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Genetic variation in GC and CYP2R1 affects 25-hydroxyvitamin D concentration and skeletal parameters: A genome-wide association study in 24-month-old Finnish children


Autoři: Anders Kämpe aff001;  Maria Enlund-Cerullo aff003;  Saara Valkama aff003;  Elisa Holmlund-Suila aff003;  Jenni Rosendahl aff003;  Helena Hauta-alus aff003;  Minna Pekkinen aff003;  Sture Andersson aff003;  Outi Mäkitie aff001
Působiště autorů: Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden aff001;  Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden aff002;  Children’s Hospital, Pediatric Research Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland aff003;  Folkhälsan Research Center, Helsinki, Finland aff004;  Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Finland aff005
Vyšlo v časopise: Genetic variation in GC and CYP2R1 affects 25-hydroxyvitamin D concentration and skeletal parameters: A genome-wide association study in 24-month-old Finnish children. PLoS Genet 15(12): e32767. doi:10.1371/journal.pgen.1008530
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pgen.1008530

Souhrn

Vitamin D is important for normal skeletal homeostasis, especially in growing children. There are no previous genome-wide association (GWA) studies exploring genetic factors that influence vitamin D metabolism in early childhood. We performed a GWA study on serum 25-hydroxyvitamin D (25(OH)D) and response to supplementation in 761 healthy term-born Finnish 24-month-old children, who participated in a randomized clinical trial comparing effects of 10 μg and 30 μg of daily vitamin D supplementation from age 2 weeks to 24 months. Using the Illumina Infinium Global Screening Array, which has been optimized for imputation, a total of 686085 markers were genotyped across the genome. Serum 25(OH)D was measured at the end of the intervention at 24 months of age. Skeletal parameters reflecting bone strength were determined at the distal tibia at 24 months using peripheral quantitative computed tomography (pQCT) (data available for 648 children). For 25(OH)D, two strong GWA signals were identified, localizing to GC (Vitamin D binding protein) and CYP2R1 (Vitamin D 25-hydroxylase) genes. The GWA locus comprising the GC gene also associated with response to supplementation. Further evidence for the importance of these two genes was obtained by comparing association signals to gene expression data from the Genotype-Tissue Expression project and performing colocalization analyses. Through the identification of haplotypes associated with low or high 25(OH)D concentrations we used a Mendelian randomization approach to show that haplotypes associating with low 25(OH)D were also associated with low pQCT parameters in the 24-month-old children. In this first GWA study on 25(OH)D in this age group we show that already at the age of 24 months genetic variation influences 25(OH)D concentrations and determines response to supplementation, with genome-wide significant associations with GC and CYP2R1. Also, the dual association between haplotypes, 25(OH)D and pQCT parameters gives support for vertical pleiotropy mediated by 25(OH)D.

Klíčová slova:

Gene expression – Genetic loci – Genome-wide association studies – Haplotypes – Human genetics – Molecular genetics


Zdroje

1. Pludowski P, Holick MF, Pilz S, Wagner CL, Hollis BW, Grant WB, et al. Vitamin D effects on musculoskeletal health, immunity, autoimmunity, cardiovascular disease, cancer, fertility, pregnancy, dementia and mortality-a review of recent evidence. Autoimmun Rev. 2013;12(10):976–89. doi: 10.1016/j.autrev.2013.02.004 23542507

2. Autier P, Boniol M, Pizot C, Mullie P. Vitamin D status and ill health: a systematic review. Lancet Diabetes Endocrinol. 2014;2(1):76–89. doi: 10.1016/S2213-8587(13)70165-7 24622671

3. Rejnmark L, Bislev LS, Cashman KD, Eiriksdottir G, Gaksch M, Grubler M, et al. Non-skeletal health effects of vitamin D supplementation: A systematic review on findings from meta-analyses summarizing trial data. PLoS One. 2017;12(7):e0180512. doi: 10.1371/journal.pone.0180512 28686645

4. Avenell A, Mak JC, O'Connell D. Vitamin D and vitamin D analogues for preventing fractures in post-menopausal women and older men. The Cochrane database of systematic reviews. 2014;(4):CD000227. doi: 10.1002/14651858.CD000227.pub4 24729336

5. Khaw KT, Stewart AW, Waayer D, Lawes CMM, Toop L, Camargo CA Jr., et al. Effect of monthly high-dose vitamin D supplementation on falls and non-vertebral fractures: secondary and post-hoc outcomes from the randomised, double-blind, placebo-controlled ViDA trial. Lancet Diabetes Endocrinol. 2017;5(6):438–47. doi: 10.1016/S2213-8587(17)30103-1 28461159

