scispace - formally typeset
Search or ask a question
Author

Fabio Busonero

Bio: Fabio Busonero is an academic researcher from National Research Council. The author has contributed to research in topics: Genome-wide association study & GABAA receptor. The author has an hindex of 34, co-authored 51 publications receiving 13892 citations. Previous affiliations of Fabio Busonero include University of Cagliari & National Institutes of Health.


Papers
More filters
Journal ArticleDOI
TL;DR: Genetic loci associated with body mass index map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor, which may provide new insights into human body weight regulation.
Abstract: Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and similar to 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 x 10(-8)), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.

2,632 citations

Journal ArticleDOI
Shane A. McCarthy1, Sayantan Das2, Warren W. Kretzschmar3, Olivier Delaneau4, Andrew R. Wood5, Alexander Teumer6, Hyun Min Kang2, Christian Fuchsberger2, Petr Danecek1, Kevin Sharp3, Yang Luo1, C Sidore7, Alan Kwong2, Nicholas J. Timpson8, Seppo Koskinen, Scott I. Vrieze9, Laura J. Scott2, He Zhang2, Anubha Mahajan3, Jan H. Veldink, Ulrike Peters10, Ulrike Peters11, Carlos N. Pato12, Cornelia M. van Duijn13, Christopher E. Gillies2, Ilaria Gandin14, Massimo Mezzavilla, Arthur Gilly1, Massimiliano Cocca14, Michela Traglia, Andrea Angius7, Jeffrey C. Barrett1, D.I. Boomsma15, Kari Branham2, Gerome Breen16, Gerome Breen17, Chad M. Brummett2, Fabio Busonero7, Harry Campbell18, Andrew T. Chan19, Sai Chen2, Emily Y. Chew20, Francis S. Collins20, Laura J Corbin8, George Davey Smith8, George Dedoussis21, Marcus Dörr6, Aliki-Eleni Farmaki21, Luigi Ferrucci20, Lukas Forer22, Ross M. Fraser2, Stacey Gabriel23, Shawn Levy, Leif Groop24, Leif Groop25, Tabitha A. Harrison10, Andrew T. Hattersley5, Oddgeir L. Holmen26, Kristian Hveem26, Matthias Kretzler2, James Lee27, Matt McGue28, Thomas Meitinger29, David Melzer5, Josine L. Min8, Karen L. Mohlke30, John B. Vincent31, Matthias Nauck6, Deborah A. Nickerson11, Aarno Palotie23, Aarno Palotie19, Michele T. Pato12, Nicola Pirastu14, Melvin G. McInnis2, J. Brent Richards17, J. Brent Richards32, Cinzia Sala, Veikko Salomaa, David Schlessinger20, Sebastian Schoenherr22, P. Eline Slagboom33, Kerrin S. Small17, Tim D. Spector17, Dwight Stambolian34, Marcus A. Tuke5, Jaakko Tuomilehto, Leonard H. van den Berg, Wouter van Rheenen, Uwe Völker6, Cisca Wijmenga35, Daniela Toniolo, Eleftheria Zeggini1, Paolo Gasparini14, Matthew G. Sampson2, James F. Wilson18, Timothy M. Frayling5, Paul I.W. de Bakker36, Morris A. Swertz35, Steven A. McCarroll19, Charles Kooperberg10, Annelot M. Dekker, David Altshuler, Cristen J. Willer2, William G. Iacono28, Samuli Ripatti25, Nicole Soranzo1, Nicole Soranzo27, Klaudia Walter1, Anand Swaroop20, Francesco Cucca7, Carl A. Anderson1, Richard M. Myers, Michael Boehnke2, Mark I. McCarthy3, Mark I. McCarthy37, Richard Durbin1, Gonçalo R. Abecasis2, Jonathan Marchini3 
TL;DR: A reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry leads to accurate genotype imputation at minor allele frequencies as low as 0.1% and a large increase in the number of SNPs tested in association studies.
Abstract: We describe a reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry. Using this resource leads to accurate genotype imputation at minor allele frequencies as low as 0.1% and a large increase in the number of SNPs tested in association studies, and it can help to discover and refine causal loci. We describe remote server resources that allow researchers to carry out imputation and phasing consistently and efficiently.

