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1. Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder.

Author

Amare, Azmeraw, Thalamuthu, Anbupalam, Schubert, Klaus, Fullerton, Janice, Ahmed, Muktar, Hartmann, Simon, Papiol, Sergi, Heilbronner, Urs, Degenhardt, Franziska, Tekola-Ayele, Fasil, Hou, Liping, Hsu, Yi-Hsiang, Shekhtman, Tatyana, Adli, Mazda, Akula, Nirmala, Akiyama, Kazufumi, Ardau, Raffaella, Arias, Bárbara, Aubry, Jean-Michel, Hasler, Roland, Richard-Lepouriel, Hélène, Perroud, Nader, Backlund, Lena, Bhattacharjee, Abesh, Bellivier, Frank, Benabarre, Antonio, Bengesser, Susanne, Biernacka, Joanna, Birner, Armin, Marie-Claire, Cynthia, Cervantes, Pablo, Chen, Hsi-Chung, Chillotti, Caterina, Cichon, Sven, Cruceanu, Cristiana, Czerski, Piotr, Dalkner, Nina, Del Zompo, Maria, DePaulo, J, Étain, Bruno, Jamain, Stephane, Falkai, Peter, Forstner, Andreas, Frisen, Louise, Frye, Mark, Gard, Sébastien, Garnham, Julie, Goes, Fernando, Grigoroiu-Serbanescu, Maria, Fallgatter, Andreas, Stegmaier, Sophia, Ethofer, Thomas, Biere, Silvia, Petrova, Kristiyana, Schuster, Ceylan, Adorjan, Kristina, Budde, Monika, Heilbronner, Maria, Kalman, Janos, Kohshour, Mojtaba, Reich-Erkelenz, Daniela, Schaupp, Sabrina, Schulte, Eva, Senner, Fanny, Vogl, Thomas, Anghelescu, Ion-George, Arolt, Volker, Dannlowski, Udo, Dietrich, Detlef, Figge, Christian, Jäger, Markus, Lang, Fabian, Juckel, Georg, Konrad, Carsten, Reimer, Jens, Schmauß, Max, Schmitt, Andrea, Spitzer, Carsten, von Hagen, Martin, Wiltfang, Jens, Zimmermann, Jörg, Andlauer, Till, Fischer, Andre, Bermpohl, Felix, Ritter, Philipp, Matura, Silke, Gryaznova, Anna, Falkenberg, Irina, Yildiz, Cüneyt, Kircher, Tilo, Schmidt, Julia, Koch, Marius, Gade, Kathrin, Trost, Sarah, Haussleiter, Ida, Lambert, Martin, Rohenkohl, Anja, Kraft, Vivien, Grof, Paul, and Hashimoto, Ryota

Subjects
Bipolar Disorder, Humans, Female, Male, Multifactorial Inheritance, Adult, Middle Aged, Lithium, Treatment Outcome, Bayes Theorem, Genome-Wide Association Study, Glutamic Acid, Cohort Studies, Lithium Compounds, Acetylcholine, Polymorphism, Single Nucleotide, Antimanic Agents
Abstract

Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental health disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithiums possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N = 2367) and replicated in the combined PsyCourse (N = 89) and BipoLife (N = 102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P

Published
2023

2. Exploring the genetics of lithium response in bipolar disorders

Author

Herrera-Rivero, Marisol, Adli, Mazda, Akiyama, Kazufumi, Akula, Nirmala, Amare, Azmeraw T., Ardau, Raffaella, Arias, Bárbara, Aubry, Jean-Michel, Backlund, Lena, Bellivier, Frank, Benabarre, Antonio, Bengesser, Susanne, Bhattacharjee, Abesh Kumar, Biernacka, Joanna M., Birner, Armin, Cearns, Micah, Cervantes, Pablo, Chen, Hsi-Chung, Chillotti, Caterina, Cichon, Sven, Clark, Scott R., Colom, Francesc, Cruceanu, Cristiana, Czerski, Piotr M., Dalkner, Nina, Degenhardt, Franziska, Del Zompo, Maria, DePaulo, J. Raymond, Etain, Bruno, Falkai, Peter, Ferensztajn-Rochowiak, Ewa, Forstner, Andreas J., Frank, Josef, Frisén, Louise, Frye, Mark A., Fullerton, Janice M., Gallo, Carla, Gard, Sébastien, Garnham, Julie S., Goes, Fernando S., Grigoroiu-Serbanescu, Maria, Grof, Paul, Hashimoto, Ryota, Hasler, Roland, Hauser, Joanna, Heilbronner, Urs, Herms, Stefan, Hoffmann, Per, Hou, Liping, Hsu, Yi-Hsiang, Jamain, Stephane, Jiménez, Esther, Kahn, Jean-Pierre, Kassem, Layla, Kato, Tadafumi, Kelsoe, John, Kittel-Schneider, Sarah, Kuo, Po-Hsiu, Kusumi, Ichiro, König, Barbara, Laje, Gonzalo, Landén, Mikael, Lavebratt, Catharina, Leboyer, Marion, Leckband, Susan G., Maj, Mario, Manchia, Mirko, Marie-Claire, Cynthia, Martinsson, Lina, McCarthy, Michael J., McElroy, Susan L., Millischer, Vincent, Mitjans, Marina, Mondimore, Francis M., Monteleone, Palmiero, Nievergelt, Caroline M., Novák, Tomas, Nöthen, Markus M., O’Donovan, Claire, Ozaki, Norio, Papiol, Sergi, Pfennig, Andrea, Pisanu, Claudia, Potash, James B., Reif, Andreas, Reininghaus, Eva, Richard-Lepouriel, Hélène, Roberts, Gloria, Rouleau, Guy A., Rybakowski, Janusz K., Schalling, Martin, Schofield, Peter R., Schubert, Klaus Oliver, Schulte, Eva C., Schweizer, Barbara W., Severino, Giovanni, Shekhtman, Tatyana, Shilling, Paul D., Shimoda, Katzutaka, Simhandl, Christian, Slaney, Claire M., Squassina, Alessio, Stamm, Thomas, Stopkova, Pavla, Streit, Fabian, Tekola-Ayele, Fasil, Thalamuthu, Anbupalam, Tortorella, Alfonso, Turecki, Gustavo, Veeh, Julia, Vieta, Eduard, Viswanath, Biju, Witt, Stephanie H., Zandi, Peter P., Alda, Martin, Bauer, Michael, McMahon, Francis J., Mitchell, Philip B., Rietschel, Marcella, Schulze, Thomas G., and Baune, Bernhard T.

Published
2024
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6. Plasma proteomic associations with genetics and health in the UK Biobank

Author

Sun, Benjamin B., Chiou, Joshua, Traylor, Matthew, Benner, Christian, Hsu, Yi-Hsiang, Richardson, Tom G., Surendran, Praveen, Mahajan, Anubha, Robins, Chloe, Vasquez-Grinnell, Steven G., Hou, Liping, Kvikstad, Erika M., Burren, Oliver S., Davitte, Jonathan, Ferber, Kyle L., Gillies, Christopher E., Hedman, Åsa K., Hu, Sile, Lin, Tinchi, Mikkilineni, Rajesh, Pendergrass, Rion K., Pickering, Corran, Prins, Bram, Baird, Denis, Chen, Chia-Yen, Ward, Lucas D., Deaton, Aimee M., Welsh, Samantha, Willis, Carissa M., Lehner, Nick, Arnold, Matthias, Wörheide, Maria A., Suhre, Karsten, Kastenmüller, Gabi, Sethi, Anurag, Cule, Madeleine, Raj, Anil, Burkitt-Gray, Lucy, Melamud, Eugene, Black, Mary Helen, Fauman, Eric B., Howson, Joanna M. M., Kang, Hyun Min, McCarthy, Mark I., Nioi, Paul, Petrovski, Slavé, Scott, Robert A., Smith, Erin N., Szalma, Sándor, Waterworth, Dawn M., Mitnaul, Lyndon J., Szustakowski, Joseph D., Gibson, Bradford W., Miller, Melissa R., and Whelan, Christopher D.

Published
2023
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7. Understanding the complex genetic architecture connecting rheumatoid arthritis, osteoporosis and inflammation: discovering causal pathways

Author

Kasher, Melody, Williams, Frances MK, Freidin, Maxim B, Malkin, Ida, Cherny, Stacey S, Benjamin, Emelia, Chasman, Daniel I, Dehghan, Abbas, Ahluwalia, Tarunveer Singh, Meigs, James, Tracy, Russell, Alizadeh, Behrooz Z, Ligthart, Symen, Bis, Josh, Eiriksdottir, Gudny, Pankratz, Nathan, Gross, Myron, Rainer, Alex, Snieder, Harold, Wilson, James G, Psaty, Bruce M, Dupuis, Josee, Prins, Bram, Vaso, Urmo, Stathopoulou, Maria, Franke, Lude, Lehtimaki, Terho, Koenig, Wolfgang, Jamshidi, Yalda, Siest, Sophie, Abbasi, Ali, Uitterlinden, Andre G, Abdollahi, Mohammadreza, Schnabel, Renate, Schick, Ursula M, Nolte, Ilja M, Kraja, Aldi, Hsu, Yi-Hsiang, Tylee, Daniel S, Zwicker, Alyson, Uher, Rudolf, Davey-Smith, George, Morrison, Alanna C, Hicks, Andrew, van Duijn, Cornelia M, Ward-Caviness, Cavin, Boerwinkle, Eric, Rotter, J, Rice, Ken, Lange, Leslie, Perola, Markus, de Geus, Eco, Morris, Andrew P, Makela, Kari Matti, Stacey, David, Eriksson, Johan, Frayling, Tim M, Slagboom, Eline P, and Livshits, Gregory

Subjects
Aging, Autoimmune Disease, Arthritis, Osteoporosis, Human Genome, Heart Disease, Cardiovascular, Rheumatoid Arthritis, Genetics, 2.1 Biological and endogenous factors, Aetiology, Inflammatory and immune system, Arthritis, Rheumatoid, C-Reactive Protein, Genome-Wide Association Study, Humans, Inflammation, Mendelian Randomization Analysis, Polymorphism, Single Nucleotide, CHARGE Inflammation Working Group, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Rheumatoid arthritis (RA) and osteoporosis (OP) are two comorbid complex inflammatory conditions with evidence of shared genetic background and causal relationships. We aimed to clarify the genetic architecture underlying RA and various OP phenotypes while additionally considering an inflammatory component, C-reactive protein (CRP). Genome-wide association study summary statistics were acquired from the GEnetic Factors for OSteoporosis Consortium, Cohorts for Heart and Aging Research Consortium and UK Biobank. Mendelian randomization (MR) was used to detect the presence of causal relationships. Colocalization analysis was performed to determine shared genetic variants between CRP and OP phenotypes. Analysis of pleiotropy between traits owing to shared causal single nucleotide polymorphisms (SNPs) was performed using PL eiotropic A nalysis under CO mposite null hypothesis (PLACO). MR analysis was suggestive of horizontal pleiotropy between RA and OP traits. RA was a significant causal risk factor for CRP (β = 0.027, 95% confidence interval = 0.016-0.038). There was no evidence of CRP→OP causal relationship, but horizontal pleiotropy was apparent. Colocalization established shared genomic regions between CRP and OP, including GCKR and SERPINA1 genes. Pleiotropy arising from shared causal SNPs revealed through the colocalization analysis was all confirmed by PLACO. These genes were found to be involved in the same molecular function 'protein binding' (GO:0005515) associated with RA, OP and CRP. We identified three major components explaining the epidemiological relationship among RA, OP and inflammation: (1) Pleiotropy explains a portion of the shared genetic relationship between RA and OP, albeit polygenically; (2) RA contributes to CRP elevation and (3) CRP, which is influenced by RA, demonstrated pleiotropy with OP.

