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1. Petrarch Among Editions, Readers and Postillators

Author: Loredana Chines
Subjects: petrarch, incunabula, sixteenth-century editions, marginal notes, annotations, Bibliography. Library science. Information resources
Abstract: This work delves into the papers of the most significant and rare Petrarchian editions - including incunabula and cinquecentine - contained in the precious book collection of Jacopo Loris Bononi preserved in Castiglione del Terziere. It investigates the peculiar characteristics and cultural contexts that gave rise to the individual prints, the possession notes and the heterogeneous typology of annotations and marginal notes found in the volumes, opening up unprecedented scenarios of responsive readers interacting in various ways with the text.
Published: 2024
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2. Noncoding variants alter GATA2 expression in rhombomere 4 motor neurons and cause dominant hereditary congenital facial paresis

Author: Tenney, Alan P, Di Gioia, Silvio Alessandro, Webb, Bryn D, Chan, Wai-Man, de Boer, Elke, Garnai, Sarah J, Barry, Brenda J, Ray, Tammy, Kosicki, Michael, Robson, Caroline D, Zhang, Zhongyang, Collins, Thomas E, Gelber, Alon, Pratt, Brandon M, Fujiwara, Yuko, Varshney, Arushi, Lek, Monkol, Warburton, Peter E, Van Ryzin, Carol, Lehky, Tanya J, Zalewski, Christopher, King, Kelly A, Brewer, Carmen C, Thurm, Audrey, Snow, Joseph, Facio, Flavia M, Narisu, Narisu, Bonnycastle, Lori L, Swift, Amy, Chines, Peter S, Bell, Jessica L, Mohan, Suresh, Whitman, Mary C, Staffieri, Sandra E, Elder, James E, Demer, Joseph L, Torres, Alcy, Rachid, Elza, Al-Haddad, Christiane, Boustany, Rose-Mary, Mackey, David A, Brady, Angela F, Fenollar-Cortés, María, Fradin, Melanie, Kleefstra, Tjitske, Padberg, George W, Raskin, Salmo, Sato, Mario Teruo, Orkin, Stuart H, Parker, Stephen CJ, Hadlock, Tessa A, Vissers, Lisenka ELM, van Bokhoven, Hans, Jabs, Ethylin Wang, Collins, Francis S, Pennacchio, Len A, Manoli, Irini, and Engle, Elizabeth C
Subjects: Biological Sciences, Genetics, 2.1 Biological and endogenous factors, Animals, Mice, Facial Paralysis, GATA2 Transcription Factor, Motor Neurons, Neurogenesis, Neurons, Efferent, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract: Hereditary congenital facial paresis type 1 (HCFP1) is an autosomal dominant disorder of absent or limited facial movement that maps to chromosome 3q21-q22 and is hypothesized to result from facial branchial motor neuron (FBMN) maldevelopment. In the present study, we report that HCFP1 results from heterozygous duplications within a neuron-specific GATA2 regulatory region that includes two enhancers and one silencer, and from noncoding single-nucleotide variants (SNVs) within the silencer. Some SNVs impair binding of NR2F1 to the silencer in vitro and in vivo and attenuate in vivo enhancer reporter expression in FBMNs. Gata2 and its effector Gata3 are essential for inner-ear efferent neuron (IEE) but not FBMN development. A humanized HCFP1 mouse model extends Gata2 expression, favors the formation of IEEs over FBMNs and is rescued by conditional loss of Gata3. These findings highlight the importance of temporal gene regulation in development and of noncoding variation in rare mendelian disease.
Published: 2023

3. The Flexible Plasma Trap (FPT) for the production of overdense plasmas

Author: Gammino, S., Celona, L., Mascali, D., Castro, G., Torrisi, G., Neri, L., Mazzaglia, M., Sorbello, G., Leonardi, O., Allegra, L., Calabrese, G., Chines, F., Gallo, G., and Passerello, S.
Subjects: Physics - Accelerator Physics
Abstract: Electron Cyclotron Resonance Ion Sources are currently the most efficient ion sources among those used in facilities dedicated to nuclear physics. The need for a more flexible magnetic field and RF injection system suggested to design and develop a different type of plasma trap, named Flexible Plasma Trap (FPT). The magnetic field of FPT is generated by means of three coils while microwaves in the range 4-7 GHz can be injected by three different inputs, one placed along the axis and two placed radially. FPT can work in different plasma heating schemes so it will be an ideal tool for studies of plasma and multidisciplinary physics. Moreover, a microwave launcher has been designed and installed to the FPT for launching microwaves with a variable tilt angle with respect to the magnetic field. This paper describes the characteristics of the FPT along with the preliminary results of plasma diagnostics.
Published: 2022
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4. Potential Role of Biofeedback Visual Training in High-Speed Motorbike Drivers

Author: Vingolo EM, Chines C, Tanassi C, Charte A, Cecchinello L, and Campigotto M
Subjects: microperimetry, fixation, biofeedback, motorcycle, high speed drivers, Ophthalmology, RE1-994
Abstract: Enzo Maria Vingolo,1 Carmelo Chines,2 Cesare Tanassi,3 Angel Charte,4 Lucio Cecchinello,5 Mauro Campigotto3 1University Sapienza of Rome, Department of Ophthalmology Polo Pontino Ospedale A. Fiorini, Terracina, Italy; 2Ophthalmology, Oculista Italiano Journal, Catania, Italy; 3Nidek Inc, Fremont, CA, USA; 4Medicine, Universitat de Barcelona, Barcelona, Catalunya, Spain; 5LCR Honda Motor, Tokyo, JapanCorrespondence: Enzo Maria Vingolo, University “Sapienza” of Rome, Polo Pontino Italy, Department of Ophthalmology, Ospedale A. Fiorini, Terracina, 04120, Italy, Email enzomaria.vingolo@uniroma1.itPurpose: In several sports, appropriate training strategies remain a challenge for athletes and coaches, with the goal of improving performance. Extensive research has proposed several technical tools for obtaining parametric evaluations before competition in real life. This study aimed to assess whether some retinal performances might be improved using psychophysical techniques in health professionals involved in motorcycle sports (FIM MotoE).Methods: Two MotoE drivers were screened at baseline using complete ophthalmological examinations and evaluation of retinal reaction times, followed by a biofeedback training program. After 4 months of training, the subjects underwent a control visit using the same protocol as the baseline.Results: Central reaction time was shorter for 75% of drivers, with a consistent reduction (mean value of 20%). The peripheral reaction time showed an increasing trend after visual training. In both drivers, fixation stability improved dramatically (in 30% increments).Conclusion: The potential role of advanced technology was applied to high-speed drivers. Our results may be due to an attentional shift from the peripheral retina to the central retina during training. In our opinion, training potentiates the most useful pathways at the expense of less involved retinal and cortical areas, thus improving driving abilities and safety.Keywords: microperimetry, fixation, biofeedback, motorcycle, high-speed drivers
Published: 2023

5. Mitochondrial DNA is a target of HBV integration

Author: Domenico Giosa, Daniele Lombardo, Cristina Musolino, Valeria Chines, Giuseppina Raffa, Francesca Casuscelli di Tocco, Deborah D’Aliberti, Giuseppe Caminiti, Carlo Saitta, Angela Alibrandi, Riccardo Aiese Cigliano, Orazio Romeo, Giuseppe Navarra, Giovanni Raimondo, and Teresa Pollicino
Subjects: Biology (General), QH301-705.5
Abstract: Abstract Hepatitis B virus (HBV) may integrate into the genome of infected cells and contribute to hepatocarcinogenesis. However, the role of HBV integration in hepatocellular carcinoma (HCC) development remains unclear. In this study, we apply a high-throughput HBV integration sequencing approach that allows sensitive identification of HBV integration sites and enumeration of integration clones. We identify 3339 HBV integration sites in paired tumour and non-tumour tissue samples from 7 patients with HCC. We detect 2107 clonally expanded integrations (1817 in tumour and 290 in non-tumour tissues), and a significant enrichment of clonal HBV integrations in mitochondrial DNA (mtDNA) preferentially occurring in the oxidative phosphorylation genes (OXPHOS) and D-loop region. We also find that HBV RNA sequences are imported into the mitochondria of hepatoma cells with the involvement of polynucleotide phosphorylase (PNPASE), and that HBV RNA might have a role in the process of HBV integration into mtDNA. Our results suggest a potential mechanism by which HBV integration may contribute to HCC development.
Published: 2023
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6. Mitochondrial DNA is a target of HBV integration

Author: Giosa, Domenico, Lombardo, Daniele, Musolino, Cristina, Chines, Valeria, Raffa, Giuseppina, Casuscelli di Tocco, Francesca, D’Aliberti, Deborah, Caminiti, Giuseppe, Saitta, Carlo, Alibrandi, Angela, Aiese Cigliano, Riccardo, Romeo, Orazio, Navarra, Giuseppe, Raimondo, Giovanni, and Pollicino, Teresa
Published: 2023
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7. Evaluation of common genetic variants in 82 candidate genes as risk factors for neural tube defects

Author: Pangilinan Faith, Molloy Anne M, Mills James L, Troendle James F, Parle-McDermott Anne, Signore Caroline, O’Leary Valerie B, Chines Peter, Seay Jessica M, Geiler-Samerotte Kerry, Mitchell Adam, VanderMeer Julia E, Krebs Kristine M, Sanchez Angelica, Cornman-Homonoff Joshua, Stone Nicole, Conley Mary, Kirke Peadar N, Shane Barry, Scott John M, and Brody Lawrence C
Subjects: Neural tube defects, Spina bifida, Folic acid, One-carbon metabolism, Candidate gene, Internal medicine, RC31-1245, Genetics, QH426-470
Abstract: Abstract Background Neural tube defects (NTDs) are common birth defects (~1 in 1000 pregnancies in the US and Europe) that have complex origins, including environmental and genetic factors. A low level of maternal folate is one well-established risk factor, with maternal periconceptional folic acid supplementation reducing the occurrence of NTD pregnancies by 50-70%. Gene variants in the folate metabolic pathway (e.g., MTHFR rs1801133 (677 C > T) and MTHFD1 rs2236225 (R653Q)) have been found to increase NTD risk. We hypothesized that variants in additional folate/B12 pathway genes contribute to NTD risk. Methods A tagSNP approach was used to screen common variation in 82 candidate genes selected from the folate/B12 pathway and NTD mouse models. We initially genotyped polymorphisms in 320 Irish triads (NTD cases and their parents), including 301 cases and 341 Irish controls to perform case–control and family based association tests. Significantly associated polymorphisms were genotyped in a secondary set of 250 families that included 229 cases and 658 controls. The combined results for 1441 SNPs were used in a joint analysis to test for case and maternal effects. Results Nearly 70 SNPs in 30 genes were found to be associated with NTDs at the p MFTC, CDKN2A, ADA, PEMT, CUBN, GART, DNMT3A, MTHFD1 and T (Brachyury)) and included the known NTD risk factor MTHFD1 R653Q (rs2236225). The single strongest signal was observed in a new candidate, MFTC rs17803441 (OR = 1.61 [1.23-2.08], p = 0.0003 for the minor allele). Though nominally significant, these associations did not remain significant after correction for multiple hypothesis testing. Conclusions To our knowledge, with respect to sample size and scope of evaluation of candidate polymorphisms, this is the largest NTD genetic association study reported to date. The scale of the study and the stringency of correction are likely to have contributed to real associations failing to survive correction. We have produced a ranked list of variants with the strongest association signals. Variants in the highest rank of associations are likely to include true associations and should be high priority candidates for further study of NTD risk.
Published: 2012
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8. Validation of the Surrogate Threshold Effect for Change in Bone Mineral Density as a Surrogate Endpoint for Fracture Outcomes: The FNIH‐ASBMR SABRE Project

Author: Eastell, Richard, Vittinghoff, Eric, Lui, Li‐Yung, McCulloch, Charles E, Pavo, Imre, Chines, Arkadi, Khosla, Sundeep, Cauley, Jane A, Mitlak, Bruce, Bauer, Douglas C, Bouxsein, Mary, and Black, Dennis M
Subjects: Biomedical and Clinical Sciences, Clinical Sciences, Physical Injury - Accidents and Adverse Effects, Osteoporosis, Clinical Trials and Supportive Activities, Clinical Research, 8.4 Research design and methodologies (health services), Health and social care services research, Musculoskeletal, Biomarkers, Bone Density, Bone Density Conservation Agents, Diphosphonates, Fractures, Bone, Humans, BONE MINERAL DENSITY, FRACTURE, SURROGATE, BISPHOSPHONATES, SELECTIVE ESTROGEN RECEPTOR MODULATORS, Biological Sciences, Engineering, Medical and Health Sciences, Anatomy & Morphology, Biological sciences, Biomedical and clinical sciences
Abstract: The surrogate threshold effect (STE) is defined as the minimum treatment effect on a surrogate that is reliably predictive of a treatment effect on the clinical outcome. It provides a framework for implementing a clinical trial with a surrogate endpoint. The aim of this study was to update our previous analysis by validating the STE for change in total hip (TH) BMD as a surrogate for fracture risk reduction; the novelty of this study was this validation. To do so, we used individual patient data from 61,415 participants in 16 RCTs that evaluated bisphosphonates (nine trials), selective estrogen receptor modulators (four trials), denosumab (one trial), odanacatib (one trial), and teriparatide (one trial) to estimate trial-specific treatment effects on TH BMD and all, vertebral, hip, and nonvertebral fractures. We then conducted a random effects meta-regression of the log relative fracture risk reduction against 24-month change in TH BMD, and computed the STE as the intersection of the upper 95% prediction limit of this regression with the line of no fracture reduction. We validated the STE by checking whether the number of fractures in each trial provided 80% power and determining what proportion of trials with BMD changes ≥ STE reported significant reductions in fracture risk. We applied this analysis to (i) the trials on which we estimated the STE; and (ii) trials on which we did not estimate the STE. We found that the STEs for all, vertebral, hip, and nonvertebral fractures were 1.83%, 1.42%, 3.18%, and 2.13%, respectively. Among trials used to estimate STE, 27 of 28 were adequately powered, showed BMD effects exceeding the STE, and showed significant reductions in fracture risk. Among the validation set of 11 trials, 10 met these criteria. Thus STE differs by fracture type and has been validated in trials not used to develop the approach. © 2021 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).
Published: 2020

9. A Randomized, Placebo-Controlled Study of Romosozumab for the Treatment of Hip Fractures.

Author: Karachalios, Theofilos, Nowak, Lauren, Sancheti, Parag, Poolman, Rudolf, Caminis, John, Daizadeh, Nadia, Dent-Acosta, Ricardo, Egbuna, Ogo, Chines, Arkadi, Maddox, Judy, Grauer, Andreas, Bhandari, Mohit, Schemitsch, Emil, and Miclau, Theodore
Subjects: Aged, Aged, 80 and over, Antibodies, Monoclonal, Bone Density Conservation Agents, Double-Blind Method, Female, Hip Fractures, Humans, Injections, Subcutaneous, Male, Middle Aged
Abstract: BACKGROUND: Romosozumab is a bone-forming antibody that increases bone formation and decreases bone resorption. We conducted a double-blinded, randomized, phase-2, dose-finding trial to evaluate the effect of romosozumab on the clinical outcomes of open reduction and internal fixation of intertrochanteric or femoral neck hip fractures. METHODS: Patients (55 to 94 years old) were randomized 2:3:3:3 to receive 3 subcutaneous injections of romosozumab (70, 140, or 210 mg) or a placebo postoperatively on day 1 and weeks 2, 6, and 12. The primary end point was the difference in the mean timed Up & Go (TUG) score over weeks 6 to 20 for romosozumab versus placebo. Additional end points included the time to radiographic evidence of healing and the score on the Radiographic Union Scale for Hip (RUSH). RESULTS: A total of 332 patients were randomized: 243 to receive romosozumab (70 mg, n = 60; 140 mg, n = 93; and 210 mg, n = 90) and 89 to receive a placebo. Although TUG scores improved during the study, they did not differ significantly between the romosozumab and placebo groups over weeks 6 to 20 (p = 0.198). The median time to radiographic evidence of healing was 16.4 to 16.9 weeks across treatment groups. The RUSH scores improved over time across treatment groups but did not differ significantly between the romosozumab and placebo groups. The overall safety and tolerability profile of romosozumab was comparable with that of the placebo. CONCLUSIONS: Romosozumab did not improve the fracture-healing-related clinical and radiographic outcomes in the study population. LEVEL OF EVIDENCE: Therapeutic Level I. See Instructions for Authors for a complete description of levels of evidence.
Published: 2020

