Genetic polymorphisms

Genetic polymorphisms


LASAC872, LASAC873

Contact: Natasja van Schoor

Background
Single nucleotide polymorphisms (SNPs) are natural variations in the DNA sequence that occur in at least 1% of the population. These natural variations might increase the risk on certain complex diseases, such as osteoporosis. (In contrast: mutations occur in less than 1% of the population and have a strong relationship with a certain disease). Haplotype blocks are fixed combinations of close-by alleles of SNPs across a gene.

SNPs Vitamin D Recepter (VDR)
In Table 1 and Figure 1 (pdf),  the SNPs of the VDR and their position on the gene are presented. The selected SNPs were chosen because they are probably the most important contributors to fracture risk. The tagging SNPs (colored red in Figure 1) were used to determine the haplotype alleles. Furthermore, the SNPs BsmI, ApaI en TaqI were derived from the tagging SNPs.

Table 1. SNPs of the VDR

Haplo-block

Name SNPs

Position SNPs
(figure 1)

2

122R / Cdx-2

1e-G-1739A

2

308R / Gata

1a-A-1012G

3

-

1b-C-2481A

3

-

1b-G-886A

3

-

1b-C-673T

3

-

1b-C25A

-

FokI

E2-C4T

5

BsmI

E8-G-284A

5

ApaI

E9-T-48G

5

TaqI

E9-T32C

5

291M

U-A311C

5

444K

U-G464T

5

282W

U-A2978T

Note: Block 3 is very rare

Haplotype blocks VDR
Using the program PHASE (version 2), Joyce van Meurs from Rotterdam calculated the most frequent haplotypes.

Explanation variables LASA-block2-haplo (as an example):
ea_hap: haplotype genotypes block 2 
ea1_hap: frequency of haplotype 1 of block 2 (0, 1 or 2 times). For example: 2 means that a person is homozygote for this haplotype. 
ea2_hap: frequency of haplotype 2 of block 2
ea3_hap: frequency of haplotype 3 of block 2

Note: there is no variable of haplotype 5 of block 5 because of too low frequency (3,5%).

Yue Fang from Rotterdam has calculated that the VDR haplotypes of block 2, 3 and 5 as well as Bsm, Apa and Taq are in Hardy-Weinberg equilibrium (HWE) for LASA. Definition 
HWE = In a population, allele and genotype proportions will remain constant over generations.

SNPs Glucocorticoid Receptor (GR)
The SNPs and haplotypes of the GR are presented in Figure 2 (pdf). E22E and R23K (rs6189 and rs6190), are linked together in exon 2 and were identified as a G>A substitution, leading to an arginine-to-lysine change in codon 23. N363S (rs6195), was identified as an A>G substitution in exon 2 leading to an asparagine-to-serine change. The 9beta SNP (rs6198) was identified as an A>G substitution located in the 3'UTR of exon 9b, which encodes the 3'UTR of the mRNA of the hGRb isoform. The substitution is located in an AUUUA motif, which is known to destabilize mRNA and decrease receptor protein expression in vitro. The BclI SNP was identified as a C>G substitution in intron 2, 646 nucleotides downstream from exon 2 (1). 
The SNPs were used to infer haplotypes using the program PHASE. Haplotypes 2, 3, 4 and 5 represented the BclI SNP, the 9beta SNP, the N363S SNP and ER22/23EK+9beta SNP, respectively (see Figure 2). The ER22/23EK was always accompanied by the 9beta SNP (resulting in haplotype 5) but not vice versa (haplotype 3) (1). An interesting overview of the glucocorticoid receptor was given by van Rossum (2).

Sensitivity of GR genotypes
The sensitivity of a SNP determines how well the receptor binds to the protein, and thus serves as a measure of the availability of the protein on tissue level. If the sensitivity is higher, less proteins are needed to exert its effect, or the greater the influence of the protein on the tissue.
BclI (2;3) and N363S (2;3): elevated sensitivity
9beta (4) en ER22/23EK (5): reduced sensitivity

Measurements in LASA

Blood collection
Blood samples were obtained from respondents who participated in the medical interview of the second data collection cycle of LASA (1995/96), who were born in 1930 or before (aged 65 years and older as of January 1, 1996) and were living in Amsterdam, Zwolle and Oss and surroundings (n=1509). At the visit in the hospital or health care center, morning blood samples were obtained (n=1352), centrifuged and frozen at -80° C until DNA isolation and determination of VDR, ER and GR genotyping in 2004/2005.

