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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Am J Hypertens. Author manuscript; available in PMC Feb 20, 2009.
Published in final edited form as:
PMCID: PMC2645713
NIHMSID: NIHMS92644
REGIONAL ASSOCIATION-BASED FINE MAPPING FOR SODIUM-LITHIUM COUNTERTRANSPORT ON CHROMOSOME 10
Alanna C. Morrison, PhD,a Eric Boerwinkle, PhD,a Stephen T. Turner, MD,b and Robert E. Ferrell, PhDc
aHuman Genetics Center, University of Texas Health Science Center at Houston, 1200 Herman Pressler; Suite 453E, Houston, TX 77030
bDivision of Nephrology and Hypertension, Mayo Clinic, 200 First Street SW, Rochester, MN 55905
cDepartment of Human Genetics, Graduate School of Public Health, University of Pittsburgh, 130 DeSoto Street, Room 324 Parran Hall, Pittsburgh, PA 15261
Correspondence: Alanna C. Morrison, Ph.D. Human Genetics Center, University of Texas Health Science Center at Houston 1200 Herman Pressler; Suite 453E Houston, TX 77030 Phone: 713-500-9800 Fax: 713-500-0900 E-mail: Alanna.C.Morrison/at/uth.tmc.edu
Background:
Increased erythrocyte sodium-lithium countertransport (SLC) has been observed in patients with essential hypertension. Consistent evidence of genetic linkage was shown for SLC on chromosome 10, and a region of interest was localized between 26 and 56 Mb.
Methods:
This study surveyed single nucleotide polymorphisms (SNPs) in 54 genes that reside in the region of interest and investigated their association with SLC and blood pressure. These SNPs were genotyped in 1133 non-Hispanic White individuals from 255 pedigrees comprising the second phase of the Rochester Family Heart Study. The variance components-based genetics software package SOLAR was used to evaluate whether a SNP contributes to a significant fraction of the trait heritability.
Results:
Of the 77 SNPs surveyed in this study across the region of interest, four SNPs were associated with SLC (p<0.04), five SNPs were associated with blood pressure (p<0.04), and two SNPs in mannose-binding lectin 2 (MBL2) were associated with both phenotypes. In general, the pairwise linkage disequilibrium among the genotyped SNPs was low.
Conclusion:
This fine-mapping survey of genetic variation in a linkage region of interest provides overall support for association mapping for SLC on chromosome 10. Genes significantly associated with systolic blood pressure and/or SLC in these families will be prioritized for future studies.
Keywords: sodium-lithium countertransport, blood pressure, association, polymorphism, chromosome
Efforts to identify genetic variation influencing common chronic diseases such as hypertension are aided by the evaluation of intermediate traits and the application of well-designed analytical methodology. Experimental and epidemiological studies have suggested that sodium-lithium countertransport (SLC) may be considered an intermediate phenotype for hypertension.1 Increased erythrocyte SLC has been consistently documented in patients with essential hypertension2, and the reported heritability of SLC ranges from 55% to 88%.3, 4 Several studies provide evidence of a genetic basis for SLC 3-7, including four genome-wide analyses of SLC in humans.8-11 In the Rochester Family Heart Study, we observed consistent evidence of linkage (LOD > 2) for SLC on chromosome 10 in two independent samples of non-Hispanic White families.11 Overlap of the 1-LOD confidence intervals for the observed linkage between the two samples defined a genomic region of interest on chromosome 10 between 26 and 56 Mb on the physical map (NCBI Build 34). This study was designed to survey genetic variation in 54 genes that reside in the region of interest and test its association with SLC and blood pressure in the Rochester Family Heart Study cohort. Prioritization of genes on chromosome 10 associated with SLC and/or blood pressure will guide future association mapping efforts with the ultimate goal of localizing the functional genetic variation responsible for inter-individual phenotypic variation.
