Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture. - Test2 - elhamkhani - TriplyDB

Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture.

Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture.

http://www.wikidata.org/entity/Q34268288

about

Rapid-throughput skeletal phenotyping of 100 knockout mice identifies 9 new genes that determine bone strength The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data Mutations in WNT1 cause different forms of bone fragility Genome-wide meta-analyses of multiancestry cohorts identify multiple new susceptibility loci for refractive error and myopia The role of microRNAs in bone remodeling Fundamentals of Clinical Outcomes Assessment for Spinal Disorders: Clinical Outcome Instruments and Applications.Perspectives on pharmacogenomics of antiretroviral medications and HIV-associated comorbidities Bone composition: relationship to bone fragility and antiosteoporotic drug effects Endocrine crosstalk between muscle and bone A new WNT on the bone: WNT16, cortical bone thickness, porosity and fractures Clinical review: Genome-wide association studies of skeletal phenotypes: what we have learned and where we are headed Genome-wide association reveals QTL for growth, bone and in vivo carcass traits as assessed by computed tomography in Scottish Blackface lambs.Novel genetic loci underlying human intracranial volume identified through genome-wide association Rapid phenotyping of knockout mice to identify genetic determinants of bone strength The National Osteoporosis Foundation's position statement on peak bone mass development and lifestyle factors: a systematic review and implementation recommendations 2014 Female Athlete Triad Coalition Consensus Statement on Treatment and Return to Play of the Female Athlete Triad: 1st International Conference held in San Francisco, California, May 2012 and 2nd International Conference held in Indianapolis, Indi On individual genome-wide association studies and their meta-analysis Genetic variants underlying risk of endometriosis: insights from meta-analysis of eight genome-wide association and replication datasets The causal effect of vitamin D binding protein (DBP) levels on calcemic and cardiometabolic diseases: a Mendelian randomization study Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters Assessment of gene-by-sex interaction effect on bone mineral density Meta-analysis identifies a MECOM gene as a novel predisposing factor of osteoporotic fracture Genome-wide association meta-analyses identified 1q43 and 2q32.2 for hip Ward's triangle areal bone mineral density Integrating GWAS and Co-expression Network Data Identifies Bone Mineral Density Genes SPTBN1 and MARK3 and an Osteoblast Functional Module.Using GWAS to identify novel therapeutic targets for osteoporosis.Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture.Contemporary Approaches for Identifying Rare Bone Disease Causing Genes.Quantitative trait loci for bone mineral density and femoral morphology in an advanced intercross population of mice Bicc1 is a genetic determinant of osteoblastogenesis and bone mineral density.Trps1 differentially modulates the bone mineral density between male and female mice and its polymorphism associates with BMD differently between women and men.Systems-level analysis of genome-wide association data Systems genetic analysis of osteoblast-lineage cells The fragile elderly hip: mechanisms associated with age-related loss of strength and toughness Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study.Evaluation of the genetic overlap between osteoarthritis with body mass index and height using genome-wide association scan data Genetic determinants of heel bone properties: genome-wide association meta-analysis and replication in the GEFOS/GENOMOS consortium Joint analysis of functional genomic data and genome-wide association studies of 18 human traits.Functional and genomic context in pathway analysis of GWAS data.Applying personal genetic data to injury risk assessment in athletes.Integrative Analysis of Transcriptomic and Epigenomic Data to Reveal Regulation Patterns for BMD Variation.