10. A Randomized, Placebo-Controlled Study of Romosozumab for the Treatment of Hip Fractures

Author: Schemitsch, Emil H, Miclau, Theodore, Karachalios, Theofilos, Nowak, Lauren L, Sancheti, Parag, Poolman, Rudolf W, Caminis, John, Daizadeh, Nadia, Dent-Acosta, Ricardo E, Egbuna, Ogo, Chines, Arkadi, Maddox, Judy, Grauer, Andreas, and Bhandari, Mohit
Subjects: Clinical Research, Clinical Trials and Supportive Activities, Osteoporosis, Evaluation of treatments and therapeutic interventions, 6.1 Pharmaceuticals, Musculoskeletal, Aged, Aged, 80 and over, Antibodies, Monoclonal, Bone Density Conservation Agents, Double-Blind Method, Female, Hip Fractures, Humans, Injections, Subcutaneous, Male, Middle Aged, Biomedical Engineering, Clinical Sciences, Orthopedics
Abstract: BackgroundRomosozumab is a bone-forming antibody that increases bone formation and decreases bone resorption. We conducted a double-blinded, randomized, phase-2, dose-finding trial to evaluate the effect of romosozumab on the clinical outcomes of open reduction and internal fixation of intertrochanteric or femoral neck hip fractures.MethodsPatients (55 to 94 years old) were randomized 2:3:3:3 to receive 3 subcutaneous injections of romosozumab (70, 140, or 210 mg) or a placebo postoperatively on day 1 and weeks 2, 6, and 12. The primary end point was the difference in the mean timed "Up & Go" (TUG) score over weeks 6 to 20 for romosozumab versus placebo. Additional end points included the time to radiographic evidence of healing and the score on the Radiographic Union Scale for Hip (RUSH).ResultsA total of 332 patients were randomized: 243 to receive romosozumab (70 mg, n = 60; 140 mg, n = 93; and 210 mg, n = 90) and 89 to receive a placebo. Although TUG scores improved during the study, they did not differ significantly between the romosozumab and placebo groups over weeks 6 to 20 (p = 0.198). The median time to radiographic evidence of healing was 16.4 to 16.9 weeks across treatment groups. The RUSH scores improved over time across treatment groups but did not differ significantly between the romosozumab and placebo groups. The overall safety and tolerability profile of romosozumab was comparable with that of the placebo.ConclusionsRomosozumab did not improve the fracture-healing-related clinical and radiographic outcomes in the study population.Level of evidenceTherapeutic Level I. See Instructions for Authors for a complete description of levels of evidence.
Published: 2020

11. Assessing Genomic Mutations in SARS-CoV-2: Potential Resistance to Antiviral Drugs in Viral Populations from Untreated COVID-19 Patients

Author: Daniele Lombardo, Cristina Musolino, Valeria Chines, Giuseppe Caminiti, Claudia Palermo, Irene Cacciola, Giuseppina Raffa, and Teresa Pollicino
Subjects: SARS-CoV-2, COVID-19, coronaviruses, antiviral drugs, antiviral therapy, antiviral drug resistance, Biology (General), QH301-705.5
Abstract: Naturally occurring SARS-CoV-2 variants mutated in genomic regions targeted by antiviral drugs have not been extensively studied. This study investigated the potential of the RNA-dependent RNA polymerase (RdRp) complex subunits and non-structural protein (Nsp)5 of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) to accumulate natural mutations that could affect the efficacy of antiviral drugs. To this aim, SARS-CoV-2 genomic sequences isolated from 4155 drug-naive individuals from southern Italy were analyzed using the Illumina MiSeq platform. Sequencing of the 4155 samples showed the following viral variant distribution: 71.2% Delta, 22.2% Omicron, and 6.4% Alpha. In the Nsp12 sequences, we found 84 amino acid substitutions. The most common one was P323L, detected in 3777/4155 (91%) samples, with 2906/3777 (69.9%) also showing the G671S substitution in combination. Additionally, we identified 28, 14, and 24 different amino acid substitutions in the Nsp5, Nsp7, and Nsp8 genomic regions, respectively. Of note, the V186F and A191V substitutions, affecting residues adjacent to the active site of Nsp5 (the target of the antiviral drug Paxlovid), were found in 157/4155 (3.8%) and 3/4155 (0.07%) samples, respectively. In conclusion, the RdRp complex subunits and the Nsp5 genomic region exhibit susceptibility to accumulating natural mutations. This susceptibility poses a potential risk to the efficacy of antiviral drugs, as these mutations may compromise the drug ability to inhibit viral replication
Published: 2023
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12. Erratum: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.

Author: Flannick, Jason, Fuchsberger, Christian, Mahajan, Anubha, Teslovich, Tanya M, Agarwala, Vineeta, Gaulton, Kyle J, Caulkins, Lizz, Koesterer, Ryan, Ma, Clement, Moutsianas, Loukas, McCarthy, Davis J, Rivas, Manuel A, Perry, John RB, Sim, Xueling, Blackwell, Thomas W, Robertson, Neil R, Rayner, N William, Cingolani, Pablo, Locke, Adam E, Tajes, Juan Fernandez, Highland, Heather M, Dupuis, Josee, Chines, Peter S, Lindgren, Cecilia M, Hartl, Christopher, Jackson, Anne U, Chen, Han, Huyghe, Jeroen R, van de Bunt, Martijn, Pearson, Richard D, Kumar, Ashish, Müller-Nurasyid, Martina, Grarup, Niels, Stringham, Heather M, Gamazon, Eric R, Lee, Jaehoon, Chen, Yuhui, Scott, Robert A, Below, Jennifer E, Chen, Peng, Huang, Jinyan, Go, Min Jin, Stitzel, Michael L, Pasko, Dorota, Parker, Stephen CJ, Varga, Tibor V, Green, Todd, Beer, Nicola L, Day-Williams, Aaron G, Ferreira, Teresa, Fingerlin, Tasha, Horikoshi, Momoko, Hu, Cheng, Huh, Iksoo, Ikram, Mohammad Kamran, Kim, Bong-Jo, Kim, Yongkang, Kim, Young Jin, Kwon, Min-Seok, Lee, Juyoung, Lee, Selyeong, Lin, Keng-Han, Maxwell, Taylor J, Nagai, Yoshihiko, Wang, Xu, Welch, Ryan P, Yoon, Joon, Zhang, Weihua, Barzilai, Nir, Voight, Benjamin F, Han, Bok-Ghee, Jenkinson, Christopher P, Kuulasmaa, Teemu, Kuusisto, Johanna, Manning, Alisa, Ng, Maggie CY, Palmer, Nicholette D, Balkau, Beverley, Stančáková, Alena, Abboud, Hanna E, Boeing, Heiner, Giedraitis, Vilmantas, Prabhakaran, Dorairaj, Gottesman, Omri, Scott, James, Carey, Jason, Kwan, Phoenix, Grant, George, Smith, Joshua D, Neale, Benjamin M, Purcell, Shaun, Butterworth, Adam S, Howson, Joanna MM, Lee, Heung Man, Lu, Yingchang, Kwak, Soo-Heon, Zhao, Wei, Danesh, John, and Lam, Vincent KL
Abstract: This corrects the article DOI: 10.1038/sdata.2017.179.
Published: 2018

13. Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees

Author: Jun, Goo, Manning, Alisa, Almeida, Marcio, Zawistowski, Matthew, Wood, Andrew R, Teslovich, Tanya M, Fuchsberger, Christian, Feng, Shuang, Cingolani, Pablo, Gaulton, Kyle J, Dyer, Thomas, Blackwell, Thomas W, Chen, Han, Chines, Peter S, Choi, Sungkyoung, Churchhouse, Claire, Fontanillas, Pierre, King, Ryan, Lee, SungYoung, Lincoln, Stephen E, Trubetskoy, Vasily, DePristo, Mark, Fingerlin, Tasha, Grossman, Robert, Grundstad, Jason, Heath, Alison, Kim, Jayoun, Kim, Young Jin, Laramie, Jason, Lee, Jaehoon, Li, Heng, Liu, Xuanyao, Livne, Oren, Locke, Adam E, Maller, Julian, Mazur, Alexander, Morris, Andrew P, Pollin, Toni I, Ragona, Derek, Reich, David, Rivas, Manuel A, Scott, Laura J, Sim, Xueling, Tearle, Rick G, Teo, Yik Ying, Williams, Amy L, Zöllner, Sebastian, Curran, Joanne E, Peralta, Juan, Akolkar, Beena, Bell, Graeme I, Burtt, Noël P, Cox, Nancy J, Florez, Jose C, Hanis, Craig L, McKeon, Catherine, Mohlke, Karen L, Seielstad, Mark, Wilson, James G, Atzmon, Gil, Below, Jennifer E, Dupuis, Josée, Nicolae, Dan L, Lehman, Donna, Park, Taesung, Won, Sungho, Sladek, Robert, Altshuler, David, McCarthy, Mark I, Duggirala, Ravindranath, Boehnke, Michael, Frayling, Timothy M, Abecasis, Gonçalo R, and Blangero, John
Subjects: Diabetes, Genetics, Human Genome, Clinical Research, Obesity, Genetic Testing, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Diabetes Mellitus, Type 2, Family Health, Female, Gene Frequency, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Genotype, Humans, Male, Mexican Americans, Pedigree, Phenotype, Quantitative Trait Loci, Whole Genome Sequencing, genetics, sequencing, type 2 diabetes, eQTL, rare variants
Abstract: A major challenge in evaluating the contribution of rare variants to complex disease is identifying enough copies of the rare alleles to permit informative statistical analysis. To investigate the contribution of rare variants to the risk of type 2 diabetes (T2D) and related traits, we performed deep whole-genome analysis of 1,034 members of 20 large Mexican-American families with high prevalence of T2D. If rare variants of large effect accounted for much of the diabetes risk in these families, our experiment was powered to detect association. Using gene expression data on 21,677 transcripts for 643 pedigree members, we identified evidence for large-effect rare-variant cis-expression quantitative trait loci that could not be detected in population studies, validating our approach. However, we did not identify any rare variants of large effect associated with T2D, or the related traits of fasting glucose and insulin, suggesting that large-effect rare variants account for only a modest fraction of the genetic risk of these traits in this sample of families. Reliable identification of large-effect rare variants will require larger samples of extended pedigrees or different study designs that further enrich for such variants.
Published: 2018

14. Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.

Author: Flannick, Jason, Fuchsberger, Christian, Mahajan, Anubha, Teslovich, Tanya M, Agarwala, Vineeta, Gaulton, Kyle J, Caulkins, Lizz, Koesterer, Ryan, Ma, Clement, Moutsianas, Loukas, McCarthy, Davis J, Rivas, Manuel A, Perry, John RB, Sim, Xueling, Blackwell, Thomas W, Robertson, Neil R, Rayner, N William, Cingolani, Pablo, Locke, Adam E, Tajes, Juan Fernandez, Highland, Heather M, Dupuis, Josee, Chines, Peter S, Lindgren, Cecilia M, Hartl, Christopher, Jackson, Anne U, Chen, Han, Huyghe, Jeroen R, van de Bunt, Martijn, Pearson, Richard D, Kumar, Ashish, Müller-Nurasyid, Martina, Grarup, Niels, Stringham, Heather M, Gamazon, Eric R, Lee, Jaehoon, Chen, Yuhui, Scott, Robert A, Below, Jennifer E, Chen, Peng, Huang, Jinyan, Go, Min Jin, Stitzel, Michael L, Pasko, Dorota, Parker, Stephen CJ, Varga, Tibor V, Green, Todd, Beer, Nicola L, Day-Williams, Aaron G, Ferreira, Teresa, Fingerlin, Tasha, Horikoshi, Momoko, Hu, Cheng, Huh, Iksoo, Ikram, Mohammad Kamran, Kim, Bong-Jo, Kim, Yongkang, Kim, Young Jin, Kwon, Min-Seok, Lee, Juyoung, Lee, Selyeong, Lin, Keng-Han, Maxwell, Taylor J, Nagai, Yoshihiko, Wang, Xu, Welch, Ryan P, Yoon, Joon, Zhang, Weihua, Barzilai, Nir, Voight, Benjamin F, Han, Bok-Ghee, Jenkinson, Christopher P, Kuulasmaa, Teemu, Kuusisto, Johanna, Manning, Alisa, Ng, Maggie CY, Palmer, Nicholette D, Balkau, Beverley, Stančáková, Alena, Abboud, Hanna E, Boeing, Heiner, Giedraitis, Vilmantas, Prabhakaran, Dorairaj, Gottesman, Omri, Scott, James, Carey, Jason, Kwan, Phoenix, Grant, George, Smith, Joshua D, Neale, Benjamin M, Purcell, Shaun, Butterworth, Adam S, Howson, Joanna MM, Lee, Heung Man, Lu, Yingchang, Kwak, Soo-Heon, Zhao, Wei, Danesh, John, and Lam, Vincent KL
Subjects: Humans, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Genetic Variation, Diabetes, Human Genome, Genetics, 2.1 Biological and endogenous factors, Metabolic and endocrine
Abstract: To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.
Published: 2017

15. An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans

Author: Scott, Robert A, Scott, Laura J, Mägi, Reedik, Marullo, Letizia, Gaulton, Kyle J, Kaakinen, Marika, Pervjakova, Natalia, Pers, Tune H, Johnson, Andrew D, Eicher, John D, Jackson, Anne U, Ferreira, Teresa, Lee, Yeji, Ma, Clement, Steinthorsdottir, Valgerdur, Thorleifsson, Gudmar, Qi, Lu, Van Zuydam, Natalie R, Mahajan, Anubha, Chen, Han, Almgren, Peter, Voight, Ben F, Grallert, Harald, Müller-Nurasyid, Martina, Ried, Janina S, Rayner, William N, Robertson, Neil, Karssen, Lennart C, van Leeuwen, Elisabeth M, Willems, Sara M, Fuchsberger, Christian, Kwan, Phoenix, Teslovich, Tanya M, Chanda, Pritam, Li, Man, Lu, Yingchang, Dina, Christian, Thuillier, Dorothee, Yengo, Loic, Jiang, Longda, Sparso, Thomas, Kestler, Hans A, Chheda, Himanshu, Eisele, Lewin, Gustafsson, Stefan, Frånberg, Mattias, Strawbridge, Rona J, Benediktsson, Rafn, Hreidarsson, Astradur B, Kong, Augustine, Sigurðsson, Gunnar, Kerrison, Nicola D, Luan, Jian'an, Liang, Liming, Meitinger, Thomas, Roden, Michael, Thorand, Barbara, Esko, Tõnu, Mihailov, Evelin, Fox, Caroline, Liu, Ching-Ti, Rybin, Denis, Isomaa, Bo, Lyssenko, Valeriya, Tuomi, Tiinamaija, Couper, David J, Pankow, James S, Grarup, Niels, Have, Christian T, Jørgensen, Marit E, Jørgensen, Torben, Linneberg, Allan, Cornelis, Marilyn C, van Dam, Rob M, Hunter, David J, Kraft, Peter, Sun, Qi, Edkins, Sarah, Owen, Katharine R, Perry, John RB, Wood, Andrew R, Zeggini, Eleftheria, Tajes-Fernandes, Juan, Abecasis, Goncalo R, Bonnycastle, Lori L, Chines, Peter S, Stringham, Heather M, Koistinen, Heikki A, Kinnunen, Leena, Sennblad, Bengt, Mühleisen, Thomas W, Nöthen, Markus M, Pechlivanis, Sonali, Baldassarre, Damiano, Gertow, Karl, Humphries, Steve E, Tremoli, Elena, Klopp, Norman, Meyer, Julia, and Steinbach, Gerald
Subjects: Human Genome, Diabetes, Obesity, Genetics, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Diabetes Mellitus, Type 2, Gene Expression Regulation, Genetic Variation, Genome-Wide Association Study, Humans, White People, DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Medical and Health Sciences, Endocrinology & Metabolism
Abstract: To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10-8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.
Published: 2017

16. A Low-Frequency Inactivating Akt2 Variant Enriched in the Finnish Population is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk.