6. Holick MF. Vitamin D deficiency. N Engl J Med. 2007;357(3):266–81. doi: 10.1056/NEJMra070553 17634462

7. Carpenter TO, Shaw NJ, Portale AA, Ward LM, Abrams SA, Pettifor JM. Rickets. Nat Rev Dis Primers. 2017;3:17101. doi: 10.1038/nrdp.2017.101 29265106

8. Misra M, Pacaud D, Petryk A, Collett-Solberg PF, Kappy M, Drug, et al. Vitamin D deficiency in children and its management: review of current knowledge and recommendations. Pediatrics. 2008;122(2):398–417. doi: 10.1542/peds.2007-1894 18676559

9. Pekkinen M, Viljakainen H, Saarnio E, Lamberg-Allardt C, Makitie O. Vitamin D Is a Major Determinant of Bone Mineral Density at School Age. PLoS One. 2012;7(7).

10. Soininen S, Eloranta AM, Lindi V, Venalainen T, Zaproudina N, Mahonen A, et al. Determinants of serum 25-hydroxyvitamin D concentration in Finnish children: the Physical Activity and Nutrition in Children (PANIC) study. Br J Nutr. 2016;115(6):1080–91. doi: 10.1017/S0007114515005292 26836317

11. Raulio S, Erlund I, Mannisto S, Sarlio-Lahteenkorva S, Sundvall J, Tapanainen H, et al. Successful nutrition policy: improvement of vitamin D intake and status in Finnish adults over the last decade. Eur J Public Health. 2017;27(2):268–73. doi: 10.1093/eurpub/ckw154 28339536

12. Rosendahl J, Valkama S, Holmlund-Suila E, Enlund-Cerullo M, Hauta-Alus H, Helve O, et al. Effect of Higher vs Standard Dosage of Vitamin D3 Supplementation on Bone Strength and Infection in Healthy Infants: A Randomized Clinical Trial. JAMA Pediatr. 2018;172(7):646–54. doi: 10.1001/jamapediatrics.2018.0602 29813149

13. Hauta-Alus HH, Kajantie E, Holmlund-Suila EM, Rosendahl J, Valkama SM, Enlund-Cerullo M, et al. High Pregnancy, Cord Blood, and Infant Vitamin D Concentrations May Predict Slower Infant Growth. J Clin Endocrinol Metab. 2019;104(2):397–407. doi: 10.1210/jc.2018-00602 30247704

14. Wang TJ, Zhang F, Richards JB, Kestenbaum B, van Meurs JB, Berry D, et al. Common genetic determinants of vitamin D insufficiency: a genome-wide association study. Lancet. 2010;376(9736):180–8. doi: 10.1016/S0140-6736(10)60588-0 20541252

15. Lasky-Su J, Lange N, Brehm JM, Damask A, Soto-Quiros M, Avila L, et al. Genome-wide association analysis of circulating vitamin D levels in children with asthma. Hum Genet. 2012;131(9):1495–505. doi: 10.1007/s00439-012-1185-z 22673963

16. Jiang X, O'Reilly PF, Aschard H, Hsu YH, Richards JB, Dupuis J, et al. Genome-wide association study in 79,366 European-ancestry individuals informs the genetic architecture of 25-hydroxyvitamin D levels. Nature communications. 2018;9(1):260. doi: 10.1038/s41467-017-02662-2 29343764

17. O'Brien KM, Sandler DP, Shi M, Harmon QE, Taylor JA, Weinberg CR. Genome-Wide Association Study of Serum 25-Hydroxyvitamin D in US Women. Front Genet. 2018;9. doi: 10.3389/fgene.2018.00009

18. Sapkota BR, Hopkins R, Bjonnes A, Ralhan S, Wander GS, Mehra NK, et al. Genome-wide association study of 25(OH) Vitamin D concentrations in Punjabi Sikhs: Results of the Asian Indian diabetic heart study. J Steroid Biochem Mol Biol. 2016;158:149–56. doi: 10.1016/j.jsbmb.2015.12.014 26704534

19. Ahn J, Yu K, Stolzenberg-Solomon R, Simon KC, McCullough ML, Gallicchio L, et al. Genome-wide association study of circulating vitamin D levels. Hum Mol Genet. 2010;19(13):2739–45. doi: 10.1093/hmg/ddq155 20418485

20. Anderson D, Holt BJ, Pennell CE, Holt PG, Hart PH, Blackwell JM. Genome-wide association study of vitamin D levels in children: replication in the Western Australian Pregnancy Cohort (Raine) study. Genes Immun. 2014;15(8):578–83. doi: 10.1038/gene.2014.52 25208829