P2860

Q21563368-013051A5-950C-41C3-B43E-67C67D1F5929 Q24289484-563A31D8-B834-4605-93EA-9879B556FD7F Q24336287-84A1A0B2-0F13-4F77-B7FA-31D157BE9177 Q24631992-C00C080F-32B7-45C9-B9C4-851F5EDC17CA Q26799815-0B438736-0930-437D-8869-9A5DA8B8E6B8 Q26801597-D4C32603-1A56-4FC2-B098-06DCE7D2878E Q26853274-C2054629-0C95-4D26-BAC7-EF452E8745D6 Q26863596-972ECDA1-1361-4BDF-91FE-324D48BE1970 Q27008987-4678F0E8-3A4E-4C85-81ED-394CF31462D1 Q27009420-2223FBB6-6FB5-4CAA-A307-50C47B34BB58 Q27014915-83018F04-9312-4832-BFED-3F062D697686 Q27319936-D950B367-2266-4F7E-977B-F4E0CC857864 Q27653381-CE327A76-A2CA-4D15-B2D1-8B83AB1496B3 Q28066355-E11AECAD-EF37-4D4A-94A6-8F9FCA25F466 Q28070124-EDF40FC1-B8A4-44B5-83EC-278B6A5B3D9B Q28306617-575DF3D5-7B3C-4892-9C0E-DFDB9D69AF89 Q28392036-B3FD2F57-6479-4745-AA63-8A14769B7180 Q28392307-90C36075-79DB-44B7-A402-17316ECA3A3A Q28544415-4D2E35EF-1A62-46FE-9279-E1281BB8EBF4 Q28592966-542B0E51-C0F7-449B-9D5E-53879512AA98 Q28727687-E6C846D3-B5F4-43C8-8735-5DBED769C6C2 Q28943527-58DE45AA-8366-4573-9B39-7AACCE503189 Q29248524-CDBDAF2E-08B7-4256-A743-3794C33F9CBF Q30275376-59F7A0A4-B06C-40D4-96D3-F61F11920C26 Q30275429-0D824EB9-7509-4C62-947E-8230FBC71A02 Q30278692-90430034-C3A3-4D1D-BE47-3CEA734AE438 Q30405866-8154EFF7-CF42-4A80-AF7F-35DEC7464B30 Q30412080-A057135B-3F88-4DE9-BB47-DE86DE20935E Q30412670-1E747A12-CA62-4039-A1DA-B94827A12245 Q30415336-632E1A43-107A-4F92-BB0A-BC15C5E2653F Q30422887-18F250AF-2241-437D-9BCE-5D125BA53A69 Q30422958-F52E2BF6-6836-4F3C-98ED-DE7E9C1D9D41 Q30439769-F81C73D7-23BF-4C73-B95B-62B1B0FFFEA0 Q30490746-807B7ED6-42AE-4C2A-ADC4-6B81580AD470 Q30562762-3CDD3A85-8E39-40EA-8DED-DBD7BECF5EF4 Q30579240-CAAA1509-9563-4E50-BCE2-BF593E15917B Q30794057-5DB46791-0B3E-478A-B3E9-D6CFC2CE68F7 Q30844756-B7F17BE5-C9CD-4377-BC35-4AE5A66EB19B Q30940212-799072E1-6213-4DC7-B3F0-340A7FC143EC Q30995063-D2756AFE-4D09-4AAF-ABE2-49E6E5038BA3

P2860

Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture.

http://www.wikidata.org/entity/Q34268288

description

2012 nî lūn-bûn

@nan

2012 թուականի Ապրիլին հրատարակուած գիտական յօդուած

@hyw

2012 թվականի ապրիլին հրատարակված գիտական հոդված

@hy

2012年の論文

@ja

2012年論文

@yue

2012年論文

@zh-hant

2012年論文

@zh-hk

2012年論文

@zh-mo

2012年論文

@zh-tw

2012年论文

@wuu

name

Genome-wide meta-analysis iden ...... ociated with risk of fracture.

@ast

Genome-wide meta-analysis iden ...... ociated with risk of fracture.

@en

Genome-wide meta-analysis iden ...... ociated with risk of fracture.

@nl

type

label

Genome-wide meta-analysis iden ...... ociated with risk of fracture.

@ast

Genome-wide meta-analysis iden ...... ociated with risk of fracture.

@en

Genome-wide meta-analysis iden ...... ociated with risk of fracture.

@nl

prefLabel

Genome-wide meta-analysis iden ...... ociated with risk of fracture.

@ast

Genome-wide meta-analysis iden ...... ociated with risk of fracture.

@en

Genome-wide meta-analysis iden ...... ociated with risk of fracture.