Measurement procedure & variable information
Determination was performed in Rotterdam in cooperation with the endocrinology laboratory of the VUmc. Adequate DNA samples were obtained in 953 respondents. VDR, ER and GR could be determined in 935 persons.

At the time LASA got involved, part of the inconsistencies were already removed from the files. Globally, the following reasons for exclusion were given: 6x "pipetteer" mistakes; 8x gender inconsistencies between LASA data and assay SRY gene (see also paragraph "precision"); 3x too low DNA; 1x inconsistencies in 3 samples for respnr 16318. LASA (Natasja van Schoor), the endocrinology laboratory of the VUmc (Ebbo Dekema), and the Erasmuc MC (Pascal Arp) together developed a set with respondent numbers having adequate samples (n=935 in LASAC872). When new SNPs are determined, the new datafiles should be merged with LASAC872, because this file contains the respondent numbers with adequate samples. Other details of the lab procedure are described in the standard operating procedures (SOPs). An example of a description of the lab procedures followed in Rotterdam can be found in reference (1).

Precision
To check the genotyping procedures, we have compared gender as documented in LASA with DNA gender (SRY gene) and testosteron level. The number of persons with incorrect gender determination was 8. This is a measure for the precision of the genotyping. The error percentage was 8/935=0.9%. The persons with incorrect gender determination were removed from the file (resulting n=935).

Analysis
The frequencies of haplotypes differ between different ethnicities. It is important to take this into consideration. It is recommended to remove non-Caucasians from the file using LASAB004 (select aethnic=-2 and aethnic=1) (resulting n=922). Furthermore, the most frequent homozygote genotype is usually presented first, then the heterozygotes and then the less frequent homozygote genotype. One usually assumes that the less frequent genotype contains the variation. In the analyses, one usually starts with dose-allele-effects. Secondly, based on risk and power, one may analyze recessive (recessive versus the rest) and dominant models (dominant homozygote versus the rest). 

Availability of data per wave 

Numbers per wave

SNPs

 

B

C

 
2B*

G

 

3B*

All regions

 

935

 

 

 

* 2B=baseline second cohort;
   3B=baseline third cohort

Previous use in LASA
Peeters et al. (2008) showed that high salivary cortisol is associated with a higher risk of loss of grip strength in older persons. GR genotypes modify the relationship between muscle mass and muscle strength. Bet et al. (2008) found a gene-environment (GE) interaction between common variants of the GR gene and childhood adversity, demonstrating a vulnerable phenotype for developing clinically relevant depressive symptoms at old age.

References

  1. van Schoor NM, Dennison E, Lips P, Uitterlinden AG, Cooper C. Serum fasting cortisol in relation to bone, and the role of genetic variations in the glucocorticoid receptor. Clin Endocrinol (Oxf) 2007.
  2. van Rossum EF, Lamberts SW. Polymorphisms in the glucocorticoid receptor gene and their associations with metabolic parameters and body composition. Recent Prog.Horm.Res. 2004;59:333-57.
  3. Huizenga NA, Koper JW, de Lange P, Pols HA, Stolk RP, Burger H et al. A polymorphism in the glucocorticoid receptor gene may be associated with an increased sensitivity to glucocorticoids in vivo. J.Clin.Endocrinol Metab 1998;83(1):144-51.
  4. Schaaf MJ, Cidlowski JA. AUUUA motifs in the 3'UTR of human glucocorticoid receptor alpha and beta mRNA destabilize mRNA and decrease receptor protein expression. Steroids 2002;67(7):627-36.
  5. van Rossum EF, Koper JW, Huizenga NA, Uitterlinden AG, Janssen JA, Brinkmann AO et al. A polymorphism in the glucocorticoid receptor gene, which decreases sensitivity to glucocorticoids in vivo, is associated with low insulin and cholesterol levels. Diabetes 2002;51(10):3128-34.

Appendix 1 Preparation of the VDR dataset (pdf)