2,149 citations

Journal ArticleDOI
TL;DR: In this paper, a genome-wide association scan was conducted to identify genetic variants associated with obesity-related quantitative traits in the genetically isolated population of Sardinia, and the results showed that common genetic variants in the FTO gene are associated with substantial changes in body weight.
Abstract: The obesity epidemic is responsible for a substantial economic burden in developed countries and is a major risk factor for type 2 diabetes and cardiovascular disease. The disease is the result not only of several environmental risk factors, but also of genetic predisposition. To take advantage of recent advances in gene-mapping technology, we executed a genome-wide association scan to identify genetic variants associated with obesity-related quantitative traits in the genetically isolated population of Sardinia. Initial analysis suggested that several SNPs in the FTO and PFKP genes were associated with increased BMI, hip circumference, and weight. Within the FTO gene, rs9930506 showed the strongest association with BMI (p ¼ 8.6 310 � 7 ), hip circumference (p ¼ 3.4 3 10 � 8 ), and weight (p ¼ 9.1 3 10 � 7 ). In Sardinia, homozygotes for the rare ‘‘G’’ allele of this SNP (minor allele frequency ¼ 0.46) were 1.3 BMI units heavier than homozygotes for the common ‘‘A’’ allele. Within the PFKP gene, rs6602024 showed very strong association with BMI (p ¼4.9 310 � 6 ). Homozygotes for the rare ‘‘A’’ allele of this SNP (minor allele frequency ¼0.12) were 1.8 BMI units heavier than homozygotes for the common ‘‘G’’ allele. To replicate our findings, we genotyped these two SNPs in the GenNet study. In European Americans (N ¼ 1,496) and in Hispanic Americans (N ¼ 839), we replicated significant association between rs9930506 in the FTO gene and BMI (p-value for meta-analysis of European American and Hispanic American follow-up samples, p ¼0.001), weight (p ¼0.001), and hip circumference (p ¼0.0005). We did not replicate association between rs6602024 and obesity-related traits in the GenNet sample, although we found that in European Americans, Hispanic Americans, and African Americans, homozygotes for the rare ‘‘A’’ allele were, on average, 1.0–3.0 BMI units heavier than homozygotes for the more common ‘‘G’’ allele. In summary, we have completed a whole genome– association scan for three obesity-related quantitative traits and report that common genetic variants in the FTO gene are associated with substantial changes in BMI, hip circumference, and body weight. These changes could have a significant impact on the risk of obesity-related morbidity in the general population.

1,619 citations

Journal ArticleDOI
TL;DR: In this paper, the authors used genotype imputation and meta-analysis to identify genetic variants influencing plasma lipid concentrations, using three genome-wide scans totaling 8,816 individuals and comprising 6,068 individuals specific to their study.
Abstract: To identify genetic variants influencing plasma lipid concentrations, we first used genotype imputation and meta-analysis to combine three genome-wide scans totaling 8,816 individuals and comprising 6,068 individuals specific to our study (1,874 individuals from the FUSION study of type 2 diabetes and 4,184 individuals from the SardiNIA study of aging-associated variables) and 2,758 individuals from the Diabetes Genetics Initiative, reported in a companion study in this issue. We subsequently examined promising signals in 11,569 additional individuals. Overall, we identify strongly associated variants in eleven loci previously implicated in lipid metabolism (ABCA1, the APOA5-APOA4-APOC3-APOA1 and APOE-APOC clusters, APOB, CETP, GCKR, LDLR, LPL, LIPC, LIPG and PCSK9) and also in several newly identified loci (near MVK-MMAB and GALNT2, with variants primarily associated with high-density lipoprotein (HDL) cholesterol; near SORT1, with variants primarily associated with low-density lipoprotein (LDL) cholesterol; near TRIB1, MLXIPL and ANGPTL3, with variants primarily associated with triglycerides; and a locus encompassing several genes near NCAN, with variants strongly associated with both triglycerides and LDL cholesterol). Notably, the 11 independent variants associated with increased LDL cholesterol concentrations in our study also showed increased frequency in a sample of coronary artery disease cases versus controls.