Published
2022

9. Blood transcriptomic signature in type-2 biomarker-low severe asthma and asthma control

Author

Zeng, Xue, Qing, Jing, Li, Chi-Ming, Lu, Jiamiao, Yamawaki, Tracy, Hsu, Yi-Hsiang, Vander Lugt, Bryan, Hsu, Hailing, Busby, John, McDowell, P.J., Jackson, David J., Djukanovic, Ratko, Matthews, John G., Arron, Joseph R., Bradding, Peter, Brightling, Christopher E., Chaudhuri, Rekha, Choy, David F., Cowan, D., Fowler, S.J., Hardman, Timothy C., Harrison, Tim, Howarth, Peter, Lordan, James, Mansur, A.H., Menzies-Gow, Andrew, Pavord, Ian D., Walker, Samantha, Woodcock, Ashley, and Heaney, Liam G.

Published
2023
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10. Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients

Author

Schubert, Klaus Oliver, Thalamuthu, Anbupalam, Amare, Azmeraw T, Frank, Joseph, Streit, Fabian, Adl, Mazda, Akula, Nirmala, Akiyama, Kazufumi, Ardau, Raffaella, Arias, Bárbara, Aubry, Jean-Michel, Backlund, Lena, Bhattacharjee, Abesh Kumar, Bellivier, Frank, Benabarre, Antonio, Bengesser, Susanne, Biernacka, Joanna M, Birner, Armin, Marie-Claire, Cynthia, Cearns, Micah, Cervantes, Pablo, Chen, Hsi-Chung, Chillotti, Caterina, Cichon, Sven, Clark, Scott R, Cruceanu, Cristiana, Czerski, Piotr M, Dalkner, Nina, Dayer, Alexandre, Degenhardt, Franziska, Del Zompo, Maria, DePaulo, J Raymond, Étain, Bruno, Falkai, Peter, Forstner, Andreas J, Frisen, Louise, Frye, Mark A, Fullerton, Janice M, Gard, Sébastien, Garnham, Julie S, Goes, Fernando S, Grigoroiu-Serbanescu, Maria, Grof, Paul, Hashimoto, Ryota, Hauser, Joanna, Heilbronner, Urs, Herms, Stefan, Hoffmann, Per, Hou, Liping, Hsu, Yi-Hsiang, Jamain, Stephane, Jiménez, Esther, Kahn, Jean-Pierre, Kassem, Layla, Kuo, Po-Hsiu, Kato, Tadafumi, Kelsoe, John, Kittel-Schneider, Sarah, Ferensztajn-Rochowiak, Ewa, König, Barbara, Kusumi, Ichiro, Laje, Gonzalo, Landén, Mikael, Lavebratt, Catharina, Leboyer, Marion, Leckband, Susan G, Maj, Mario, Manchia, Mirko, Martinsson, Lina, McCarthy, Michael J, McElroy, Susan, Colom, Francesc, Mitjans, Marina, Mondimore, Francis M, Monteleone, Palmiero, Nievergelt, Caroline M, Nöthen, Markus M, Novák, Tomas, O’Donovan, Claire, Ozaki, Norio, Ösby, Urban, Papiol, Sergi, Pfennig, Andrea, Pisanu, Claudia, Potash, James B, Reif, Andreas, Reininghaus, Eva, Rouleau, Guy A, Rybakowski, Janusz K, Schalling, Martin, Schofield, Peter R, Schweizer, Barbara W, Severino, Giovanni, Shekhtman, Tatyana, Shilling, Paul D, Shimoda, Katzutaka, Simhandl, Christian, Slaney, Claire M, Squassina, Alessio, and Stamm, Thomas

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Serious Mental Illness, Mental Health, Brain Disorders, Schizophrenia, Bipolar Disorder, Aetiology, 2.1 Biological and endogenous factors, Mental health, Good Health and Well Being, Depression, Depressive Disorder, Major, Genetic Predisposition to Disease, Humans, Lithium, Multifactorial Inheritance, Risk Factors, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Clinical Sciences, Public Health and Health Services, Clinical sciences, Neurosciences, Biological psychology
Abstract

Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium's therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi+Gen; www.ConLiGen.org ). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD.

Published
2021

12. Disentangling the genetics of lean mass.

Author

Karasik, David, Zillikens, M, Hsu, Yi-Hsiang, Aghdassi, Ali, Akesson, Kristina, Amin, Najaf, Barroso, Inês, Bennett, David, Bertram, Lars, Bochud, Murielle, Borecki, Ingrid, Broer, Linda, Buchman, Aron, Byberg, Liisa, Campbell, Harry, Campos-Obando, Natalia, Cauley, Jane, Cawthon, Peggy, Chambers, John, Chen, Zhao, Cho, Nam, Choi, Hyung, Chou, Wen-Chi, Cummings, Steven, de Groot, Lisette, De Jager, Phillip, Demuth, Ilja, Diatchenko, Luda, Econs, Michael, Eiriksdottir, Gudny, Enneman, Anke, Eriksson, Joel, Eriksson, Johan, Estrada, Karol, Evans, Daniel, Feitosa, Mary, Fu, Mao, Gieger, Christian, Grallert, Harald, Gudnason, Vilmundur, Lenore, Launer, Hayward, Caroline, Hofman, Albert, Homuth, Georg, Huffman, Kim, Husted, Lise, Illig, Thomas, Ingelsson, Erik, Ittermann, Till, Jansson, John-Olov, Johnson, Toby, Biffar, Reiner, Jordan, Joanne, Jula, Antti, Karlsson, Magnus, Khaw, Kay-Tee, Kilpeläinen, Tuomas, Klopp, Norman, Kloth, Jacqueline, Koller, Daniel, Kooner, Jaspal, Kraus, William, Kritchevsky, Stephen, Kutalik, Zoltán, Kuulasmaa, Teemu, Kuusisto, Johanna, Laakso, Markku, Lahti, Jari, Langdahl, Bente, Lerch, Markus, Lewis, Joshua, Lill, Christina, Lind, Lars, Lindgren, Cecilia, Liu, Yongmei, Livshits, Gregory, Ljunggren, Östen, Loos, Ruth, Lorentzon, Mattias, Luan, Jianan, Luben, Robert, Malkin, Ida, McGuigan, Fiona, Medina-Gomez, Carolina, Meitinger, Thomas, Melhus, Håkan, Mellström, Dan, Michaëlsson, Karl, Mitchell, Braxton, Morris, Andrew, Mosekilde, Leif, Nethander, Maria, Newman, Anne, OConnell, Jeffery, Oostra, Ben, Orwoll, Eric, Palotie, Aarno, Peacock, Munro, Perola, Markus, and Peters, Annette

Subjects
ADAMTS Proteins, Absorptiometry, Photon, Adipose Tissue, Adolescent, Adult, Aged, Aged, 80 and over, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Body Composition, Body Fluid Compartments, Electric Impedance, Extracellular Matrix Proteins, Female, Genome-Wide Association Study, Humans, Male, Middle Aged, Muscle, Skeletal, Phenotype, Polymorphism, Single Nucleotide, RNA-Binding Proteins, Receptor, Melanocortin, Type 4, Versicans, White People, Young Adult
Abstract

BACKGROUND: Lean body mass (LM) plays an important role in mobility and metabolic function. We previously identified five loci associated with LM adjusted for fat mass in kilograms. Such an adjustment may reduce the power to identify genetic signals having an association with both lean mass and fat mass. OBJECTIVES: To determine the impact of different fat mass adjustments on genetic architecture of LM and identify additional LM loci. METHODS: We performed genome-wide association analyses for whole-body LM (20 cohorts of European ancestry with n = 38,292) measured using dual-energy X-ray absorptiometry) or bioelectrical impedance analysis, adjusted for sex, age, age2, and height with or without fat mass adjustments (Model 1 no fat adjustment; Model 2 adjustment for fat mass as a percentage of body mass; Model 3 adjustment for fat mass in kilograms). RESULTS: Seven single-nucleotide polymorphisms (SNPs) in separate loci, including one novel LM locus (TNRC6B), were successfully replicated in an additional 47,227 individuals from 29 cohorts. Based on the strengths of the associations in Model 1 vs Model 3, we divided the LM loci into those with an effect on both lean mass and fat mass in the same direction and refer to those as sumo wrestler loci (FTO and MC4R). In contrast, loci with an impact specifically on LM were termed body builder loci (VCAN and ADAMTSL3). Using existing available genome-wide association study databases, LM increasing alleles of SNPs in sumo wrestler loci were associated with an adverse metabolic profile, whereas LM increasing alleles of SNPs in body builder loci were associated with metabolic protection. CONCLUSIONS: In conclusion, we identified one novel LM locus (TNRC6B). Our results suggest that a genetically determined increase in lean mass might exert either harmful or protective effects on metabolic traits, depending on its relation to fat mass.