Author: Manning, Alisa, Highland, Heather M, Gasser, Jessica, Sim, Xueling, Tukiainen, Taru, Fontanillas, Pierre, Grarup, Niels, Rivas, Manuel A, Mahajan, Anubha, Locke, Adam E, Cingolani, Pablo, Pers, Tune H, Viñuela, Ana, Brown, Andrew A, Wu, Ying, Flannick, Jason, Fuchsberger, Christian, Gamazon, Eric R, Gaulton, Kyle J, Im, Hae Kyung, Teslovich, Tanya M, Blackwell, Thomas W, Bork-Jensen, Jette, Burtt, Noël P, Chen, Yuhui, Green, Todd, Hartl, Christopher, Kang, Hyun Min, Kumar, Ashish, Ladenvall, Claes, Ma, Clement, Moutsianas, Loukas, Pearson, Richard D, Perry, John RB, Rayner, N William, Robertson, Neil R, Scott, Laura J, van de Bunt, Martijn, Eriksson, Johan G, Jula, Antti, Koskinen, Seppo, Lehtimäki, Terho, Palotie, Aarno, Raitakari, Olli T, Jacobs, Suzanne BR, Wessel, Jennifer, Chu, Audrey Y, Scott, Robert A, Goodarzi, Mark O, Blancher, Christine, Buck, Gemma, Buck, David, Chines, Peter S, Gabriel, Stacey, Gjesing, Anette P, Groves, Christopher J, Hollensted, Mette, Huyghe, Jeroen R, Jackson, Anne U, Jun, Goo, Justesen, Johanne Marie, Mangino, Massimo, Murphy, Jacquelyn, Neville, Matt, Onofrio, Robert, Small, Kerrin S, Stringham, Heather M, Trakalo, Joseph, Banks, Eric, Carey, Jason, Carneiro, Mauricio O, DePristo, Mark, Farjoun, Yossi, Fennell, Timothy, Goldstein, Jacqueline I, Grant, George, Hrabé de Angelis, Martin, Maguire, Jared, Neale, Benjamin M, Poplin, Ryan, Purcell, Shaun, Schwarzmayr, Thomas, Shakir, Khalid, Smith, Joshua D, Strom, Tim M, Wieland, Thomas, Lindstrom, Jaana, Brandslund, Ivan, Christensen, Cramer, Surdulescu, Gabriela L, Lakka, Timo A, Doney, Alex SF, Nilsson, Peter, Wareham, Nicholas J, Langenberg, Claudia, Varga, Tibor V, Franks, Paul W, Rolandsson, Olov, Rosengren, Anders H, and Farook, Vidya S
Subjects: Genetics, Diabetes, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Black or African American, Alleles, Asian People, Case-Control Studies, Diabetes Mellitus, Type 2, Fasting, Finland, Gene Frequency, Genetic Predisposition to Disease, Genotype, Hispanic or Latino, Humans, Insulin, Insulin Resistance, Odds Ratio, Proto-Oncogene Proteins c-akt, White People, Medical and Health Sciences, Endocrinology & Metabolism
Abstract: To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting plasma insulin (FI), a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in FI levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-h insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio 1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2.
Published: 2017

17. Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults.

Author: Graff, Mariaelisa, Scott, Robert A, Justice, Anne E, Young, Kristin L, Feitosa, Mary F, Barata, Llilda, Winkler, Thomas W, Chu, Audrey Y, Mahajan, Anubha, Hadley, David, Xue, Luting, Workalemahu, Tsegaselassie, Heard-Costa, Nancy L, den Hoed, Marcel, Ahluwalia, Tarunveer S, Qi, Qibin, Ngwa, Julius S, Renström, Frida, Quaye, Lydia, Eicher, John D, Hayes, James E, Cornelis, Marilyn, Kutalik, Zoltan, Lim, Elise, Luan, Jian'an, Huffman, Jennifer E, Zhang, Weihua, Zhao, Wei, Griffin, Paula J, Haller, Toomas, Ahmad, Shafqat, Marques-Vidal, Pedro M, Bien, Stephanie, Yengo, Loic, Teumer, Alexander, Smith, Albert Vernon, Kumari, Meena, Harder, Marie Neergaard, Justesen, Johanne Marie, Kleber, Marcus E, Hollensted, Mette, Lohman, Kurt, Rivera, Natalia V, Whitfield, John B, Zhao, Jing Hua, Stringham, Heather M, Lyytikäinen, Leo-Pekka, Huppertz, Charlotte, Willemsen, Gonneke, Peyrot, Wouter J, Wu, Ying, Kristiansson, Kati, Demirkan, Ayse, Fornage, Myriam, Hassinen, Maija, Bielak, Lawrence F, Cadby, Gemma, Tanaka, Toshiko, Mägi, Reedik, van der Most, Peter J, Jackson, Anne U, Bragg-Gresham, Jennifer L, Vitart, Veronique, Marten, Jonathan, Navarro, Pau, Bellis, Claire, Pasko, Dorota, Johansson, Åsa, Snitker, Søren, Cheng, Yu-Ching, Eriksson, Joel, Lim, Unhee, Aadahl, Mette, Adair, Linda S, Amin, Najaf, Balkau, Beverley, Auvinen, Juha, Beilby, John, Bergman, Richard N, Bergmann, Sven, Bertoni, Alain G, Blangero, John, Bonnefond, Amélie, Bonnycastle, Lori L, Borja, Judith B, Brage, Søren, Busonero, Fabio, Buyske, Steve, Campbell, Harry, Chines, Peter S, Collins, Francis S, Corre, Tanguy, Smith, George Davey, Delgado, Graciela E, Dueker, Nicole, Dörr, Marcus, Ebeling, Tapani, Eiriksdottir, Gudny, Esko, Tõnu, and Faul, Jessica D
Subjects: CHARGE Consortium, EPIC-InterAct Consortium, PAGE Consortium, Humans, Obesity, Genetic Predisposition to Disease, Body Mass Index, Waist-Hip Ratio, Exercise, Genotype, Female, Male, Adiposity, Waist Circumference, Genome-Wide Association Study, Epigenomics, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Genetics, Developmental Biology
Abstract: Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.
Published: 2017

18. Genetic Regulation of Adipose Gene Expression and Cardio-Metabolic Traits

Author: Civelek, Mete, Wu, Ying, Pan, Calvin, Raulerson, Chelsea K, Ko, Arthur, He, Aiqing, Tilford, Charles, Saleem, Niyas K, Stančáková, Alena, Scott, Laura J, Fuchsberger, Christian, Stringham, Heather M, Jackson, Anne U, Narisu, Narisu, Chines, Peter S, Small, Kerrin S, Kuusisto, Johanna, Parks, Brian W, Pajukanta, Päivi, Kirchgessner, Todd, Collins, Francis S, Gargalovic, Peter S, Boehnke, Michael, Laakso, Markku, Mohlke, Karen L, and Lusis, Aldons J
Subjects: Prevention, Genetics, Human Genome, Biotechnology, Aetiology, 2.1 Biological and endogenous factors, Aged, Animals, Cardiovascular Diseases, Databases, Genetic, Gene Expression Profiling, Gene Expression Regulation, Genome-Wide Association Study, Genotyping Techniques, Humans, Male, Metabolic Syndrome, Mice, Middle Aged, Nuclear Proteins, Phenotype, Quantitative Trait Loci, Reproducibility of Results, Subcutaneous Fat, Trans-Activators, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract: Subcutaneous adipose tissue stores excess lipids and maintains energy balance. We performed expression quantitative trait locus (eQTL) analyses by using abdominal subcutaneous adipose tissue of 770 extensively phenotyped participants of the METSIM study. We identified cis-eQTLs for 12,400 genes at a 1% false-discovery rate. Among an approximately 680 known genome-wide association study (GWAS) loci for cardio-metabolic traits, we identified 140 coincident cis-eQTLs at 109 GWAS loci, including 93 eQTLs not previously described. At 49 of these 140 eQTLs, gene expression was nominally associated (p < 0.05) with levels of the GWAS trait. The size of our dataset enabled identification of five loci associated (p < 5 × 10-8) with at least five genes located >5 Mb away. These trans-eQTL signals confirmed and extended the previously reported KLF14-mediated network to 55 target genes, validated the CIITA regulation of class II MHC genes, and identified ZNF800 as a candidate master regulator. Finally, we observed similar expression-clinical trait correlations of genes associated with GWAS loci in both humans and a panel of genetically diverse mice. These results provide candidate genes for further investigation of their potential roles in adipose biology and in regulating cardio-metabolic traits.
Published: 2017

19. New Antimicrobial Resistance Strategies: An Adaptive Resistance Network Conferring Reduced Glycopeptide Susceptibility in VISA

Author: Elvira Aguglia, Eleonora Chines, Stefania Stefani, and Viviana Cafiso
Subjects: VISA, CA-MRSA, omics, reduced glycopeptide susceptibility, adaptive resistance pathways, Therapeutics. Pharmacology, RM1-950
Abstract: Background: Vancomycin-intermediate Staphylococcus aureus (VISA) emerges typically in the healthcare-associated methicillin-resistant S. aureus and more rarely in community-acquired S. aureus (CA-MRSA). VISA is a serious concern for public health due to its association with persistent infections, the failure of vancomycin treatment, and poor clinical outcomes. Currently, the burden of VISA is somewhat high, even though vancomycin is the mainstay treatment for severe MRSA infections. The molecular mechanisms of reduced glycopeptide susceptibility in S. aureus are constantly under investigation but have still not yet been fully characterized. Methods: Our goal was to investigate the reduced glycopeptide susceptibility mechanisms emerging in a VISA CA-MRSA versus its vancomycin-susceptible (VSSA) CA-MRSA parents in a hospitalized patient undergoing glycopeptide treatment. Comparative integrated omics, Illumina MiSeq whole-genome sequencing (WGS), RNA-Seq, and bioinformatics were performed. Results: Through a comparison of VISA CA-MRSA vs. its VSSA CA-MRSA parent, mutational and transcriptomic adaptations were found in a pool of genes involved, directly or indirectly, in the biosynthesis of the glycopeptide target conferring or supporting the VISA phenotype, and its cross-resistance with daptomycin. This pool included key genes responsible for the biosynthesis of the peptidoglycan precursors, i.e., D-Ala, the D-Ala-D-Ala dipeptide termini of the pentapeptide, and its incorporation in the nascent pentapeptide, as key targets of the glycopeptide resistance. Furthermore, accessory glycopeptide-target genes involved in the pathways corroborated the key adaptations, and thus, supported the acquisition of the VISA phenotype i.e., transporters, nucleotide metabolism genes, and transcriptional regulators. Finally, transcriptional changes were also found in computationally predicted cis-acting small antisense RNA triggering genes related both to the key or accessory adaptive pathways. Conclusion: Our investigation describes an adaptive resistance pathway acquired under antimicrobial therapy conferring reduced glycopeptide susceptibility in a VISA CA-MRSA due to a comprehensive network of mutational and transcriptional adaptations in genes involved in pathways responsible for the biosynthesis of glycopeptide’s target or supporters of the key resistance path.
Published: 2023
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20. The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals.

Author: Ehret, Georg B, Ferreira, Teresa, Chasman, Daniel I, Jackson, Anne U, Schmidt, Ellen M, Johnson, Toby, Thorleifsson, Gudmar, Luan, Jian'an, Donnelly, Lousie A, Kanoni, Stavroula, Petersen, Ann-Kristin, Pihur, Vasyl, Strawbridge, Rona J, Shungin, Dmitry, Hughes, Maria F, Meirelles, Osorio, Kaakinen, Marika, Bouatia-Naji, Nabila, Kristiansson, Kati, Shah, Sonia, Kleber, Marcus E, Guo, Xiuqing, Lyytikäinen, Leo-Pekka, Fava, Cristiano, Eriksson, Niclas, Nolte, Ilja M, Magnusson, Patrik K, Salfati, Elias L, Rallidis, Loukianos S, Theusch, Elizabeth, Smith, Andrew JP, Folkersen, Lasse, Witkowska, Kate, Pers, Tune H, Joehanes, Roby, Kim, Stuart K, Lataniotis, Lazaros, Jansen, Rick, Johnson, Andrew D, Warren, Helen, Kim, Young Jin, Zhao, Wei, Wu, Ying, Tayo, Bamidele O, Bochud, Murielle, CHARGE-EchoGen consortium, CHARGE-HF consortium, Wellcome Trust Case Control Consortium, Absher, Devin, Adair, Linda S, Amin, Najaf, Arking, Dan E, Axelsson, Tomas, Baldassarre, Damiano, Balkau, Beverley, Bandinelli, Stefania, Barnes, Michael R, Barroso, Inês, Bevan, Stephen, Bis, Joshua C, Bjornsdottir, Gyda, Boehnke, Michael, Boerwinkle, Eric, Bonnycastle, Lori L, Boomsma, Dorret I, Bornstein, Stefan R, Brown, Morris J, Burnier, Michel, Cabrera, Claudia P, Chambers, John C, Chang, I-Shou, Cheng, Ching-Yu, Chines, Peter S, Chung, Ren-Hua, Collins, Francis S, Connell, John M, Döring, Angela, Dallongeville, Jean, Danesh, John, de Faire, Ulf, Delgado, Graciela, Dominiczak, Anna F, Doney, Alex SF, Drenos, Fotios, Edkins, Sarah, Eicher, John D, Elosua, Roberto, Enroth, Stefan, Erdmann, Jeanette, Eriksson, Per, Esko, Tonu, Evangelou, Evangelos, Evans, Alun, Fall, Tove, Farrall, Martin, Felix, Janine F, Ferrières, Jean, Ferrucci, Luigi, Fornage, Myriam, and Forrester, Terrence
Subjects: CHARGE-EchoGen consortium, CHARGE-HF consortium, Wellcome Trust Case Control Consortium, Cells, Cultured, Humans, Hypertension, Microarray Analysis, Blood Pressure, Polymorphism, Single Nucleotide, African Continental Ancestry Group, Asian Continental Ancestry Group, Genome-Wide Association Study, Cells, Cultured, Polymorphism, Single Nucleotide, Developmental Biology, Biological Sciences, Medical and Health Sciences
Abstract: To dissect the genetic architecture of blood pressure and assess effects on target organ damage, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry, and genotypes from an additional 140,886 individuals were used for validation. We identified 66 blood pressure-associated loci, of which 17 were new; 15 harbored multiple distinct association signals. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in blood pressure control through modulation of vascular tone across multiple tissues. The 66 index SNPs combined in a risk score showed comparable effects in 64,421 individuals of non-European descent. The 66-SNP blood pressure risk score was significantly associated with target organ damage in multiple tissues but with minor effects in the kidney. Our findings expand current knowledge of blood pressure-related pathways and highlight tissues beyond the classical renal system in blood pressure regulation.
Published: 2016

21. Efficacy and safety of denosumab vs. bisphosphonates in postmenopausal women previously treated with oral bisphosphonates

Author: Miller, P.D., Pannacciulli, N., Malouf-Sierra, J., Singer, A., Czerwiński, E., Bone, H.G., Wang, C., Huang, S., Chines, A., Lems, W., and Brown, J.P.
Published: 2020
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22. Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci

Author: Gaulton, Kyle J, Ferreira, Teresa, Lee, Yeji, Raimondo, Anne, Mägi, Reedik, Reschen, Michael E, Mahajan, Anubha, Locke, Adam, William Rayner, N, Robertson, Neil, Scott, Robert A, Prokopenko, Inga, Scott, Laura J, Green, Todd, Sparso, Thomas, Thuillier, Dorothee, Yengo, Loic, Grallert, Harald, Wahl, Simone, Frånberg, Mattias, Strawbridge, Rona J, Kestler, Hans, Chheda, Himanshu, Eisele, Lewin, Gustafsson, Stefan, Steinthorsdottir, Valgerdur, Thorleifsson, Gudmar, Qi, Lu, Karssen, Lennart C, van Leeuwen, Elisabeth M, Willems, Sara M, Li, Man, Chen, Han, Fuchsberger, Christian, Kwan, Phoenix, Ma, Clement, Linderman, Michael, Lu, Yingchang, Thomsen, Soren K, Rundle, Jana K, Beer, Nicola L, van de Bunt, Martijn, Chalisey, Anil, Kang, Hyun Min, Voight, Benjamin F, Abecasis, Gonçalo R, Almgren, Peter, Baldassarre, Damiano, Balkau, Beverley, Benediktsson, Rafn, Blüher, Matthias, Boeing, Heiner, Bonnycastle, Lori L, Bottinger, Erwin P, Burtt, Noël P, Carey, Jason, Charpentier, Guillaume, Chines, Peter S, Cornelis, Marilyn C, Couper, David J, Crenshaw, Andrew T, van Dam, Rob M, Doney, Alex SF, Dorkhan, Mozhgan, Edkins, Sarah, Eriksson, Johan G, Esko, Tonu, Eury, Elodie, Fadista, João, Flannick, Jason, Fontanillas, Pierre, Fox, Caroline, Franks, Paul W, Gertow, Karl, Gieger, Christian, Gigante, Bruna, Gottesman, Omri, Grant, George B, Grarup, Niels, Groves, Christopher J, Hassinen, Maija, Have, Christian T, Herder, Christian, Holmen, Oddgeir L, Hreidarsson, Astradur B, Humphries, Steve E, Hunter, David J, Jackson, Anne U, Jonsson, Anna, Jørgensen, Marit E, Jørgensen, Torben, Kao, Wen-Hong L, Kerrison, Nicola D, Kinnunen, Leena, Klopp, Norman, Kong, Augustine, Kovacs, Peter, Kraft, Peter, Kravic, Jasmina, and Langford, Cordelia
Subjects: Biological Sciences, Genetics, Liver Disease, Diabetes, Human Genome, Digestive Diseases, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Binding Sites, Case-Control Studies, Chromatin Immunoprecipitation, Chromosome Mapping, Diabetes Mellitus, Type 2, Gene Expression Regulation, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Hepatocyte Nuclear Factor 3-beta, Humans, Islets of Langerhans, Liver, Molecular Sequence Annotation, Polymorphism, Single Nucleotide, Receptor, Melatonin, MT2, DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract: We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.
Published: 2015

23. An integrated map of structural variation in 2,504 human genomes.

Author: Sudmant, Peter H, Rausch, Tobias, Gardner, Eugene J, Handsaker, Robert E, Abyzov, Alexej, Huddleston, John, Zhang, Yan, Ye, Kai, Jun, Goo, Fritz, Markus Hsi-Yang, Konkel, Miriam K, Malhotra, Ankit, Stütz, Adrian M, Shi, Xinghua, Casale, Francesco Paolo, Chen, Jieming, Hormozdiari, Fereydoun, Dayama, Gargi, Chen, Ken, Malig, Maika, Chaisson, Mark JP, Walter, Klaudia, Meiers, Sascha, Kashin, Seva, Garrison, Erik, Auton, Adam, Lam, Hugo YK, Mu, Xinmeng Jasmine, Alkan, Can, Antaki, Danny, Bae, Taejeong, Cerveira, Eliza, Chines, Peter, Chong, Zechen, Clarke, Laura, Dal, Elif, Ding, Li, Emery, Sarah, Fan, Xian, Gujral, Madhusudan, Kahveci, Fatma, Kidd, Jeffrey M, Kong, Yu, Lameijer, Eric-Wubbo, McCarthy, Shane, Flicek, Paul, Gibbs, Richard A, Marth, Gabor, Mason, Christopher E, Menelaou, Androniki, Muzny, Donna M, Nelson, Bradley J, Noor, Amina, Parrish, Nicholas F, Pendleton, Matthew, Quitadamo, Andrew, Raeder, Benjamin, Schadt, Eric E, Romanovitch, Mallory, Schlattl, Andreas, Sebra, Robert, Shabalin, Andrey A, Untergasser, Andreas, Walker, Jerilyn A, Wang, Min, Yu, Fuli, Zhang, Chengsheng, Zhang, Jing, Zheng-Bradley, Xiangqun, Zhou, Wanding, Zichner, Thomas, Sebat, Jonathan, Batzer, Mark A, McCarroll, Steven A, 1000 Genomes Project Consortium, Mills, Ryan E, Gerstein, Mark B, Bashir, Ali, Stegle, Oliver, Devine, Scott E, Lee, Charles, Eichler, Evan E, and Korbel, Jan O
Subjects: Genomes Project Consortium, Humans, Genetic Predisposition to Disease, Physical Chromosome Mapping, Sequence Analysis, DNA, Genetics, Medical, Genetics, Population, Genomics, Sequence Deletion, Amino Acid Sequence, Genotype, Haplotypes, Homozygote, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genome, Human, Molecular Sequence Data, Genetic Variation, Genome-Wide Association Study, Mutation Rate, Sequence Analysis, DNA, Genetics, Medical, Population, Polymorphism, Single Nucleotide, Genome, Human, General Science & Technology
Abstract: Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.
Published: 2015

24. A systems genetics approach identifies CXCL14, ITGAX, and LPCAT2 as novel aggressive prostate cancer susceptibility genes.

Author: Williams, Kendra, Lee, Minnkyong, Hu, Ying, Andreas, Jonathan, Patel, Shashank, Zhang, Suiyuan, Chines, Peter, Elkahloun, Abdel, Chandrasekharappa, Settara, Gutkind, J, Molinolo, Alfredo, and Crawford, Nigel
Subjects: 1-Acylglycerophosphocholine O-Acyltransferase, Animals, CD11c Antigen, Cell Transformation, Neoplastic, Chemokines, CXC, Disease Models, Animal, Gene Expression Regulation, Neoplastic, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Mice, Prostatic Neoplasms, Quantitative Trait Loci, Ribonuclease H
Abstract: Although prostate cancer typically runs an indolent course, a subset of men develop aggressive, fatal forms of this disease. We hypothesize that germline variation modulates susceptibility to aggressive prostate cancer. The goal of this work is to identify susceptibility genes using the C57BL/6-Tg(TRAMP)8247Ng/J (TRAMP) mouse model of neuroendocrine prostate cancer. Quantitative trait locus (QTL) mapping was performed in transgene-positive (TRAMPxNOD/ShiLtJ) F2 intercross males (n = 228), which facilitated identification of 11 loci associated with aggressive disease development. Microarray data derived from 126 (TRAMPxNOD/ShiLtJ) F2 primary tumors were used to prioritize candidate genes within QTLs, with candidate genes deemed as being high priority when possessing both high levels of expression-trait correlation and a proximal expression QTL. This process enabled the identification of 35 aggressive prostate tumorigenesis candidate genes. The role of these genes in aggressive forms of human prostate cancer was investigated using two concurrent approaches. First, logistic regression analysis in two human prostate gene expression datasets revealed that expression levels of five genes (CXCL14, ITGAX, LPCAT2, RNASEH2A, and ZNF322) were positively correlated with aggressive prostate cancer and two genes (CCL19 and HIST1H1A) were protective for aggressive prostate cancer. Higher than average levels of expression of the five genes that were positively correlated with aggressive disease were consistently associated with patient outcome in both human prostate cancer tumor gene expression datasets. Second, three of these five genes (CXCL14, ITGAX, and LPCAT2) harbored polymorphisms associated with aggressive disease development in a human GWAS cohort consisting of 1,172 prostate cancer patients. This study is the first example of using a systems genetics approach to successfully identify novel susceptibility genes for aggressive prostate cancer. Such approaches will facilitate the identification of novel germline factors driving aggressive disease susceptibility and allow for new insights into these deadly forms of prostate cancer.
Published: 2014

25. Defining the role of common variation in the genomic and biological architecture of adult human height

Author: Wood, Andrew R, Esko, Tonu, Yang, Jian, Vedantam, Sailaja, Pers, Tune H, Gustafsson, Stefan, Chu, Audrey Y, Estrada, Karol, Luan, Jian'an, Kutalik, Zoltán, Amin, Najaf, Buchkovich, Martin L, Croteau-Chonka, Damien C, Day, Felix R, Duan, Yanan, Fall, Tove, Fehrmann, Rudolf, Ferreira, Teresa, Jackson, Anne U, Karjalainen, Juha, Lo, Ken Sin, Locke, Adam E, Mägi, Reedik, Mihailov, Evelin, Porcu, Eleonora, Randall, Joshua C, Scherag, André, Vinkhuyzen, Anna AE, Westra, Harm-Jan, Winkler, Thomas W, Workalemahu, Tsegaselassie, Zhao, Jing Hua, Absher, Devin, Albrecht, Eva, Anderson, Denise, Baron, Jeffrey, Beekman, Marian, Demirkan, Ayse, Ehret, Georg B, Feenstra, Bjarke, Feitosa, Mary F, Fischer, Krista, Fraser, Ross M, Goel, Anuj, Gong, Jian, Justice, Anne E, Kanoni, Stavroula, Kleber, Marcus E, Kristiansson, Kati, Lim, Unhee, Lotay, Vaneet, Lui, Julian C, Mangino, Massimo, Leach, Irene Mateo, Medina-Gomez, Carolina, Nalls, Michael A, Nyholt, Dale R, Palmer, Cameron D, Pasko, Dorota, Pechlivanis, Sonali, Prokopenko, Inga, Ried, Janina S, Ripke, Stephan, Shungin, Dmitry, Stancáková, Alena, Strawbridge, Rona J, Sung, Yun Ju, Tanaka, Toshiko, Teumer, Alexander, Trompet, Stella, van der Laan, Sander W, van Setten, Jessica, Van Vliet-Ostaptchouk, Jana V, Wang, Zhaoming, Yengo, Loïc, Zhang, Weihua, Afzal, Uzma, Ärnlöv, Johan, Arscott, Gillian M, Bandinelli, Stefania, Barrett, Amy, Bellis, Claire, Bennett, Amanda J, Berne, Christian, Blüher, Matthias, Bolton, Jennifer L, Böttcher, Yvonne, Boyd, Heather A, Bruinenberg, Marcel, Buckley, Brendan M, Buyske, Steven, Caspersen, Ida H, Chines, Peter S, Clarke, Robert, Claudi-Boehm, Simone, Cooper, Matthew, Daw, E Warwick, De Jong, Pim A, Deelen, Joris, and Delgado, Graciela
Subjects: Biological Sciences, Genetics, Biotechnology, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Adult, Analysis of Variance, Body Height, Genetic Variation, Genetics, Population, Genome-Wide Association Study, Humans, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide, White People, Electronic Medical Records and Genomics (eMEMERGEGE) Consortium, MIGen Consortium, PAGEGE Consortium, LifeLines Cohort Study, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract: Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.
Published: 2014

26. Rare variants in PPARG with decreased activity in adipocyte differentiation are associated with increased risk of type 2 diabetes

Author: Majithia, Amit R, Flannick, Jason, Shahinian, Peter, Guo, Michael, Bray, Mark-Anthony, Fontanillas, Pierre, Gabriel, Stacey B, Rosen, Evan D, Altshuler, David, Manning, Alisa K, Hartl, Christopher, Agarwala, Vineeta, Green, Todd, Banks, Eric, DePristo, Mark, Poplin, Ryan, Shakir, Khalid, Fennell, Timothy, Njølstad, Pål R, Burtt, Noël, Gabriel, Stacey, Fuchsberger, Christian, Kang, Hun Min, Sim, Xueling, Ma, Clement, Locke, Adam, Blackwell, Thomas, Jackson, Anne, Teslovich, Tanya M, Stringham, Heather, Chines, Peter, Kwan, Phoenix, Huyghe, Jeroen, Tan, Adrian, Jun, Goo, Stitzel, Michael, Bergman, Richard N, Bonnycastle, Lori, Tuomilehto, Jaakko, Collins, Francis S, Scott, Laura, Mohlke, Karen, Abecasis, Gonçalo, Boehnke, Michael, Strom, Tim, Gieger, Christian, Nurasyid, Martina Müller, Grallert, Harald, Kriebel, Jennifer, Ried, Janina, de Angelis, Martin Hrabé, Huth, Cornelia, Meisinger, Christa, Peters, Annette, Rathmann, Wolfgang, Strauch, Konstantin, Meitinger, Thomas, Kravic, Jasmina, Algren, Peter, Ladenvall, Claes, Toumi, Tiinamaija, Isomaa, Bo, Groop, Leif, Gaulton, Kyle, Moutsianas, Loukas, Rivas, Manny, Pearson, Richard, Mahajan, Anubha, Prokopenko, Inga, Kumar, Ashish, Perry, John, Howie, Bryan, van de Bunt, Martijn, Small, Kerrin, Lindgren, Cecilia, Lunter, Gerton, Robertson, Neil, Rayner, William, Morris, Andrew, Buck, David, Hattersley, Andrew, Spector, Tim, McVean, Gil, Frayling, Tim, Donnelly, Peter, McCarthy, Mark, Gupta, Namrata, Taylor, Herman, Fox, Ervin, Cheh, Christopher Newton, Wilson, James G, O'Donnell, Christopher J, Kathiresan, Sekar, Hirschhorn, Joel, Seidman, JG, and Seidman, Christine
Subjects: Genetics, Biotechnology, Human Genome, Diabetes, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Adipocytes, Adult, Aged, Aged, 80 and over, Case-Control Studies, Cell Differentiation, Diabetes Mellitus, Type 2, Ethnicity, Female, Genetic Predisposition to Disease, Humans, Male, Middle Aged, PPAR gamma, Polymorphism, Single Nucleotide, Risk Factors, Sequence Analysis, DNA, GoT2D Consortium, NHGRI JHS/FHS Allelic Spectrum Project, SIGMA T2D Consortium, T2D-GENES Consortium
Abstract: Peroxisome proliferator-activated receptor gamma (PPARG) is a master transcriptional regulator of adipocyte differentiation and a canonical target of antidiabetic thiazolidinedione medications. In rare families, loss-of-function (LOF) mutations in PPARG are known to cosegregate with lipodystrophy and insulin resistance; in the general population, the common P12A variant is associated with a decreased risk of type 2 diabetes (T2D). Whether and how rare variants in PPARG and defects in adipocyte differentiation influence risk of T2D in the general population remains undetermined. By sequencing PPARG in 19,752 T2D cases and controls drawn from multiple studies and ethnic groups, we identified 49 previously unidentified, nonsynonymous PPARG variants (MAF < 0.5%). Considered in aggregate (with or without computational prediction of functional consequence), these rare variants showed no association with T2D (OR = 1.35; P = 0.17). The function of the 49 variants was experimentally tested in a novel high-throughput human adipocyte differentiation assay, and nine were found to have reduced activity in the assay. Carrying any of these nine LOF variants was associated with a substantial increase in risk of T2D (OR = 7.22; P = 0.005). The combination of large-scale DNA sequencing and functional testing in the laboratory reveals that approximately 1 in 1,000 individuals carries a variant in PPARG that reduces function in a human adipocyte differentiation assay and is associated with a substantial risk of T2D.
Published: 2014

