Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress 2023 EHA Congress 2023 ASCO Annual Meeting
Clinical Collections
Advances in Alzheimer’s

At a glance: The ONWARDS insulin icodec trials

A round-up of the ONWARDS phase 3 clinical trials evaluating the novel weekly insulin icodec in people with diabetes.
ADVANCED SEARCH
Log in
Top
BMC Medicine
Published in: BMC Medicine 1/2011

Open Access 01-12-2011 | Research article

Synopsis and meta-analysis of genetic association studies in osteoporosis for the focal adhesion family genes: the CUMAGAS-OSTEOporosis information system

Published in: BMC Medicine | Issue 1/2011

Login to get access

Abstract

Background

Focal adhesion (FA) family genes have been studied as candidate genes for osteoporosis, but the results of genetic association studies (GASs) are controversial. To clarify these data, a systematic assessment of GASs for FA genes in osteoporosis was conducted.

Methods

We developed Cumulative Meta-Analysis of GAS-OSTEOporosis (CUMAGAS-OSTEOporosis), a web-based information system that allows the retrieval, analysis and meta-analysis (for allele contrast, recessive, dominant, additive and codominant models) of data from GASs on osteoporosis with the capability of update. GASs were identified by searching the PubMed and HuGE PubLit databases.

Results

Data from 72 studies involving 13 variants of 6 genes were analyzed and catalogued in CUMAGAS-OSTEOporosis. Twenty-two studies produced significant associations with osteoporosis risk under any genetic model. All studies were underpowered (<50%). In four studies, the controls deviated from the Hardy-Weinberg equilibrium. Eight variants were chosen for meta-analysis, and significance was shown for the variants collagen, type I, α1 (COL1A1) G2046T (all genetic models), COL1A1 G-1997T (allele contrast and dominant model) and integrin β-chain β3 (ITGB3) T176C (recessive and additive models). In COL1A1 G2046T, subgroup analysis has shown significant associations for Caucasians, adults, females, males and postmenopausal women. A differential magnitude of effect in large versus small studies (that is, indication of publication bias) was detected for the variant COL1A1 G2046T.