Published
2019

15. Correction: Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients

Author

Schubert, Klaus Oliver, Thalamuthu, Anbupalam, Amare, Azmeraw T., Frank, Joseph, Streit, Fabian, Adl, Mazda, Akula, Nirmala, Akiyama, Kazufumi, Ardau, Raffaella, Arias, Bárbara, Aubry, Jean-Michel, Backlund, Lena, Bhattacharjee, Abesh Kumar, Bellivier, Frank, Benabarre, Antonio, Bengesser, Susanne, Biernacka, Joanna M., Birner, Armin, Marie-Claire, Cynthia, Cearns, Micah, Cervantes, Pablo, Chen, Hsi-Chung, Chillotti, Caterina, Cichon, Sven, Clark, Scott R., Cruceanu, Cristiana, Czerski, Piotr M., Dalkner, Nina, Dayer, Alexandre, Degenhardt, Franziska, Del Zompo, Maria, DePaulo, J. Raymond, Étain, Bruno, Falkai, Peter, Forstner, Andreas J., Frisen, Louise, Frye, Mark A., Fullerton, Janice M., Gard, Sébastien, Garnham, Julie S., Goes, Fernando S., Grigoroiu-Serbanescu, Maria, Grof, Paul, Hashimoto, Ryota, Hauser, Joanna, Heilbronner, Urs, Herms, Stefan, Hoffmann, Per, Hou, Liping, Hsu, Yi-Hsiang, Jamain, Stephane, Jiménez, Esther, Kahn, Jean-Pierre, Kassem, Layla, Kuo, Po-Hsiu, Kato, Tadafumi, Kelsoe, John, Kittel-Schneider, Sarah, Ferensztajn-Rochowiak, Ewa, König, Barbara, Kusumi, Ichiro, Laje, Gonzalo, Landén, Mikael, Lavebratt, Catharina, Leboyer, Marion, Leckband, Susan G., Maj, Mario, Manchia, Mirko, Martinsson, Lina, McCarthy, Michael J., McElroy, Susan, Colom, Francesc, Mitjans, Marina, Mondimore, Francis M., Monteleone, Palmiero, Nievergelt, Caroline M., Nöthen, Markus M., Novák, Tomas, O’Donovan, Claire, Ozaki, Norio, Ösby, Urban, Papiol, Sergi, Pfennig, Andrea, Pisanu, Claudia, Potash, James B., Reif, Andreas, Reininghaus, Eva, Rouleau, Guy A., Rybakowski, Janusz K., Schalling, Martin, Schofield, Peter R., Schweizer, Barbara W., Severino, Giovanni, Shekhtman, Tatyana, Shilling, Paul D., Shimoda, Katzutaka, Simhandl, Christian, Slaney, Claire M., Squassina, Alessio, Stamm, Thomas, Stopkova, Pavla, Tekola-Ayele, Fasil, Tortorella, Alfonso, Turecki, Gustavo, Veeh, Julia, Vieta, Eduard, Witt, Stephanie H., Roberts, Gloria, Zandi, Peter P., Alda, Martin, Bauer, Michael, McMahon, Francis J., Mitchell, Philip B., Schulze, Thomas G., Rietschel, Marcella, and Baune, Bernhard T.

Published
2022
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16. Genome-wide association study in 79,366 European-ancestry individuals informs the genetic architecture of 25-hydroxyvitamin D levels

Author

Jiang, Xia, O’Reilly, Paul F, Aschard, Hugues, Hsu, Yi-Hsiang, Richards, J Brent, Dupuis, Josée, Ingelsson, Erik, Karasik, David, Pilz, Stefan, Berry, Diane, Kestenbaum, Bryan, Zheng, Jusheng, Luan, Jianan, Sofianopoulou, Eleni, Streeten, Elizabeth A, Albanes, Demetrius, Lutsey, Pamela L, Yao, Lu, Tang, Weihong, Econs, Michael J, Wallaschofski, Henri, Völzke, Henry, Zhou, Ang, Power, Chris, McCarthy, Mark I, Michos, Erin D, Boerwinkle, Eric, Weinstein, Stephanie J, Freedman, Neal D, Huang, Wen-Yi, Van Schoor, Natasja M, van der Velde, Nathalie, Groot, Lisette CPGM de, Enneman, Anke, Cupples, L Adrienne, Booth, Sarah L, Vasan, Ramachandran S, Liu, Ching-Ti, Zhou, Yanhua, Ripatti, Samuli, Ohlsson, Claes, Vandenput, Liesbeth, Lorentzon, Mattias, Eriksson, Johan G, Shea, M Kyla, Houston, Denise K, Kritchevsky, Stephen B, Liu, Yongmei, Lohman, Kurt K, Ferrucci, Luigi, Peacock, Munro, Gieger, Christian, Beekman, Marian, Slagboom, Eline, Deelen, Joris, Heemst, Diana van, Kleber, Marcus E, März, Winfried, de Boer, Ian H, Wood, Alexis C, Rotter, Jerome I, Rich, Stephen S, Robinson-Cohen, Cassianne, den Heijer, Martin, Jarvelin, Marjo-Riitta, Cavadino, Alana, Joshi, Peter K, Wilson, James F, Hayward, Caroline, Lind, Lars, Michaëlsson, Karl, Trompet, Stella, Zillikens, M Carola, Uitterlinden, Andre G, Rivadeneira, Fernando, Broer, Linda, Zgaga, Lina, Campbell, Harry, Theodoratou, Evropi, Farrington, Susan M, Timofeeva, Maria, Dunlop, Malcolm G, Valdes, Ana M, Tikkanen, Emmi, Lehtimäki, Terho, Lyytikäinen, Leo-Pekka, Kähönen, Mika, Raitakari, Olli T, Mikkilä, Vera, Ikram, M Arfan, Sattar, Naveed, Jukema, J Wouter, Wareham, Nicholas J, Langenberg, Claudia, Forouhi, Nita G, Gundersen, Thomas E, Khaw, Kay-Tee, Butterworth, Adam S, Danesh, John, and Spector, Timothy

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Inflammatory and immune system, Amidohydrolases, Autoimmune Diseases, Cohort Studies, Female, Genome-Wide Association Study, Humans, Male, Polymorphism, Single Nucleotide, Vesicular Transport Proteins, Vitamin D, White People
Abstract

Vitamin D is a steroid hormone precursor that is associated with a range of human traits and diseases. Previous GWAS of serum 25-hydroxyvitamin D concentrations have identified four genome-wide significant loci (GC, NADSYN1/DHCR7, CYP2R1, CYP24A1). In this study, we expand the previous SUNLIGHT Consortium GWAS discovery sample size from 16,125 to 79,366 (all European descent). This larger GWAS yields two additional loci harboring genome-wide significant variants (P = 4.7×10-9 at rs8018720 in SEC23A, and P = 1.9×10-14 at rs10745742 in AMDHD1). The overall estimate of heritability of 25-hydroxyvitamin D serum concentrations attributable to GWAS common SNPs is 7.5%, with statistically significant loci explaining 38% of this total. Further investigation identifies signal enrichment in immune and hematopoietic tissues, and clustering with autoimmune diseases in cell-type-specific analysis. Larger studies are required to identify additional common SNPs, and to explore the role of rare or structural variants and gene-gene interactions in the heritability of circulating 25-hydroxyvitamin D levels.

Published
2018

18. A regulatory variant at 3q21.1 confers an increased pleiotropic risk for hyperglycemia and altered bone mineral density

Author

Sinnott-Armstrong, Nasa, Sousa, Isabel S., Laber, Samantha, Rendina-Ruedy, Elizabeth, Nitter Dankel, Simon E., Ferreira, Teresa, Mellgren, Gunnar, Karasik, David, Rivas, Manuel, Pritchard, Jonathan, Guntur, Anyonya R., Cox, Roger D., Lindgren, Cecilia M., Hauner, Hans, Sallari, Richard, Rosen, Clifford J., Hsu, Yi-Hsiang, Lander, Eric S., Kiel, Douglas P., and Claussnitzer, Melina

Published
2021
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19. Erratum: Large meta-analysis of genome-wide association studies identifies five loci for lean body mass.

Author

Zillikens, M Carola, Demissie, Serkalem, Hsu, Yi-Hsiang, Yerges-Armstrong, Laura M, Chou, Wen-Chi, Stolk, Lisette, Livshits, Gregory, Broer, Linda, Johnson, Toby, Koller, Daniel L, Kutalik, Zoltán, Luan, Jian'an, Malkin, Ida, Ried, Janina S, Smith, Albert V, Thorleifsson, Gudmar, Vandenput, Liesbeth, Hua Zhao, Jing, Zhang, Weihua, Aghdassi, Ali, Åkesson, Kristina, Amin, Najaf, Baier, Leslie J, Barroso, Inês, Bennett, David A, Bertram, Lars, Biffar, Rainer, Bochud, Murielle, Boehnke, Michael, Borecki, Ingrid B, Buchman, Aron S, Byberg, Liisa, Campbell, Harry, Campos Obanda, Natalia, Cauley, Jane A, Cawthon, Peggy M, Cederberg, Henna, Chen, Zhao, Cho, Nam H, Jin Choi, Hyung, Claussnitzer, Melina, Collins, Francis, Cummings, Steven R, De Jager, Philip L, Demuth, Ilja, Dhonukshe-Rutten, Rosalie AM, Diatchenko, Luda, Eiriksdottir, Gudny, Enneman, Anke W, Erdos, Mike, Eriksson, Johan G, Eriksson, Joel, Estrada, Karol, Evans, Daniel S, Feitosa, Mary F, Fu, Mao, Garcia, Melissa, Gieger, Christian, Girke, Thomas, Glazer, Nicole L, Grallert, Harald, Grewal, Jagvir, Han, Bok-Ghee, Hanson, Robert L, Hayward, Caroline, Hofman, Albert, Hoffman, Eric P, Homuth, Georg, Hsueh, Wen-Chi, Hubal, Monica J, Hubbard, Alan, Huffman, Kim M, Husted, Lise B, Illig, Thomas, Ingelsson, Erik, Ittermann, Till, Jansson, John-Olov, Jordan, Joanne M, Jula, Antti, Karlsson, Magnus, Khaw, Kay-Tee, Kilpeläinen, Tuomas O, Klopp, Norman, Kloth, Jacqueline SL, Koistinen, Heikki A, Kraus, William E, Kritchevsky, Stephen, Kuulasmaa, Teemu, Kuusisto, Johanna, Laakso, Markku, Lahti, Jari, Lang, Thomas, Langdahl, Bente L, Launer, Lenore J, Lee, Jong-Young, Lerch, Markus M, Lewis, Joshua R, Lind, Lars, Lindgren, Cecilia, and Liu, Yongmei

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics
Abstract

A correction to this article has been published and is linked from the HTML version of this article.