27. Impact of Type 2 Diabetes Susceptibility Variants on Quantitative Glycemic Traits Reveals Mechanistic Heterogeneity

Author: Dimas, Antigone S, Lagou, Vasiliki, Barker, Adam, Knowles, Joshua W, Mägi, Reedik, Hivert, Marie-France, Benazzo, Andrea, Rybin, Denis, Jackson, Anne U, Stringham, Heather M, Song, Ci, Fischer-Rosinsky, Antje, Boesgaard, Trine Welløv, Grarup, Niels, Abbasi, Fahim A, Assimes, Themistocles L, Hao, Ke, Yang, Xia, Lecoeur, Cécile, Barroso, Inês, Bonnycastle, Lori L, Böttcher, Yvonne, Bumpstead, Suzannah, Chines, Peter S, Erdos, Michael R, Graessler, Jurgen, Kovacs, Peter, Morken, Mario A, Narisu, Narisu, Payne, Felicity, Stancakova, Alena, Swift, Amy J, Tönjes, Anke, Bornstein, Stefan R, Cauchi, Stéphane, Froguel, Philippe, Meyre, David, Schwarz, Peter EH, Häring, Hans-Ulrich, Smith, Ulf, Boehnke, Michael, Bergman, Richard N, Collins, Francis S, Mohlke, Karen L, Tuomilehto, Jaakko, Quertemous, Thomas, Lind, Lars, Hansen, Torben, Pedersen, Oluf, Walker, Mark, Pfeiffer, Andreas FH, Spranger, Joachim, Stumvoll, Michael, Meigs, James B, Wareham, Nicholas J, Kuusisto, Johanna, Laakso, Markku, Langenberg, Claudia, Dupuis, Josée, Watanabe, Richard M, Florez, Jose C, Ingelsson, Erik, McCarthy, Mark I, Prokopenko, Inga, and Investigators, on behalf of the MAGIC
Subjects: Biomedical and Clinical Sciences, Genetics, Diabetes, Autoimmune Disease, Clinical Research, Prevention, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Alleles, Cluster Analysis, Diabetes Mellitus, Type 2, Female, Gene Frequency, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Humans, Insulin, Insulin Resistance, Insulin Secretion, Insulin-Secreting Cells, Male, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Risk Factors, Transcription Factors, MAGIC Investigators, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences
Abstract: Patients with established type 2 diabetes display both β-cell dysfunction and insulin resistance. To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci, and indices of proinsulin processing, insulin secretion, and insulin sensitivity. We included data from up to 58,614 nondiabetic subjects with basal measures and 17,327 with dynamic measures. We used additive genetic models with adjustment for sex, age, and BMI, followed by fixed-effects, inverse-variance meta-analyses. Cluster analyses grouped risk loci into five major categories based on their relationship to these continuous glycemic phenotypes. The first cluster (PPARG, KLF14, IRS1, GCKR) was characterized by primary effects on insulin sensitivity. The second cluster (MTNR1B, GCK) featured risk alleles associated with reduced insulin secretion and fasting hyperglycemia. ARAP1 constituted a third cluster characterized by defects in insulin processing. A fourth cluster (TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without a detectable change in fasting glucose levels. The final group contained 20 risk loci with no clear-cut associations to continuous glycemic traits. By assembling extensive data on continuous glycemic traits, we have exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition.
Published: 2014

28. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility

Author: Mahajan, Anubha, Go, Min Jin, Zhang, Weihua, Below, Jennifer E, Gaulton, Kyle J, Ferreira, Teresa, Horikoshi, Momoko, Johnson, Andrew D, Ng, Maggie CY, Prokopenko, Inga, Saleheen, Danish, Wang, Xu, Zeggini, Eleftheria, Abecasis, Goncalo R, Adair, Linda S, Almgren, Peter, Atalay, Mustafa, Aung, Tin, Baldassarre, Damiano, Balkau, Beverley, Bao, Yuqian, Barnett, Anthony H, Barroso, Ines, Basit, Abdul, Been, Latonya F, Beilby, John, Bell, Graeme I, Benediktsson, Rafn, Bergman, Richard N, Boehm, Bernhard O, Boerwinkle, Eric, Bonnycastle, Lori L, Burtt, Noël, Cai, Qiuyin, Campbell, Harry, Carey, Jason, Cauchi, Stephane, Caulfield, Mark, Chan, Juliana CN, Chang, Li-Ching, Chang, Tien-Jyun, Chang, Yi-Cheng, Charpentier, Guillaume, Chen, Chien-Hsiun, Chen, Han, Chen, Yuan-Tsong, Chia, Kee-Seng, Chidambaram, Manickam, Chines, Peter S, Cho, Nam H, Cho, Young Min, Chuang, Lee-Ming, Collins, Francis S, Cornelis, Marilyn C, Couper, David J, Crenshaw, Andrew T, van Dam, Rob M, Danesh, John, Das, Debashish, de Faire, Ulf, Dedoussis, George, Deloukas, Panos, Dimas, Antigone S, Dina, Christian, Doney, Alex SF, Donnelly, Peter J, Dorkhan, Mozhgan, van Duijn, Cornelia, Dupuis, Josée, Edkins, Sarah, Elliott, Paul, Emilsson, Valur, Erbel, Raimund, Eriksson, Johan G, Escobedo, Jorge, Esko, Tonu, Eury, Elodie, Florez, Jose C, Fontanillas, Pierre, Forouhi, Nita G, Forsen, Tom, Fox, Caroline, Fraser, Ross M, Frayling, Timothy M, Froguel, Philippe, Frossard, Philippe, Gao, Yutang, Gertow, Karl, Gieger, Christian, Gigante, Bruna, Grallert, Harald, Grant, George B, Groop, Leif C, Groves, Christopher J, Grundberg, Elin, Guiducci, Candace, Hamsten, Anders, Han, Bok-Ghee, Hara, Kazuo, and Hassanali, Neelam
Subjects: Biological Sciences, Genetics, Human Genome, Diabetes, Metabolic and endocrine, Alleles, Asian People, Case-Control Studies, Diabetes Mellitus, Type 2, Genetic Predisposition to Disease, Genome-Wide Association Study, Hispanic or Latino, Humans, Polymorphism, Single Nucleotide, Risk Factors, White People, DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Asian Genetic Epidemiology Network Type 2 Diabetes (AGEN-T2D) Consortium, South Asian Type 2 Diabetes (SAT2D) Consortium, Mexican American Type 2 Diabetes (MAT2D) Consortium, Type 2 Diabetes Genetic Exploration by Nex-generation sequencing in muylti-Ethnic Samples (T2D-GENES) Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract: To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.
Published: 2014

29. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility.

Author: DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Asian Genetic Epidemiology Network Type 2 Diabetes (AGEN-T2D) Consortium, South Asian Type 2 Diabetes (SAT2D) Consortium, Mexican American Type 2 Diabetes (MAT2D) Consortium, Type 2 Diabetes Genetic Exploration by Nex-generation sequencing in muylti-Ethnic Samples (T2D-GENES) Consortium, Mahajan, Anubha, Go, Min Jin, Zhang, Weihua, Below, Jennifer E, Gaulton, Kyle J, Ferreira, Teresa, Horikoshi, Momoko, Johnson, Andrew D, Ng, Maggie CY, Prokopenko, Inga, Saleheen, Danish, Wang, Xu, Zeggini, Eleftheria, Abecasis, Goncalo R, Adair, Linda S, Almgren, Peter, Atalay, Mustafa, Aung, Tin, Baldassarre, Damiano, Balkau, Beverley, Bao, Yuqian, Barnett, Anthony H, Barroso, Ines, Basit, Abdul, Been, Latonya F, Beilby, John, Bell, Graeme I, Benediktsson, Rafn, Bergman, Richard N, Boehm, Bernhard O, Boerwinkle, Eric, Bonnycastle, Lori L, Burtt, Noël, Cai, Qiuyin, Campbell, Harry, Carey, Jason, Cauchi, Stephane, Caulfield, Mark, Chan, Juliana CN, Chang, Li-Ching, Chang, Tien-Jyun, Chang, Yi-Cheng, Charpentier, Guillaume, Chen, Chien-Hsiun, Chen, Han, Chen, Yuan-Tsong, Chia, Kee-Seng, Chidambaram, Manickam, Chines, Peter S, Cho, Nam H, Cho, Young Min, Chuang, Lee-Ming, Collins, Francis S, Cornelis, Marylin C, Couper, David J, Crenshaw, Andrew T, van Dam, Rob M, Danesh, John, Das, Debashish, de Faire, Ulf, Dedoussis, George, Deloukas, Panos, Dimas, Antigone S, Dina, Christian, Doney, Alex S, Donnelly, Peter J, Dorkhan, Mozhgan, van Duijn, Cornelia, Dupuis, Josée, Edkins, Sarah, Elliott, Paul, Emilsson, Valur, Erbel, Raimund, Eriksson, Johan G, Escobedo, Jorge, Esko, Tonu, Eury, Elodie, Florez, Jose C, Fontanillas, Pierre, Forouhi, Nita G, Forsen, Tom, Fox, Caroline, Fraser, Ross M, Frayling, Timothy M, Froguel, Philippe, Frossard, Philippe, Gao, Yutang, Gertow, Karl, Gieger, Christian, Gigante, Bruna, Grallert, Harald, Grant, George B, Grrop, Leif C, and Groves, Chrisropher J
Subjects: DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Asian Genetic Epidemiology Network Type 2 Diabetes (AGEN-T2D) Consortium, South Asian Type 2 Diabetes (SAT2D) Consortium, Mexican American Type 2 Diabetes (MAT2D) Consortium, Type 2 Diabetes Genetic Exploration by Nex-generation sequencing in muylti-Ethnic Samples (T2D-GENES) Consortium, Humans, Diabetes Mellitus, Type 2, Genetic Predisposition to Disease, Risk Factors, Case-Control Studies, Polymorphism, Single Nucleotide, Alleles, Asian Continental Ancestry Group, European Continental Ancestry Group, Hispanic Americans, Genome-Wide Association Study, Diabetes Mellitus, Type 2, Polymorphism, Single Nucleotide, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract: To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.
Published: 2014

30. Chromatin stretch enhancer states drive cell-specific gene regulation and harbor human disease risk variants.

Author: Parker, Stephen CJ, Stitzel, Michael L, Taylor, D Leland, Orozco, Jose Miguel, Erdos, Michael R, Akiyama, Jennifer A, van Bueren, Kelly Lammerts, Chines, Peter S, Narisu, Narisu, NISC Comparative Sequencing Program, Black, Brian L, Visel, Axel, Pennacchio, Len A, Collins, Francis S, National Institutes of Health Intramural Sequencing Center Comparative Sequencing Program Authors, and NISC Comparative Sequencing Program Authors
Subjects: NISC Comparative Sequencing Program, National Institutes of Health Intramural Sequencing Center Comparative Sequencing Program Authors, NISC Comparative Sequencing Program Authors, Chromatin, Animals, Mice, Transgenic, Humans, Mice, Diabetes Mellitus, Type 2, Luciferases, Chromatin Immunoprecipitation, Gene Expression Profiling, Cell Differentiation, Gene Expression Regulation, Insulin-Secreting Cells, Enhancer Elements, Genetic, Genome-Wide Association Study, Epigenomics, High-Throughput Nucleotide Sequencing, Biotechnology, Diabetes, Human Genome, Genetics, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine
Abstract: Chromatin-based functional genomic analyses and genomewide association studies (GWASs) together implicate enhancers as critical elements influencing gene expression and risk for common diseases. Here, we performed systematic chromatin and transcriptome profiling in human pancreatic islets. Integrated analysis of islet data with those from nine cell types identified specific and significant enrichment of type 2 diabetes and related quantitative trait GWAS variants in islet enhancers. Our integrated chromatin maps reveal that most enhancers are short (median = 0.8 kb). Each cell type also contains a substantial number of more extended (≥ 3 kb) enhancers. Interestingly, these stretch enhancers are often tissue-specific and overlap locus control regions, suggesting that they are important chromatin regulatory beacons. Indeed, we show that (i) tissue specificity of enhancers and nearby gene expression increase with enhancer length; (ii) neighborhoods containing stretch enhancers are enriched for important cell type-specific genes; and (iii) GWAS variants associated with traits relevant to a particular cell type are more enriched in stretch enhancers compared with short enhancers. Reporter constructs containing stretch enhancer sequences exhibited tissue-specific activity in cell culture experiments and in transgenic mice. These results suggest that stretch enhancers are critical chromatin elements for coordinating cell type-specific regulatory programs and that sequence variation in stretch enhancers affects risk of major common human diseases.
Published: 2013

31. Long-term denosumab treatment restores cortical bone loss and reduces fracture risk at the forearm and humerus: analyses from the FREEDOM Extension cross-over group

Author: Bilezikian, J.P., Lin, C.J.F., Brown, J.P., Wang, A.T., Yin, X., Ebeling, P.R., Fahrleitner-Pammer, A., Franek, E., Gilchrist, N., Miller, P.D., Simon, J.A., Valter, I., Zerbini, C.A.F., Libanati, C., and Chines, A.
Published: 2019
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32. The risk of subsequent osteoporotic fractures is decreased in subjects experiencing fracture while on denosumab: results from the FREEDOM and FREEDOM Extension studies

Author: Kendler, D. L., Chines, A., Brandi, M. L., Papapoulos, S., Lewiecki, E. M., Reginster, J-Y., Muñoz Torres, M., Wang, A., and Bone, H. G.
Published: 2019
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33. Evaluation of common genetic variants in 82candidate genes as risk factors for neural tubedefects

Author: Pangilinan, Faith, Molloy, Anne M, Mills, James L, Troendle, James F, Parle-McDermott, Anne, Signore, Caroline, O’Leary, Valerie B, Chines, Peter, Seay, Jessica M, Geiler-Samerotte, Kerry, Mitchell, Adam, VanderMeer, Julia E, Krebs, Kristine M, Sanchez, Angelica, Cornman-Homonoff, Joshua, Stone, Nicole, Conley, Mary, Kirke, Peadar N, Shane, Barry, Scott, John M, and Brody, Lawrence C
Abstract: AbstractBackgroundNeural tube defects (NTDs) are common birth defects (~1 in 1000 pregnancies in the US and Europe) that have complex origins, including environmental and genetic factors. A low level of maternal folate is one well-established risk factor, with maternal periconceptional folic acid supplementation reducing the occurrence of NTD pregnancies by 50-70%. Gene variants in the folate metabolic pathway (e.g., MTHFR rs1801133 (677 C > T) and MTHFD1 rs2236225 (R653Q)) have been found to increase NTD risk. We hypothesized that variants in additional folate/B12 pathway genes contribute to NTD risk.MethodsA tagSNP approach was used to screen common variation in 82 candidate genes selected from the folate/B12 pathway and NTD mouse models. We initially genotyped polymorphisms in 320 Irish triads (NTD cases and their parents), including 301 cases and 341 Irish controls to perform case–control and family based association tests. Significantly associated polymorphisms were genotyped in a secondary set of 250 families that included 229 cases and 658 controls. The combined results for 1441 SNPs were used in a joint analysis to test for case and maternal effects.ResultsNearly 70 SNPs in 30 genes were found to be associated with NTDs at the p
Published: 2012

34. No Interactions Between Previously Associated 2-Hour Glucose Gene Variants and Physical Activity or BMI on 2-Hour Glucose Levels

Author: Scott, Robert A, Chu, Audrey Y, Grarup, Niels, Manning, Alisa K, Hivert, Marie-France, Shungin, Dmitry, Tönjes, Anke, Yesupriya, Ajay, Barnes, Daniel, Bouatia-Naji, Nabila, Glazer, Nicole L, Jackson, Anne U, Kutalik, Zoltán, Lagou, Vasiliki, Marek, Diana, Rasmussen-Torvik, Laura J, Stringham, Heather M, Tanaka, Toshiko, Aadahl, Mette, Arking, Dan E, Bergmann, Sven, Boerwinkle, Eric, Bonnycastle, Lori L, Bornstein, Stefan R, Brunner, Eric, Bumpstead, Suzannah J, Brage, Soren, Carlson, Olga D, Chen, Han, Chen, Yii-Der Ida, Chines, Peter S, Collins, Francis S, Couper, David J, Dennison, Elaine M, Dowling, Nicole F, Egan, Josephine S, Ekelund, Ulf, Erdos, Michael R, Forouhi, Nita G, Fox, Caroline S, Goodarzi, Mark O, Grässler, Jürgen, Gustafsson, Stefan, Hallmans, Göran, Hansen, Torben, Hingorani, Aroon, Holloway, John W, Hu, Frank B, Isomaa, Bo, Jameson, Karen A, Johansson, Ingegerd, Jonsson, Anna, Jørgensen, Torben, Kivimaki, Mika, Kovacs, Peter, Kumari, Meena, Kuusisto, Johanna, Laakso, Markku, Lecoeur, Cécile, Lévy-Marchal, Claire, Li, Guo, Loos, Ruth JF, Lyssenko, Valeri, Marmot, Michael, Marques-Vidal, Pedro, Morken, Mario A, Müller, Gabriele, North, Kari E, Pankow, James S, Payne, Felicity, Prokopenko, Inga, Psaty, Bruce M, Renström, Frida, Rice, Ken, Rotter, Jerome I, Rybin, Denis, Sandholt, Camilla H, Sayer, Avan A, Shrader, Peter, Schwarz, Peter EH, Siscovick, David S, Stančáková, Alena, Stumvoll, Michael, Teslovich, Tanya M, Waeber, Gérard, Williams, Gordon H, Witte, Daniel R, Wood, Andrew R, Xie, Weijia, Boehnke, Michael, Cooper, Cyrus, Ferrucci, Luigi, Froguel, Philippe, Groop, Leif, Kao, WH Linda, Vollenweider, Peter, Walker, Mark, Watanabe, Richard M, Pedersen, Oluf, and Meigs, James B
Subjects: Biomedical and Clinical Sciences, Clinical Research, Genetics, Diabetes, Prevention, Obesity, Nutrition, 2.1 Biological and endogenous factors, Aetiology, 2.3 Psychological, social and economic factors, Metabolic and endocrine, Blood Glucose, Body Mass Index, Epigenesis, Genetic, Gene Expression Regulation, Genotype, Humans, Life Style, Motor Activity, Polymorphism, Single Nucleotide, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences
Abstract: Gene-lifestyle interactions have been suggested to contribute to the development of type 2 diabetes. Glucose levels 2 h after a standard 75-g glucose challenge are used to diagnose diabetes and are associated with both genetic and lifestyle factors. However, whether these factors interact to determine 2-h glucose levels is unknown. We meta-analyzed single nucleotide polymorphism (SNP) × BMI and SNP × physical activity (PA) interaction regression models for five SNPs previously associated with 2-h glucose levels from up to 22 studies comprising 54,884 individuals without diabetes. PA levels were dichotomized, with individuals below the first quintile classified as inactive (20%) and the remainder as active (80%). BMI was considered a continuous trait. Inactive individuals had higher 2-h glucose levels than active individuals (β = 0.22 mmol/L [95% CI 0.13-0.31], P = 1.63 × 10(-6)). All SNPs were associated with 2-h glucose (β = 0.06-0.12 mmol/allele, P ≤ 1.53 × 10(-7)), but no significant interactions were found with PA (P > 0.18) or BMI (P ≥ 0.04). In this large study of gene-lifestyle interaction, we observed no interactions between genetic and lifestyle factors, both of which were associated with 2-h glucose. It is perhaps unlikely that top loci from genome-wide association studies will exhibit strong subgroup-specific effects, and may not, therefore, make the best candidates for the study of interactions.
Published: 2012