Study Population
Study participants were from the Rochester Family Heart Study, the overall objective of which is to identify and characterize genetic variation influencing risk of cardiovascular disease in the general population of Rochester, MN. Individuals were ascertained without regard to health or disease between 1984 and 1991 through index school children in the Rochester, MN, school system and these individuals took part in a detailed physical examination at the Mayo Clinic. The sampling details, clinic examination protocol, and baseline characteristics have been described by Moll et al12 and Turner et al.13 Sampling was done in two phases, differing only with respect to falling under different National Institutes of Health grant cycles, resulting in two independent samples of pedigrees referred to as Phase 1 and Phase 2. Genotyping for this project was completed in 1133 non-Hispanic White parents and children from 255 Phase 2 pedigrees that had available DNA. Restricting the analysis to the lower two generations of the pedigrees limits the potential confounding effects of age and body mass index on the SLC distribution. Appropriate institutional review boards approved the Rochester Family Heart Study, and all participants provided informed consent.
Phenotypic Measures
The standard assay procedure to measure SLC in erythrocytes has been described elsewhere.1, 11, 14, 15 Blood pressure was measured with a random-zero sphygmomanometer. Three blood pressure readings, at least two minutes apart, were measured in the right arm after the subject had been sitting quietly for at least five minutes. The pressure at Korotkoff phase I sound was taken as systolic blood pressure. Diastolic blood pressure was determined at the occurrence of Korotkoff phase V sound. Blood pressure measures for this study were the averages of the three readings taken for each subject.
Single nucleotide polymorphism (SNP) selection and genotype determination
The region of interest on chromosome 10, identified from linkage analyses in the Rochester Family Heart Study, corresponds to 26 to 56 Mb on the physical map (NCBI Build 34) and contains 54 genes. As an initial survey of genetic variation in these genes, at least one SNP was chosen from public16 or private17 databases for genotyping. Table 1 shows the genes evaluated in this study, the number of SNPs genotyped in each gene, and allele frequencies estimated in a sample of unrelated individuals (N=255) generated by a randomly sampling one individual from each pedigree. Thirty-eight genes contain only one SNP, eleven genes contain two SNPs, three genes contain three SNPs, and two genes contain four SNPs. Pairwise linkage disequilibrium among the 77 SNPs was evaluated using Haploview.18 Average pairwise linkage disequilibrium measured by r2 was 0.005. Only two pairs of SNPs had a pairwise r2 greater than 0.80: rs10899795 in FYXD4 and rs4597022 in HNRPF (r2=0.84) and rs1657224 in PARD3 and rs1362999 in CFP1 (r2=1.0)
Table 1
Table 1
Description of genetic variation surveyed in a 30 Mb region on chromosome 10
SNPs were genotyped by the fluorescence polarization method described by Chen et al.19 using the L.J.L. Biosystems' Analyst HT Assay Detection System. Data were analyzed using the Allele Caller software package. Genotype clusters generated by Allele Caller are checked visually by the operator and questionable calls are repeated or assigned by direct sequencing of the sample.
Statistical Analyses
Agreement of genotype frequencies with Hardy-Weinberg equilibrium expectations was tested using a χ2 goodness-of-fit test in a random sample (N=255) comprised of one individual from each pedigree. Association between each SNP and blood pressure or SLC was evaluated using the variance components-based genetics software package SOLAR.20 SOLAR evaluates whether a SNP contributes to a significant fraction of the trait heritability by comparing models including or excluding the SNP genotype, coded as the additive effect of the rare allele, as a covariate. Age, gender and triglyceride levels were included in the variance-components models as potential confounders. No adjustment for multiple comparisons was made within this study given the consistent published evidence11 of the existence of a gene influencing SLC and/or blood pressure in this region of chromosome 10 as well as evidence that variation in multiple genes may contribute to SLC.10 This region of chromosome 10 was identified by evidence of linkage to SLC in the Rochester Family Heart Study.11 Therefore, for each individual SNP significantly associated with SLC in the variance-components model, we evaluated the decrease in the LOD score from the peak LOD of 2.27 at 55 cM originally observed in the Phase 2 pedigrees.
Genotype frequencies of all SNPs agreed with Hardy-Weinberg expectations. Descriptive characteristics of the Rochester Family Heart Study for the phenotypes of interest are shown in Table 2. The proportion of males in the total sample of pedigrees was 51.8 percent.