Published
2017

20. Low-Frequency Synonymous Coding Variation in CYP2R1 Has Large Effects on Vitamin D Levels and Risk of Multiple Sclerosis

Author

Manousaki, Despoina, Dudding, Tom, Haworth, Simon, Hsu, Yi-Hsiang, Liu, Ching-Ti, Medina-Gómez, Carolina, Voortman, Trudy, van der Velde, Nathalie, Melhus, Håkan, Robinson-Cohen, Cassianne, Cousminer, Diana L, Nethander, Maria, Vandenput, Liesbeth, Noordam, Raymond, Forgetta, Vincenzo, Greenwood, Celia MT, Biggs, Mary L, Psaty, Bruce M, Rotter, Jerome I, Zemel, Babette S, Mitchell, Jonathan A, Taylor, Bruce, Lorentzon, Mattias, Karlsson, Magnus, Jaddoe, Vincent VW, Tiemeier, Henning, Campos-Obando, Natalia, Franco, Oscar H, Utterlinden, Andre G, Broer, Linda, van Schoor, Natasja M, Ham, Annelies C, Ikram, M Arfan, Karasik, David, de Mutsert, Renée, Rosendaal, Frits R, Heijer, Martin den, Wang, Thomas J, Lind, Lars, Orwoll, Eric S, Mook-Kanamori, Dennis O, Michaëlsson, Karl, Kestenbaum, Bryan, Ohlsson, Claes, Mellström, Dan, de Groot, Lisette CPGM, Grant, Struan FA, Kiel, Douglas P, Zillikens, M Carola, Rivadeneira, Fernando, Sawcer, Stephen, Timpson, Nicholas J, and Richards, J Brent

Subjects
Biological Sciences, Health Sciences, Genetics, Prevention, Multiple Sclerosis, Nutrition, Autoimmune Disease, Neurodegenerative, Human Genome, Neurosciences, Brain Disorders, 2.1 Biological and endogenous factors, Neurological, Cholestanetriol 26-Monooxygenase, Cytochrome P450 Family 2, Gene Frequency, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Risk Factors, Vitamin D, Vitamin D Deficiency, GWAS, low-frequency genetic variants, multiple sclerosis, vitamin D, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Vitamin D insufficiency is common, correctable, and influenced by genetic factors, and it has been associated with risk of several diseases. We sought to identify low-frequency genetic variants that strongly increase the risk of vitamin D insufficiency and tested their effect on risk of multiple sclerosis, a disease influenced by low vitamin D concentrations. We used whole-genome sequencing data from 2,619 individuals through the UK10K program and deep-imputation data from 39,655 individuals genotyped genome-wide. Meta-analysis of the summary statistics from 19 cohorts identified in CYP2R1 the low-frequency (minor allele frequency = 2.5%) synonymous coding variant g.14900931G>A (p.Asp120Asp) (rs117913124[A]), which conferred a large effect on 25-hydroxyvitamin D (25OHD) levels (-0.43 SD of standardized natural log-transformed 25OHD per A allele; p value = 1.5 × 10-88). The effect on 25OHD was four times larger and independent of the effect of a previously described common variant near CYP2R1. By analyzing 8,711 individuals, we showed that heterozygote carriers of this low-frequency variant have an increased risk of vitamin D insufficiency (odds ratio [OR] = 2.2, 95% confidence interval [CI] = 1.78-2.78, p = 1.26 × 10-12). Individuals carrying one copy of this variant also had increased odds of multiple sclerosis (OR = 1.4, 95% CI = 1.19-1.64, p = 2.63 × 10-5) in a sample of 5,927 case and 5,599 control subjects. In conclusion, we describe a low-frequency CYP2R1 coding variant that exerts the largest effect upon 25OHD levels identified to date in the general European population and implicates vitamin D in the etiology of multiple sclerosis.

Published
2017

21. Large meta-analysis of genome-wide association studies identifies five loci for lean body mass.

Author

Zillikens, M Carola, Demissie, Serkalem, Hsu, Yi-Hsiang, Yerges-Armstrong, Laura M, Chou, Wen-Chi, Stolk, Lisette, Livshits, Gregory, Broer, Linda, Johnson, Toby, Koller, Daniel L, Kutalik, Zoltán, Luan, Jian'an, Malkin, Ida, Ried, Janina S, Smith, Albert V, Thorleifsson, Gudmar, Vandenput, Liesbeth, Hua Zhao, Jing, Zhang, Weihua, Aghdassi, Ali, Åkesson, Kristina, Amin, Najaf, Baier, Leslie J, Barroso, Inês, Bennett, David A, Bertram, Lars, Biffar, Rainer, Bochud, Murielle, Boehnke, Michael, Borecki, Ingrid B, Buchman, Aron S, Byberg, Liisa, Campbell, Harry, Campos Obanda, Natalia, Cauley, Jane A, Cawthon, Peggy M, Cederberg, Henna, Chen, Zhao, Cho, Nam H, Jin Choi, Hyung, Claussnitzer, Melina, Collins, Francis, Cummings, Steven R, De Jager, Philip L, Demuth, Ilja, Dhonukshe-Rutten, Rosalie AM, Diatchenko, Luda, Eiriksdottir, Gudny, Enneman, Anke W, Erdos, Mike, Eriksson, Johan G, Eriksson, Joel, Estrada, Karol, Evans, Daniel S, Feitosa, Mary F, Fu, Mao, Garcia, Melissa, Gieger, Christian, Girke, Thomas, Glazer, Nicole L, Grallert, Harald, Grewal, Jagvir, Han, Bok-Ghee, Hanson, Robert L, Hayward, Caroline, Hofman, Albert, Hoffman, Eric P, Homuth, Georg, Hsueh, Wen-Chi, Hubal, Monica J, Hubbard, Alan, Huffman, Kim M, Husted, Lise B, Illig, Thomas, Ingelsson, Erik, Ittermann, Till, Jansson, John-Olov, Jordan, Joanne M, Jula, Antti, Karlsson, Magnus, Khaw, Kay-Tee, Kilpeläinen, Tuomas O, Klopp, Norman, Kloth, Jacqueline SL, Koistinen, Heikki A, Kraus, William E, Kritchevsky, Stephen, Kuulasmaa, Teemu, Kuusisto, Johanna, Laakso, Markku, Lahti, Jari, Lang, Thomas, Langdahl, Bente L, Launer, Lenore J, Lee, Jong-Young, Lerch, Markus M, Lewis, Joshua R, Lind, Lars, Lindgren, Cecilia, and Liu, Yongmei

Subjects
Humans, Thinness, 17-Hydroxysteroid Dehydrogenases, Aldehyde Oxidoreductases, Extracellular Matrix Proteins, Body Composition, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Regulatory Elements, Transcriptional, Versicans, Genome-Wide Association Study, Insulin Receptor Substrate Proteins, ADAMTS Proteins, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Human Genome, Genetics, 1.1 Normal biological development and functioning
Abstract

Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p

Published
2017

22. Novel Genetic Variants Associated With Increased Vertebral Volumetric BMD, Reduced Vertebral Fracture Risk, and Increased Expression of SLC1A3 and EPHB2

Author

Nielson, Carrie M, Liu, Ching‐Ti, Smith, Albert V, Ackert‐Bicknell, Cheryl L, Reppe, Sjur, Jakobsdottir, Johanna, Wassel, Christina, Register, Thomas C, Oei, Ling, Alonso, Nerea, Oei, Edwin H, Parimi, Neeta, Samelson, Elizabeth J, Nalls, Mike A, Zmuda, Joseph, Lang, Thomas, Bouxsein, Mary, Latourelle, Jeanne, Claussnitzer, Melina, Siggeirsdottir, Kristin, Srikanth, Priya, Lorentzen, Erik, Vandenput, Liesbeth, Langefeld, Carl, Raffield, Laura, Terry, Greg, Cox, Amanda J, Allison, Matthew A, Criqui, Michael H, Bowden, Don, Ikram, M Arfan, Mellström, Dan, Karlsson, Magnus K, Carr, John, Budoff, Matthew, Phillips, Caroline, Cupples, L Adrienne, Chou, Wen‐Chi, Myers, Richard H, Ralston, Stuart H, Gautvik, Kaare M, Cawthon, Peggy M, Cummings, Steven, Karasik, David, Rivadeneira, Fernando, Gudnason, Vilmundur, Orwoll, Eric S, Harris, Tamara B, Ohlsson, Claes, Kiel, Douglas P, and Hsu, Yi‐Hsiang

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Clinical Sciences, Genetics, Human Genome, Aging, Osteoporosis, Biomedical Imaging, Aetiology, 2.1 Biological and endogenous factors, Musculoskeletal, Animals, Biopsy, Bone Density, Cancellous Bone, Excitatory Amino Acid Transporter 1, Gene Expression Regulation, Genetic Association Studies, Genetic Predisposition to Disease, Humans, Linkage Disequilibrium, Lumbar Vertebrae, Mice, Molecular Sequence Annotation, Organ Size, Osteoblasts, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Receptor, EphB2, Risk Factors, Spinal Fractures, Spine, BONE QCT, CT, ANALYSIS, QUANTITATION OF BONE, OSTEOPOROSIS, DISEASES AND DISORDERS OF, RELATED TO BONE, GENERAL POPULATION STUDIES, EPIDEMIOLOGY, HUMAN ASSOCIATION STUDIES, GENETIC RESEARCH, FRACTURE RISK ASSESSMENT, ANALYSIS/QUANTITATION OF BONE, BONE QCT/μCT, DISEASES AND DISORDERS OF/RELATED TO BONE, EPIDEMIOLOGY, HUMAN ASSOCIATION STUDIES, Engineering, Medical and Health Sciences, Anatomy & Morphology, Biological sciences, Biomedical and clinical sciences
Abstract

Genome-wide association studies (GWASs) have revealed numerous loci for areal bone mineral density (aBMD). We completed the first GWAS meta-analysis (n = 15,275) of lumbar spine volumetric BMD (vBMD) measured by quantitative computed tomography (QCT), allowing for examination of the trabecular bone compartment. SNPs that were significantly associated with vBMD were also examined in two GWAS meta-analyses to determine associations with morphometric vertebral fracture (n = 21,701) and clinical vertebral fracture (n = 5893). Expression quantitative trait locus (eQTL) analyses of iliac crest biopsies were performed in 84 postmenopausal women, and murine osteoblast expression of genes implicated by eQTL or by proximity to vBMD-associated SNPs was examined. We identified significant vBMD associations with five loci, including: 1p36.12, containing WNT4 and ZBTB40; 8q24, containing TNFRSF11B; and 13q14, containing AKAP11 and TNFSF11. Two loci (5p13 and 1p36.12) also contained associations with radiographic and clinical vertebral fracture, respectively. In 5p13, rs2468531 (minor allele frequency [MAF] = 3%) was associated with higher vBMD (β = 0.22, p = 1.9 × 10-8 ) and decreased risk of radiographic vertebral fracture (odds ratio [OR] = 0.75; false discovery rate [FDR] p = 0.01). In 1p36.12, rs12742784 (MAF = 21%) was associated with higher vBMD (β = 0.09, p = 1.2 × 10-10 ) and decreased risk of clinical vertebral fracture (OR = 0.82; FDR p = 7.4 × 10-4 ). Both SNPs are noncoding and were associated with increased mRNA expression levels in human bone biopsies: rs2468531 with SLC1A3 (β = 0.28, FDR p = 0.01, involved in glutamate signaling and osteogenic response to mechanical loading) and rs12742784 with EPHB2 (β = 0.12, FDR p = 1.7 × 10-3 , functions in bone-related ephrin signaling). Both genes are expressed in murine osteoblasts. This is the first study to link SLC1A3 and EPHB2 to clinically relevant vertebral osteoporosis phenotypes. These results may help elucidate vertebral bone biology and novel approaches to reducing vertebral fracture incidence. © 2016 American Society for Bone and Mineral Research.

