian, Mel, Healey, Catherine S., Jakubowska, Anna, Lubinski, Jan, Jaworska-Bieniek, Katarzyna, Durda, Katarzyna, Sangrajrang, Suleeporn, Gaborieau, Valerie, Brennan, Paul, Mckay, James, Slager, Susan, Toland, Amanda E., Yannoukakos, Drakoulis, Shen, Chen-Yang, Hsiung, Chia-Ni, Wu, Pei-Ei, Ding, Shian-ling, Ashworth, Alan, Jones, Michael, Orr, Nick, Swerdlow, Anthony J, Tsimiklis, Helen, Makalic, Enes, Schmidt, Daniel F., Bui, Quang M., Chanock, Stephen J., Hunter, David J., Hein, Rebecca, Dahmen, Norbert, Beckmann, Lars, Aaltonen, Kirsimari, Muranen, Taru A., Heikkinen, Tuomas, Irwanto, Astrid, Rahman, Nazneen, Turnbull, Clare A., Waisfisz, Quinten, Meijers-Heijboer, Hanne E. J., Adank, Muriel A., Van Der Luijt, Rob B., Hall, Per, Chenevix-Trench, Georgia, Dunning, Alison, Easton, Douglas F., and Cox, Angela

Published
2015
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12. Relationships between age and epi-genotype of the FMR1 exon 1/intron 1 boundary are consistent with non-random X-chromosome inactivation in FM individuals, with the selection for the unmethylated state being most significant between birth and puberty

Author

Godler, David E., Inaba, Yoshimi, Shi, Elva Z., Skinner, Cindy, Bui, Quang M., Francis, David, Amor, David J., Hopper, John L., Loesch, Danuta Z., Hagerman, Randi J., Schwartz, Charles E., and Slater, Howard R.

Published
2013
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17. FMR1 allele size distribution in 35,000 males and females: a comparison of developmental delay and general population cohorts

Author

Kraan, Claudine M., primary, Bui, Quang M., additional, Field, Mike, additional, Archibald, Alison D., additional, Metcalfe, Sylvia A., additional, Christie, Louise M., additional, Bennetts, Bruce H., additional, Oertel, Ralph, additional, Smith, Melanie J., additional, du Sart, Desiree, additional, Bruno, Damien, additional, Wotton, Tiffany L., additional, Amor, David J., additional, Francis, David, additional, and Godler, David E., additional

Published
2018
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18. Use of a Novel Nonparametric Version of DEPTH to Identify Genomic Regions Associated with Prostate Cancer Risk

Author

MacInnis, Robert J, Schmidt, Daniel F, Makalic, Enes, Severi, Gianluca, FitzGerald, Liesel M, Reumann, Matthias, Kapuscinski, Miroslaw K, Kowalczyk, Adam, Zhou, Zeyu, Goudey, Benjamin, Qian, Guoqi, Bui, Quang M, Park, Daniel J, Freeman, Adam, Southey, Melissa C, Al Olama, Ali Amin, Kote-Jarai, Zsofia, Eeles, Rosalind A, Hopper, John L, Giles, Graham G, UK Genetic Prostate Cancer Study Collaborators, Amin Al Olama, Ali [0000-0002-7178-3431], and Apollo - University of Cambridge Repository

Subjects
Machine Learning, Male, Australia, Humans, Prostatic Neoplasms, Genetic Predisposition to Disease, Middle Aged, Polymorphism, Single Nucleotide, United Kingdom, Genome-Wide Association Study
Abstract