@nl

P1433

Q34268288-A8ED025A-C243-4877-82C2-CB1CAF46BD2A

P1476

Q34268288-F6BCA67D-6CC5-417F-B011-202D365883B3

P2093

Q34268288-006B698A-5F16-4FC8-A840-A85BFE635481

Q34268288-02B424C4-2F6B-4E4F-BDA3-48174EA6123D

Q34268288-03920A92-EDAC-48C2-80A9-146BC70F90B7

Q34268288-03CCE399-388F-46B3-9D98-5499B57E5FBD

Q34268288-03CCF1EE-A5DE-4A8A-8534-C5E5BC71FCE3

Q34268288-0757111B-E999-46E5-9712-49316D96517C

Q34268288-095FA9D2-6B99-4164-9C85-3EB6BE954307

Q34268288-0A75A03B-4599-4407-9172-28C946810842

Q34268288-0F1358A7-FFE9-4ECB-89D8-E889BEF68441

Q34268288-1180D85E-5552-4AAC-9EBD-BA3E924FD5CA

P2860

Q34268288-0252C0F2-536F-431B-ACCA-55D38FFF9BE6

Q34268288-0C8BA96D-DDC1-44E2-9330-B37515D0AAE4

Q34268288-0F9A2CAC-A71D-45EE-AC74-8336EDADCFA9

Q34268288-17E1CCC9-65A6-4C57-BE4F-FD7CC05BBFE7

Q34268288-18C7DDDF-6C6F-48C9-9D74-F3B064BEB4E6

Q34268288-19DEF3BD-C04B-449B-BEBF-FA6DE38555C1

Q34268288-1E211E18-FD4D-457F-BC84-2A1A57BFEF6C

Q34268288-206FCE9E-3A8C-405D-8224-B5E823DA8CBC

Q34268288-2B440E20-C530-4CA6-A64F-BD54CC45D89A

Q34268288-2CE7F315-2B0C-43F4-9A8A-10FE007ED513

P2888

Q34268288-77146EC3-CB97-4770-A50B-D9FEA655CE9B

P304

Q34268288-FA0C81DA-17A1-4695-92E4-5BCFE82BB390

P31

Q34268288-21b0af7b-cba9-4610-95fc-8c3902029aa6

Q34268288-38B50051-C7FE-40D3-9DB4-245837A54731

P356

Q34268288-7B749DD9-5637-4F8B-B3B4-D8B6B90EC55B

P407

Q34268288-E2208FEA-9802-4E5E-B35D-756D4E3189AA

P433

Q34268288-F16BC9E8-4ED1-4EBB-AABE-AADF3015F3A7

P478

Q34268288-B79C97B2-0285-4556-8D79-A640DAE6C480

P50

Q34268288-0D31F105-4062-4B61-B47A-F8EBCFF8B888

Q34268288-105417B8-3A48-4B35-96EA-5C78234324FD

Q34268288-11089300-4FC6-4657-8DB5-1E34EE3945EA

Q34268288-115B6564-1D32-47E4-9F3F-67A48F881B58

Q34268288-11953C1A-BB1A-479F-8E17-9E53C903058A

Q34268288-13FB097A-1FAC-4BE4-9264-6F9EEB2A8BBA

Q34268288-1637DA8A-1A3B-45F5-BE95-894B7811A043

Q34268288-1819A1B3-4017-4B33-980C-F592157A8B66

Q34268288-19FA71BC-E5F3-4B98-B92F-CFBA9EC10A62

Q34268288-1B2A57B1-EDF4-496F-87AD-4AB02184D766

P577

Q34268288-82563036-37FC-4B09-8A57-32BF8F772729

P5875

Q34268288-6227DA8B-3FBC-418F-980C-F3635E30BADD

P698

Q34268288-8A3578FA-A9AA-4897-8D06-3F400C427427

P932

Q34268288-7F0EB21C-CD80-4B70-BEB6-95100A949AD2

P356

P1433

Nature Genetics

P1476

Genome-wide meta-analysis iden ...... ociated with risk of fracture.

@en

P2093

Aaron K Aragaki

http://www.w3.org/2001/XMLSchema#string

Andrea Z Lacroix

http://www.w3.org/2001/XMLSchema#string

Andrew R Wood

http://www.w3.org/2001/XMLSchema#string

Annie Wai Chee Kung

http://www.w3.org/2001/XMLSchema#string

Barbara Obermayer-Pietsch

http://www.w3.org/2001/XMLSchema#string

Ben A Oostra

http://www.w3.org/2001/XMLSchema#string

Bente Lomholt Langdahl

http://www.w3.org/2001/XMLSchema#string

Brendan M Buckley

http://www.w3.org/2001/XMLSchema#string

Candace M Kammerer

http://www.w3.org/2001/XMLSchema#string

Ching-Ti Liu

http://www.w3.org/2001/XMLSchema#string

P2860

Twenty bone-mineral-density loci identified by large-scale meta-analysis of genome-wide association studies

Bone dysplasia sclerosteosis results from loss of the SOST gene product, a novel cystine knot-containing protein

Hundreds of variants clustered in genomic loci and biological pathways affect human height

A second generation human haplotype map of over 3.1 million SNPs

Merlin--rapid analysis of dense genetic maps using sparse gene flow trees

Loss of the ClC-7 chloride channel leads to osteopetrosis in mice and man

Genomewide association studies and assessment of the risk of disease

New sequence variants associated with bone mineral density

European bone mineral density loci are also associated with BMD in East-Asian populations

Genetics and beyond--the transcriptome of human monocytes and disease susceptibility

P2888

P304

491-501

http://www.w3.org/2001/XMLSchema#string

P31

scholarly article

P356

10.1038/NG.2249

http://www.w3.org/2001/XMLSchema#string

P407

P433

5

http://www.w3.org/2001/XMLSchema#string

P478

44

http://www.w3.org/2001/XMLSchema#string

P50

Fernando Rivadeneira

Vilmundur Gudnason

Gudmar Thorleifsson

Unnur Þorsteinsdóttir

Cornelia M. van Duijn

Charles Kooperberg

Göran Hallmans

P577

2012-04-15T00:00:00Z

http://www.w3.org/2001/XMLSchema#dateTime

P5875

224038213

http://www.w3.org/2001/XMLSchema#string

P698

22504420

http://www.w3.org/2001/XMLSchema#string

P932

3338864

http://www.w3.org/2001/XMLSchema#string