Conclusion

There is evidence of an implication of FA family genes in osteoporosis. CUMAGAS-OSTEOporosis could be a useful tool for current genomic epidemiology research in the field of osteoporosis.
Appendix
Available only for authorised users
Literature
1.
Stewart TL, Ralston SH: Role of genetic factors in the pathogenesis of osteoporosis. J Endocrinol. 2000, 166: 235-245. 10.1677/joe.0.1660235.CrossRefPubMed
2.
Zintzaras E, Rodopoulou P, Koukoulis GN: BsmI, TaqI, ApaI and FokI polymorphisms in the vitamin D receptor (VDR) gene and the risk of osteoporosis: a meta-analysis. Dis Markers. 2006, 22: 317-326.CrossRefPubMed
3.
4.
Zaidel-Bar R, Cohen M, Addadi L, Geiger B: Hierarchical assembly of cell-matrix adhesion complexes. Biochem Soc Trans. 2004, 32: 416-420. 10.1042/BST0320416.CrossRefPubMed
5.
Petit V, Thiery JP: Focal adhesions: structure and dynamics. Biol Cell. 2000, 92: 477-494. 10.1016/S0248-4900(00)01101-1.CrossRefPubMed
6.
Li WF, Hou SX, Yu B, Li MM, Férec C, Chen JM: Genetics of osteoporosis: accelerating pace in gene identification and validation. Hum Genet. 2010, 127: 249-285. 10.1007/s00439-009-0773-z.CrossRefPubMed
7.
Mann V, Ralston SH: Meta-analysis of COL1A1 Sp1 polymorphism in relation to bone mineral density and osteoporotic fracture. Bone. 2003, 32: 711-717. 10.1016/S8756-3282(03)00087-5.CrossRefPubMed
8.
Zintzaras E, Lau J: Synthesis of genetic association studies for pertinent gene-disease associations requires appropriate methodological and statistical approaches. J Clin Epidemiol. 2008, 61: 634-645. 10.1016/j.jclinepi.2007.12.011.CrossRefPubMed
9.
10.
Zintzaras E, Zdoukopoulos N: A field synopsis and meta-analysis of genetic association studies in peripheral arterial disease: the CUMAGAS-PAD database. Am J Epidemiol. 2009, 170: 1-11. 10.1093/aje/kwp094.CrossRefPubMed
11.
Zintzaras E, Kitsios G: Field synopsis and synthesis of candidate-gene association studies in chronic lymphocytic leukemia: the CUMAGAS-CLL information system. Am J Epidemiol. 2009, 170: 671-678. 10.1093/aje/kwp201.CrossRefPubMed
12.
Yu W, Gwinn M, Clyne M, Yesupriya A, Khoury MJ: A navigator for human genome epidemiology. Nat Genet. 2008, 40: 124-125. 10.1038/ng0208-124.CrossRefPubMed
13.
Hindorff LA, Sethupathy P, Junkins HA, Ramos EM, Mehta JP, Collins FS, Manolio TA: Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc Natl Acad Sci USA. 2009, 106: 9362-9367. 10.1073/pnas.0903103106.CrossRefPubMedPubMedCentral
14.
15.
Johnson AD, Handsaker RE, Pulit SL, Nizzari MM, O'Donnell CJ, de Bakker PI: SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap. Bioinformatics. 2008, 24: 2938-2939. 10.1093/bioinformatics/btn564.CrossRefPubMedPubMedCentral
16.
Sherry ST, Ward MH, Kholodov M, Baker J, Phan L, Smigielski EM, Sirotkin K: dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 2001, 29: 308-311. 10.1093/nar/29.1.308.CrossRefPubMedPubMedCentral
17.
Ioannidis JP, Trikalinos TA, Zintzaras E: Extreme between-study homogeneity in meta-analyses could offer useful insights. J Clin Epidemiol. 2006, 59: 1023-1032. 10.1016/j.jclinepi.2006.02.013.CrossRefPubMed
18.
Zintzaras E, Ioannidis JP: Heterogeneity testing in meta-analysis of genome searches. Genet Epidemiol. 2005, 28: 123-137. 10.1002/gepi.20048.CrossRefPubMed
19.
DerSimonian R, Laird N: Meta-analysis in clinical trials. Control Clin Trials. 1986, 7: 177-188. 10.1016/0197-2456(86)90046-2.CrossRefPubMed
20.
Trikalinos TA, Salanti G, Zintzaras E, Ioannidis JP: Meta-analysis methods. Adv Genet. 2008, 60: 311-334. full_text.CrossRefPubMed
21.
Harbord RM, Egger M, Sterne JA: A modified test for small-study effects in meta-analyses of controlled trials with binary endpoints. Stat Med. 2006, 25: 3443-3457. 10.1002/sim.2380.CrossRefPubMed
22.
Zintzaras E: Variance estimation of allele-based odds ratio in the absence of Hardy-Weinberg equilibrium. Eur J Epidemiol. 2008, 23: 323-326. 10.1007/s10654-008-9242-6.CrossRefPubMed
23.
Ralston SH, Uitterlinden AG, Brandi ML, Balcells S, Langdahl BL, Lips P, Lorenc R, Obermayer-Pietsch B, Scollen S, Bustamante M, Husted LB, Carey AH, Diez-Perez A, Dunning AM, Falchetti A, Karczmarewicz E, Kruk M, van Leeuwen JP, van Meurs JB, Mangion J, McGuigan FE, Mellibovsky L, del Monte F, Pols HA, Reeve J, Reid DM, Renner W, Rivadeneira F, van Schoor NM, Sherlock RE, GENOMOS Investigators, et al: Large-scale evidence for the effect of the COLIA1 Sp1 polymorphism on osteoporosis outcomes: the GENOMOS study. PLoS Med. 2006, 3: e90-10.1371/journal.pmed.0030090.CrossRefPubMedPubMedCentral