BACKGROUND: We have developed a genome-wide association study analysis method called DEPTH (DEPendency of association on the number of Top Hits) to identify genomic regions potentially associated with disease by considering overlapping groups of contiguous markers (e.g., SNPs) across the genome. DEPTH is a machine learning algorithm for feature ranking of ultra-high dimensional datasets, built from well-established statistical tools such as bootstrapping, penalized regression, and decision trees. Unlike marginal regression, which considers each SNP individually, the key idea behind DEPTH is to rank groups of SNPs in terms of their joint strength of association with the outcome. Our aim was to compare the performance of DEPTH with that of standard logistic regression analysis. METHODS: We selected 1,854 prostate cancer cases and 1,894 controls from the UK for whom 541,129 SNPs were measured using the Illumina Infinium HumanHap550 array. Confirmation was sought using 4,152 cases and 2,874 controls, ascertained from the UK and Australia, for whom 211,155 SNPs were measured using the iCOGS Illumina Infinium array. RESULTS: From the DEPTH analysis, we identified 14 regions associated with prostate cancer risk that had been reported previously, five of which would not have been identified by conventional logistic regression. We also identified 112 novel putative susceptibility regions. CONCLUSIONS: DEPTH can reveal new risk-associated regions that would not have been identified using a conventional logistic regression analysis of individual SNPs. IMPACT: This study demonstrates that the DEPTH algorithm could identify additional genetic susceptibility regions that merit further investigation. Cancer Epidemiol Biomarkers Prev; 25(12); 1619-24. ©2016 AACR.

Published
2016
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20. The use of droplet digital PCR and high resolution melt for detection of low level mosaicism

Author

Godler, David E., primary, Christodoulou, John, additional, Bruno, Damien, additional, Li, Xin, additional, Inaba, Yoshimi, additional, Bui, Quang M., additional, Francis, David, additional, Elliot, Justine, additional, Wotton, Tiffany, additional, Cohen, Jonathan, additional, Rogers, Carolyn, additional, Field, Mike, additional, Slater, Howard R., additional, and Amor, David J., additional

Published
2018
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21. Use of a Novel Nonparametric Version of DEPTH to Identify Genomic Regions Associated with Prostate Cancer Risk

Author

MacInnis, Robert J., primary, Schmidt, Daniel F., additional, Makalic, Enes, additional, Severi, Gianluca, additional, FitzGerald, Liesel M., additional, Reumann, Matthias, additional, Kapuscinski, Miroslaw K., additional, Kowalczyk, Adam, additional, Zhou, Zeyu, additional, Goudey, Benjamin, additional, Qian, Guoqi, additional, Bui, Quang M., additional, Park, Daniel J., additional, Freeman, Adam, additional, Southey, Melissa C., additional, Al Olama, Ali Amin, additional, Kote-Jarai, Zsofia, additional, Eeles, Rosalind A., additional, Hopper, John L., additional, and Giles, Graham G., additional

Published
2016
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22. FMR1allele size distribution in 35,000 males and females: a comparison of developmental delay and general population cohorts

Author

Kraan, Claudine M., Bui, Quang M., Field, Mike, Archibald, Alison D., Metcalfe, Sylvia A., Christie, Louise M., Bennetts, Bruce H., Oertel, Ralph, Smith, Melanie J., du Sart, Desiree, Bruno, Damien, Wotton, Tiffany L., Amor, David J., Francis, David, and Godler, David E.

Abstract

Developmental delay phenotypes have been associated with FMR1premutation (PM: 55–200 CGG repeats) and “gray zone” (GZ: 45–54 CGG repeats) alleles. However, these associations have not been confirmed by larger studies to be useful in pediatric diagnostic or screening settings.

Published
2018
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23. A meta-analysis of genome-wide association studies of breast cancer identifies two novel susceptibility loci at 6q14 and 20q11

Author

Buring, Julie E., Rhie, Suhn Kyong, Cox, Angela, Bernstein, Leslie, Clavel-Chapelon, Françoise, Beckmann, Matthias W., Eccles, Diana, Chang-Claude, Jenny, Beckmann, Lars, Carpenter, Jane E., Aittomäki, Kristiina, Baglietto, Laura, Blomqvist, Carl, Ambrosone, Christine B., Stram, Daniel O., Bandera, Elisa V., Couch, Fergus J., Millikan, Robert C., Buys, Saundra S., Campa, Daniele, Chasman, Daniel I., Chen, Gary K., Bui, Quang M., Berg, Christine D., Siddiq, Afshan, Lindström, Sara, Chen, Constance, Michailidou, Kyriaki, Amiano, Pilar, Brauch, Hiltrud, Apicella, Carmel, and Brinton, Louise