Table 2
Table 2
Descriptive characteristics of the Rochester Family Heart Study sample
The results from the variance-components analyses incorporating each SNP are shown in Table 3 for those SNPs demonstrating a significant association with either SLC or blood pressure (p<0.05) after taking into account the potential confounding effects of age, gender and triglyceride levels. The proportion of phenotypic variance attributable to each SNP is also reported in Table 3 and for each SNP demonstrating a significant association with SLC, we observed a reduction in the LOD score assessed at the peak evidence for linkage reported in Morrison et el.11 Inclusion of rs1838065 in MBL2 in the variance components model resulted in the greatest decrease in the LOD to 0.80 at 55 cM. When both rs930507 and rs1838065 in MBL2 were included in the linkage analysis model, a LOD of 0.77 at 55 cM was observed.
Table 3
Table 3
SNPs demonstrating a significant association with blood pressure and sodium-lithium countertransport
A total of seven SNPs associated with blood pressure and/or SLC were identified in the linkage region of interest on chromosome 10. Two of these SNPs, rs930507 and rs1838065, reside in mannose-binding lectin 2 (MBL2) and are the only polymorphisms to show a significant effect on both SLC and blood pressure. Pairwise linkage disequilibrium between the two MBL2 SNPs is low (r2=0.15).
This study is a survey of genetic variation in 54 genes that reside in a region on chromosome 10 with consistent evidence of linkage for SLC and blood pressure.11 Association-based fine-mapping of this region demonstrates that variation in three genes is associated with SLC, variation in four genes is associated with blood pressure, and variation in one gene is associated with both phenotypes. Of the seven SNPs associated with blood pressure and/or SLC, only two of these SNPs reside in the same gene, mannose-binding lectin 2 (MBL2).
It is interesting to note that two SNPs in this study, rs930507 and rs1838065 in MBL2, demonstrated a significant association with SLC and blood pressure. These SNPs also appeared to contribute most to the linkage evidence for SLC in this region of chromosome 10, resulting in a reduction in the LOD score from 2.27 to 0.77 at 55 cM when they were both included in the linkage analysis model. MBL2 encodes the soluble mannose-binding protein found in serum. This protein, secreted by the liver, is a part of the acute-phase response and is involved in innate immune defense. It recognizes mannose and N-acetylglucosamine on bacterial pathogens, and is capable of activating the complement system.21 Three nonsynonymous polymorphisms in exon 1 of MBL2 have been associated with low serum levels of mannose-binding lectin and increased risk of infections22 as well as worsened prognosis for chronic diseases such as cystic fibrosis23, rheumatoid arthritis24, and systemic lupus erythematosus.25 These SNPs in exon 1 of MBL2 have also been associated with an increased risk of coronary artery disease26, arterial thrombosis among patients with systemic lupus erythematosus21 and increased systemic arterial stiffness in patients after Kawasaki disease.27 Using available information from the International HapMap Project Caucasian data, we determined that the SNP at codon 54 (rs1800450) is not in linkage disequilibrium with either of the two MBL2 SNPs evaluated in this study (r2=0.06 with rs930507 and r2=0.13 with rs1838065). Although the mechanism by which genetic variation in MBL2 modulates systemic arterial stiffness is unknown, it is clear that MBL2 plays a role in the inflammatory pathophysiology of the vasculature. Evidence from animal models and human population-based studies suggest vascular inflammation may be involved in the initiation as well as development of hypertension.28 These observations, coupled with the results from this study, lend support to the prioritization of MBL2 as a putative candidate gene for SLC and susceptibility to hypertension.
Additional evidence that this region of chromosome 10 harbors a gene associated with blood pressure-related phenotypes comes from a genome-wide SNP scan of the Framingham Heart Study Offspring Cohort. On chromosome 10, a putative association between rs1916565 and diastolic blood pressure was identified (http://gmed.bu.edu).29 Rs1916565 resides between the CHAT and PARG genes evaluated as a part of our study. Also on chromosome 10, an association was identified between a SNP (rs10508995) proximal to MBL2 and systolic blood pressure (http://gmed.bu.edu). Utilizing Caucasian data from the International HapMap Project we determined that rs10508995 is not in strong linkage disequilibrium (r2<0.02) with the two MBL2 SNPs genotyped in our study, and rs10508995 was not significantly associated with SLC or blood pressure in the Rochester Family Heart Study (data not shown).