Published
2016

23. Targeted sequencing of genome wide significant loci associated with bone mineral density (BMD) reveals significant novel and rare variants: the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) targeted sequencing study.

Author

Hsu, Yi-Hsiang, Li, Guo, Liu, Ching-Ti, Brody, Jennifer A, Karasik, David, Chou, Wen-Chi, Demissie, Serkalem, Nandakumar, Kannabiran, Zhou, Yanhua, Cheng, Chia-Ho, Gill, Richard, Gibbs, Richard A, Muzny, Donna, Santibanez, Jireh, Estrada, Karol, Rivadeneira, Fernando, Harris, Tamara, Gudnason, Vilmundur, Uitterlinden, Andre, Psaty, Bruce M, Robbins, John A, Adrienne Cupples, L, and Kiel, Douglas P

Subjects
Biological Sciences, Genetics, Human Genome, Osteoporosis, 2.1 Biological and endogenous factors, Aetiology, Aging, Bone Density, Cardiovascular Diseases, Cohort Studies, Epidemiologic Studies, Female, Femur Neck, GTPase-Activating Proteins, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, MEF2 Transcription Factors, Male, Middle Aged, Polymorphism, Single Nucleotide, Medical and Health Sciences, Genetics & Heredity
Abstract

BackgroundBone mineral density (BMD) is a heritable phenotype that predicts fracture risk. We performed fine-mapping by targeted sequencing at WLS, MEF2C, ARHGAP1/F2 and JAG1 loci prioritized by eQTL and bioinformatic approaches among 56 BMD loci from our previous GWAS meta-analysis. Targeted sequencing was conducted in 1,291 Caucasians from the Framingham Heart Study ( n =  925) and Cardiovascular Health Study ( n =  366), including 206 women and men with extreme low femoral neck (FN) BMD. A total of 4,964 sequence variants (SNVs) were observed and 80% were rare with MAF

Published
2016

25. Indoor Localization with Adaptive Channel Model Estimation in WiFi Networks

Author

Huang, Yung-Fa, Hsu, Yi-Hsiang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Ruediger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Kim, Kuinam J., editor, and Kim, Hyuncheol, editor

Published
2019
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27. GWAS analysis of handgrip and lower body strength in older adults in the CHARGE consortium.

Author

Matteini, Amy M, Tanaka, Toshiko, Karasik, David, Atzmon, Gil, Chou, Wen-Chi, Eicher, John D, Johnson, Andrew D, Arnold, Alice M, Callisaya, Michele L, Davies, Gail, Evans, Daniel S, Holtfreter, Birte, Lohman, Kurt, Lunetta, Kathryn L, Mangino, Massimo, Smith, Albert V, Smith, Jennifer A, Teumer, Alexander, Yu, Lei, Arking, Dan E, Buchman, Aron S, Chibinik, Lori B, De Jager, Philip L, Evans, Denis A, Faul, Jessica D, Garcia, Melissa E, Gillham-Nasenya, Irina, Gudnason, Vilmundur, Hofman, Albert, Hsu, Yi-Hsiang, Ittermann, Till, Lahousse, Lies, Liewald, David C, Liu, Yongmei, Lopez, Lorna, Rivadeneira, Fernando, Rotter, Jerome I, Siggeirsdottir, Kristin, Starr, John M, Thomson, Russell, Tranah, Gregory J, Uitterlinden, André G, Völker, Uwe, Völzke, Henry, Weir, David R, Yaffe, Kristine, Zhao, Wei, Zhuang, Wei Vivian, Zmuda, Joseph M, Bennett, David A, Cummings, Steven R, Deary, Ian J, Ferrucci, Luigi, Harris, Tamara B, Kardia, Sharon LR, Kocher, Thomas, Kritchevsky, Stephen B, Psaty, Bruce M, Seshadri, Sudha, Spector, Timothy D, Srikanth, Velandai K, Windham, B Gwen, Zillikens, M Carola, Newman, Anne B, Walston, Jeremy D, Kiel, Douglas P, and Murabito, Joanne M

Subjects
Humans, Hand Strength, Cohort Studies, Reproducibility of Results, Chromatin Immunoprecipitation, Epigenesis, Genetic, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Adult, Aged, Muscle Strength, Genome-Wide Association Study, Molecular Sequence Annotation, SNP, aging, genomewide association, meta-analysis, muscle strength, older adults, Epigenesis, Genetic, Polymorphism, Single Nucleotide, Developmental Biology, Medical and Health Sciences, Biological Sciences
Abstract

Decline in muscle strength with aging is an important predictor of health trajectory in the elderly. Several factors, including genetics, are proposed contributors to variability in muscle strength. To identify genetic contributors to muscle strength, a meta-analysis of genomewide association studies of handgrip was conducted. Grip strength was measured using a handheld dynamometer in 27 581 individuals of European descent over 65 years of age from 14 cohort studies. Genomewide association analysis was conducted on ~2.7 million imputed and genotyped variants (SNPs). Replication of the most significant findings was conducted using data from 6393 individuals from three cohorts. GWAS of lower body strength was also characterized in a subset of cohorts. Two genomewide significant (P-value< 5 × 10(-8) ) and 39 suggestive (P-value< 5 × 10(-5) ) associations were observed from meta-analysis of the discovery cohorts. After meta-analysis with replication cohorts, genomewide significant association was observed for rs752045 on chromosome 8 (β = 0.47, SE = 0.08, P-value = 5.20 × 10(-10) ). This SNP is mapped to an intergenic region and is located within an accessible chromatin region (DNase hypersensitivity site) in skeletal muscle myotubes differentiated from the human skeletal muscle myoblasts cell line. This locus alters a binding motif of the CCAAT/enhancer-binding protein-β (CEBPB) that is implicated in muscle repair mechanisms. GWAS of lower body strength did not yield significant results. A common genetic variant in a chromosomal region that regulates myotube differentiation and muscle repair may contribute to variability in grip strength in the elderly. Further studies are needed to uncover the mechanisms that link this genetic variant with muscle strength.

Published
2016

29. HLA-DRB1 and HLA-DQB1 genetic diversity modulates response to lithium in bipolar affective disorders

Author

Le Clerc, Sigrid, Lombardi, Laura, Baune, Bernhard T., Amare, Azmeraw T., Schubert, Klaus Oliver, Hou, Liping, Clark, Scott R., Papiol, Sergi, Cearns, Micah, Heilbronner, Urs, Degenhardt, Franziska, Tekola-Ayele, Fasil, Hsu, Yi-Hsiang, Shekhtman, Tatyana, Adli, Mazda, Akula, Nirmala, Akiyama, Kazufumi, Ardau, Raffaella, Arias, Bárbara, Aubry, Jean-Michel, Backlund, Lena, Bhattacharjee, Abesh Kumar, Bellivier, Frank, Benabarre, Antonio, Bengesser, Susanne, Biernacka, Joanna M., Birner, Armin, Brichant-Petitjean, Clara, Cervantes, Pablo, Chen, Hsi-Chung, Chillotti, Caterina, Cichon, Sven, Cruceanu, Cristiana, Czerski, Piotr M., Dalkner, Nina, Dayer, Alexandre, Del Zompo, Maria, DePaulo, J. Raymond, Étain, Bruno, Jamain, Stephane, Falkai, Peter, Forstner, Andreas J., Frisen, Louise, Frye, Mark A., Fullerton, Janice M., Gard, Sébastien, Garnham, Julie S., Goes, Fernando S., Grigoroiu-Serbanescu, Maria, Grof, Paul, Hashimoto, Ryota, Hauser, Joanna, Herms, Stefan, Hoffmann, Per, Jiménez, Esther, Kahn, Jean-Pierre, Kassem, Layla, Kuo, Po-Hsiu, Kato, Tadafumi, Kelsoe, John R., Kittel-Schneider, Sarah, Ferensztajn-Rochowiak, Ewa, König, Barbara, Kusumi, Ichiro, Laje, Gonzalo, Landén, Mikael, Lavebratt, Catharina, Leckband, Susan G., Tortorella, Alfonso, Manchia, Mirko, Martinsson, Lina, McCarthy, Michael J., McElroy, Susan L., Colom, Francesc, Millischer, Vincent, Mitjans, Marina, Mondimore, Francis M., Monteleone, Palmiero, Nievergelt, Caroline M., Nöthen, Markus M., Novák, Tomas, O’Donovan, Claire, Ozaki, Norio, Ösby, Urban, Pfennig, Andrea, Potash, James B., Reif, Andreas, Reininghaus, Eva, Rouleau, Guy A., Rybakowski, Janusz K., Schalling, Martin, Schofield, Peter R., Schweizer, Barbara W., Severino, Giovanni, Shilling, Paul D., Shimoda, Katzutaka, Simhandl, Christian, Slaney, Claire M., Pisanu, Claudia, Squassina, Alessio, Stamm, Thomas, Stopkova, Pavla, Maj, Mario, Turecki, Gustavo, Vieta, Eduard, Veeh, Julia, Witt, Stephanie H., Wright, Adam, Zandi, Peter P., Mitchell, Philip B., Bauer, Michael, Alda, Martin, Rietschel, Marcella, McMahon, Francis J., Schulze, Thomas G., Spadoni, Jean-Louis, Boukouaci, Wahid, Richard, Jean-Romain, Le Corvoisier, Philippe, Barrau, Caroline, Zagury, Jean-François, Leboyer, Marion, and Tamouza, Ryad

Published
2021
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32. Whole‐genome sequencing identifies EN1 as a determinant of bone density and fracture