Abstract

Genome-wide association studies (GWAS) of breast cancer defined by hormone receptor status have revealed loci contributing to susceptibility of estrogen receptor (ER)-negative subtypes. To identify additional genetic variants for ER-negative breast cancer, we conducted the largest meta-analysis of ER-negative disease to date, comprising 4754 ER-negative cases and 31 663 controls from three GWAS: NCI Breast and Prostate Cancer Cohort Consortium (BPC3) (2188 ER-negative cases; 25 519 controls of European ancestry), Triple Negative Breast Cancer Consortium (TNBCC) (1562 triple negative cases; 3399 controls of European ancestry) and African American Breast Cancer Consortium (AABC) (1004 ER-negative cases; 2745 controls). We performed in silico replication of 86 SNPs at P ≤ 1 × 10-5 in an additional 11 209 breast cancer cases (946 with ER-negative disease) and 16 057 controls of Japanese, Latino and European ancestry. We identified two novel loci for breast cancer at 20q11 and 6q14. SNP rs2284378 at 20q11 was associated with ER-negative breast cancer (combined two-stage OR = 1.16; P = 1.1 × 10−8) but showed a weaker association with overall breast cancer (OR = 1.08, P = 1.3 × 10–6) based on 17 869 cases and 43 745 controls and no association with ER-positive disease (OR = 1.01, P = 0.67) based on 9965 cases and 22 902 controls. Similarly, rs17530068 at 6q14 was associated with breast cancer (OR = 1.12; P = 1.1 × 10−9), and with both ER-positive (OR = 1.09; P = 1.5 × 10−5) and ER-negative (OR = 1.16, P = 2.5 × 10−7) disease. We also confirmed three known loci associated with ER-negative (19p13) and both ER-negative and ER-positive breast cancer (6q25 and 12p11). Our results highlight the value of large-scale collaborative studies to identify novel breast cancer risk loci.

Published
2012
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24. Detection of skewed X-chromosome inactivation in Fragile X syndrome and X chromosome aneuploidy using quantitative melt analysis

Author

Godler, David E., primary, Inaba, Yoshimi, additional, Schwartz, Charles E., additional, Bui, Quang M., additional, Shi, Elva Z., additional, Li, Xin, additional, Herlihy, Amy S., additional, Skinner, Cindy, additional, Hagerman, Randi J., additional, Francis, David, additional, Amor, David J., additional, Metcalfe, Sylvia A., additional, Hopper, John L., additional, and Slater, Howard R., additional

Published
2015
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25. Early Detection of Fragile X Syndrome: Applications of a Novel Approach for Improved Quantitative Methylation Analysis in Venous Blood and Newborn Blood Spots

Author

Inaba, Yoshimi, primary, Schwartz, Charles E, primary, Bui, Quang M, primary, Li, Xin, primary, Skinner, Cindy, primary, Field, Michael, primary, Wotton, Tiffany, primary, Hagerman, Randi J, primary, Francis, David, primary, Amor, David J, primary, Hopper, John L, primary, Loesch, Danuta Z, primary, Bretherton, Lesley, primary, Slater, Howard R, primary, and Godler, David E, primary

Published
2014
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27. Fragile X–related element 2 methylation analysis may provide a suitable option for inclusion of fragile X syndrome and/or sex chromosome aneuploidy into newborn screening: a technical validation study

Author

Inaba, Yoshimi, primary, Herlihy, Amy S., additional, Schwartz, Charles E., additional, Skinner, Cindy, additional, Bui, Quang M., additional, Cobb, Joanna, additional, Shi, Elva Z., additional, Francis, David, additional, Arvaj, Alison, additional, Amor, David J., additional, Pope, Kate, additional, Wotton, Tiffany, additional, Cohen, Jonathan, additional, Hewitt, Jacqueline K., additional, Hagerman, Randi J., additional, Metcalfe, Sylvia A., additional, Hopper, John L., additional, Loesch, Danuta Z., additional, Slater, Howard R., additional, and Godler, David E., additional

Published
2013
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28. Fragile X Mental Retardation 1 (FMR1) Intron 1 Methylation in Blood Predicts Verbal Cognitive Impairment in Female Carriers of Expanded FMR1 Alleles: Evidence from a Pilot Study