35. A genome-wide association search for type 2 diabetes genes in African Americans.

Author: Palmer, Nicholette D, McDonough, Caitrin W, Hicks, Pamela J, Roh, Bong H, Wing, Maria R, An, S Sandy, Hester, Jessica M, Cooke, Jessica N, Bostrom, Meredith A, Rudock, Megan E, Talbert, Matthew E, Lewis, Joshua P, DIAGRAM Consortium, MAGIC Investigators, Ferrara, Assiamira, Lu, Lingyi, Ziegler, Julie T, Sale, Michele M, Divers, Jasmin, Shriner, Daniel, Adeyemo, Adebowale, Rotimi, Charles N, Ng, Maggie CY, Langefeld, Carl D, Freedman, Barry I, Bowden, Donald W, Voight, Benjamin F, Scott, Laura J, Steinthorsdottir, Valgerdur, Morris, Andrew P, Dina, Christian, Welch, Ryan P, Zeggini, Eleftheria, Huth, Cornelia, Aulchenko, Yurii S, Thorleifsson, Gudmar, McCulloch, Laura J, Ferreira, Teresa, Grallert, Harald, Amin, Najaf, Wu, Guanming, Willer, Cristen J, Raychaudhuri, Soumya, McCarroll, Steve A, Langenberg, Claudia, Hofmann, Oliver M, Dupuis, Josée, Qi, Lu, Segrè, Ayellet V, van Hoek, Mandy, Navarro, Pau, Ardlie, Kristin, Balkau, Beverley, Benediktsson, Rafn, Bennett, Amanda J, Blagieva, Roza, Boerwinkle, Eric, Bonnycastle, Lori L, Boström, Kristina Bengtsson, Bravenboer, Bert, Bumpstead, Suzannah, Burtt, Noël P, Charpentier, Guillaume, Chines, Peter S, Cornelis, Marilyn, Couper, David J, Crawford, Gabe, Doney, Alex SF, Elliott, Katherine S, Elliott, Amanda L, Erdos, Michael R, Fox, Caroline S, Franklin, Christopher S, Ganser, Martha, Gieger, Christian, Grarup, Niels, Green, Todd, Griffin, Simon, Groves, Christopher J, Guiducci, Candace, Hadjadj, Samy, Hassanali, Neelam, Herder, Christian, Isomaa, Bo, Jackson, Anne U, Johnson, Paul RV, Jørgensen, Torben, Kao, Wen HL, Klopp, Norman, Kong, Augustine, Kraft, Peter, Kuusisto, Johanna, Lauritzen, Torsten, Li, Man, Lieverse, Aloysius, Lindgren, Cecilia M, Lyssenko, Valeriya, Marre, Michel, Meitinger, Thomas, and Midthjell, Kristian
Subjects: DIAGRAM Consortium, MAGIC Investigators, Humans, Diabetes Mellitus, Type 2, Genetic Predisposition to Disease, Case-Control Studies, Cohort Studies, Genotype, Polymorphism, Single Nucleotide, Adult, Aged, Middle Aged, African Americans, Female, Male, Meta-Analysis as Topic, Validation Studies as Topic, Genome-Wide Association Study, Diabetes Mellitus, Type 2, Polymorphism, Single Nucleotide, General Science & Technology
Abstract: African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P
Published: 2012

36. Romosozumab improves lumbar spine BMD and bone strength greater than alendronate as assessed by quantitative computed tomography and finite element analysis in the ARCH trial

Author: Jacques P. Brown, Arkadi Chines, Roland Chapurlat, Joseph Foldes, Xavier Nogues, Roberto Civitelli, Tobias De Villiers, Fabio Massari, Cristiano Zerbini, Wenjing Yang, Chris Recknor, and Cesar Libanati
Subjects: Diseases of the musculoskeletal system, RC925-935
Published: 2020
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37. BoostMe accurately predicts DNA methylation values in whole-genome bisulfite sequencing of multiple human tissues

Author: Luli S. Zou, Michael R. Erdos, D. Leland Taylor, Peter S. Chines, Arushi Varshney, The McDonnell Genome Institute, Stephen C. J. Parker, Francis S. Collins, and John P. Didion
Subjects: DNA methylation, XGBoost, Whole-genome bisulfite sequencing (WGBS), EPIC, Imputation, Adipose, Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract: Abstract Background Bisulfite sequencing is widely employed to study the role of DNA methylation in disease; however, the data suffer from biases due to coverage depth variability. Imputation of methylation values at low-coverage sites may mitigate these biases while also identifying important genomic features associated with predictive power. Results Here we describe BoostMe, a method for imputing low-quality DNA methylation estimates within whole-genome bisulfite sequencing (WGBS) data. BoostMe uses a gradient boosting algorithm, XGBoost, and leverages information from multiple samples for prediction. We find that BoostMe outperforms existing algorithms in speed and accuracy when applied to WGBS of human tissues. Furthermore, we show that imputation improves concordance between WGBS and the MethylationEPIC array at low WGBS depth, suggesting improved WGBS accuracy after imputation. Conclusions Our findings support the use of BoostMe as a preprocessing step for WGBS analysis.
Published: 2018
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38. Comprehensive Association Study of Type 2 Diabetes and Related Quantitative Traits With 222 Candidate Genes

Author: Gaulton, Kyle J, Willer, Cristen J, Li, Yun, Scott, Laura J, Conneely, Karen N, Jackson, Anne U, Duren, William L, Chines, Peter S, Narisu, Narisu, Bonnycastle, Lori L, Luo, Jingchun, Tong, Maurine, Sprau, Andrew G, Pugh, Elizabeth W, Doheny, Kimberly F, Valle, Timo T, Abecasis, Gonçalo R, Tuomilehto, Jaakko, Bergman, Richard N, Collins, Francis S, Boehnke, Michael, and Mohlke, Karen L
Subjects: Biomedical and Clinical Sciences, Biotechnology, Diabetes, Genetics, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Adult, Aged, Diabetes Mellitus, Type 2, Female, Finland, Gene Frequency, Genes, p53, Genetic Predisposition to Disease, Genotype, Glucose Transporter Type 2, Humans, Male, Middle Aged, Nuclear Respiratory Factor 1, Phosphoric Diester Hydrolases, Polymorphism, Single Nucleotide, Potassium Channels, Inwardly Rectifying, Pyrophosphatases, Quantitative Trait, Heritable, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences
Abstract: ObjectiveType 2 diabetes is a common complex disorder with environmental and genetic components. We used a candidate gene-based approach to identify single nucleotide polymorphism (SNP) variants in 222 candidate genes that influence susceptibility to type 2 diabetes.Research design and methodsIn a case-control study of 1,161 type 2 diabetic subjects and 1,174 control Finns who are normal glucose tolerant, we genotyped 3,531 tagSNPs and annotation-based SNPs and imputed an additional 7,498 SNPs, providing 99.9% coverage of common HapMap variants in the 222 candidate genes. Selected SNPs were genotyped in an additional 1,211 type 2 diabetic case subjects and 1,259 control subjects who are normal glucose tolerant, also from Finland.ResultsUsing SNP- and gene-based analysis methods, we replicated previously reported SNP-type 2 diabetes associations in PPARG, KCNJ11, and SLC2A2; identified significant SNPs in genes with previously reported associations (ENPP1 [rs2021966, P = 0.00026] and NRF1 [rs1882095, P = 0.00096]); and implicated novel genes, including RAPGEF1 (rs4740283, P = 0.00013) and TP53 (rs1042522, Arg72Pro, P = 0.00086), in type 2 diabetes susceptibility.ConclusionsOur study provides an effective gene-based approach to association study design and analysis. One or more of the newly implicated genes may contribute to type 2 diabetes pathogenesis. Analysis of additional samples will be necessary to determine their effect on susceptibility.
Published: 2008

39. Major amputations in type 2 diabetes between 2001 and 2015 in Spain: regional differences

Author: Rodríguez Pérez, María del Cristo, Chines, Chiara, Pedrero García, Arturo J., Sousa, Djeniffer, Cuevas Fernández, Francisco J., Marcelino-Rodríguez, Itahisa, Domínguez Coello, Santiago, and Cabrera de León, Antonio
Published: 2020
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40. Diversity patterns of alien and native plant species in Trieste port area: exploring the role of urban habitats in biodiversity conservation

Author: Tordoni, Enrico, Napolitano, Rossella, Nimis, Pierluigi, Castello, Miris, Altobelli, Alfredo, Da Re, Daniele, Zago, Samanta, Chines, Arianna, Martellos, Stefano, Maccherini, Simona, and Bacaro, Giovanni
Published: 2017
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41. At the Crossroads of Apoptosis and Autophagy: Multiple Roles of the Co-Chaperone BAG3 in Stress and Therapy Resistance of Cancer

Author: Donat Kögel, Benedikt Linder, Andreas Brunschweiger, Silvia Chines, and Christian Behl
Subjects: cancer, therapy resistance, chaperones, apoptosis, cell survival, autophagy, tumor progression, Cytology, QH573-671
Abstract: BAG3, a multifunctional HSP70 co-chaperone and anti-apoptotic protein that interacts with the ATPase domain of HSP70 through its C-terminal BAG domain plays a key physiological role in cellular proteostasis. The HSP70/BAG3 complex determines the levels of a large number of selective client proteins by regulating their turnover via the two major protein degradation pathways, i.e. proteasomal degradation and macroautophagy. On the one hand, BAG3 competes with BAG1 for binding to HSP70, thereby preventing the proteasomal degradation of its client proteins. By functionally interacting with HSP70 and LC3, BAG3 also delivers polyubiquitinated proteins to the autophagy pathway. BAG3 exerts a number of key physiological functions, including an involvement in cellular stress responses, proteostasis, cell death regulation, development, and cytoskeletal dynamics. Conversely, aberrant BAG3 function/expression has pathophysiological relevance correlated to cardiomyopathies, neurodegeneration, and cancer. Evidence obtained in recent years underscores the fact that BAG3 drives several key hallmarks of cancer, including cell adhesion, metastasis, angiogenesis, enhanced autophagic activity, and apoptosis inhibition. This review provides a state-of-the-art overview on the role of BAG3 in stress and therapy resistance of cancer, with a particular focus on BAG3-dependent modulation of apoptotic signaling and autophagic/lysosomal activity.
Published: 2020
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42. Interactions between genetic variation and cellular environment in skeletal muscle gene expression.

Author: D Leland Taylor, David A Knowles, Laura J Scott, Andrea H Ramirez, Francesco Paolo Casale, Brooke N Wolford, Li Guan, Arushi Varshney, Ricardo D'Oliveira Albanus, Stephen C J Parker, Narisu Narisu, Peter S Chines, Michael R Erdos, Ryan P Welch, Leena Kinnunen, Jouko Saramies, Jouko Sundvall, Timo A Lakka, Markku Laakso, Jaakko Tuomilehto, Heikki A Koistinen, Oliver Stegle, Michael Boehnke, Ewan Birney, and Francis S Collins
Subjects: Medicine, Science
Abstract: From whole organisms to individual cells, responses to environmental conditions are influenced by genetic makeup, where the effect of genetic variation on a trait depends on the environmental context. RNA-sequencing quantifies gene expression as a molecular trait, and is capable of capturing both genetic and environmental effects. In this study, we explore opportunities of using allele-specific expression (ASE) to discover cis-acting genotype-environment interactions (GxE)-genetic effects on gene expression that depend on an environmental condition. Treating 17 common, clinical traits as approximations of the cellular environment of 267 skeletal muscle biopsies, we identify 10 candidate environmental response expression quantitative trait loci (reQTLs) across 6 traits (12 unique gene-environment trait pairs; 10% FDR per trait) including sex, systolic blood pressure, and low-density lipoprotein cholesterol. Although using ASE is in principle a promising approach to detect GxE effects, replication of such signals can be challenging as validation requires harmonization of environmental traits across cohorts and a sufficient sampling of heterozygotes for a transcribed SNP. Comprehensive discovery and replication will require large human transcriptome datasets, or the integration of multiple transcribed SNPs, coupled with standardized clinical phenotyping.
Published: 2018
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43. BoostMe accurately predicts DNA methylation values in whole-genome bisulfite sequencing of multiple human tissues

Author: Zou, Luli S., Erdos, Michael R., Taylor, D. Leland, Chines, Peter S., Varshney, Arushi, The McDonnell Genome Institute, Parker, Stephen C. J., Collins, Francis S., and Didion, John P.
Published: 2018
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44. Common, low-frequency, and rare genetic variants associated with lipoprotein subclasses and triglyceride measures in Finnish men from the METSIM study.

Author: James P Davis, Jeroen R Huyghe, Adam E Locke, Anne U Jackson, Xueling Sim, Heather M Stringham, Tanya M Teslovich, Ryan P Welch, Christian Fuchsberger, Narisu Narisu, Peter S Chines, Antti J Kangas, Pasi Soininen, Mika Ala-Korpela, Johanna Kuusisto, Francis S Collins, Markku Laakso, Michael Boehnke, and Karen L Mohlke
Subjects: Genetics, QH426-470
Abstract: Lipid and lipoprotein subclasses are associated with metabolic and cardiovascular diseases, yet the genetic contributions to variability in subclass traits are not fully understood. We conducted single-variant and gene-based association tests between 15.1M variants from genome-wide and exome array and imputed genotypes and 72 lipid and lipoprotein traits in 8,372 Finns. After accounting for 885 variants at 157 previously identified lipid loci, we identified five novel signals near established loci at HIF3A, ADAMTS3, PLTP, LCAT, and LIPG. Four of the signals were identified with a low-frequency (0.005
Published: 2017
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45. Correction: Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults.