Author

Zheng, Hou‐Feng, Forgetta, Vincenzo, Hsu, Yi‐Hsiang, Estrada, Karol, Rosello‐Diez, Alberto, Leo, Paul J, Dahia, Chitra L, Park‐Min, Kyung Hyun, Tobias, Jonathan H, Kooperberg, Charles, Kleinman, Aaron, Styrkarsdottir, Unnur, Liu, Ching‐Ti, Uggla, Charlotta, Evans, Daniel S, Nielson, Carrie M, Walter, Klaudia, Pettersson‐Kymmer, Ulrika, McCarthy, Shane, Eriksson, Joel, Kwan, Tony, Jhamai, Mila, Trajanoska, Katerina, Memari, Yasin, Min, Josine, Huang, Jie, Danecek, Petr, Wilmot, Beth, Li, Rui, Chou, Wen‐Chi, Mokry, Lauren E, Moayyeri, Alireza, Claussnitzer, Melina, Cheng, Chia‐Ho, Cheung, Warren, Medina‐Gómez, Carolina, Ge, Bing, Chen, Shu‐Huang, Choi, Kwangbom, Oei, Ling, Fraser, James, Kraaij, Robert, Hibbs, Matthew A, Gregson, Celia L, Paquette, Denis, Hofman, Albert, Wibom, Carl, Tranah, Gregory J, Marshall, Mhairi, Gardiner, Brooke B, Cremin, Katie, Auer, Paul, Hsu, Li, Ring, Sue, Tung, Joyce Y, Thorleifsson, Gudmar, Enneman, Anke W, van Schoor, Natasja M, de Groot, Lisette CPGM, van der Velde, Nathalie, Melin, Beatrice, Kemp, John P, Christiansen, Claus, Sayers, Adrian, Zhou, Yanhua, Calderari, Sophie, van Rooij, Jeroen, Carlson, Chris, Peters, Ulrike, Berlivet, Soizik, Dostie, Josée, Uitterlinden, Andre G, Williams, Stephen R, Farber, Charles, Grinberg, Daniel, LaCroix, Andrea Z, Haessler, Jeff, Chasman, Daniel I, Giulianini, Franco, Rose, Lynda M, Ridker, Paul M, Eisman, John A, Nguyen, Tuan V, Center, Jacqueline R, Nogues, Xavier, Garcia‐Giralt, Natalia, Launer, Lenore L, Gudnason, Vilmunder, Mellström, Dan, Vandenput, Liesbeth, Amin, Najaf, van Duijn, Cornelia M, Karlsson, Magnus K, Ljunggren, Östen, Svensson, Olle, Hallmans, Göran, Rousseau, François, Giroux, Sylvie, Bussière, Johanne, and Arp, Pascal P

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Clinical Sciences, Genetics, Human Genome, Biotechnology, Osteoporosis, Stem Cell Research, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Aetiology, Underpinning research, Musculoskeletal, Injuries and accidents, Animals, Bone Density, Bone and Bones, Disease Models, Animal, Europe, Exome, Female, Fractures, Bone, Gene Frequency, Genetic Predisposition to Disease, Genetic Variation, Genome, Human, Genomics, Genotype, Homeodomain Proteins, Humans, Mice, Sequence Analysis, DNA, White People, Wnt Proteins, AOGC Consortium, UK10K Consortium, General Science & Technology
Abstract

The extent to which low-frequency (minor allele frequency (MAF) between 1-5%) and rare (MAF ≤ 1%) variants contribute to complex traits and disease in the general population is mainly unknown. Bone mineral density (BMD) is highly heritable, a major predictor of osteoporotic fractures, and has been previously associated with common genetic variants, as well as rare, population-specific, coding variants. Here we identify novel non-coding genetic variants with large effects on BMD (ntotal = 53,236) and fracture (ntotal = 508,253) in individuals of European ancestry from the general population. Associations for BMD were derived from whole-genome sequencing (n = 2,882 from UK10K (ref. 10); a population-based genome sequencing consortium), whole-exome sequencing (n = 3,549), deep imputation of genotyped samples using a combined UK10K/1000 Genomes reference panel (n = 26,534), and de novo replication genotyping (n = 20,271). We identified a low-frequency non-coding variant near a novel locus, EN1, with an effect size fourfold larger than the mean of previously reported common variants for lumbar spine BMD (rs11692564(T), MAF = 1.6%, replication effect size = +0.20 s.d., Pmeta = 2 × 10(-14)), which was also associated with a decreased risk of fracture (odds ratio = 0.85; P = 2 × 10(-11); ncases = 98,742 and ncontrols = 409,511). Using an En1(cre/flox) mouse model, we observed that conditional loss of En1 results in low bone mass, probably as a consequence of high bone turnover. We also identified a novel low-frequency non-coding variant with large effects on BMD near WNT16 (rs148771817(T), MAF = 1.2%, replication effect size = +0.41 s.d., Pmeta = 1 × 10(-11)). In general, there was an excess of association signals arising from deleterious coding and conserved non-coding variants. These findings provide evidence that low-frequency non-coding variants have large effects on BMD and fracture, thereby providing rationale for whole-genome sequencing and improved imputation reference panels to study the genetic architecture of complex traits and disease in the general population.

Published
2015

33. FTO Obesity Variant Circuitry and Adipocyte Browning in Humans

Author

Claussnitzer, Melina, Dankel, Simon N, Kim, Kyoung-Han, Quon, Gerald, Meuleman, Wouter, Haugen, Christine, Glunk, Viktoria, Sousa, Isabel S, Beaudry, Jacqueline L, Puviindran, Vijitha, Abdennur, Nezar A, Liu, Jannel, Svensson, Per-Arne, Hsu, Yi-Hsiang, Drucker, Daniel J, Mellgren, Gunnar, Hui, Chi-Chung, Hauner, Hans, and Kellis, Manolis

Subjects
Biomedical and Clinical Sciences, Nutrition, Obesity, Human Genome, Genetics, Aetiology, 2.1 Biological and endogenous factors, Cancer, Metabolic and endocrine, Adipocytes, Alleles, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Animals, Base Sequence, Clustered Regularly Interspaced Short Palindromic Repeats, Epigenomics, Gene Expression, Genetic Engineering, Humans, Mice, Mitochondria, Molecular Sequence Data, Phenotype, Proteins, RNA Editing, Risk, Thermogenesis, Medical and Health Sciences, General & Internal Medicine, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundGenomewide association studies can be used to identify disease-relevant genomic regions, but interpretation of the data is challenging. The FTO region harbors the strongest genetic association with obesity, yet the mechanistic basis of this association remains elusive.MethodsWe examined epigenomic data, allelic activity, motif conservation, regulator expression, and gene coexpression patterns, with the aim of dissecting the regulatory circuitry and mechanistic basis of the association between the FTO region and obesity. We validated our predictions with the use of directed perturbations in samples from patients and from mice and with endogenous CRISPR-Cas9 genome editing in samples from patients.ResultsOur data indicate that the FTO allele associated with obesity represses mitochondrial thermogenesis in adipocyte precursor cells in a tissue-autonomous manner. The rs1421085 T-to-C single-nucleotide variant disrupts a conserved motif for the ARID5B repressor, which leads to derepression of a potent preadipocyte enhancer and a doubling of IRX3 and IRX5 expression during early adipocyte differentiation. This results in a cell-autonomous developmental shift from energy-dissipating beige (brite) adipocytes to energy-storing white adipocytes, with a reduction in mitochondrial thermogenesis by a factor of 5, as well as an increase in lipid storage. Inhibition of Irx3 in adipose tissue in mice reduced body weight and increased energy dissipation without a change in physical activity or appetite. Knockdown of IRX3 or IRX5 in primary adipocytes from participants with the risk allele restored thermogenesis, increasing it by a factor of 7, and overexpression of these genes had the opposite effect in adipocytes from nonrisk-allele carriers. Repair of the ARID5B motif by CRISPR-Cas9 editing of rs1421085 in primary adipocytes from a patient with the risk allele restored IRX3 and IRX5 repression, activated browning expression programs, and restored thermogenesis, increasing it by a factor of 7.ConclusionsOur results point to a pathway for adipocyte thermogenesis regulation involving ARID5B, rs1421085, IRX3, and IRX5, which, when manipulated, had pronounced pro-obesity and anti-obesity effects. (Funded by the German Research Center for Environmental Health and others.).

Published
2015

34. Meta-analysis of genome-wide association studies identifies two loci associated with circulating osteoprotegerin levels

Author

Kwan, Johnny SH, Hsu, Yi-Hsiang, Cheung, Ching-Lung, Dupuis, Josée, Saint-Pierre, Aude, Eriksson, Joel, Handelman, Samuel K, Aragaki, Aaron, Karasik, David, Pramstaller, Peter P, Kooperberg, Charles, Lacroix, Andrea Z, Larson, Martin G, Lau, Kam-Shing, Lorentzon, Mattias, Pichler, Irene, Sham, Pak C, Taliun, Daniel, Vandenput, Liesbeth, Kiel, Douglas P, Hicks, Andrew A, Jackson, Rebecca D, Ohlsson, Claes, Benjamin, Emelia J, and Kung, Annie WC

Subjects
Biological Sciences, Genetics, Human Genome, Biotechnology, Atherosclerosis, Asian People, Chromosomes, Human, Pair 14, Chromosomes, Human, Pair 17, Female, Genetic Loci, Genome, Human, Genome-Wide Association Study, Humans, Male, Osteoprotegerin, Polymorphism, Genetic, Quantitative Trait, Heritable, White People, Medical and Health Sciences, Genetics & Heredity
Abstract

Osteoprotegerin (OPG) is involved in bone homeostasis and tumor cell survival. Circulating OPG levels are also important biomarkers of various clinical traits, such as cancers and atherosclerosis. OPG levels were measured in serum or in plasma. In a meta-analysis of genome-wide association studies in up to 10 336 individuals from European and Asian origin, we discovered that variants >100 kb upstream of the TNFRSF11B gene encoding OPG and another new locus on chromosome 17q11.2 were significantly associated with OPG variation. We also identified a suggestive locus on chromosome 14q21.2 associated with the trait. Moreover, we estimated that over half of the heritability of OPG levels could be explained by all variants examined in our study. Our findings provide further insight into the genetic regulation of circulating OPG levels.