Author

Godler, David E, primary, Slater, Howard R, primary, Bui, Quang M, primary, Storey, Elsdon, primary, Ono, Michele Y, primary, Gehling, Freya, primary, Inaba, Yoshimi, primary, Francis, David, primary, Hopper, John L, primary, Kinsella, Glynda, primary, Amor, David J, primary, Hagerman, Randi J, primary, and Loesch, Danuta Z, primary

Published
2012
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30. Evidence for the toxicity of bidirectional transcripts and mitochondrial dysfunction in blood associated with small CGG expansions in the FMR1 gene in patients with parkinsonism

Author

Loesch, Danuta Z., primary, Godler, David E., additional, Evans, Andrew, additional, Bui, Quang M., additional, Gehling, Freya, additional, Kotschet, Katya E., additional, Trost, Nicholas, additional, Storey, Elsdon, additional, Stimpson, Paige, additional, Kinsella, Glynda, additional, Francis, David, additional, Thorburn, David R., additional, Venn, Alison, additional, Slater, Howard R., additional, and Horne, Malcolm, additional

Published
2011
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38. Evidence for the toxicity of bidirectional transcripts and mitochondrial dysfunction in blood associated with small CGG expansions in the FMR1gene in patients with parkinsonism

Author

Loesch, Danuta Z., Godler, David E., Evans, Andrew, Bui, Quang M., Gehling, Freya, Kotschet, Katya E., Trost, Nicholas, Storey, Elsdon, Stimpson, Paige, Kinsella, Glynda, Francis, David, Thorburn, David R., Venn, Alison, Slater, Howard R., and Horne, Malcolm

Abstract

Our previous results showed that both gray zone and lower end premutation range (40–85 repeats) fragile X mental retardation 1 (FMR1) alleles were more common among males with parkinsonism than in the general population. This study aimed to determine whether these alleles have a significant role in the manifestations and pathogenesis of parkinsonian disorders.

Published
2011
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39. FMR1 Intron 1 Methylation Predicts FMRP Expression in Blood of Female Carriers of Expanded FMR1 Alleles

Author

Randi J Hagerman, Quang M. Bui, Danuta Z. Loesch, Michele Ono, Freya Gehling, David J. Amor, John L. Hopper, David Francis, David E. Godler, Howard R. Slater, Godler, David E, Slater, Howard R, Bui, Quang M, Ono, Michele, Gehling, Freya, Francis, David, Amor, David J, Hopper, John L, Hagerman, Randi, and Loesch, Danuta Z

Subjects
Adult, Heterozygote, congenital, hereditary, and neonatal diseases and abnormalities, Adolescent, Biology, Pathology and Forensic Medicine, Fragile X Mental Retardation Protein, fragile X mental retardation gene protein product (FMRP), medicine, Humans, Epigenetics, fragile X syndrome, Allele, Child, FMR 1 gene, Alleles, X chromosome, Genetics, Reproducibility of Results, Regular Article, Methylation, DNA Methylation, Middle Aged, medicine.disease, FMR1, Molecular biology, Introns, Fragile X syndrome, Blotting, Southern, Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization, DNA methylation, Linear Models, Molecular Medicine, CpG Islands, Female, Trinucleotide Repeat Expansion, Trinucleotide repeat expansion
Abstract

Fragile X syndrome (FXS) is caused by loss of the fragile X mental retardation gene protein product (FMRP) through promoter hypermethylation, which is usually associated with CGG expansion to full mutation size (>200 CGG repeats). Methylation-sensitive Southern blotting is the current gold standard for the molecular diagnosis of FXS. For females, Southern blotting provides the activation ratio (AR), which is the proportion of unmethylated alleles on the active X chromosome. Herein, we examine the relationship of FMRP expression with methylation patterns of two fragile X-related epigenetic elements (FREE) analyzed using matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry and the AR. We showed that the differential methylation of the FREE2 sequence within fragile X mental retardation gene intron 1 was related to depletion of FMRP expression. We also show that, using the combined cohort of 12 females with premutation (55 to 200 CGG repeats) and 22 females with full mutation alleles, FREE2 methylation analysis was superior to the AR as a predictor of the proportion of FMRP-positive cells in blood. Because matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry is amenable to high-throughput processing and requires minimal DNA, these findings have implications for routine FXS testing and population screening. Refereed/Peer-reviewed