A strength of this study is that we have genotyped SNPs in all 54 genes in the region of interest on chromosome 10. However, 70% of the genes surveyed contained only one genotyped SNP. Given this generalized survey of the region, lack of an association with SLC or blood pressure is not a basis for excluding a gene from further study. However, detection of an association with one of the 54 genes in this region may be used to prioritize that gene for future study. A potential limitation of this study is that the pedigrees were not ascertained with regard to health or disease and the children's generation in particular, with a mean age of 15.5 years, represents low blood pressures (systolic blood pressure 104.6±10.1 mm Hg and diastolic blood pressure 63.0±9.8 mm Hg). Although it is important to note the sample of pedigrees in this study are the same families that contributed to the evidence of linkage for SLC in this region of chromosome 10.11
Evidence of association for rs930507 and rs1838065 in MBL2 and SLC and systolic blood pressure has been found in a region of linkage for SLC and blood pressure on chromosome 10. MBL2 may be considered a candidate gene for SLC and susceptibility to hypertension. Prioritization of genes on chromosome 10 associated with SLC and/or blood pressure will guide future association-based fine-mapping efforts, with the ultimate goal of localizing the functional genetic variation responsible for inter-individual variation in these traits.
Acknowledgments
We thank the participants of the Rochester Family Heart Study for their time and effort. Support for this work was provided by National Heart, Lung, and Blood Institute Contract R01-HL-077491.
Footnotes
Conflict of Interest
The authors of this manuscript have no conflict of interest to disclose.
1. Canessa M, Adragna N, Solomon H, Connolly T, Tosteson D. Increased sodium-lithium countertransport in red cells of patients with essential hypertension. New England Journal of Medicine. 1980;302:772–776. [PubMed]
2. West I, Rutherford P, Thomas T. Sodium-lithium countertransport: Physiology and function. Journal of Hypertension. 1998;16:3–13. [PubMed]
3. Hasstedt S, Wu L, Ash K, Kuida H, Williams R. Hypertension and sodium-lithium countertransport in utah pedigrees: Evidence for major-locus inheritance. American Journal of Human Genetics. 1988;43:14–22. [PubMed]
4. Dadone M, Hasstedt S, Hunt S, Smith J, Ash K, Williams R. Genetic analysis of sodium-lithium countertransport in 10 hypertension-prone kindreds. American Journal of Medical Genetics. 1984;17:565–577. [PubMed]
5. Boerwinkle E, Turner S, Weinshilbaum R, Johnson M, Richelson E, Sing C. Analysis of the distribution of erythrocyte sodium lithium countertransport in a sample representative of the general population. Genetic Epidemiology. 1986;3:365–378. [PubMed]
6. Hunt S, Stephenson S, Hopkins P, Hasstedt S, Williams R. A prospective study of sodium-lithium countertransport and hypertension in utah. Hypertension. 1991;17:1–7. [PubMed]
7. Kammerer C, Cox L, Mahaney M, Rogers J, Shade R. Sodium-lithium countertransport activity is linked to chromosome 5 in baboons. Hypertension. 2001;37:398–402. [PubMed]
8. Schork N, Gardner J, Zhang L, Fallin D, Thiel B, Jakubowski H, Aviv A. Genomic association/linkage of sodium lithium countertransport in ceph pedigrees. Hypertension. 2002;40:619–628. [PubMed]
9. Weder A, Delgado M, Zhu X, Gleiberman L, Kan D, Chakravarti A. Erythrocyte sodium-lithium countertransport and blood pressure: A genome-wide linkage study. Hypertension. 2003;41:842–846. [PubMed]
10. Hasstedt S, Camp N, Hopkins P, Coon H, McKinney J, Cawthon R, Hunt S. Model-fitting and linkage analysis of sodium-lithium countertransport. European Journal of Human Genetics. 2004;12:1055–1061. [PubMed]
11. Morrison A, Boerwinkle E, Turner S, Ferrell R. Genome-wide linkage study of erythrocyte sodium-lithium countertransport. American Journal of Hypertension. 2005;18:653–656. [PubMed]
12. Moll P, Sing C, Weidman W, Gordon H, Ellefson R, Hogdson P, Kottke B. Total cholesterol and lipoproteins in school children: Prediction of coronary heart disease in adult relatives. Circulation. 1983;67:127–134. [PubMed]
13. Turner S, Weidman W, Michels V, Reed T, Ormson C, Fuller T, Sing C. Distribution of sodium-lithium countertransport and blood pressure in caucasians five to eighty-nine years of age. Hypertension. 1989;13:378–391. [PubMed]
14. Smith J, Price A, Williams R, Hentschel W, Sprowell W, Hunt S, Ash K. A reproducible sodium-lithium countertransport assay: The outcome of changing key laboratory parameters. Clinica Chimica Acta. 1982;122:327–335. [PubMed]
15. Hardman T, Thomas T, Lant A. Characterization of the erythrocyte sodium-lithium countertransporter: Limitations and assumptions of traditional and kinetic methodologies. Journal of Membrane Biology. 1998;161:197–205. [PubMed]
