Recessive inheritance of a high number of sodium pump sites

Two-dimensional, sex-specific autosomal linkage scan of the number of sodium pump sites

OBJECTIVES

The sodium pump consists of the membrane-bound enzyme sodium/potassium-ATPase, which exchanges internal sodium ions for external potassium ions. Obesity, hypertension, and diabetes associate with the activity of the sodium pump, motivating gene discovery for sodium pump number.

METHODS

Variance components linkage analysis was applied to the number of red blood cell sodium pump sites measured by ouabain-binding assays on 1375 members of 46 Utah pedigrees. Both one-dimensional (1D) and two-dimensional (2D) autosome-wide linkage analyses of pump number were performed on the combined sample as well as separately on the male and female subsets.

RESULTS

Two significant 1D linkages were identified: on chromosome 1p13 in the combined sample [1D logarithm of odds (LOD) score = 3.76] and on chromosome 17p21 in the female subset (1D LOD score = 3.24). In addition, two significant 2D linkages were identified in the female subset: on chromosome 10q22 interacting with chromosome 18q11 (2D LOD score = 7.18) and on chromosome 13q21 interacting with chromosome 4q31 (2D LOD score = 6.05). Single-nucleotide polymorphism rs17376826 in neuropeptide Y receptor Y2, an obesity-associated gene and a candidate in the chromosome 4q31 linkage region, is associated with pump number (P = 0.046 in the combined sample and P = 0.042 in the female subset).

CONCLUSION

Pump number is influenced by multiple genes, possibly including neuropeptide Y receptor Y2.

Linkage of the Na,K-ATPase alpha 2 and beta 1 genes with resting and exercise heart rate and blood pressure: cross-sectional and longitudinal observations from the Quebec Family Study

OBJECTIVE

To investigate whether genetic variations in the genes encoding the alpha and beta subunits of the Na,K-ATPase are linked with hemodynamic phenotypes.

DESIGN AND PARTICIPANTS

Cross-sectional data based on 533 subjects (no antihypertensive medication) were obtained from 150 families of phase 2 of the Quebec Family Study, together with longitudinal data from 338 subjects (105 families) who had been measured 12 years earlier in phase 1 of the Quebec Family Study.

MAIN OUTCOME MEASURES

Restriction fragment length polymorphisms were examined at the alpha 2 (exon 1 and exon 21-22 with BglII) and beta 1 (Msp I and Pvu II) loci of Na,K-ATPase. Hemodynamic phenotypes measured included systolic and diastolic blood pressure, heart rate and rate-pressure product at rest and during low-intensity exercise.

RESULTS

Sib-pair analysis revealed relatively strong linkages (P = 0.0003-0.002) between the resting heart rate and rate-pressure product and the alpha 2 exon 21-22 marker and alpha 2 haplotype. Moreover, the alpha 2 exon 21-22 marker showed suggestive linkages (P = 0.01 to 0.043) with resting systolic blood pressure and exercise diastolic blood pressure, heart rate and rate-pressure product, and the alpha 2 haplotype with exercise diastolic blood pressure and rate-pressure product and the 12-year change in resting systolic blood pressure (P = 0.03 to 0.05). Both the beta 1 Msp I marker and the beta 1 haplotype were linked with the resting rate-pressure product (P = 0.007 and 0.003, respectively), and all beta 1 markers showed linkage with the change in resting systolic blood pressure (P = 0.00005 to 0.024). In men, there was a significant (P = 0.01) interaction between the alpha 2 exon 21-22 genotype and the postglucose plasma insulin level with regard to resting systolic blood pressure.

CONCLUSIONS

These data suggest that the alpha 2 and beta 1 genes of Na,K-ATPase contribute to the regulation of hemodynamic phenotypes in healthy subjects.

Evidence for multiple genes determining sodium transport

Sodium transport comprises a set of interacting systems. Consequently, a defective sodium transport gene affects multiple sodium transport systems, and a sodium transport variable measured on a sample of individuals reflects genetic variation from a number of different genes, complicating the task of identifying the effect of a single gene. To test for genes which affect sodium transport, we first applied principal components analysis to 14 variables related to sodium transport, thereby defining uncorrelated sources of variation in the variables. The sample consisted of 1,218 members of 68 pedigrees ascertained through probands with early-onset stroke, hypertension, or coronary heart disease. Segregation analysis of the 14 principal components scores provided evidence for 8 genetic variants which alter sodium transport. One of the 8 variants is recessive, has homozygous genotype frequency estimated as 8.8% of the population, and increases sodium-lithium countertransport, the passive sodium leak, body mass index, and triglyceride; the genetic variant may coincide with an insulin resistance gene. A second of the 8 variants is also recessive, has homozygous genotype frequency estimated as 7.4% of the population, and increases intraerythrocytic sodium and the passive sodium leak while decreasing sodium pump number; the genetic variant may reduce pump number. Two of the 8 variants substantially increase sodium-lithium countertransport; frequency estimates for heterozygotes for the dominant variant and homozygotes for the recessive variant equal 1.8% and 3.1%, respectively. Another of the 8 variants is recessive, has homozygous genotype frequency estimated as 1.9%, and increases body mass index. Each of the 3 remaining variants is rare and expressed in less than 1% of the sample.

A gene-environment interaction between inferred kallikrein genotype and potassium

Urinary kallikrein excretion has been shown statistically to be partially determined by a major gene in large Utah pedigrees with the use of segregation analysis. A previous twin analysis of environmental factors influencing urinary kallikrein level showed that urinary potassium twin differences were strongly related to differences in urinary kallikrein. The present study uses 769 individuals in 58 Utah pedigrees to analyze the association of urinary potassium with urinary kallikrein within statistically inferred kallikrein genotypes. Fitting genotype-specific curves relating urinary kallikrein level to 12-hour urinary potassium amount within a major gene, polygene, and common environment model, we showed a significant statistical urinary potassium interaction with the inferred major gene for kallikrein (P = .0002). The heterozygotes (with a frequency of 50%) had a significant association between urinary kallikrein and potassium (slope, 0.51 +/- 0.04 SD), whereas there was no association with potassium in the low homozygotes, suggesting a genetic defect involving the kallikrein response to potassium. The model predicted that an increase in urinary potassium excretion of 0.8 SD above the mean in these pedigrees would be associated with high kallikrein levels in the heterozygotes similar to the high homozygotes. A decrease of 1.3 SD in urinary potassium excretion in heterozygous individuals was associated with kallikrein levels similar to the homozygous individuals with low kallikrein. Because in the steady state urinary potassium represents dietary potassium intake, this study suggests that an increase in dietary potassium intake in 50% of these pedigree members, estimated to be heterozygous at the kallikrein locus, would be associated with an increase in an underlying genetically determined low kallikrein level.(ABSTRACT TRUNCATED AT 250 WORDS)

Variance components/major locus likelihood approximation for quantitative, polychotomous, and multivariate data

Pearson [Philos Trans R Soc Lond [A] 200:1-66, 1903], Mendell and Elston [Biometrics 30:41-57, 1974], and Rice et al. [Biometrics 35:451-459, 1979] approximated the likelihood of the multifactorial model on a dichotomous phenotype by a procedure of successive univariate computation and conditioning. Hasstedt [Pap: Pedigree Analysis Package, Rev. 3. 1989] and Demenais [Am J Hum Genet 49:773-785, 1991] extended the algorithm to include a major locus. Here I extend the algorithm to polychotomous, quantitative, and multivariate phenotypes, add a major locus to the model, and describe and evaluate the accuracy of an approximation of the resulting variance components/major locus model.