Published
2011

40. Evidence for the toxicity of bidirectional transcripts and mitochondrial dysfunction in blood associated with small CGG expansions in the FMR1 gene in patients with parkinsonism

Author

Quang M. Bui, Elsdon Storey, Glynda J. Kinsella, Nicholas Trost, David E. Godler, Freya Gehling, Alison Venn, Katya Kotschet, David R. Thorburn, Howard R. Slater, Andrew Evans, David Francis, Paige Stimpson, Danuta Z. Loesch, Malcolm K. Horne, Loesch, Danuta Z, Godler, David E, Evans, Andrew, Bui, Quang M, Gehling, Freya, Kotschet, Katya E, Trost, Nicholas, Storey, Elsdon, Stimpson, Paige, Kinsella, Glynda, Francis, David, Thorburn, David R, Venn, Alison, Slater, Howard R, and Horne, Malcolm

Subjects
Male, medicine.medical_specialty, Pathology, Transcription, Genetic, Population, Disease, Motor Activity, Biology, DNA, Mitochondrial, Article, Pathogenesis, Fragile X Mental Retardation Protein, Parkinsonian Disorders, gray zone, Internal medicine, mitochondrial dysfunction, medicine, Humans, RNA, Messenger, Allele, Cognitive decline, education, Alleles, Genetic Association Studies, parkinsonism, Genetics (clinical), Aged, Aged, 80 and over, education.field_of_study, Parkinsonism, Middle Aged, medicine.disease, FMR1, nervous system diseases, premutation, Endocrinology, Trinucleotide Repeat Expansion, Trinucleotide repeat expansion
Abstract

Purpose: Our previous results showed that both gray zone and lower end premutation range (40-85 repeats) fragile X mental retardation 1(FMR1) alleles were more common among males with parkinsonism than in the general population. This study aimed to determine whether these alleles have a significant role in the manifestations and pathogenesis of parkinsonian disorders. Methods: Detailed clinical assessment and genetic testing were performed in 14 male carriers of premutation and gray zone FMR1 alleles and in 24 non carriers identified in a sample of males with parkinsonism. Results: The premutation gray zone carriers presented with more severe symptoms than disease controls matched for age, diagnosis, disease duration, and treatment. The Parkinson disease (Unified Parkinson's Disease Rating Scale) motor score and the measures of cognitive decline (Mini-Mental State Examination and/or Addenbrooke's Cognitive Examination Final Revised Version Ascores) were significantly correlated with the size of the CGG repeat and the (elevated) levels of antisense FMR1 and Cytochrome C1 mRNAs in blood leukocytes. In addition, the carriers showed a significant depletion of the nicotinamide adenine dinucleotide, reduced dehydrogenase sub unit 1 mitochondrial gene in whole blood. Conclusion: Small CGG expansion FMR1 alleles (gray zone and lower end premutation) play a significant role in the development of the parkinsonian phenotype,possibly through the cytotoxic effect of elevated sense and/or antisense FMR1 transcripts involving mitochondrial dysfunction and leading to progressive neurodegeneration. Refereed/Peer-reviewed

Published
2011

41. Classification of Vietnamese Cashew Nut ( Anacardium occidentale L.) Products Using Statistical Algorithms Based on ICP/MS Data: A Study of Food Categorization.

Author

Nguyen-Quang T, Bui-Quang M, Pham-Van T, Le-Van N, Nguyen-Hoang K, Nguyen-Minh D, Phung-Thi T, Le-Viet A, Tran-Ha Minh D, Nguyen-Tien D, Hoang-Le TA, and Truong-Ngoc M