21. Manousaki D, Dudding T, Haworth S, Hsu YH, Liu CT, Medina-Gomez C, et al. Low-Frequency Synonymous Coding Variation in CYP2R1 Has Large Effects on Vitamin D Levels and Risk of Multiple Sclerosis. Am J Hum Genet. 2017;101(2):227–38. doi: 10.1016/j.ajhg.2017.06.014 28757204

22. Hong J, Hatchell KE, Bradfield JP, Bjonnes A, Chesi A, Lai CQ, et al. Transethnic Evaluation Identifies Low-Frequency Loci Associated With 25-Hydroxyvitamin D Concentrations. J Clin Endocrinol Metab. 2018;103(4):1380–92. doi: 10.1210/jc.2017-01802 29325163

23. Buniello A, MacArthur JAL, Cerezo M, Harris LW, Hayhurst J, Malangone C, et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Res. 2019;47(D1):D1005–D12. doi: 10.1093/nar/gky1120 30445434

24. Silva MC, Furlanetto TW. Intestinal absorption of vitamin D: a systematic review. Nutr Rev. 2018;76(1):60–76. doi: 10.1093/nutrit/nux034 29025082

25. Database: Human Protein Atlas available [Accessed May 2019]. Available from: www.proteinatlas.org.

26. Speeckaert M, Huang G, Delanghe JR, Taes YE. Biological and clinical aspects of the vitamin D binding protein (Gc-globulin) and its polymorphism. Clin Chim Acta. 2006;372(1–2):33–42. doi: 10.1016/j.cca.2006.03.011 16697362

27. Henderson CM, Fink SL, Bassyouni H, Argiropoulos B, Brown L, Laha TJ, et al. Vitamin D-Binding Protein Deficiency and Homozygous Deletion of the GC Gene. N Engl J Med. 2019;380(12):1150–7. doi: 10.1056/NEJMoa1807841 30893535

28. Cheng JB, Levine MA, Bell NH, Mangelsdorf DJ, Russell DW. Genetic evidence that the human CYP2R1 enzyme is a key vitamin D 25-hydroxylase. Proc Natl Acad Sci U S A. 2004;101(20):7711–5. doi: 10.1073/pnas.0402490101 15128933

29. Wu Y, Zheng Z, Visscher PM, Yang J. Quantifying the mapping precision of genome-wide association studies using whole-genome sequencing data. Genome Biol. 2017;18(1):86. doi: 10.1186/s13059-017-1216-0 28506277

30. Brodie A, Azaria JR, Ofran Y. How far from the SNP may the causative genes be? Nucleic Acids Res. 2016;44(13):6046–54. doi: 10.1093/nar/gkw500 27269582

31. Carithers LJ, Ardlie K, Barcus M, Branton PA, Britton A, Buia SA, et al. A Novel Approach to High-Quality Postmortem Tissue Procurement: The GTEx Project. Biopreserv Biobank. 2015;13(5):311–9. doi: 10.1089/bio.2015.0032 26484571

32. Giambartolomei C, Vukcevic D, Schadt EE, Franke L, Hingorani AD, Wallace C, et al. Bayesian Test for Colocalisation between Pairs of Genetic Association Studies Using Summary Statistics. PLoS genetics. 2014;10(5).

33. Franceschini N, Giambartolomei C, de Vries PS, Finan C, Bis JC, Huntley RP, et al. GWAS and colocalization analyses implicate carotid intima-media thickness and carotid plaque loci in cardiovascular outcomes. Nature communications. 2018;9(1):5141. doi: 10.1038/s41467-018-07340-5 30510157

34. Uhlen M, Fagerberg L, Hallstrom BM, Lindskog C, Oksvold P, Mardinoglu A, et al. Proteomics. Tissue-based map of the human proteome. Science. 2015;347(6220):1260419. doi: 10.1126/science.1260419 25613900

35. Karras SN, Koufakis T, Fakhoury H, Kotsa K. Deconvoluting the Biological Roles of Vitamin D-Binding Protein During Pregnancy: A Both Clinical and Theoretical Challenge. Front Endocrinol (Lausanne). 2018;9:259.