1,616 citations

Shane A. McCarthy, Sayantan Das, Warren W. Kretzschmar, Olivier Delaneau, Andrew R. Wood, Alexander Teumer, Hyun Min Kang, Christian Fuchsberger, Petr Danecek, Kevin Sharp, Yang Luo, Carlo Sidorel, Alan Kwong, Nicholas J. Timpson, Seppo Koskinen, Scott I. Vrieze, Laura J. Scott, He Zhang, Anubha Mahajan, Jan H. Veldink, Ulrike Peters, Carlos N. Pato, Cornelia M. van Duijn, Christopher E. Gillies, Ilaria Gandin, Massimo Mezzavilla, Arthur Gilly, Massimiliano Cocca, Michela Traglia, Andrea Angius, Jeffrey C. Barrett, D.I. Boomsma, Kari Branham, Gerome Breen, Chad M. Brummett, Fabio Busonero, Harry Campbell, Andrew T. Chan, Sai Che, Emily Y. Chew, Francis S. Collins, Laura J Corbin, George Davey Smith, George Dedoussis, Marcus Dörr, Aliki-Eleni Farmaki, Luigi Ferrucci, Lukas Forer, Ross M. Fraser, Stacey Gabriel, Shawn Levy, Leif Groop, Tabitha A. Harrison, Andrew T. Hattersley, Oddgeir L. Holmen, Kristian Hveem, Matthias Kretzler, James Lee, Matt McGue, Thomas Meitinger, David Melzer, Josine L. Min, Karen L. Mohlke, John B. Vincent, Matthias Nauck, Deborah A. Nickerson, Aarno Palotie, Michele T. Pato, Nicola Pirastu, Melvin G. McInnis, J. Brent Richards, Cinzia Sala, Veikko Salomaa, David Schlessinger, Sebastian Schoenherr, P. Eline Slagboom, Kerrin S. Small, Tim D. Spector, Dwight Stambolian, Marcus A. Tuke, Jaakko Tuomilehto, Leonard H. van den Berg, Wouter van Rheenen, Uwe Völker, Cisca Wijmenga, Daniela Toniolo, Eleftheria Zeggini, Paolo Gasparini, Matthew G. Sampson, James F. Wilson, Timothy M. Frayling, Paul I.W. de Bakker, Morris A. Swertz, Steven A. McCarroll, Charles Kooperberg, Annelot M. Dekker, David Altshuler, Cristen J. Willer, William G. Iacono, Samuli Ripatti, Nicole Soranzo, Klaudia Walter, Anand Swaroop, Francesco Cucca, Carl A. Anderson, Richard M. Myers, Michael Boehnke, Mark I. McCarthy, Richard Durbin, Gonçalo R. Abecasis, Jonathan Marchini 
01 Jan 2016
TL;DR: In this article, a reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry is presented.
Abstract: We describe a reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry. Using this resource leads to accurate genotype imputation at minor allele frequencies as low as 0.1% and a large increase in the number of SNPs tested in association studies, and it can help to discover and refine causal loci. We describe remote server resources that allow researchers to carry out imputation and phasing consistently and efficiently.

1,261 citations


Cited by
More filters
Journal ArticleDOI
Adam Auton1, Gonçalo R. Abecasis2, David Altshuler3, Richard Durbin4  +514 moreInstitutions (90)
01 Oct 2015-Nature
TL;DR: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations, and has reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-generation sequencing, deep exome sequencing, and dense microarray genotyping.
Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.

12,661 citations

Journal ArticleDOI
28 Oct 2010-Nature
TL;DR: The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation as a foundation for investigating the relationship between genotype and phenotype as mentioned in this paper, and the results of the pilot phase of the project, designed to develop and compare different strategies for genomewide sequencing with high-throughput platforms.
Abstract: The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation as a foundation for investigating the relationship between genotype and phenotype. Here we present results of the pilot phase of the project, designed to develop and compare different strategies for genome-wide sequencing with high-throughput platforms. We undertook three projects: low-coverage whole-genome sequencing of 179 individuals from four populations; high-coverage sequencing of two mother-father-child trios; and exon-targeted sequencing of 697 individuals from seven populations. We describe the location, allele frequency and local haplotype structure of approximately 15 million single nucleotide polymorphisms, 1 million short insertions and deletions, and 20,000 structural variants, most of which were previously undescribed. We show that, because we have catalogued the vast majority of common variation, over 95% of the currently accessible variants found in any individual are present in this data set. On average, each person is found to carry approximately 250 to 300 loss-of-function variants in annotated genes and 50 to 100 variants previously implicated in inherited disorders. We demonstrate how these results can be used to inform association and functional studies. From the two trios, we directly estimate the rate of de novo germline base substitution mutations to be approximately 10(-8) per base pair per generation. We explore the data with regard to signatures of natural selection, and identify a marked reduction of genetic variation in the neighbourhood of genes, due to selection at linked sites. These methods and public data will support the next phase of human genetic research.