Abstract

Fingerprinting techniques, which utilize the unique chemical and physical properties of food samples, have emerged as a promising approach for food authentication and traceability. Recent studies have demonstrated significant advancements in food authentication through the use of fingerprinting methods, such as multivariate statistical analysis techniques applied to trace elements and isotope ratios. However, further research is required to optimize these methods and ensure their validity and reliability in real-world applications. In this study, the inductively coupled plasma mass spectrometry (ICP-MS) analytical method was employed to determine the content of 21 elements in 300 cashew nut ( Anacardium occidentale L.) samples from 5 brands. Multivariate statistical methods, such as principal components analysis (PCA), were employed to analyze the data obtained and establish the provenance of the cashew nuts. While cashew nuts are widely marketed in many countries, no universal method has been utilized to differentiate the origin of these nuts. Our study represents the initial step in identifying the geographical origin of commercial cashew nuts marketed in Vietnam. The analysis showed significant differences in the means of 21 of the 40 analyzed elements among the cashew nut samples from the 5 brands, including 7 Li, 11 B, 24 Mg, 27 Al, 44 Ca, 48 Ti, 51 V, 52 Cr, 55 Mn, 57 Fe, 60 Ni, 63 Cu, 66 Zn, 93 Nb, 98 Mo, 111 Cd, 115 In, 121 Sb, 138 Ba, 208 Pb, and 209 Bi. The PCA analysis indicated that the cashew nut samples can be accurately classified according to their original locations. This research serves as a prerequisite for future studies involving the combination of elemental composition analysis with statistical classification methods for the accurate establishment of cashew nut provenance, which involves the identification of key markers for the original discrimination of cashew nuts., Competing Interests: The authors declare that they have no conflicts of interest in this article., (Copyright © 2023 Trung Nguyen-Quang et al.)

Published
2023
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42. Rapid Identification of Geographical Origin of Commercial Soybean Marketed in Vietnam by ICP-MS.

Author

Nguyen-Quang T, Bui-Quang M, and Truong-Ngoc M

Abstract

Inductively coupled plasma mass spectrometry (ICP-MS) analytical method was used to determine the content of 40 elements in 38 soybean samples ( Glycine Max ) from 4 countries. Multivariate statistical methods, such as principal components analysis (PCA), were performed to analyze the obtained data to establish the provenance of the soybeans. Although soybean is widely marketed in many countries, no universal method is used to discriminate the origin of these cereals. Our study introduced the initial step to the identification of the geographical origin of commercial soybean marketed in Vietnam. The analysis pointed out that there are significant differences in the mean of 33 of the 40 analyzed elements among 4 countries' soybean samples, namely, 11 B, 27 Al, 44 Ca, 45 Sc, 47 Ti, 55 Mn, 56 Fe, 59 Co, 60 Ni, 63 Cu, 66 Zn, 69 Ga, 75 As, 78 Se, 85 Rb, 88 Sr, 89 Y, 90 Zr, 93 Nb, 95 Mo, 103 Rh, 137 Ba, 163 Dy, 165 Ho, 175 Lu, 178 Hf, 181 Ta, 182 W, 185 Re, 197 Au, 202 Hg, 205 Tl, and 208 Pb. The PCA analysis showed that the soybean samples can be classified correctly according to their original locations. This research can be used as a prerequisite for future studies of using the combination of elemental composition analysis with statistical classification methods for an accurate provenance establishment of soybean, which determined a variation of key markers for the original discrimination of soybean., Competing Interests: All authors declare no conflicts of interest., (Copyright © 2021 Trung Nguyen-Quang et al.)

Published
2021
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43. Large-scale genotyping identifies 41 new loci associated with breast cancer risk.