24.
Langdahl BL, Ralston SH, Grant SF, Eriksen EF: An Sp1 binding site polymorphism in the COLIA1 gene predicts osteoporotic fractures in both men and women. J Bone Miner Res. 1998, 13: 1384-1389. 10.1359/jbmr.1998.13.9.1384.CrossRefPubMed
25.
Välimäki S, Tähtelä R, Kainulainen K, Laitinen K, Löyttyniemi E, Sulkava R, Välimäki M, Kontula K: Relation of collagen type I alpha 1 (COLIA 1) and vitamin D receptor genotypes to bone mass, turnover, and fractures in early postmenopausal women and to hip fractures in elderly people. Eur J Intern Med. 2001, 12: 48-56.CrossRefPubMed
26.
McGuigan FE, Armbrecht G, Smith R, Felsenberg D, Reid DM, Ralston SH: Predication of osteoporotic fractures by bone densitometry and COLIA1 genotyping: a prospective, population-based study in men and women. Osteoporos Int. 2001, 12: 91-96. 10.1007/s001980170139.CrossRefPubMed
27.
Husted LB, Harsløf T, Gonzalez-Bofill N, Schmitz A, Carstens M, Stenkjaer L, Langdahl BL: Haplotypes of promoter and intron 1 polymorphisms in the COLIA1 gene are associated with increased risk of osteoporosis. Calcif Tissue Int. 2009, 84: 85-96. 10.1007/s00223-008-9199-1.CrossRefPubMed
28.
Liu YZ, Pei YF, Liu JF, Yang F, Guo Y, Zhang L, Liu XG, Yan H, Wang L, Zhang YP, Levy S, Recker RR, Deng HW: Powerful bivariate genome-wide association analyses suggest the SOX6 gene influencing both obesity and osteoporosis phenotypes in males. PLoS One. 2009, 4: e6827-10.1371/journal.pone.0006827.CrossRefPubMedPubMedCentral
29.
Kiel DP, Demissie S, Dupuis J, Lunetta KL, Murabito JM, Karasik D: Genome-wide association with bone mass and geometry in the Framingham Heart Study. BMC Med Genet. 2007, 8 (Suppl 1): S14-10.1186/1471-2350-8-S1-S14.CrossRefPubMedPubMedCentral
30.
Keen RW, Woodford-Richens KL, Grant SF, Ralston SH, Lanchbury JS, Spector TD: Association of polymorphism at the type I collagen (COL1A1) locus with reduced bone mineral density, increased fracture risk, and increased collagen turnover. Arthritis Rheum. 1999, 42: 285-290. 10.1002/1529-0131(199902)42:2<285::AID-ANR10>3.0.CO;2-3.CrossRefPubMed
31.
Jin H, van't Hof RJ, Albagha OM, Ralston SH: Promoter and intron 1 polymorphisms of COL1A1 interact to regulate transcription and susceptibility to osteoporosis. Hum Mol Genet. 2009, 18: 2729-2738. 10.1093/hmg/ddp205.CrossRefPubMed
32.
García-Giralt N, Enjuanes A, Bustamante M, Mellibovsky L, Nogués X, Carreras R, Díez-Pérez A, Grinberg D, Balcells S: In vitro functional assay of alleles and haplotypes of two COL1A1-promoter SNPs. Bone. 2005, 36: 902-908.CrossRefPubMed
33.
Teitelbaum SL: Osteoclasts, integrins, and osteoporosis. J Bone Miner Metab. 2000, 18: 344-349. 10.1007/s007740070007.CrossRefPubMed
34.
Honda S, Honda Y, Bauer B, Ruan C, Kunicki TJ: The impact of three-dimensional structure on the expression of PlA alloantigens on human integrin β3. Blood. 1995, 86: 234-242.PubMed
35.
Zintzaras E, Kitsios GD, Ziogas DC, Rodopoulou P, Karachalios T: Field synopsis and synthesis of genetic association studies in osteoarthritis: the CUMAGAS-OSTEO information system. Am J Epidemiol. 2010, 171: 851-858. 10.1093/aje/kwq016.CrossRefPubMed
36.
Kitsios GD, Zintzaras E: Synopsis and data synthesis of genetic association studies in hypertension for the adrenergic receptor family genes: the CUMAGAS-HYPERT database. Am J Hypertens. 2010, 23: 305-313. 10.1038/ajh.2009.251.CrossRefPubMed
37.
Goldstein DB: Common genetic variation and human traits. N Engl J Med. 2009, 360: 1696-1698. 10.1056/NEJMp0806284.CrossRefPubMed
38.
Muncer S, Taylor S, Craigie M: Power dressing and meta-analysis: incorporating power analysis into meta-analysis. J Adv Nurs. 2002, 38: 274-280. 10.1046/j.1365-2648.2002.02177.x.CrossRefPubMed
39.
Zintzaras E, Ioannidis JP: Meta-analysis for ranked discovery datasets: theoretical framework and empirical demonstration for microarrays. Comput Biol Chem. 2008, 32: 38-46. 10.1016/j.compbiolchem.2007.09.003.CrossRefPubMed
40.
GAIN Collaborative Research Group, Manolio TA, Rodriguez LL, Brooks L, Abecasis G, Association Study of Psoriasis, Ballinger D, Daly M, Donnelly P, Faraone SV, International Multi-Center ADHD Genetics Project, Frazer K, Gabriel S, Gejman P, Molecular Genetics of Schizophrenia Collaboration, Guttmacher A, Harris EL, Insel T, Kelsoe JR, Bipolar Genome Study, Lander E, McCowin N, Mailman MD, Nabel E, Ostell J, Pugh E, Sherry S, Sullivan PF, Major Depression Stage 1 Genomewide Association in Population-Based Samples Study, Thompson JF, Warram J, Genetics of Kidneys in Diabetes (GoKinD) Study, Wholley D, Milos PM, Collins FS: New models of collaboration in genome-wide assosiation studies: the Genetic Associatiof Information Network. Nat Genet. 2007, 39: 1045-1051. 10.1038/ng2127.CrossRef