7,538 citations

Journal ArticleDOI
TL;DR: March 5, 2019 e1 WRITING GROUP MEMBERS Emelia J. Virani, MD, PhD, FAHA, Chair Elect On behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee.
Abstract: March 5, 2019 e1 WRITING GROUP MEMBERS Emelia J. Benjamin, MD, ScM, FAHA, Chair Paul Muntner, PhD, MHS, FAHA, Vice Chair Alvaro Alonso, MD, PhD, FAHA Marcio S. Bittencourt, MD, PhD, MPH Clifton W. Callaway, MD, FAHA April P. Carson, PhD, MSPH, FAHA Alanna M. Chamberlain, PhD Alexander R. Chang, MD, MS Susan Cheng, MD, MMSc, MPH, FAHA Sandeep R. Das, MD, MPH, MBA, FAHA Francesca N. Delling, MD, MPH Luc Djousse, MD, ScD, MPH Mitchell S.V. Elkind, MD, MS, FAHA Jane F. Ferguson, PhD, FAHA Myriam Fornage, PhD, FAHA Lori Chaffin Jordan, MD, PhD, FAHA Sadiya S. Khan, MD, MSc Brett M. Kissela, MD, MS Kristen L. Knutson, PhD Tak W. Kwan, MD, FAHA Daniel T. Lackland, DrPH, FAHA Tené T. Lewis, PhD Judith H. Lichtman, PhD, MPH, FAHA Chris T. Longenecker, MD Matthew Shane Loop, PhD Pamela L. Lutsey, PhD, MPH, FAHA Seth S. Martin, MD, MHS, FAHA Kunihiro Matsushita, MD, PhD, FAHA Andrew E. Moran, MD, MPH, FAHA Michael E. Mussolino, PhD, FAHA Martin O’Flaherty, MD, MSc, PhD Ambarish Pandey, MD, MSCS Amanda M. Perak, MD, MS Wayne D. Rosamond, PhD, MS, FAHA Gregory A. Roth, MD, MPH, FAHA Uchechukwu K.A. Sampson, MD, MBA, MPH, FAHA Gary M. Satou, MD, FAHA Emily B. Schroeder, MD, PhD, FAHA Svati H. Shah, MD, MHS, FAHA Nicole L. Spartano, PhD Andrew Stokes, PhD David L. Tirschwell, MD, MS, MSc, FAHA Connie W. Tsao, MD, MPH, Vice Chair Elect Mintu P. Turakhia, MD, MAS, FAHA Lisa B. VanWagner, MD, MSc, FAST John T. Wilkins, MD, MS, FAHA Sally S. Wong, PhD, RD, CDN, FAHA Salim S. Virani, MD, PhD, FAHA, Chair Elect On behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee

5,739 citations

Journal ArticleDOI
TL;DR: The Statistical Update represents the most up-to-date statistics related to heart disease, stroke, and the cardiovascular risk factors listed in the AHA's My Life Check - Life’s Simple 7, which include core health behaviors and health factors that contribute to cardiovascular health.
Abstract: Each chapter listed in the Table of Contents (see next page) is a hyperlink to that chapter. The reader clicks the chapter name to access that chapter. Each chapter listed here is a hyperlink. Click on the chapter name to be taken to that chapter. Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together in a single document the most up-to-date statistics related to heart disease, stroke, and the cardiovascular risk factors listed in the AHA’s My Life Check - Life’s Simple 7 (Figure1), which include core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure [BP], and glucose control) that contribute to cardiovascular health. The Statistical Update represents …

5,102 citations

Journal ArticleDOI
TL;DR: This year's edition of the Statistical Update includes data on the monitoring and benefits of cardiovascular health in the population, metrics to assess and monitor healthy diets, an enhanced focus on social determinants of health, a focus on the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors, implementation strategies, and implications of the American Heart Association’s 2020 Impact Goals.
Abstract: Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports on the most up-to-date statistics related to heart disease, stroke, and cardiovas...

5,078 citations