Author

Michailidou K, Hall P, Gonzalez-Neira A, Ghoussaini M, Dennis J, Milne RL, Schmidt MK, Chang-Claude J, Bojesen SE, Bolla MK, Wang Q, Dicks E, Lee A, Turnbull C, Rahman N, Fletcher O, Peto J, Gibson L, Dos Santos Silva I, Nevanlinna H, Muranen TA, Aittomäki K, Blomqvist C, Czene K, Irwanto A, Liu J, Waisfisz Q, Meijers-Heijboer H, Adank M, van der Luijt RB, Hein R, Dahmen N, Beckman L, Meindl A, Schmutzler RK, Müller-Myhsok B, Lichtner P, Hopper JL, Southey MC, Makalic E, Schmidt DF, Uitterlinden AG, Hofman A, Hunter DJ, Chanock SJ, Vincent D, Bacot F, Tessier DC, Canisius S, Wessels LF, Haiman CA, Shah M, Luben R, Brown J, Luccarini C, Schoof N, Humphreys K, Li J, Nordestgaard BG, Nielsen SF, Flyger H, Couch FJ, Wang X, Vachon C, Stevens KN, Lambrechts D, Moisse M, Paridaens R, Christiaens MR, Rudolph A, Nickels S, Flesch-Janys D, Johnson N, Aitken Z, Aaltonen K, Heikkinen T, Broeks A, Veer LJ, van der Schoot CE, Guénel P, Truong T, Laurent-Puig P, Menegaux F, Marme F, Schneeweiss A, Sohn C, Burwinkel B, Zamora MP, Perez JI, Pita G, Alonso MR, Cox A, Brock IW, Cross SS, Reed MW, Sawyer EJ, Tomlinson I, Kerin MJ, Miller N, Henderson BE, Schumacher F, Le Marchand L, Andrulis IL, Knight JA, Glendon G, Mulligan AM, Lindblom A, Margolin S, Hooning MJ, Hollestelle A, van den Ouweland AM, Jager A, Bui QM, Stone J, Dite GS, Apicella C, Tsimiklis H, Giles GG, Severi G, Baglietto L, Fasching PA, Haeberle L, Ekici AB, Beckmann MW, Brenner H, Müller H, Arndt V, Stegmaier C, Swerdlow A, Ashworth A, Orr N, Jones M, Figueroa J, Lissowska J, Brinton L, Goldberg MS, Labrèche F, Dumont M, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Grip M, Brauch H, Hamann U, Brüning T, Radice P, Peterlongo P, Manoukian S, Bonanni B, Devilee P, Tollenaar RA, Seynaeve C, van Asperen CJ, Jakubowska A, Lubinski J, Jaworska K, Durda K, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Bogdanova NV, Antonenkova NN, Dörk T, Kristensen VN, Anton-Culver H, Slager S, Toland AE, Edge S, Fostira F, Kang D, Yoo KY, Noh DY, Matsuo K, Ito H, Iwata H, Sueta A, Wu AH, Tseng CC, Van Den Berg D, Stram DO, Shu XO, Lu W, Gao YT, Cai H, Teo SH, Yip CH, Phuah SY, Cornes BK, Hartman M, Miao H, Lim WY, Sng JH, Muir K, Lophatananon A, Stewart-Brown S, Siriwanarangsan P, Shen CY, Hsiung CN, Wu PE, Ding SL, Sangrajrang S, Gaborieau V, Brennan P, McKay J, Blot WJ, Signorello LB, Cai Q, Zheng W, Deming-Halverson S, Shrubsole M, Long J, Simard J, Garcia-Closas M, Pharoah PD, Chenevix-Trench G, Dunning AM, Benitez J, and Easton DF

Subjects
Case-Control Studies, Cooperative Behavior, Female, Gene-Environment Interaction, Genome-Wide Association Study, Genotype, Humans, Meta-Analysis as Topic, Risk Factors, Breast Neoplasms etiology, Genetic Loci genetics, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide genetics
Abstract

Breast cancer is the most common cancer among women. Common variants at 27 loci have been identified as associated with susceptibility to breast cancer, and these account for ∼9% of the familial risk of the disease. We report here a meta-analysis of 9 genome-wide association studies, including 10,052 breast cancer cases and 12,575 controls of European ancestry, from which we selected 29,807 SNPs for further genotyping. These SNPs were genotyped in 45,290 cases and 41,880 controls of European ancestry from 41 studies in the Breast Cancer Association Consortium (BCAC). The SNPs were genotyped as part of a collaborative genotyping experiment involving four consortia (Collaborative Oncological Gene-environment Study, COGS) and used a custom Illumina iSelect genotyping array, iCOGS, comprising more than 200,000 SNPs. We identified SNPs at 41 new breast cancer susceptibility loci at genome-wide significance (P < 5 × 10(-8)). Further analyses suggest that more than 1,000 additional loci are involved in breast cancer susceptibility.

Published
2013
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