Author: Mariaelisa Graff, Robert A Scott, Anne E Justice, Kristin L Young, Mary F Feitosa, Llilda Barata, Thomas W Winkler, Audrey Y Chu, Anubha Mahajan, David Hadley, Luting Xue, Tsegaselassie Workalemahu, Nancy L Heard-Costa, Marcel den Hoed, Tarunveer S Ahluwalia, Qibin Qi, Julius S Ngwa, Frida Renström, Lydia Quaye, John D Eicher, James E Hayes, Marilyn Cornelis, Zoltan Kutalik, Elise Lim, Jian'an Luan, Jennifer E Huffman, Weihua Zhang, Wei Zhao, Paula J Griffin, Toomas Haller, Shafqat Ahmad, Pedro M Marques-Vidal, Stephanie Bien, Loic Yengo, Alexander Teumer, Albert Vernon Smith, Meena Kumari, Marie Neergaard Harder, Johanne Marie Justesen, Marcus E Kleber, Mette Hollensted, Kurt Lohman, Natalia V Rivera, John B Whitfield, Jing Hua Zhao, Heather M Stringham, Leo-Pekka Lyytikäinen, Charlotte Huppertz, Gonneke Willemsen, Wouter J Peyrot, Ying Wu, Kati Kristiansson, Ayse Demirkan, Myriam Fornage, Maija Hassinen, Lawrence F Bielak, Gemma Cadby, Toshiko Tanaka, Reedik Mägi, Peter J van der Most, Anne U Jackson, Jennifer L Bragg-Gresham, Veronique Vitart, Jonathan Marten, Pau Navarro, Claire Bellis, Dorota Pasko, Åsa Johansson, Søren Snitker, Yu-Ching Cheng, Joel Eriksson, Unhee Lim, Mette Aadahl, Linda S Adair, Najaf Amin, Beverley Balkau, Juha Auvinen, John Beilby, Richard N Bergman, Sven Bergmann, Alain G Bertoni, John Blangero, Amélie Bonnefond, Lori L Bonnycastle, Judith B Borja, Søren Brage, Fabio Busonero, Steve Buyske, Harry Campbell, Peter S Chines, Francis S Collins, Tanguy Corre, George Davey Smith, Graciela E Delgado, Nicole Dueker, Marcus Dörr, Tapani Ebeling, Gudny Eiriksdottir, Tõnu Esko, Jessica D Faul, Mao Fu, Kristine Færch, Christian Gieger, Sven Gläser, Jian Gong, Penny Gordon-Larsen, Harald Grallert, Tanja B Grammer, Niels Grarup, Gerard van Grootheest, Kennet Harald, Nicholas D Hastie, Aki S Havulinna, Dena Hernandez, Lucia Hindorff, Lynne J Hocking, Oddgeir L Holmens, Christina Holzapfel, Jouke Jan Hottenga, Jie Huang, Tao Huang, Jennie Hui, Cornelia Huth, Nina Hutri-Kähönen, Alan L James, John-Olov Jansson, Min A Jhun, Markus Juonala, Leena Kinnunen, Heikki A Koistinen, Ivana Kolcic, Pirjo Komulainen, Johanna Kuusisto, Kirsti Kvaløy, Mika Kähönen, Timo A Lakka, Lenore J Launer, Benjamin Lehne, Cecilia M Lindgren, Mattias Lorentzon, Robert Luben, Michel Marre, Yuri Milaneschi, Keri L Monda, Grant W Montgomery, Marleen H M De Moor, Antonella Mulas, Martina Müller-Nurasyid, A W Musk, Reija Männikkö, Satu Männistö, Narisu Narisu, Matthias Nauck, Jennifer A Nettleton, Ilja M Nolte, Albertine J Oldehinkel, Matthias Olden, Ken K Ong, Sandosh Padmanabhan, Lavinia Paternoster, Jeremiah Perez, Markus Perola, Annette Peters, Ulrike Peters, Patricia A Peyser, Inga Prokopenko, Hannu Puolijoki, Olli T Raitakari, Tuomo Rankinen, Laura J Rasmussen-Torvik, Rajesh Rawal, Paul M Ridker, Lynda M Rose, Igor Rudan, Cinzia Sarti, Mark A Sarzynski, Kai Savonen, William R Scott, Serena Sanna, Alan R Shuldiner, Steve Sidney, Günther Silbernagel, Blair H Smith, Jennifer A Smith, Harold Snieder, Alena Stančáková, Barbara Sternfeld, Amy J Swift, Tuija Tammelin, Sian-Tsung Tan, Barbara Thorand, Dorothée Thuillier, Liesbeth Vandenput, Henrik Vestergaard, Jana V van Vliet-Ostaptchouk, Marie-Claude Vohl, Uwe Völker, Gérard Waeber, Mark Walker, Sarah Wild, Andrew Wong, Alan F Wright, M Carola Zillikens, Niha Zubair, Christopher A Haiman, Loic Lemarchand, Ulf Gyllensten, Claes Ohlsson, Albert Hofman, Fernando Rivadeneira, André G Uitterlinden, Louis Pérusse, James F Wilson, Caroline Hayward, Ozren Polasek, Francesco Cucca, Kristian Hveem, Catharina A Hartman, Anke Tönjes, Stefania Bandinelli, Lyle J Palmer, Sharon L R Kardia, Rainer Rauramaa, Thorkild I A Sørensen, Jaakko Tuomilehto, Veikko Salomaa, Brenda W J H Penninx, Eco J C de Geus, Dorret I Boomsma, Terho Lehtimäki, Massimo Mangino, Markku Laakso, Claude Bouchard, Nicholas G Martin, Diana Kuh, Yongmei Liu, Allan Linneberg, Winfried März, Konstantin Strauch, Mika Kivimäki, Tamara B Harris, Vilmundur Gudnason, Henry Völzke, Lu Qi, Marjo-Riitta Järvelin, John C Chambers, Jaspal S Kooner, Philippe Froguel, Charles Kooperberg, Peter Vollenweider, Göran Hallmans, Torben Hansen, Oluf Pedersen, Andres Metspalu, Nicholas J Wareham, Claudia Langenberg, David R Weir, David J Porteous, Eric Boerwinkle, Daniel I Chasman, CHARGE Consortium, EPIC-InterAct Consortium, PAGE Consortium, Gonçalo R Abecasis, Inês Barroso, Mark I McCarthy, Timothy M Frayling, Jeffrey R O'Connell, Cornelia M van Duijn, Michael Boehnke, Iris M Heid, Karen L Mohlke, David P Strachan, Caroline S Fox, Ching-Ti Liu, Joel N Hirschhorn, Robert J Klein, Andrew D Johnson, Ingrid B Borecki, Paul W Franks, Kari E North, L Adrienne Cupples, Ruth J F Loos, and Tuomas O Kilpeläinen
Subjects: Genetics, QH426-470
Abstract: [This corrects the article DOI: 10.1371/journal.pgen.1006528.].
Published: 2017
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46. Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults.

Author: Mariaelisa Graff, Robert A Scott, Anne E Justice, Kristin L Young, Mary F Feitosa, Llilda Barata, Thomas W Winkler, Audrey Y Chu, Anubha Mahajan, David Hadley, Luting Xue, Tsegaselassie Workalemahu, Nancy L Heard-Costa, Marcel den Hoed, Tarunveer S Ahluwalia, Qibin Qi, Julius S Ngwa, Frida Renström, Lydia Quaye, John D Eicher, James E Hayes, Marilyn Cornelis, Zoltan Kutalik, Elise Lim, Jian'an Luan, Jennifer E Huffman, Weihua Zhang, Wei Zhao, Paula J Griffin, Toomas Haller, Shafqat Ahmad, Pedro M Marques-Vidal, Stephanie Bien, Loic Yengo, Alexander Teumer, Albert Vernon Smith, Meena Kumari, Marie Neergaard Harder, Johanne Marie Justesen, Marcus E Kleber, Mette Hollensted, Kurt Lohman, Natalia V Rivera, John B Whitfield, Jing Hua Zhao, Heather M Stringham, Leo-Pekka Lyytikäinen, Charlotte Huppertz, Gonneke Willemsen, Wouter J Peyrot, Ying Wu, Kati Kristiansson, Ayse Demirkan, Myriam Fornage, Maija Hassinen, Lawrence F Bielak, Gemma Cadby, Toshiko Tanaka, Reedik Mägi, Peter J van der Most, Anne U Jackson, Jennifer L Bragg-Gresham, Veronique Vitart, Jonathan Marten, Pau Navarro, Claire Bellis, Dorota Pasko, Åsa Johansson, Søren Snitker, Yu-Ching Cheng, Joel Eriksson, Unhee Lim, Mette Aadahl, Linda S Adair, Najaf Amin, Beverley Balkau, Juha Auvinen, John Beilby, Richard N Bergman, Sven Bergmann, Alain G Bertoni, John Blangero, Amélie Bonnefond, Lori L Bonnycastle, Judith B Borja, Søren Brage, Fabio Busonero, Steve Buyske, Harry Campbell, Peter S Chines, Francis S Collins, Tanguy Corre, George Davey Smith, Graciela E Delgado, Nicole Dueker, Marcus Dörr, Tapani Ebeling, Gudny Eiriksdottir, Tõnu Esko, Jessica D Faul, Mao Fu, Kristine Færch, Christian Gieger, Sven Gläser, Jian Gong, Penny Gordon-Larsen, Harald Grallert, Tanja B Grammer, Niels Grarup, Gerard van Grootheest, Kennet Harald, Nicholas D Hastie, Aki S Havulinna, Dena Hernandez, Lucia Hindorff, Lynne J Hocking, Oddgeir L Holmens, Christina Holzapfel, Jouke Jan Hottenga, Jie Huang, Tao Huang, Jennie Hui, Cornelia Huth, Nina Hutri-Kähönen, Alan L James, John-Olov Jansson, Min A Jhun, Markus Juonala, Leena Kinnunen, Heikki A Koistinen, Ivana Kolcic, Pirjo Komulainen, Johanna Kuusisto, Kirsti Kvaløy, Mika Kähönen, Timo A Lakka, Lenore J Launer, Benjamin Lehne, Cecilia M Lindgren, Mattias Lorentzon, Robert Luben, Michel Marre, Yuri Milaneschi, Keri L Monda, Grant W Montgomery, Marleen H M De Moor, Antonella Mulas, Martina Müller-Nurasyid, A W Musk, Reija Männikkö, Satu Männistö, Narisu Narisu, Matthias Nauck, Jennifer A Nettleton, Ilja M Nolte, Albertine J Oldehinkel, Matthias Olden, Ken K Ong, Sandosh Padmanabhan, Lavinia Paternoster, Jeremiah Perez, Markus Perola, Annette Peters, Ulrike Peters, Patricia A Peyser, Inga Prokopenko, Hannu Puolijoki, Olli T Raitakari, Tuomo Rankinen, Laura J Rasmussen-Torvik, Rajesh Rawal, Paul M Ridker, Lynda M Rose, Igor Rudan, Cinzia Sarti, Mark A Sarzynski, Kai Savonen, William R Scott, Serena Sanna, Alan R Shuldiner, Steve Sidney, Günther Silbernagel, Blair H Smith, Jennifer A Smith, Harold Snieder, Alena Stančáková, Barbara Sternfeld, Amy J Swift, Tuija Tammelin, Sian-Tsung Tan, Barbara Thorand, Dorothée Thuillier, Liesbeth Vandenput, Henrik Vestergaard, Jana V van Vliet-Ostaptchouk, Marie-Claude Vohl, Uwe Völker, Gérard Waeber, Mark Walker, Sarah Wild, Andrew Wong, Alan F Wright, M Carola Zillikens, Niha Zubair, Christopher A Haiman, Loic Lemarchand, Ulf Gyllensten, Claes Ohlsson, Albert Hofman, Fernando Rivadeneira, André G Uitterlinden, Louis Pérusse, James F Wilson, Caroline Hayward, Ozren Polasek, Francesco Cucca, Kristian Hveem, Catharina A Hartman, Anke Tönjes, Stefania Bandinelli, Lyle J Palmer, Sharon L R Kardia, Rainer Rauramaa, Thorkild I A Sørensen, Jaakko Tuomilehto, Veikko Salomaa, Brenda W J H Penninx, Eco J C de Geus, Dorret I Boomsma, Terho Lehtimäki, Massimo Mangino, Markku Laakso, Claude Bouchard, Nicholas G Martin, Diana Kuh, Yongmei Liu, Allan Linneberg, Winfried März, Konstantin Strauch, Mika Kivimäki, Tamara B Harris, Vilmundur Gudnason, Henry Völzke, Lu Qi, Marjo-Riitta Järvelin, John C Chambers, Jaspal S Kooner, Philippe Froguel, Charles Kooperberg, Peter Vollenweider, Göran Hallmans, Torben Hansen, Oluf Pedersen, Andres Metspalu, Nicholas J Wareham, Claudia Langenberg, David R Weir, David J Porteous, Eric Boerwinkle, Daniel I Chasman, CHARGE Consortium, EPIC-InterAct Consortium, PAGE Consortium, Gonçalo R Abecasis, Inês Barroso, Mark I McCarthy, Timothy M Frayling, Jeffrey R O'Connell, Cornelia M van Duijn, Michael Boehnke, Iris M Heid, Karen L Mohlke, David P Strachan, Caroline S Fox, Ching-Ti Liu, Joel N Hirschhorn, Robert J Klein, Andrew D Johnson, Ingrid B Borecki, Paul W Franks, Kari E North, L Adrienne Cupples, Ruth J F Loos, and Tuomas O Kilpeläinen
Subjects: Genetics, QH426-470
Abstract: Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.
Published: 2017
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47. The genetic architecture of type 2 diabetes