Published
2014

36. Pleiotropic genes for metabolic syndrome and inflammation

Author

Kraja, Aldi T, Chasman, Daniel I, North, Kari E, Reiner, Alexander P, Yanek, Lisa R, Kilpeläinen, Tuomas O, Smith, Jennifer A, Dehghan, Abbas, Dupuis, Josée, Johnson, Andrew D, Feitosa, Mary F, Tekola-Ayele, Fasil, Chu, Audrey Y, Nolte, Ilja M, Dastani, Zari, Morris, Andrew, Pendergrass, Sarah A, Sun, Yan V, Ritchie, Marylyn D, Vaez, Ahmad, Lin, Honghuang, Ligthart, Symen, Marullo, Letizia, Rohde, Rebecca, Shao, Yaming, Ziegler, Mark A, Im, Hae Kyung, Group, Cross Consortia Pleiotropy, Heart and, the Cohorts for, Epidemiology, Aging Research in Genetic, Consortium, the Genetic Investigation of Anthropometric Traits, Consortium, the Global Lipids Genetics, the Meta-Analyses of Glucose, Consortium, Insulin-related traits, Consortium, the Global BPgen, Consortium, The ADIPOGen, Study, the Women's Genome Health, Study, the Howard University Family, Schnabel, Renate B, Jørgensen, Torben, Jørgensen, Marit E, Hansen, Torben, Pedersen, Oluf, Stolk, Ronald P, Snieder, Harold, Hofman, Albert, Uitterlinden, Andre G, Franco, Oscar H, Ikram, M Arfan, Richards, J Brent, Rotimi, Charles, Wilson, James G, Lange, Leslie, Ganesh, Santhi K, Nalls, Mike, Rasmussen-Torvik, Laura J, Pankow, James S, Coresh, Josef, Tang, Weihong, Kao, WH Linda, Boerwinkle, Eric, Morrison, Alanna C, Ridker, Paul M, Becker, Diane M, Rotter, Jerome I, Kardia, Sharon LR, Loos, Ruth JF, Larson, Martin G, Hsu, Yi-Hsiang, Province, Michael A, Tracy, Russell, Voight, Benjamin F, Vaidya, Dhananjay, O'Donnell, Christopher J, Benjamin, Emelia J, Alizadeh, Behrooz Z, Prokopenko, Inga, Meigs, James B, and Borecki, Ingrid B

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Obesity, Cardiovascular, Human Genome, Prevention, Diabetes, Nutrition, Clinical Research, 2.1 Biological and endogenous factors, Biomarkers, Computational Biology, Gene Regulatory Networks, Genetic Pleiotropy, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Inflammation, Meta-Analysis as Topic, Metabolic Syndrome, Phenotype, Quantitative Trait, Heritable, Metabolic syndrome, Inflammatory markers, Pleiotropic associations, Meta-analysis, Regulome, Cross Consortia Pleiotropy Group, Cohorts for Heart and, Aging Research in Genetic Epidemiology, Genetic Investigation of Anthropometric Traits Consortium, Global Lipids Genetics Consortium, Meta-Analyses of Glucose, Insulin-related traits Consortium, Global BPgen Consortium, ADIPOGen Consortium, Women's Genome Health Study, Howard University Family Study, Clinical Sciences, Genetics & Heredity, Clinical sciences
Abstract

Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network. To test this hypothesis a staged approach was undertaken. (a) We analyzed 17 metabolic and inflammatory traits in more than 85,500 participants from 14 large epidemiological studies within the Cross Consortia Pleiotropy Group. Individuals classified with MetS (NCEP definition), versus those without, showed on average significantly different levels for most inflammatory markers studied. (b) Paired average correlations between 8 metabolic traits and 9 inflammatory markers from the same studies as above, estimated with two methods, and factor analyses on large simulated data, helped in identifying 8 combinations of traits for follow-up in meta-analyses, out of 130,305 possible combinations between metabolic traits and inflammatory markers studied. (c) We performed correlated meta-analyses for 8 metabolic traits and 6 inflammatory markers by using existing GWAS published genetic summary results, with about 2.5 million SNPs from twelve predominantly largest GWAS consortia. These analyses yielded 130 unique SNPs/genes with pleiotropic associations (a SNP/gene associating at least one metabolic trait and one inflammatory marker). Of them twenty-five variants (seven loci newly reported) are proposed as MetS candidates. They map to genes MACF1, KIAA0754, GCKR, GRB14, COBLL1, LOC646736-IRS1, SLC39A8, NELFE, SKIV2L, STK19, TFAP2B, BAZ1B, BCL7B, TBL2, MLXIPL, LPL, TRIB1, ATXN2, HECTD4, PTPN11, ZNF664, PDXDC1, FTO, MC4R and TOMM40. Based on large data evidence, we conclude that inflammation is a feature of MetS and several gene variants show pleiotropic genetic associations across phenotypes and might explain a part of MetS correlated genetic architecture. These findings warrant further functional investigation.

Published
2014

37. Bicc1 is a genetic determinant of osteoblastogenesis and bone mineral density

Author

Mesner, Larry D, Ray, Brianne, Hsu, Yi-Hsiang, Manichaikul, Ani, Lum, Eric, Bryda, Elizabeth C, Rich, Stephen S, Rosen, Clifford J, Criqui, Michael H, Allison, Matthew, Budoff, Matthew J, Clemens, Thomas L, and Farber, Charles R

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Osteoporosis, Women's Health, Human Genome, 2.1 Biological and endogenous factors, Underpinning research, 1.1 Normal biological development and functioning, Aetiology, Musculoskeletal, Animals, Bone Density, Carbolines, Carrier Proteins, Cell Differentiation, Female, Gene Knockdown Techniques, Gene Regulatory Networks, Humans, Male, Mice, Mice, Inbred C57BL, Mice, Knockout, Osteoblasts, Osteogenesis, Polymorphism, Single Nucleotide, Quantitative Trait Loci, RNA-Binding Proteins, TRPP Cation Channels, Medical and Health Sciences, Immunology, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Patient bone mineral density (BMD) predicts the likelihood of osteoporotic fracture. While substantial progress has been made toward elucidating the genetic determinants of BMD, our understanding of the factors involved remains incomplete. Here, using a systems genetics approach in the mouse, we predicted that bicaudal C homolog 1 (Bicc1), which encodes an RNA-binding protein, is responsible for a BMD quantitative trait locus (QTL) located on murine chromosome 10. Consistent with this prediction, mice heterozygous for a null allele of Bicc1 had low BMD. We used a coexpression network-based approach to determine how Bicc1 influences BMD. Based on this analysis, we inferred that Bicc1 was involved in osteoblast differentiation and that polycystic kidney disease 2 (Pkd2) was a downstream target of Bicc1. Knock down of Bicc1 and Pkd2 impaired osteoblastogenesis, and Bicc1 deficiency-dependent osteoblast defects were rescued by Pkd2 overexpression. Last, in 2 human BMD genome-wide association (GWAS) meta-analyses, we identified SNPs in BICC1 and PKD2 that were associated with BMD. These results, in both mice and humans, identify Bicc1 as a genetic determinant of osteoblastogenesis and BMD and suggest that it does so by regulating Pkd2 transcript levels.

Published
2014

38. Genetic determinants of heel bone properties: genome-wide association meta-analysis and replication in the GEFOS/GENOMOS consortium.

Author

Moayyeri, Alireza, Hsu, Yi-Hsiang, Karasik, David, Estrada, Karol, Xiao, Su-Mei, Nielson, Carrie, Srikanth, Priya, Giroux, Sylvie, Wilson, Scott G, Zheng, Hou-Feng, Smith, Albert V, Pye, Stephen R, Leo, Paul J, Teumer, Alexander, Hwang, Joo-Yeon, Ohlsson, Claes, McGuigan, Fiona, Minster, Ryan L, Hayward, Caroline, Olmos, José M, Lyytikäinen, Leo-Pekka, Lewis, Joshua R, Swart, Karin MA, Masi, Laura, Oldmeadow, Chris, Holliday, Elizabeth G, Cheng, Sulin, van Schoor, Natasja M, Harvey, Nicholas C, Kruk, Marcin, del Greco M, Fabiola, Igl, Wilmar, Trummer, Olivia, Grigoriou, Efi, Luben, Robert, Liu, Ching-Ti, Zhou, Yanhua, Oei, Ling, Medina-Gomez, Carolina, Zmuda, Joseph, Tranah, Greg, Brown, Suzanne J, Williams, Frances M, Soranzo, Nicole, Jakobsdottir, Johanna, Siggeirsdottir, Kristin, Holliday, Kate L, Hannemann, Anke, Go, Min Jin, Garcia, Melissa, Polasek, Ozren, Laaksonen, Marika, Zhu, Kun, Enneman, Anke W, McEvoy, Mark, Peel, Roseanne, Sham, Pak Chung, Jaworski, Maciej, Johansson, Åsa, Hicks, Andrew A, Pludowski, Pawel, Scott, Rodney, Dhonukshe-Rutten, Rosalie AM, van der Velde, Nathalie, Kähönen, Mika, Viikari, Jorma S, Sievänen, Harri, Raitakari, Olli T, González-Macías, Jesús, Hernández, Jose L, Mellström, Dan, Ljunggren, Osten, Cho, Yoon Shin, Völker, Uwe, Nauck, Matthias, Homuth, Georg, Völzke, Henry, Haring, Robin, Brown, Matthew A, McCloskey, Eugene, Nicholson, Geoffrey C, Eastell, Richard, Eisman, John A, Jones, Graeme, Reid, Ian R, Dennison, Elaine M, Wark, John, Boonen, Steven, Vanderschueren, Dirk, Wu, Frederick CW, Aspelund, Thor, Richards, J Brent, Bauer, Doug, Hofman, Albert, Khaw, Kay-Tee, Dedoussis, George, Obermayer-Pietsch, Barbara, Gyllensten, Ulf, Pramstaller, Peter P, and Lorenc, Roman S

Subjects
Calcaneus, Humans, Osteoporosis, Genetic Predisposition to Disease, Ultrasonography, Cohort Studies, Bone Density, Polymorphism, Single Nucleotide, Adult, Aged, Aged, 80 and over, Middle Aged, Female, Male, Fractures, Bone, Genome-Wide Association Study, Young Adult, Human Genome, Genetics, Aging, 2.1 Biological and endogenous factors, Aetiology, Musculoskeletal, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Quantitative ultrasound of the heel captures heel bone properties that independently predict fracture risk and, with bone mineral density (BMD) assessed by X-ray (DXA), may be convenient alternatives for evaluating osteoporosis and fracture risk. We performed a meta-analysis of genome-wide association (GWA) studies to assess the genetic determinants of heel broadband ultrasound attenuation (BUA; n = 14 260), velocity of sound (VOS; n = 15 514) and BMD (n = 4566) in 13 discovery cohorts. Independent replication involved seven cohorts with GWA data (in silico n = 11 452) and new genotyping in 15 cohorts (de novo n = 24 902). In combined random effects, meta-analysis of the discovery and replication cohorts, nine single nucleotide polymorphisms (SNPs) had genome-wide significant (P < 5 × 10(-8)) associations with heel bone properties. Alongside SNPs within or near previously identified osteoporosis susceptibility genes including ESR1 (6q25.1: rs4869739, rs3020331, rs2982552), SPTBN1 (2p16.2: rs11898505), RSPO3 (6q22.33: rs7741021), WNT16 (7q31.31: rs2908007), DKK1 (10q21.1: rs7902708) and GPATCH1 (19q13.11: rs10416265), we identified a new locus on chromosome 11q14.2 (rs597319 close to TMEM135, a gene recently linked to osteoblastogenesis and longevity) significantly associated with both BUA and VOS (P < 8.23 × 10(-14)). In meta-analyses involving 25 cohorts with up to 14 985 fracture cases, six of 10 SNPs associated with heel bone properties at P < 5 × 10(-6) also had the expected direction of association with any fracture (P < 0.05), including three SNPs with P < 0.005: 6q22.33 (rs7741021), 7q31.31 (rs2908007) and 10q21.1 (rs7902708). In conclusion, this GWA study reveals the effect of several genes common to central DXA-derived BMD and heel ultrasound/DXA measures and points to a new genetic locus with potential implications for better understanding of osteoporosis pathophysiology.

