Multivariate and gene-based association testing of sarcopenia: Bushehr Elderly Health Program (BEH)
-
Mohammad Noorchenarboo
,
Mahdi Akbarzadeh
,
Noushin Fahimfar
,
Gita Shafiee
,
Hamed Moheimani
,
Kazem Khalagi
,
Mahsa Mohammad Amoli
,
Bagher Larijani
,
Iraj Nabipour
,
Afshin Ostovar
,
Abbas Dehghan
,
Mehdi Yaseri
Abstract
Introduction: Sarcopenia can be measured by a variety of indicators, and in many cases these indicators are quite positively correlated. With the aim of improving statistical model results, the objective of this study was to use multivariate methods to identify genetic variants affecting sarcopenia indices simultaneously.
Methods: GWAS analysis was performed based on data collected from 2426 Iranians aged 60 and over who were enrolled in the Bushehr Elderly Health program (BEH). DNA samples were collected from all subjects during this phase to measure prevalence of musculoskeletal disorders and risk factors. To analyze BEH DNA samples, we used a combination of Multiphen test, which is a linear combination of phenotypes most associated with genotypes, and GATES, a gene-based association test that can handle millions of SNP results efficiently and that can assess gene-level statistical significance.
Result: The upper and lower 50 kb of the IL10 gene are extracted from chromosome 1 at the position (206940947, 206945839). The next step was done to calculate P-values for SNPs in this gene of SMI and handgrip using Multiphen (joint model). In the Gates method, these P-values are used to calculate the overall P-value (0.046). Given the fact that this value is less than 5%, it is clear that this gene has been effective in preventing sarcopenia in the Iranian elderly population. The tutorial describes how Multiphen and Gates can be used to analyze sarcopenia, a multifactorial disease. In this study, the gene Il10 (P-value = 0.046) was analyzed as a risk gene for sarcopenia.
Conclusion: GWAS (Genome-wide association study) is a primary method for identifying genetic variants that influence the phenotype of a disease. Multi-phenotype analysis, which evaluates multiple phenotypes associated with the disease, can, however, identify additional genetic associations associated with the disease. An alternative to univariate GWAS, Multiphen tests the most related linear combinations of multifactorial diseases using a multi-phenotypic approach rather than univariate GWAS. The overall P-value of the selected gene is determined by using Gates, a gene-based analysis.
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40. A. J. Cruz-Jentoft et al., "Sarcopeni a: revised European consensus on definition and diagnosis," Age and ageing, vol. 48, no. 1, pp. 16-31, 2019.
41 G. Shafiee et al., "Appendicular skeletal muscle mass reference values and the peak muscle mass to identify sarcopenia among Iranian healthy population," International journal of preventive medicine, vol. 9, 2018.
42. G. Shafiee et al., "Comparison of EWGSOP-1and EWGSOP-2 diagnostic criteria on prevalence of and risk factors for sarcopenia among Iranian older people: the Bushehr Elderly Health (BEH) program," Journal of Diabetes & Metabolic Disorders, vol. 19, no. 2,pp. 727-734, 2020.
43. R. Hai et al., "Genome-wide association study of copy number variation identified gremlin1 as a candidate gene for lean body mass," (in English), J. Hum. Genet., Article vol. 57, no. 1, pp. 33-37, 2012, doi: 10.1038/jhg.2011.125.
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45. Y. F. Guo et al., "Suggestion of GLYAT gene underlying variation of bone size and body lean mass as revealed by a bivariate genome-wide association study," (in English), Hum. Genet., Article vol. 132, no. 2, pp. 189-199, 2013, doi: 10.1007/s00439-012-1236-5.
46. J. Huang et al., "METTL21C is a potential pleiotropic gene for osteoporosis and sarcopenia acting through the modulation of the NF-κB signaling pathway," (in English), J. Bone Miner. Res., Article vol. 29, no. 7, pp.1531-1540, 2014, doi: 10.1002/jbmr.2200.
47. A. N. Singh and B. Gasman,"Disentangling the genetics of sarcopenia: Prioritization of NUDT3 and KLF5 as genes
for lean mass & HLA-DQB1-AS1 for hand grip strength with the associated enhancing SNPs & a scoring system," (in English), BMC Med. Genet., Article vol. 21, no. 1, 2020, Artno. 40, doi: 10.1186/s12881-020-0977-6.
48. S. Ran, X. He, Z. Jiang, B. Liu, and H. Deng, "Genome-wide association analysis identifying that genes ANXA8 and C10orf11are candidate genes for sarcopenia," (inChinese), Shanghai Ligong Daxue Xuebao,Article vol. 42, no. 3, pp. 305-310, 2020, doi:10.13255/j.cnki.jusst.20190423002.