41.
Zhai G, van Meurs JB, Livshits G, Meulenbelt I, Valdes AM, Soranzo N, Hart D, Zhang F, Kato BS, Richards JB, Williams FM, Inouye M, Kloppenburg M, Deloukas P, Slagboom E, Uitterlinden A, Spector TD: A genome-wide association study suggests that a locus within the ataxin 2 binding protein 1 gene is associated with hand osteoarthritis: the Treat-OA consortium. J Med Genet. 2009, 46: 614-616. 10.1136/jmg.2009.067314.CrossRefPubMedPubMedCentral
42.
Calnan M, Smith GD, Sterne JA: The publication process itself was the major cause of publication bias in genetic epidemiology. J Clin Epidemiol. 2006, 59: 1312-1318. 10.1016/j.jclinepi.2006.05.002.CrossRefPubMed
43.
Ioannidis JP: Journals should publish all "null" results and should sparingly publish "positive" results. Cancer Epidemiol Biomarkers Prev. 2006, 15: 186-201. 10.1158/1055-9965.EPI-05-0921.CrossRefPubMed
44.
Evans T, Gulmezoglu M, Pang T: Registering clinical trials: an essential role for WHO. Lancet. 2004, 363: 1413-1414. 10.1016/S0140-6736(04)16136-9.CrossRefPubMed
45.
46.
Munafò MR, Clark TG, Flint J: Assessing publication bias in genetic association studies: evidence from a recent meta-analysis. Psychiatry Res. 2004, 129: 39-44.CrossRefPubMed
47.
48.
Ioannidis JP, Trikalinos TA, Ntzani EE, Contopoulos-Ioannidis DG: Genetic associations in large versus small studies: an empirical assessment. Lancet. 2003, 361: 567-571. 10.1016/S0140-6736(03)12516-0.CrossRefPubMed
49.
Zintzaras E: The generalized odds ratio as a measure of genetic risk effect in the analysis and meta-analysis of association studies. Stat Appl Genet Mol Biol. 2010, 9: Article 21
50.
Rothman KJ: No adjustments are needed for multiple comparisons. Epidemiology. 1990, 1: 43-46. 10.1097/00001648-199001000-00010.CrossRefPubMed
51.
Savitz DA, Olshan AF: Multiple comparisons and related issues in the interpretation of epidemiologic data. Am J Epidemiol. 1995, 142: 904-908.PubMed
52.
Bender R, Lange S: Adjusting for multiple testing: when and how?. J Clin Epidemiol. 2001, 54: 343-349. 10.1016/S0895-4356(00)00314-0.CrossRefPubMed
53.
54.
55.
Ioannidis JP, Ng MY, Sham PC, Zintzaras E, Lewis CM, Deng HW, Econs MJ, Karasik D, Devoto M, Kammerer CM, Spector T, Andrew T, Cupples LA, Duncan EL, Foroud T, Kiel DP, Koller D, Langdahl B, Mitchell BD, Peacock M, Recker R, Shen H, Sol-Church K, Spotila LD, Uitterlinden AG, Wilson SG, Kung AW, Ralston SH: Meta-analysis of genome-wide scans provides evidence for sex- and site-specific regulation of bone mass. J Bone Miner Res. 2007, 22: 173-183. 10.1359/jbmr.060806.CrossRefPubMedPubMedCentral
56.
Hsu YH, Xu X, Terwedow HA, Niu T, Hong X, Wu D, Wang L, Brain JD, Bouxsein ML, Cummings SR, Rosen CJ, Xu X: Large-scale genome-wide linkage analysis for loci linked to BMD at different skeletal sites in extreme selected sibships. J Bone Miner Res. 2007, 22: 184-194. 10.1359/jbmr.061015.CrossRefPubMed
Metadata
Title
Synopsis and meta-analysis of genetic association studies in osteoporosis for the focal adhesion family genes: the CUMAGAS-OSTEOporosis information system
Publication date
01-12-2011
Published in
BMC Medicine / Issue 1/2011
Electronic ISSN: 1741-7015
DOI
https://doi.org/10.1186/1741-7015-9-9

Other articles of this Issue 1/2011

BMC Medicine 1/2011 Go to the issue

Research article

Hypoperfusion of brain parenchyma is associated with the severity of chronic cerebrospinal venous insufficiency in patients with multiple sclerosis: a cross-sectional preliminary report

Research article

Tailored antiplatelet therapy can overcome clopidogrel and aspirin resistance - The BOchum CLopidogrel and Aspirin Plan (BOCLA-Plan) to improve antiplatelet therapy

Research article

Expenditures for the care of HIV-infected patients in rural areas in China's antiretroviral therapy programs

Research article

Comparison of postmenopausal endogenous sex hormones among Japanese, Japanese Brazilians, and non-Japanese Brazilians

Commentary

Using framework-based synthesis for conducting reviews of qualitative studies

Commentary

Another tool in the genome-wide association study arsenal: population-based detection of somatic gene conversion