Published
2014

39. A Novel Adaptive Indoor Positioning Using Mobile Devices with Wireless Local Area Networks.

Author

Huang, Yung-Fa, Hsu, Yi-Hsiang, Lin, Jen-Yung, and Chen, Ching-Mu

Subjects
WIRELESS LANs, WIRELESS channels, STANDARD deviations, DISTRIBUTION (Probability theory), KALMAN filtering
Abstract

In this paper, mobile devices were used to estimate the received signal strength indicator (RSSI) of wireless channels with three wireless access points (APs). Using the RSSI, the path loss exponent (PLE) was adapted to calculate the estimated distance among the test points (TPs) and the APs, through the root mean square error (RMSE). Moreover, in this paper, the proposed adaptive PLE (APLE) of the TPs was obtained by minimizing the positioning errors of the PLEs. The training samples of RSSI were measured by TPs for 6 days, and different surge processing methods were used to obtain APLE and to improve the positioning accuracy. The surge signals of RSSI were reduced by the cumulated distribution function (CDF), hybrid Kalman filter (KF), and threshold filtering methods, integrating training samples and APLE. The experimental results show that with the proposed APLE, the position accuracy can be improved by 50% compared to the free space model for six TPs. Finally, dynamic real-time indoor positioning was performed and measured for the performance evaluation of the proposed APLE models. The experimental results show that, the minimum dynamic real-time positioning error can be improved to 0.88 m in a straight-line case with the hybrid method. Moreover, the average positioning error of dynamic real-time indoor positioning can be reduced to 1.15 m using the four methods with the proposed APLE. [ABSTRACT FROM AUTHOR]

Published
2024
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43. List of Contributors

Author

Abraham, David, primary, Almeida, Maria, additional, Ambrogini, Elena, additional, Arnold, Andrew, additional, Bakos, Bence, additional, Bergwitz, Clemens, additional, Bikle, Daniel D., additional, Bilezikian, John P., additional, Binkley, Neil, additional, Bisello, Alessandro, additional, Bonewald, L.F., additional, Bou-Gharios, George, additional, Bouillon, Roger, additional, Bouxsein, Mary L., additional, Boyce, Brendan F., additional, Boyd, Steven, additional, Brandi, Maria Luisa, additional, Burr, David B., additional, Calvi, Laura M., additional, Canalis, Ernesto, additional, Cao, Xu, additional, Carmeliet, Geert, additional, Carpenter, Thomas O., additional, Chang, Wenhan, additional, Chim, Shek Man, additional, Choudhary, Shilpa, additional, Christakos, Sylvia, additional, Chun, Yong-Hee Patricia, additional, Cipriani, Cristiana, additional, Civitelli, Roberto, additional, Clemens, Thomas L., additional, Collins, Michael T., additional, Conte, Caterina, additional, Cooper, Mark S., additional, Cornish, Jillian, additional, Cremers, Serge, additional, Dawson-Hughes, Bess, additional, de Crombrugghe, Benoit, additional, DeLuca, Hector F., additional, Dempster, David W., additional, Drake, Matthew T., additional, Ducy, Patricia, additional, Ebetino, Frank H., additional, Engelke, Klaus, additional, Erben, Reinhold G., additional, Eyre, David R., additional, Farber, Charles R., additional, Feigenson, Marina, additional, Ferron, Mathieu, additional, Florenzano, Pablo, additional, Fontana, Francesca, additional, Foster, Brian L., additional, Friedman, Peter A., additional, Fukumoto, Seiji, additional, Gamer, Laura W., additional, Gardella, Thomas J., additional, Garnero, Patrick, additional, Genant, Harry K., additional, Giusti, Francesca, additional, Göbel, Andy, additional, Goltzman, David, additional, Gorski, Jeffrey P., additional, Griffith, James, additional, G Russell, R. Graham, additional, Hankenson, Kurt D., additional, Hannan, Fadil M., additional, Harris, Stephen E., additional, Hartley, Iris R., additional, Hartmann, Christine, additional, Heaney, Robert P., additional, Hendy, Geoffrey N., additional, Hilton, Matthew J., additional, Hofbauer, Lorenz C., additional, Holdsworth, Gill, additional, Hsu, Yi-Hsiang, additional, Hudson, David M., additional, Hurley, Marja, additional, Insogna, Karl L., additional, Jilka, Robert L., additional, Johnson, Mark L., additional, Johnson, Rachelle W., additional, Jones, Glenville, additional, Judex, Stefan, additional, Jüppner, Harald, additional, Kalajzic, Ivo, additional, Karsenty, Gérard, additional, Ke, Hua Zhu, additional, Khosla, Sundeep, additional, Kiel, Douglas P., additional, Klein-Nulend, J., additional, Ko, Frank C., additional, Kobayashi, Yasuhiro, additional, Konrad, Martin, additional, Kostenuik, Paul J., additional, Kovacs, Christopher S., additional, Kremer, Richard, additional, Krishnan, Venkatesh, additional, Kronenberg, Henry M., additional, Lakatos, Peter A., additional, Liberman, Uri A., additional, Lorenzo, Joseph A., additional, Lynch, Conor C., additional, Lyons, Karen M., additional, Ma, Y. Linda, additional, Maes, Christa, additional, Mannstadt, Michael, additional, Manolagas, Stavros, additional, Marcus, Robert, additional, Maridas, David E., additional, Marie, Pierre J., additional, Marini, Francesca, additional, Markovac, Jasna, additional, Martin, T. John, additional, Matthews, Brya G., additional, Maurizi, Antonio, additional, Mirfakhraee, Sasan, additional, Moe, Sharon M., additional, Monroe, David G., additional, Moreira, Carolina A., additional, Müller, Ralph, additional, Musson, David S., additional, Nakatani, Teruyo, additional, Naot, Dorit, additional, Napoli, Nicola, additional, Naveh-Many, Tally, additional, Nemeth, Edward F., additional, Nickolas, Thomas L., additional, Ominsky, Michael S., additional, Ono, Noriaki, additional, Ornitz, David M., additional, Partridge, Nicola C., additional, Patel, Vihitaben S., additional, Pike, J. Wesley, additional, Pilbeam, Carol, additional, Plum, Lori, additional, Potts, John T., additional, Puzas, J. Edward, additional, Rachner, Tilman D., additional, Rakian, Audrey, additional, Rakian, Rubie, additional, Renthal, Nora E., additional, Rhoades (Sterling), Julie A., additional, Riminucci, Mara, additional, Roberts, Scott J., additional, Robey, Pamela Gehron, additional, Rogers, Michael J., additional, Roodman, G. David, additional, Rosen, Clifford J., additional, Rosen, Vicki, additional, Rowe, David W., additional, Rubin, Janet, additional, Rubin, Clinton T., additional, Schlingmann, Karl P., additional, Seeman, Ego, additional, Seibel, Markus J., additional, Sempos, Chris, additional, Shoback, Dolores M., additional, Silve, Caroline, additional, Silver, Justin, additional, Sims, Natalie A., additional, Singer, Frederick R., additional, Stains, Joseph P., additional, Stegen, Steve, additional, Stern, Paula H., additional, Tabacco, Gaia, additional, Takacs, Istvan, additional, Takahashi, Naoyuki, additional, Tay, Donovan, additional, Teti, Anna, additional, Thakker, Rajesh V., additional, Tomlinson, Ryan E., additional, Tonelli, Francesco, additional, Towler, Dwight A., additional, Tsourdi, Elena, additional, Tu, Chia-Ling, additional, Udagawa, Nobuyuki, additional, Weaver, Connie M., additional, Wein, Marc N., additional, Weinstein, Lee S., additional, Weis, MaryAnn, additional, Whyte, Michael P., additional, Williams, Bart O., additional, Xu, Xin, additional, Yakar, Shoshana, additional, Yang, Yingzi, additional, Zanotti, Stefano, additional, and Zhou, Hong, additional

Published
2020
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46. An Improved Sleep Posture Recognition Based on Force Sensing Resistors

Author

Huang, Yung-Fa, Hsu, Yi-Hsiang, Chang, Chia-Chi, Liu, Shing-Hong, Wei, Ching-Chuan, Yao, Tsung-Yu, Lin, Chuan-Bi, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Nguyen, Ngoc Thanh, editor, Tojo, Satoshi, editor, Nguyen, Le Minh, editor, and Trawiński, Bogdan, editor

Published
2017
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48. The association of obesity and coronary artery disease genes with response to SSRIs treatment in major depression

Author

Amare, Azmeraw T., Schubert, Klaus Oliver, Tekola-Ayele, Fasil, Hsu, Yi-Hsiang, Sangkuhl, Katrin, Jenkins, Gregory, Whaley, Ryan M., Barman, Poulami, Batzler, Anthony, Altman, Russ B., Arolt, Volker, Brockmöller, Jürgen, Chen, Chia-Hui, Domschke, Katharina, Hall-Flavin, Daniel K., Hong, Chen-Jee, Illi, Ari, Ji, Yuan, Kampman, Olli, Kinoshita, Toshihiko, Leinonen, Esa, Liou, Ying-Jay, Mushiroda, Taisei, Nonen, Shinpei, Skime, Michelle K., Wang, Liewei, Kato, Masaki, Liu, Yu-Li, Praphanphoj, Verayuth, Stingl, Julia C., Bobo, William V., Tsai, Shih-Jen, Kubo, Michiaki, Klein, Teri E., Weinshilboum, Richard M., Biernacka, Joanna M., and Baune, Bernhard T.

Published
2019
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