Author: Fuchsberger, Christian, Flannick, Jason, Teslovich, Tanya M., Mahajan, Anubha, Agarwala, Vineeta, Gaulton, Kyle J., Ma, Clement, Fontanillas, Pierre, Moutsianas, Loukas, McCarthy, Davis J., Rivas, Manuel A., Perry, John R. B., Sim, Xueling, Blackwell, Thomas W., Robertson, Neil R., Rayner, N. William, Cingolani, Pablo, Locke, Adam E., Tajes, Juan Fernandez, Highland, Heather M., Dupuis, Josee, Chines, Peter S., Lindgren, Cecilia M., Hartl, Christopher, Jackson, Anne U., Chen, Han, Huyghe, Jeroen R., van de Bunt, Martijn, Pearson, Richard D., Kumar, Ashish, Müller-Nurasyid, Martina, Grarup, Niels, Stringham, Heather M., Gamazon, Eric R., Lee, Jaehoon, Chen, Yuhui, Scott, Robert A., Below, Jennifer E., Chen, Peng, Huang, Jinyan, Go, Min Jin, Stitzel, Michael L., Pasko, Dorota, Parker, Stephen C. J., Varga, Tibor V., Green, Todd, Beer, Nicola L., Day-Williams, Aaron G., Ferreira, Teresa, Fingerlin, Tasha, Horikoshi, Momoko, Hu, Cheng, Huh, Iksoo, Ikram, Mohammad Kamran, Kim, Bong-Jo, Kim, Yongkang, Kim, Young Jin, Kwon, Min-Seok, Lee, Juyoung, Lee, Selyeong, Lin, Keng-Han, Maxwell, Taylor J., Nagai, Yoshihiko, Wang, Xu, Welch, Ryan P., Yoon, Joon, Zhang, Weihua, Barzilai, Nir, Voight, Benjamin F., Han, Bok-Ghee, Jenkinson, Christopher P., Kuulasmaa, Teemu, Kuusisto, Johanna, Manning, Alisa, Ng, Maggie C. Y., Palmer, Nicholette D., Balkau, Beverley, Stančáková, Alena, Abboud, Hanna E., Boeing, Heiner, Giedraitis, Vilmantas, Prabhakaran, Dorairaj, Gottesman, Omri, Scott, James, Carey, Jason, Kwan, Phoenix, Grant, George, Smith, Joshua D., Neale, Benjamin M., Purcell, Shaun, Butterworth, Adam S., Howson, Joanna M. M., Lee, Heung Man, Lu, Yingchang, Kwak, Soo-Heon, Zhao, Wei, Danesh, John, Lam, Vincent K. L., Park, Kyong Soo, Saleheen, Danish, So, Wing Yee, Tam, Claudia H. T., Afzal, Uzma, Aguilar, David, Arya, Rector, Aung, Tin, Chan, Edmund, Navarro, Carmen, Cheng, Ching-Yu, Palli, Domenico, Correa, Adolfo, Curran, Joanne E., Rybin, Denis, Farook, Vidya S., Fowler, Sharon P., Freedman, Barry I., Griswold, Michael, Hale, Daniel Esten, Hicks, Pamela J., Khor, Chiea-Chuen, Kumar, Satish, Lehne, Benjamin, Thuillier, Dorothée, Lim, Wei Yen, Liu, Jianjun, van der Schouw, Yvonne T., Loh, Marie, Musani, Solomon K., Puppala, Sobha, Scott, William R., Yengo, Loïc, Tan, Sian-Tsung, Taylor Jr., Herman A., Thameem, Farook, Wilson, Gregory, Wong, Tien Yin, Njølstad, Pål Rasmus, Levy, Jonathan C., Mangino, Massimo, Bonnycastle, Lori L., Schwarzmayr, Thomas, Fadista, João, Surdulescu, Gabriela L., Herder, Christian, Groves, Christopher J., Wieland, Thomas, Bork-Jensen, Jette, Brandslund, Ivan, Christensen, Cramer, Koistinen, Heikki A., Doney, Alex S. F., Kinnunen, Leena, Esko, Tõnu, Farmer, Andrew J., Hakaste, Liisa, Hodgkiss, Dylan, Kravic, Jasmina, Lyssenko, Valeriya, Hollensted, Mette, Jørgensen, Marit E., Jørgensen, Torben, Ladenvall, Claes, Justesen, Johanne Marie, Käräjämäki, Annemari, Kriebel, Jennifer, Rathmann, Wolfgang, Lannfelt, Lars, Lauritzen, Torsten, Narisu, Narisu, Linneberg, Allan, Melander, Olle, Milani, Lili, Neville, Matt, Orho-Melander, Marju, Qi, Lu, Qi, Qibin, Roden, Michael, Rolandsson, Olov, Swift, Amy, Rosengren, Anders H., Stirrups, Kathleen, Wood, Andrew R., Mihailov, Evelin, Blancher, Christine, Carneiro, Mauricio O., Maguire, Jared, Poplin, Ryan, Shakir, Khalid, Fennell, Timothy, DePristo, Mark, Hrabé de Angelis, Martin, Deloukas, Panos, Gjesing, Anette P., Jun, Goo, Nilsson, Peter, Murphy, Jacquelyn, Onofrio, Robert, Thorand, Barbara, Hansen, Torben, Meisinger, Christa, Hu, Frank B., Isomaa, Bo, Karpe, Fredrik, Liang, Liming, Peters, Annette, Huth, Cornelia, O’Rahilly, Stephen P., Palmer, Colin N. A., Pedersen, Oluf, Rauramaa, Rainer, Tuomilehto, Jaakko, Salomaa, Veikko, Watanabe, Richard M., Syvänen, Ann-Christine, Bergman, Richard N., Bharadwaj, Dwaipayan, Bottinger, Erwin P., Cho, Yoon Shin, Chandak, Giriraj R., Chan, Juliana C. N., Chia, Kee Seng, Daly, Mark J., Ebrahim, Shah B., Langenberg, Claudia, Elliott, Paul, Jablonski, Kathleen A., Lehman, Donna M., Jia, Weiping, Ma, Ronald C. W., Pollin, Toni I., Sandhu, Manjinder, Tandon, Nikhil, Froguel, Philippe, Barroso, Inês, Teo, Yik Ying, Zeggini, Eleftheria, Loos, Ruth J. F., Small, Kerrin S., Ried, Janina S., DeFronzo, Ralph A., Grallert, Harald, Glaser, Benjamin, Metspalu, Andres, Wareham, Nicholas J., Walker, Mark, Banks, Eric, Gieger, Christian, Ingelsson, Erik, Im, Hae Kyung, Illig, Thomas, Franks, Paul W., Buck, Gemma, Trakalo, Joseph, Buck, David, Prokopenko, Inga, Mägi, Reedik, Lind, Lars, Farjoun, Yossi, Owen, Katharine R., Gloyn, Anna L., Strauch, Konstantin, Tuomi, Tiinamaija, Kooner, Jaspal Singh, Lee, Jong-Young, Park, Taesung, Donnelly, Peter, Morris, Andrew D., Hattersley, Andrew T., Bowden, Donald W., Collins, Francis S., Atzmon, Gil, Chambers, John C., Spector, Timothy D., Laakso, Markku, Strom, Tim M., Bell, Graeme I., Blangero, John, Duggirala, Ravindranath, Tai, E. Shyong, McVean, Gilean, Hanis, Craig L., Wilson, James G., Seielstad, Mark, Frayling, Timothy M., Meigs, James B., Cox, Nancy J., Sladek, Rob, Lander, Eric S., Gabriel, Stacey, Burtt, Noël P., Mohlke, Karen L., Meitinger, Thomas, Groop, Leif, Abecasis, Goncalo, Florez, Jose C., Scott, Laura J., Morris, Andrew P., Kang, Hyun Min, Boehnke, Michael, Altshuler, David, and McCarthy, Mark I.
Published: 2016
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48. Bridging analysis of the efficacy and safety of bazedoxifene in Japanese and global populations of postmenopausal women with osteoporosis

Author: Itabashi, Akira, Yoh, Kousei, Chines, Arkadi A., Miki, Takami, Takada, Masahiko, Sato, Hiroshi, Gorai, Itsuo, Sugimoto, Toshitsugu, Mizunuma, Hideki, Ochi, Hiroshi, Constantine, Ginger D., and Ohta, Hiroaki
Published: 2015
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49. Addressing bias in small RNA library preparation for sequencing: a new protocol recovers microRNAs that evade capture by current methods

Author: Jeanette eBaran-Gale, C. Lisa eKurtz, Michael eErdos, Christina eSison, Alice eYoung, Emily E Fannin, Peter S Chines, and Praveen eSethupathy
Subjects: microRNA, Sequencing, Small RNA library preparation, Adapter ligation bias, Adapter dimers, Genetics, QH426-470
Abstract: Recent advances in sequencing technology have helped unveil the unexpected complexity and diversity of small RNAs. A critical step in small RNA library preparation for sequencing is the ligation of adapter sequences to both the 5’ and 3’ ends of small RNAs. Studies have shown that adapter ligation introduces a significant but widely unappreciated bias in the results of high-throughput small RNA sequencing. We show that due to this bias the two widely used Illumina library preparation protocols produce strikingly different microRNA (miRNA) expression profiles in the same batch of cells. There are 102 highly expressed miRNAs that are >5-fold differentially detected and some miRNAs, such as miR-24-3p, are over 30-fold differentially detected. While some level of bias in library preparation is not surprising, the apparent massive differential bias between these two widely used adapter sets is not well appreciated. In an attempt to mitigate this bias, the new Bioo Scientific NEXTflex V2 protocol utilizes a pool of adapters with random nucleotides at the ligation boundary. We show that this protocol is able to detect robustly several miRNAs that evade capture by the Illumina-based methods. While these analyses do not indicate a definitive gold standard for small RNA library preparation, the results of the NEXTflex protocol do correlate best with RT-qPCR. As increasingly more laboratories seek to study small RNAs, researchers should be aware of the extent to which the results may differ with different protocols, and should make an informed decision about the protocol that best fits their study.
Published: 2015
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50. A genome-wide association search for type 2 diabetes genes in African Americans.

Author: Nicholette D Palmer, Caitrin W McDonough, Pamela J Hicks, Bong H Roh, Maria R Wing, S Sandy An, Jessica M Hester, Jessica N Cooke, Meredith A Bostrom, Megan E Rudock, Matthew E Talbert, Joshua P Lewis, DIAGRAM Consortium, MAGIC Investigators, Assiamira Ferrara, Lingyi Lu, Julie T Ziegler, Michele M Sale, Jasmin Divers, Daniel Shriner, Adebowale Adeyemo, Charles N Rotimi, Maggie C Y Ng, Carl D Langefeld, Barry I Freedman, Donald W Bowden, Benjamin F Voight, Laura J Scott, Valgerdur Steinthorsdottir, Andrew P Morris, Christian Dina, Ryan P Welch, Eleftheria Zeggini, Cornelia Huth, Yurii S Aulchenko, Gudmar Thorleifsson, Laura J McCulloch, Teresa Ferreira, Harald Grallert, Najaf Amin, Guanming Wu, Cristen J Willer, Soumya Raychaudhuri, Steve A McCarroll, Claudia Langenberg, Oliver M Hofmann, Josée Dupuis, Lu Qi, Ayellet V Segrè, Mandy van Hoek, Pau Navarro, Kristin Ardlie, Beverley Balkau, Rafn Benediktsson, Amanda J Bennett, Roza Blagieva, Eric Boerwinkle, Lori L Bonnycastle, Kristina Bengtsson Boström, Bert Bravenboer, Suzannah Bumpstead, Noël P Burtt, Guillaume Charpentier, Peter S Chines, Marilyn Cornelis, David J Couper, Gabe Crawford, Alex S F Doney, Katherine S Elliott, Amanda L Elliott, Michael R Erdos, Caroline S Fox, Christopher S Franklin, Martha Ganser, Christian Gieger, Niels Grarup, Todd Green, Simon Griffin, Christopher J Groves, Candace Guiducci, Samy Hadjadj, Neelam Hassanali, Christian Herder, Bo Isomaa, Anne U Jackson, Paul R V Johnson, Torben Jørgensen, Wen H L Kao, Norman Klopp, Augustine Kong, Peter Kraft, Johanna Kuusisto, Torsten Lauritzen, Man Li, Aloysius Lieverse, Cecilia M Lindgren, Valeriya Lyssenko, Michel Marre, Thomas Meitinger, Kristian Midthjell, Mario A Morken, Narisu Narisu, Peter Nilsson, Katharine R Owen, Felicity Payne, John R B Perry, Ann-Kristin Petersen, Carl Platou, Christine Proença, Inga Prokopenko, Wolfgang Rathmann, N William Rayner, Neil R Robertson, Ghislain Rocheleau, Michael Roden, Michael J Sampson, Richa Saxena, Beverley M Shields, Peter Shrader, Gunnar Sigurdsson, Thomas Sparsø, Klaus Strassburger, Heather M Stringham, Qi Sun, Amy J Swift, Barbara Thorand, Jean Tichet, Tiinamaija Tuomi, Rob M van Dam, Timon W van Haeften, Thijs van Herpt, Jana V van Vliet-Ostaptchouk, G Bragi Walters, Michael N Weedon, Cisca Wijmenga, Jacqueline Witteman, Richard N Bergman, Stephane Cauchi, Francis S Collins, Anna L Gloyn, Ulf Gyllensten, Torben Hansen, Winston A Hide, Graham A Hitman, Albert Hofman, David J Hunter, Kristian Hveem, Markku Laakso, Karen L Mohlke, Andrew D Morris, Colin N A Palmer, Peter P Pramstaller, Igor Rudan, Eric Sijbrands, Lincoln D Stein, Jaakko Tuomilehto, Andre Uitterlinden, Mark Walker, Nicholas J Wareham, Richard M Watanabe, Goncalo R Abecasis, Bernhard O Boehm, Harry Campbell, Mark J Daly, Andrew T Hattersley, Frank B Hu, James B Meigs, James S Pankow, Oluf Pedersen, H-Erich Wichmann, Inês Barroso, Jose C Florez, Timothy M Frayling, Leif Groop, Rob Sladek, Unnur Thorsteinsdottir, James F Wilson, Thomas Illig, Philippe Froguel, Cornelia M van Duijn, Kari Stefansson, David Altshuler, Michael Boehnke, Mark I McCarthy, Nicole Soranzo, Eleanor Wheeler, Nicole L Glazer, Nabila Bouatia-Naji, Reedik Mägi, Joshua Randall, Toby Johnson, Paul Elliott, Denis Rybin, Peter Henneman, Abbas Dehghan, Jouke Jan Hottenga, Kijoung Song, Anuj Goel, Josephine M Egan, Taina Lajunen, Alex Doney, Stavroula Kanoni, Christine Cavalcanti-Proença, Meena Kumari, Nicholas J Timpson, Carina Zabena, Erik Ingelsson, Ping An, Jeffrey O'Connell, Jian'an Luan, Amanda Elliott, Steven A McCarroll, Rosa Maria Roccasecca, François Pattou, Praveen Sethupathy, Yavuz Ariyurek, Philip Barter, John P Beilby, Yoav Ben-Shlomo, Sven Bergmann, Murielle Bochud, Amélie Bonnefond, Knut Borch-Johnsen, Yvonne Böttcher, Eric Brunner, Suzannah J Bumpstead, Yii-Der Ida Chen, Peter Chines, Robert Clarke, Lachlan J M Coin, Matthew N Cooper, Laura Crisponi, Ian N M Day, Eco J C de Geus, Jerome Delplanque, Annette C Fedson, Antje Fischer-Rosinsky, Nita G Forouhi, Rune Frants, Maria Grazia Franzosi, Pilar Galan, Mark O Goodarzi, Jürgen Graessler, Scott Grundy, Rhian Gwilliam, Göran Hallmans, Naomi Hammond, Xijing Han, Anna-Liisa Hartikainen, Caroline Hayward, Simon C Heath, Serge Hercberg, Andrew A Hicks, David R Hillman, Aroon D Hingorani, Jennie Hui, Joe Hung, Antti Jula, Marika Kaakinen, Jaakko Kaprio, Y Antero Kesaniemi, Mika Kivimaki, Beatrice Knight, Seppo Koskinen, Peter Kovacs, Kirsten Ohm Kyvik, G Mark Lathrop, Debbie A Lawlor, Olivier Le Bacquer, Cécile Lecoeur, Yun Li, Robert Mahley, Massimo Mangino, Alisa K Manning, María Teresa Martínez-Larrad, Jarred B McAteer, Ruth McPherson, Christa Meisinger, David Melzer, David Meyre, Braxton D Mitchell, Sutapa Mukherjee, Silvia Naitza, Matthew J Neville, Ben A Oostra, Marco Orrù, Ruth Pakyz, Giuseppe Paolisso, Cristian Pattaro, Daniel Pearson, John F Peden, Nancy L Pedersen, Markus Perola, Andreas F H Pfeiffer, Irene Pichler, Ozren Polasek, Danielle Posthuma, Simon C Potter, Anneli Pouta, Michael A Province, Bruce M Psaty, Nigel W Rayner, Kenneth Rice, Samuli Ripatti, Fernando Rivadeneira, Olov Rolandsson, Annelli Sandbaek, Manjinder Sandhu, Serena Sanna, Avan Aihie Sayer, Paul Scheet, Udo Seedorf, Stephen J Sharp, Beverley Shields, Eric J G Sijbrands, Angela Silveira, Laila Simpson, Andrew Singleton, Nicholas L Smith, Ulla Sovio, Amy Swift, Holly Syddall, Ann-Christine Syvänen, Toshiko Tanaka, Anke Tönjes, André G Uitterlinden, Ko Willems van Dijk, Dhiraj Varma, Sophie Visvikis-Siest, Veronique Vitart, Nicole Vogelzangs, Gérard Waeber, Peter J Wagner, Andrew Walley, Kim L Ward, Hugh Watkins, Sarah H Wild, Gonneke Willemsen, Jaqueline C M Witteman, John W G Yarnell, Diana Zelenika, Björn Zethelius, Guangju Zhai, Jing Hua Zhao, M Carola Zillikens, Ingrid B Borecki, Ruth J F Loos, Pierre Meneton, Patrik K E Magnusson, David M Nathan, Gordon H Williams, Kaisa Silander, Veikko Salomaa, George Davey Smith, Stefan R Bornstein, Peter Schwarz, Joachim Spranger, Fredrik Karpe, Alan R Shuldiner, Cyrus Cooper, George V Dedoussis, Manuel Serrano-Ríos, Lars Lind, Lyle J Palmer, Paul W Franks, Shah Ebrahim, Michael Marmot, W H Linda Kao, Peter Paul Pramstaller, Alan F Wright, Michael Stumvoll, Anders Hamsten, Thomas A Buchanan, Timo T Valle, Jerome I Rotter, David S Siscovick, Brenda W J H Penninx, Dorret I Boomsma, Panos Deloukas, Timothy D Spector, Luigi Ferrucci, Antonio Cao, Angelo Scuteri, David Schlessinger, Manuela Uda, Aimo Ruokonen, Marjo-Riitta Jarvelin, Dawn M Waterworth, Peter Vollenweider, Leena Peltonen, Vincent Mooser, and Robert Sladek
Subjects: Medicine, Science
Abstract: African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P
Published: 2012
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