49. P. F. O’Reilly et al., "MultiPhen: jointmodel of multiple phenotypes can increase discovery in GWAS," PloS one, vol. 7, no. 5, p.e34861, 2012.
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American Journal of Human Genetics, vol. 81, no. 6, pp. 1278-1283, 2007.
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[2] L.-K. Chen et al., "Sarcopenia in Asia: consensus report of the Asian Working Group for Sarcopenia," Journal of the American Medical Directors Association, vol. 15, no. 2, pp. 95-101, 2014.
[3] R. Hashemi et al., "Sarcopenia and its associated factors in Iranian older individuals: results of SARIR study," Archives of gerontology and geriatrics, vol. 66, pp. 18-22, 2016.
[4] M. A. Zeru, "Prevalence of Unplanned Pregnancy and associated risk factors among Pregnant Women in Ethiopia," Journal of Biostatistics and Epidemiology, vol. 7, no. 4, pp. 392-402, 2021.
[5] S. J. Prior et al., "Genetic and environmental influences on skeletal muscle phenotypes as a function of age and sex in large, multigenerational families of African heritage," Journal of applied Physiology, vol. 103, no. 4, pp. 1121-1127, 2007.
[6] G. J. Kemp et al., "Developing a toolkit for the assessment and monitoring of musculoskeletal ageing," Age and ageing, vol. 47, no. suppl_4, pp. iv1-iv19, 2018.
[7] B. Franzke, O. Neubauer, D. Cameron-Smith, and K.-H. Wagner, "Dietary protein, muscle and physical function in the very old," Nutrients, vol. 10, no. 7, p. 935, 2018.
[8] N. Buchmann, D. Spira, K. Norman, I. Demuth, R. Eckardt, and E. Steinhagen-Thiessen, "Sleep, muscle mass and muscle function in older people: a cross-sectional analysis based on data from the Berlin Aging Study II (BASE-II)," Deutsches Ärzteblatt international, vol. 113, no. 15, p. 253, 2016.
[9] O. Hamidi, S. R. Borzu, S. Maroufizadeh, and P. Amini, "Application of Multivariate Generalized Linear Mixed Model to Identify Effect of Dialysate Temperature on Physiologic Indicators among Hemodialysis Patients," Journal of Biostatistics and Epidemiology, vol. 7, no. 3, pp. 263-271, 2021.
[10] J.-I. Yoo, Y.-C. Ha, Y.-K. Lee, M.-J. Yoo, and K.-H. Koo, "High prevalence of sarcopenia among binge drinking elderly women: a nationwide population-based study," BMC geriatrics, vol. 17, no. 1, pp. 1-8, 2017.
[11] H. Zempo, E. Miyamoto‐Mikami, N. Kikuchi, N. Fuku, M. Miyachi, and H. Murakami, "Heritability estimates of muscle strength‐related phenotypes: A systematic review and meta‐analysis," Scandinavian journal of medicine & science in sports, vol. 27, no. 12, pp. 1537-1546, 2017.
[12] M. Abney, M. S. McPeek, and C. Ober, "Broad and narrow heritabilities of quantitative traits in a founder population," The American Journal of Human Genetics, vol. 68, no. 5, pp. 1302-1307, 2001.
[13] J. N. Hirschhorn and M. J. Daly, "Genome-wide association studies for common diseases and complex traits," Nature reviews genetics, vol. 6, no. 2, pp. 95-108, 2005.
[14] W. Wang, B. J. Barratt, D. G. Clayton, and J. A. Todd, "Genome-wide association studies: theoretical and practical concerns," Nature Reviews Genetics, vol. 6, no. 2, pp. 109-118, 2005.
15. M. Akbarzadeh et al., "The AGT Epistasis Pattern Proposed a Novel Role for ZBED9 In Regulating Blood Pressure: Tehran Cardiometabolic Genetic Study (TCGS)," 2022.
16. M. Akbarzadeh et al., "GWAS findings improved genomic prediction accuracy of lipid profile traits: Tehran Cardiometabolic Genetic Study," Sci. Rep., vol. 11, no. 1, pp. 1-9, 2021.
17. C. S. Ku, E. Y. Loy, Y. Pawitan, and K. S. Chia, "The pursuit of genome-wide association studies: where are we now?," Journal of human genetics, vol. 55, no. 4, pp. 195-206, 2010.
18. J. MacArthur et al., "The new NHGRIEBI Catalog of published genome-wide association studies (GWAS Catalog)," Nucleic acids research, vol. 45, no. D1, pp. D896-D901, 2017.
19. E. E. Eichler et al., "Missing heritability and strategies for finding the underlying causes of complex disease," Nature Reviews Genetics, vol. 11, no. 6, pp. 446-450, 2010.