17. Celera Discovery System 2004. http://www.celeradiscoverysystem.com.
18. Barrett J, Fry B, Maller J, Daly M. Haploview: Analysis and visualization of ld and haplotype maps. Bioinformatics. 2005;21:263–265. [PubMed]
19. Chen X, Levine L, Kwok P-Y. Fluorescence polarization in homogeneous nucleic acid analysis. Genome Research. 1999;9:492–498. [PubMed]
20. Almasy L, Blangero J. Multipoint quantitative-trait linkage analysis in general pedigrees. American Journal of Human Genetics. 1998;62:1198–1211. [PubMed]
21. Ohlenschlaeger T, Garred P, Madsen H, Jacobsen S. Mannose-binding lectin variant alleles and the risk of arterial thrombosis in systemic lupus erythematosus. New England Journal of Medicine. 2004;351:260–267. [PubMed]
22. Koch A, Melbye M, Sorensen P, Homoe P, Madsen H, Molbak K, Hansen C, Andersen L, Hahn G, Garred P. Acute respiratory tract infections and mannose-binding lectin insufficiency during early childhood. Journal of the American Medical Association. 2001;285:1316–1321. [PubMed]
23. Garred P, Pressler T, Madsen H, Frederiksen B, Svejgaard A, Hoiby N, Schwartz M, Koch C. Association of mannose-binding lectin gene heterogeneity with severity of lung disease and survival in cystic fibrosis. Journal of Clinical Investigation. 1999;104:431–437. [PMC free article] [PubMed]
24. Garred P, Madsen H, Marquart H, Hansen T, Sorensen S, Petersen J, Volck B, Svejgaard A, Graudal N, Rudd P, Dwek R, Sim R, Andersen V. Two edged role of mannose binding lectin in rheumatoid arthritis. Journal of Rheumatology. 2000;27:26–34. [PubMed]
25. Garred P, Madsen H, Halberg P, Petersen J, Kronborg G, Svejgaard A, Andersen V, Jacobsen S. Mannose-binding lectin polymorphisms and susceptibility to infection in systemic lupus erythematosus. Arthritis and Rheumatism. 1999;42:2145–2152. [PubMed]
26. Best L, Davidson M, North K, MacCluer J, Zhang Y, Lee E, Howard B, DeCroo S, Ferrell R. Prospective analysis of mannose-binding lectin genotypes and coronary artery disease in american indians. The strong heart study. Circulation. 2004;109:471–475. [PubMed]
27. Cheung Y-F, Ho M, Ip W-K, Fok S, Yung T-C, Lau Y-L. Modulating effects of mannose binding lectin genotype on arterial stiffness in children after kawasaki disease. Pediatric Research. 2004;56:591–596. [PubMed]
28. Li J-J, Fang C-H, Hui R-T. Is hypertension an inflammatory disease? Medical Hypotheses. 2005;64:236–240. [PubMed]
29. Herbert A, Lenburg M, Ulrich D, Gerry N, Schlauch K, Christman M. Open-access database of candidate associations from a genome-wide snp scan of the framingham heart study. Nature Genetics. 2007;39:135–136. [PubMed]