36. Kim D. The Role of Vitamin D in Thyroid Diseases. Int J Mol Sci. 2017;18(9).

37. Malik S, Fu L, Juras DJ, Karmali M, Wong BY, Gozdzik A, et al. Common variants of the vitamin D binding protein gene and adverse health outcomes. Crit Rev Clin Lab Sci. 2013;50(1):1–22. doi: 10.3109/10408363.2012.750262 23427793

38. Lek M, Karczewski KJ, Minikel EV, Samocha KE, Banks E, Fennell T, et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature. 2016;536(7616):285–91. doi: 10.1038/nature19057 27535533

39. Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21(2):263–5. doi: 10.1093/bioinformatics/bth457 15297300

40. Sun JY, Zhao M, Hou Y, Zhang C, Oh J, Sun Z, et al. Circulating serum vitamin D levels and total body bone mineral density: A Mendelian randomization study. J Cell Mol Med. 2019;23(3):2268–71. doi: 10.1111/jcmm.14153 30637964

41. Davies NM, Holmes MV, Davey Smith G. Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ. 2018;362:k601. doi: 10.1136/bmj.k601 30002074

42. Larsson SC, Melhus H, Michaelsson K. Circulating Serum 25-Hydroxyvitamin D Levels and Bone Mineral Density: Mendelian Randomization Study. J Bone Miner Res. 2018;33(5):840–4. doi: 10.1002/jbmr.3389 29338102

43. Helve O, Viljakainen H, Holmlund-Suila E, Rosendahl J, Hauta-Alus H, Enlund-Cerullo M, et al. Towards evidence-based vitamin D supplementation in infants: vitamin D intervention in infants (VIDI)—study design and methods of a randomised controlled double-blinded intervention study. BMC Pediatr. 2017;17(1):91. doi: 10.1186/s12887-017-0845-5 28356142

44. Saari A, Sankilampi U, Hannila ML, Kiviniemi V, Kesseli K, Dunkel L. New Finnish growth references for children and adolescents aged 0 to 20 years: Length/height-for-age, weight-for-length/height, and body mass index-for-age. Ann Med. 2011;43(3):235–48. doi: 10.3109/07853890.2010.515603 20854213

45. Manichaikul A, Mychaleckyj JC, Rich SS, Daly K, Sale M, Chen WM. Robust relationship inference in genome-wide association studies. Bioinformatics. 2010;26(22):2867–73. doi: 10.1093/bioinformatics/btq559 20926424

46. Wang C, Zhan X, Liang L, Abecasis GR, Lin X. Improved ancestry estimation for both genotyping and sequencing data using projection procrustes analysis and genotype imputation. Am J Hum Genet. 2015;96(6):926–37. doi: 10.1016/j.ajhg.2015.04.018 26027497

47. Wang C, Zhan X, Bragg-Gresham J, Kang HM, Stambolian D, Chew EY, et al. Ancestry estimation and control of population stratification for sequence-based association studies. Nat Genet. 2014;46(4):409–15. doi: 10.1038/ng.2924 24633160

48. Roshyara NR, Kirsten H, Horn K, Ahnert P, Scholz M. Impact of pre-imputation SNP-filtering on genotype imputation results. BMC Genet. 2014;15.

49. Delaneau O, Marchini J, Zagury JF. A linear complexity phasing method for thousands of genomes. Nature methods. 2011;9(2):179–81. doi: 10.1038/nmeth.1785 22138821

50. Deelen P, Bonder MJ, van der Velde KJ, Westra HJ, Winder E, Hendriksen D, et al. Genotype harmonizer: automatic strand alignment and format conversion for genotype data integration. BMC Res Notes. 2014;7:901. doi: 10.1186/1756-0500-7-901 25495213

51. Howie BN, Donnelly P, Marchini J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS genetics. 2009;5(6):e1000529. doi: 10.1371/journal.pgen.1000529 19543373

52. Howie B, Marchini J, Stephens M. Genotype imputation with thousands of genomes. G3 (Bethesda). 2011;1(6):457–70.

53. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, et al. PLINK: A tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81(3):559–75. doi: 10.1086/519795 17701901

54. Abraham G, Inouye M. Fast Principal Component Analysis of Large-Scale Genome-Wide Data. PLoS One. 2014;9(4).

55. McLaren W, Gil L, Hunt SE, Riat HS, Ritchie GR, Thormann A, et al. The Ensembl Variant Effect Predictor. Genome Biol. 2016;17(1):122. doi: 10.1186/s13059-016-0974-4 27268795

56. Vt-software. Documentation available from: http://genome.sph.umich.edu/wiki/Vt [cited May 2019].

57. Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26(6):841–2. doi: 10.1093/bioinformatics/btq033 20110278

58. Paila U, Chapman BA, Kirchner R, Quinlan AR. GEMINI: integrative exploration of genetic variation and genome annotations. PLoS Comput Biol. 2013;9(7):e1003153. doi: 10.1371/journal.pcbi.1003153 23874191

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Genetika Reprodukční medicína

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PLOS Genetics


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