20. P. M. Visscher, W. G. Hill, and N. R. Wray, "Heritability in the genomics era concepts and misconceptions," Nature reviews genetics, vol. 9, no. 4, pp. 255-266, 2008.
21. M. Akbarzadeh et al., "Parental Transmission Plays the Major Role in High Aggregation of Type 2 Diabetes in Iranian
Families: Tehran Lipid and Glucose Study," Canadian Journal of Diabetes, vol. 46, no. 1, pp. 60-68, 2022.
22. G. Kolifarhood et al., "Familial genetic and environmental risk profile and high blood pressure event: A prospective cohort of cardiometabolic and genetic study," Blood Pressure, vol. 30, no. 3, pp. 196-204, 2021.
23. B. M. Neale and P. C. Sham, "The future of association studies: gene-based analysis and replication," The American Journal of Human Genetics, vol. 75, no. 3, pp. 353-362, 2004.
24. M.-X. Li, H.-S. Gui, J. S. Kwan, and P. C. J. T. A. J. o. H. G. Sham, "GATES: a rapid and powerful gene-based association test using extended Simes procedure," vol. 88, no. 3, pp.283-293, 2011.
25. E. K. Speliotes et al., "Association analyses of 249,796 individuals reveal 18 newloci associated with body mass index," vol. 42, no. 11, pp. 937-948, 2010.
26. S. Van der Sluis, D. Posthuma, and C. V. Dolan, "TATES: efficient multivariate genotype-phenotype analysis for genome-wideassociation studies," PLoS genetics, vol. 9, no. 1, p. e1003235, 2013.
27. I. I. Gottesman and T. D. Gould, "The endophenotype concept in psychiatry: etymology and strategic intentions," American journal of psychiatry, vol. 160, no. 4, pp. 636- 645, 2003.
28. M. Moazzam-Jazi, A. S. Zahedi, M. Akbarzadeh, F. Azizi, and M. S. Daneshpour, "Diverse effect of MC4R risk alleles on obesityrelated traits over a lifetime: Evidence from a well-designed cohort study," Gene, vol. 807, p.145950, 2022.
29. A. S. Zahedi, M. Akbarzadeh, B. Sedaghati-Khayat, A. Seyedhamzehzadeh, and M. S. Daneshpour, "GCKR common functional polymorphisms are associated with metabolic syndrome and its components: a 10-year retrospective cohort study in Iranian adults," Diabetology & Metabolic Syndrome, vol. 13, no. 1, pp. 1-10, 2021.
30. S. Hosseinpour-Niazi et al., "TCF7L2 polymorphisms, nut consumption, and the risk of metabolic syndrome: a prospective population based study," Nutrition & Metabolism, vol. 18, no. 1, pp. 1-11, 2021.
31. J. Chung, G. R. Jun, J. Dupuis, and L. A. Farrer, "Comparison of methods for multivariate gene-based association tests for complex diseases using common variants," Eur J Hum Genet, vol. 27, no. 5, pp. 811-823, May
2019, doi: 10.1038/s41431-018-0327-8. 32. T. Y. Wong et al., "Relation between
fasting glucose and retinopathy for diagnosis of diabetes: three population-based crosssectional studies," The Lancet, vol. 371, no. 9614, pp. 736-743, 2008.
33. N. Sattar et al., "Can metabolic syndrome usefully predict cardiovascular disease and diabetes? Outcome data from two prospective studies," The Lancet, vol. 371, no. 9628, pp. 1927-1935, 2008.
34. E. K. Speliotes et al., "Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index," Nature genetics, vol. 42, no. 11, pp. 937-948, 2010.
35. Y.-D. Rong, A.-L. Bian, H.-Y. Hu, Y. Ma, and X.-Z. Zhou, "Study on relationship between elderly sarcopenia and inflammatory cytokine IL-6, anti-inflammatory cytokine IL-10," (in eng), BMC Geriatr, vol. 18, no. 1,pp. 308-308, 2018, doi: 10.1186/s12877-018- 1007-9.
36. A. Ostovar et al., "Bushehr elderly health (BEH) Programme, phase I (cardiovascular system)," vol. 5, no. 12, p. e009597, 2015.
37. G. Shafiee et al., "Bushehr Elderly Health (BEH) programme: study protocol and design of musculoskeletal system and cognitive function (stage II)," vol. 7, no. 8, p. e013606,2017.
38. A. Ostovar et al., "Bushehr elderly health (BEH) Programme, phase I (cardiovascular system)," BMJ open, vol. 5, no. 12, p. e009597, 2015.
39. G. Shafiee et al., "Bushehr Elderly Health (BEH) programme: study protocol and design of musculoskeletal system and cognitive function (stage II)," BMJ open, vol. 7, no. 8, p. e013606, 2017.
40. A. J. Cruz-Jentoft et al., "Sarcopeni a: revised European consensus on definition and diagnosis," Age and ageing, vol. 48, no. 1, pp. 16-31, 2019.
41 G. Shafiee et al., "Appendicular skeletal muscle mass reference values and the peak muscle mass to identify sarcopenia among Iranian healthy population," International journal of preventive medicine, vol. 9, 2018.
42. G. Shafiee et al., "Comparison of EWGSOP-1and EWGSOP-2 diagnostic criteria on prevalence of and risk factors for sarcopenia among Iranian older people: the Bushehr Elderly Health (BEH) program," Journal of Diabetes & Metabolic Disorders, vol. 19, no. 2,pp. 727-734, 2020.
43. R. Hai et al., "Genome-wide association study of copy number variation identified gremlin1 as a candidate gene for lean body mass," (in English), J. Hum. Genet., Article vol. 57, no. 1, pp. 33-37, 2012, doi: 10.1038/jhg.2011.125.
44. L.-J. Tan, S.-L. Liu, S.-F. Lei, C. J.Papasian, and H.-W. Deng, "Molecular genetic studies of gene identification for sarcopenia," Hum. Genet., vol. 131, no. 1, pp. 1-31, 2012.
45. Y. F. Guo et al., "Suggestion of GLYAT gene underlying variation of bone size and body lean mass as revealed by a bivariate genome-wide association study," (in English), Hum. Genet., Article vol. 132, no. 2, pp. 189-199, 2013, doi: 10.1007/s00439-012-1236-5.
46. J. Huang et al., "METTL21C is a potential pleiotropic gene for osteoporosis and sarcopenia acting through the modulation of the NF-κB signaling pathway," (in English), J. Bone Miner. Res., Article vol. 29, no. 7, pp.1531-1540, 2014, doi: 10.1002/jbmr.2200.
47. A. N. Singh and B. Gasman,"Disentangling the genetics of sarcopenia: Prioritization of NUDT3 and KLF5 as genes
for lean mass & HLA-DQB1-AS1 for hand grip strength with the associated enhancing SNPs & a scoring system," (in English), BMC Med. Genet., Article vol. 21, no. 1, 2020, Artno. 40, doi: 10.1186/s12881-020-0977-6.
48. S. Ran, X. He, Z. Jiang, B. Liu, and H. Deng, "Genome-wide association analysis identifying that genes ANXA8 and C10orf11are candidate genes for sarcopenia," (inChinese), Shanghai Ligong Daxue Xuebao,Article vol. 42, no. 3, pp. 305-310, 2020, doi:10.13255/j.cnki.jusst.20190423002.
49. P. F. O’Reilly et al., "MultiPhen: jointmodel of multiple phenotypes can increase discovery in GWAS," PloS one, vol. 7, no. 5, p.e34861, 2012.
50. M. I. McCarthy et al., "Genomewide association studies for complex traits: consensus, uncertainty and challenges," Naturereviews genetics, vol. 9, no. 5, pp. 356-369,2008.
51. T. A. Manolio, L. D. Brooks, and F. S. Collins, "A HapMap harvest of insights into the genetics of common disease," The Journal of clinical investigation, vol. 118, no. 5, pp. 1590- 1605, 2008.
52. W. J. Gauderman, C. Murcray, F. Gilliland, and D. V. Conti, "Testing association between disease and multiple SNPs in a
candidate gene," Genetic Epidemiology: The Official Publication of the International Genetic Epidemiology Society, vol. 31, no. 5, pp. 383- 395, 2007.
53. K. Wang and D. Abbott, "A principal components regression approach to multilocusgenetic association studies," Genetic Epidemiology: The Official Publication of the International Genetic Epidemiology Society,vol. 32, no. 2, pp. 108-118, 2008.
54. K. Wang, M. Li, and M. Bucan, "Pathway-based approaches for analysis of genomewide association studies," The
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| Files | ||
| Issue | Vol 8 No 2 (2022) | |
| Section | Original Article(s) | |
| DOI | https://doi.org/10.18502/jbe.v8i2.10417 | |
| Keywords | ||
| Bushehr Elderly Health Program (BEH); MultiPhen GATES IL10 Candidate-gene GWAS | ||
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
How to Cite
1.
Noorchenarboo M, Akbarzadeh M, Fahimfar N, Shafiee G, Moheimani H, Khalagi K, Mohammad Amoli M, Larijani B, Nabipour I, Ostovar A, Dehghan A, Yaseri M. Multivariate and gene-based association testing of sarcopenia: Bushehr Elderly Health Program (BEH). JBE. 2022;8(2):195-207.
